Schlagwort: Experience AI

  • Igniting innovation: How Experience AI is empowering teachers and students across Kenya

    Igniting innovation: How Experience AI is empowering teachers and students across Kenya

    Reading Time: 4 minutes

    This blog post is written by Victor Murithi, Communications and Media Consultant at Young Scientists Kenya, one of our global partners for Experience AI in Kenya.

    When over 100 teachers from across Kenya gathered at Kangaru High School in Embu County for the Kenya Science and Engineering Fair Nationals in April, few anticipated just how transformative a two-day workshop could be. Delivered by the Experience AI Young Scientists Kenya (YSK) team, with support from the Raspberry Pi Foundation, the training sparked more than curiosity — it sparked a shift in mindset.

    This wasn’t just about introducing new tools: it was about empowering teachers to confidently lead their students into an artificial intelligence (AI)-driven future.

    Students in a classroom learn about Experience AI.

    National reach and local impact

    What began as a plan to train just 40 teachers quickly grew into something much bigger. By the time the workshop kicked off, 104 teachers from over 80 schools across 37 counties in Kenya, had registered and participated — nearly tripling the initial target.

    This overwhelming interest confirmed a powerful insight: teachers are eager to understand AI, not only to better prepare their students for the future, but also for their own professional growth.

    The workshop’s curriculum didn’t just focus on technical skills, it aimed to create confidence, clarity, and community among the attendees — key ingredients for successfully integrating AI into teaching and learning.

    “Helping teachers move past their fear of AI and understand its potential is incredibly powerful. Because AI is the future, and through this training, we’re reaching the minds that will shape it,” explained Lucy Mwaniki, AI Community Trainer at YSK.

    Practical skills, real outcomes

    As part of the training, the attendees completed interactive worksheets, tested basic machine learning models, and sat a final comprehension test, something they found both validating and motivational.

    “We were able to do the summative test… which turned out to be a very effective way of us understanding how in-depth and how well they grasped the knowledge,” says Lucy Mwaniki.

    In one standout session, teachers collaboratively brainstormed ways AI could address national educational challenges. Ideas included models to assist students in selecting academic pathways within Kenya’s Competency Based Curriculum (CBC). Several teachers also successfully built working models, demonstrating the potential of applied learning. 

    “It was a very eye-opening session… some of the teachers were able to create a very basic model, which was a wonderful experience for them,” Lucy Mwaniki explains. 

    What made this training exceptional was its immediate applicability and long-term vision. By the end of two days, teachers weren’t just AI-aware — they were AI-ready, with many already starting to explore how AI tools could support entrepreneurship, lesson planning, and personalised learning pathways.

    Students in a classroom setting; two of them are using a laptop to learn about AI.

    Celebrating our achievements and impact 

    At the close of the training, each teacher received a Certificate of Participation, recognising their commitment to professional development and their new capacity to bring AI into the classroom. The awarding of certificates added a sense of accomplishment and pride, reinforcing that teachers are key drivers of technological transformation in education.

    And the impact of the training was measurable:

    • 95% of teachers agreed that the training increased their knowledge and confidence to teach AI concepts
    • 88% of teachers agreed that the training was high quality and useful for preparing them to teach the Experience AI lessons

    But it doesn’t end there, as Vanessa Inziani, Head of Programs at YSK, explains, “Our commitment doesn’t end with the training — we continue to support educators with resources, mentorship, and follow-up to ensure success in delivering the program in the classroom.”

    Looking ahead towards a promising AI journey

    With the rapidly evolving digital landscape, AI is no longer a distant concept — it’s a present-day classroom necessity. Yet, introducing AI into schools isn’t just about technical literacy; it’s about confidence, clarity, and community and the approach the Young Scientist Kenya team and Experience AI delivered during the two-day training is anchored in this belief. 

    As AI continues to shape the global education landscape, programs like Experience AI provide the bridge needed to equip teachers, inspire students, and future-proof education systems. The Kangaru High School session was not a one-off — it was a catalyst for systemic change. 

    Experience AI is scaling. As it expands across Kenya and beyond, the benefits are clear:

    • Empowered educators who gain confidence and skills to integrate AI in their teaching
    • Future-ready students who grasp foundational AI concepts and their real-world applications
    • Sustainable impact as trained teachers go on to influence thousands of learners in their communities

    The journey from fear to fluency starts with a single step, a willingness for us all to explore what’s possible. Together, we can equip educators, inspire students, and shape Kenya’s future, one AI-literate classroom at a time. 

    About Experience AI

    Experience AI is an AI literacy programme, co-developed by the Raspberry Pi Foundation and Google DeepMind, that teaches students aged 11 to 14 about AI and machine learning. Thanks to funding from Google.org, Young Scientists Kenya has partnered with the Raspberry Pi Foundation to provide free training to Kenyan educators, equipping them with the skills they need to effectively deliver the programme in their settings. They are one of two global partners working with the Raspberry Pi Foundation in Kenya.

    You can find out more about the programme on our website: rpf.io/expai-ysk-blogpost

    Website: LINK

  • Bridging the divide: Connecting global communities with Experience AI

    Bridging the divide: Connecting global communities with Experience AI

    Reading Time: 6 minutes

    From smart devices to workplace tools, AI is becoming part of everyday life and a major part of how people are thinking about the future — raising big questions about access, skills, and readiness.

    As governments around the world create AI strategies for the decade ahead, many are seeing an urgent need to address the large gap between how AI tools are already impacting jobs and people’s lives, and making sure young people have the chance to gain the skills and knowledge to keep up with this rapid pace of technological change. This gap is larger still when it comes to opportunities for educationally underserved communities.

    A group of students and educators holding an Experience AI poster.

    That’s why we’re excited to share how Experience AI, our AI literacy programme, is helping organisations around the world create these much-needed opportunities for young people.

    The value of a global network

    Experience AI was co-developed in 2022 by us and industry experts at Google DeepMind with a clear mission: to equip teachers with free, accessible, easy-to-use classroom resources that build AI literacy from the ground up. The programme offers a suite of materials to help students understand real-world applications of AI, the basics of machine learning, and the ethical considerations around these technologies.

    A picture of Philip Colligan delivering a talk.

    In 2023, we started building an international Experience AI network by collaborating with a group of our existing educational partners. We saw a huge amount of interest and received very positive feedback, and through our partnerships we reached an estimated one million young people. In late 2024, with support from Google.org, we tripled the size of our Experience AI partner network to 21, with new organisations joining from across Europe, the Middle East, and Africa. In this way, we aim to reach an additional 2.3 million young people by December 2026, helping them to gain the knowledge and skills to confidently engage with AI in an ever-changing world.

    Each partner in the Experience AI network is a unique educational organisation looking to create lasting social change. Through their local knowledge and networks, we can present Experience AI to educators and students in a way that is engaging and relevant for local communities. 

    A group of students participating in an Experience AI session.

    Partners help us to adapt and translate our resources, all while making sure that the core pedagogy and design principles of Experience AI are preserved. Just as importantly, these organisations train thousands of teachers on how to use the materials, providing educators with free support. With their work, they reach communities that otherwise may have never had the opportunity to learn about AI.

    We asked some of our partners to share their insights on the impact Experience AI is having on the teachers and young people in their communities.

    Building communities

    The Latvian Safer Internet Centre (LSIC), an initiative of our partner, the Latvian Internet Association (LIA), is dedicated to helping young people protect themselves online, and to preparing them for a fast-changing digital economy. As an Experience AI partner, they aim to train 850 teachers and support 43,000 students to build a strong foundation in AI literacy through the programme.

    “We hope to spark a cultural shift in how AI is […] taught in Latvian schools. Our goal is for AI literacy to become a natural part of digital competence education, not an optional extra.”

    A woman is delivering a presentation about Experience AI.

    Based in Riga, the team is travelling to 18 different regions across Latvia to bring in-person professional development to teachers, including those in rural communities far from major cities. By meeting teachers where they are, the LIA are creating invaluable networks for learning and support between communities. Through hands-on training, they are also supporting teachers to bring Experience AI into their own classroom, creating examples which are suited for their learners.

    “We chose an in-person training model because it fosters a more collaborative and engaging environment, especially for teachers who are new to AI. Many educators, particularly those who are less confident with digital tools, benefit from direct interaction, real-time discussions, and the chance to ask questions in a supportive setting.” 

    As an Experience AI partner, the Latvian Internet Association is not just delivering content but working to strengthen digital competency across the country and ensure that no teacher or student is left behind in Latvia’s AI journey. 

    One teacher shares: “The classroom training was truly valuable: it gave us the chance to exchange ideas and reflect on our diverse experiences. Hearing different perspectives was enriching, and I’m glad we’re shaping the future of our schools together.”

    “AI is for everyone”

    EdCamp Ukraine’s mission is to unite educators and help them to grow. Operating from their main base in Kharkiv, near the Eastern border and the frontline of the ongoing war in Ukraine, they see AI as both a tool for new technological breakthroughs and as something that can help build a fairer, more efficient, and resilient society.

    “We firmly believe AI should not only be an object of study — it must become a tool for amplifying human potential. AI should also not be a privilege, but a resource for everyone. We believe the Experience AI programme can truly transform education from the bottom up.”

    A man is delivering a presentation about Experience AI to a group of educators.

    Within their community of 50,000 teachers, EdCamp Ukraine ensures that every educator, regardless of their living conditions or where they work, can access high-quality, relevant, and accessible support. For the organisation, the ongoing situation in Ukraine means being flexible with planning, preparing for a range of different outcomes, and being ready to pivot delivery to different locations or to an online setting when needed. These same considerations apply to EdCamp Ukraine’s teacher community, who need to be ready to adapt their lessons for any scenario.

    “Recognising these war-related challenges helps us see the bigger picture and always have contingency plans in place. We think ahead and develop flexible scenarios.”

    Two educators looking at a laptop screen.

    This year, the team piloted Experience AI through their community of trainers, who, when they’re not training, are busy teaching in the classroom. Teacher Yuliia shared how her students valued the opportunity to be creators, rather than just users of technology:

    “One student, who is an active AI user, kept silent during the lesson. I thought he wasn’t interested, but during the reflection he shared a lot of positive feedback and expressed his gratitude. Other students said it was important that they weren’t just told about AI — they were using it, creating images, and working with apps.”

    A group of educators looking at a laptop screen.

    EdCamp Ukraine plans to roll out training for Ukrainian teachers this autumn, reaching 2,000 teachers and 40,000 young people by the end of next year. 

    More countries, more classrooms 

    Two new partners in Nigeria are about to join the Experience AI network, and there are many more organisations in more countries coming soon. As our partner network continues to grow, we are excited to reach more communities and give more young people around the world the chance to build AI literacy skills and knowledge. 

    You can find out more about Experience AI on the website. If your organisation is interested in partnering with us to deliver Experience AI, please register your interest and we will let you know about opportunities to work with us.

    Website: LINK

  • Experience AI: The story so far

    Experience AI: The story so far

    Reading Time: 5 minutes

    In April 2023, we launched our first Experience AI resources, developed in partnership with Google DeepMind to support educators to engage their students in learning about the topic of AI. Since then, the Experience AI programme has grown rapidly, reaching thousands of educators all over the world. Read on to find out more about the impact of our resources, and what we are learning.

    The Experience AI resources

    The Experience AI resources are designed to help educators introduce AI and AI safety to 11- to 14-year-olds. They consist of:

    • Foundations of AI: a comprehensive unit of six lessons including lesson plans, slide decks, activities, videos, and more to support educators to introduce AI and machine learning to young people
    • Two standalone lessons:
      • Large language models (LLMs): a lesson designed to help young people discover how large language models work, their benefits, and why their outputs are not always reliable
      • Ecosystems and AI — Biology: a lesson providing an opportunity for young people to explore how AI applications are supporting animal conservation
    • AI safety: a set of resources with a flexible design to support educators in a range of settings to equip young people with the knowledge and skills to responsibly and safely navigate the challenges associated with AI

    We also offer a free online course, Understanding AI for educators, to help educators prepare to teach about AI.

    International expansion

    The launch of Experience AI came at an important time: AI technologies are playing an ever-growing role in our everyday lives, so it is crucial for young people to gain the understanding and skills they need to critically engage with these technologies. While the resources were initially designed for use by educators in the UK, they immediately attracted interest from educators across the world, as well as individuals wanting to learn about AI. The resources have now been downloaded over 325,000 times by people from over 160 countries. This includes downloads from over 7000 educators worldwide, who will collectively reach an estimated 1.2 million young people.

    Photo of an educator teaching an Experience AI lesson.

    Thanks to funding from Google DeepMind and Google.org, we have also been working with partners from across the globe to localise and translate the resources for learners and educators in their countries, and provide training to support local educators to deliver the lessons. The educational resources are now available in up to 15 languages, and to date, we have trained over 100 representatives from 20 international partner organisations, who will go on to train local educators. Five of these organisations have begun onward training already, collectively training over 1500 local educators so far.

    The impact of Experience AI

    The Experience AI resources have been well received by students and educators. Based on responses to our follow-up surveys, in countries where we have partners: 

    • 95% of educators agreed that the Experience AI sessions have increased their students’ knowledge of AI concepts 
    • 90% of young people (including young people in formal and non-formal education settings and learning independently) indicated that they better understand what AI and machine learning are
    Photo of a young person learning about AI on a laptop.

    This is backed up by qualitative feedback from surveys and interviews.

    “Students’ perception and understanding of AI has improved and corrected. They realised they can contribute and be a part of the [development], instead of only users.” – Noorlaila, educator, SMK Cyberjaya, Malaysia

    “[Students] found it interesting in the sense that it’s relevant information and they didn’t know what information was used for training models.” – Teacher, Liceul Tehnologic “Crisan” Criscior, Romania

    “Based on my knowledge and learning about AI, I now appreciate the definition of AI as well as its implementation.” – Student, Changamwe JSS, Kenya

    Photo of a group of educators participating in an Experience AI teacher training event in Kenya.

    The training and resources also support educators to feel more confident to teach about AI:

    • 93% of international partner representatives who participated in our training agreed that the training increased their knowledge of AI concepts
    • 88% of educators receiving onward training by our international partners agreed that the training increased their confidence to teach AI concepts
    • 87% of educator respondents from our ‘Understanding AI for educators’ online course agreed that the course was useful for supporting young people

    “It was a wonderful experience for me to join this workshop. Truly I was able to learn a lot about AI and I feel more confident now to teach the kids back at school about this new knowledge.” – Nur, educator, SMK Bandar Tasek Mutiara, trained by our partner Penang Science Cluster, Malaysia

    “This was one of the best information sessions I’ve been to! So, so helpful!” – Meagan, educator, University of Alberta, trained by our partner Digital Moment, Canada

    “The layout of the course in terms of content structuring is amazing. I love the discussion forum and the insightful yet empathetic responses by the course moderators on the discussion board. Honestly, I am really glad I started my AI in education journey with you.” – Priyanka, head teacher (primary level), United Arab Emirates, online course participant

    What are we learning?

    We are committed to continually improving our resources based on feedback from users. A recent review of feedback from educators highlighted key aspects of the resources that educators value most, as well as some challenges educators are facing and possible areas for improvement. For example, educators particularly like the interactive aspects, the clear structure and explanations, and the videos featuring professionals from the AI industry. We are continuing to look for ways we can better support educators to adapt the content and language to better support students in their context, fit Experience AI into their school timetables, and overcome technical barriers. 

    We value feedback on our resources and will continue to highlight the importance of AI education in schools and work with partners across the globe to adapt our resources for different contexts.

    Get involved

    If you would like to try out our Experience AI resources, head to experience-ai.org, where you can find our free resources and online course, as well as information about local partners in your area.

    Website: LINK

  • Teaching AI safety: Lessons from Romanian educators

    Teaching AI safety: Lessons from Romanian educators

    Reading Time: 6 minutes

    This blog post has been written by our Experience AI partners in Romania, Asociatia Techsoup, who piloted our new AI safety resources with Romanian teachers at the end of 2024.

    Last year, we had the opportunity to pedagogically test the new three resources on AI safety and see first-hand the transformative effect they have on teachers and students. Here’s what we found.

    Students in class.

    Romania struggles with the digital skills gap

    To say the internet is ubiquitous in Romania is an understatement: Romania has one of the fastest internets in the world (11th place), an impressive mobile internet penetration (86% of the population), and Romania is leading Central and Eastern Europe in terms of percentage of population that is online (89% of the entire population). Unsurprisingly, most of Romania’s internet users are also social media users. 

    When you combine that with recent national initiatives, such as

    • The introduction of Information Technology and Informatics in the middle-school curriculum in 2017 as a compulsory subject
    • A Digital Agenda as a national strategy since 2015 
    • Allocation of over 20% of its most recent National Recovery and Resilience Fund for digital transition

    one might expect a similar lead in digital skills, both basic and advanced.

    But only 28% of the population, well below the 56% EU average, and just 47% of young people between 16 and 24 have basic digital skills — the lowest percentage in the European Union. 

    Findings from the latest International Computer and Information Literacy Study (ICILS, 2023)  underscore the urgent need to improve young people’s digital skills. Just 4% of students in Romania were scored at level 3 of 4, meaning they can demonstrate the capacity to work independently when using computers as information gathering and management tools, and are able, for example, to recognise that the credibility of web‐based information can be influenced by the identity, expertise, and motives of the people who create, publish, and share it.

    Students use a computer in class.

    Furthermore, 33% of students were assessed as level 1, while a further 40% of students did not even reach the minimum level set out in the ICILS, which means that they are unable to demonstrate even basic operational skills with computers or an understanding of computers as tools for completing simple tasks. For example, they can’t use computers to perform routine research and communication tasks under explicit instruction, and can’t manage simple content creation, such as entering text or images into pre‐existing templates.

    Why we wanted to pilot the Experience AI safety resources

    Add AI — and particularly generative AI — to this mix, and it spells huge trouble for educational systems unprepared for the fast rate of AI adoption by their students. Teachers need to be given the right pedagogical tools and support to address these new disruptions and the AI-related challenges that are adding to the existing post-pandemic ones.

    This is why we at Asociația Techsoup have been enthusiastically supporting Romanian teachers to deliver the Experience AI curriculum created by the Raspberry Pi Foundation and Google DeepMind. We have found it to be the best pedagogical support that prepares students to fully understand AI and to learn how to use machine learning to solve real-world problems.

    Testing the resources

    Last year, we had the opportunity to pedagogically test the new three resources on AI Safety and see first-hand the transformative effect they have on teachers and students.

    Students in class.

    We worked closely with 8 computer science teachers in 8 Romanian schools from rural and small urban areas, reaching approximately 340 students between the ages of 13 and 18.

    Before the teachers used the resources in the classroom, we worked with them in online community meetings and one-to-one phone conversations to help them review the available lesson plans, videos, and activity guides, to familiarise themselves with the structure, and to plan how to adapt the sessions to their classroom context. 

    In December 2024, the teachers delivered the resources to their students. They guided students through key topics in AI safety, including understanding how to protect their data, critically evaluating data to spot fake news, and how to use AI tools responsibly. Each session incorporated a dynamic mix of teaching methods, including short videos and presentations delivering core messages, unplugged activities to reinforce understanding, and structured discussions to encourage critical thinking and reflection. 

    Gathering feedback from users

    We then interviewed all the teachers to understand their challenges in delivering such a new curriculum and we also observed two of the lessons. We took time to discuss with students and gather in-depth feedback on their learning experiences, perspectives on AI safety, and their overall engagement with the activities, in focus groups and surveys.

    Feedback gathered in this pilot was then incorporated into the resources and recommendations given to teachers as part of the AI safety materials.

    Teachers’ perspectives on the resources

    It became obvious quite fast for both us and our teachers that the AI safety resources cover a growing and unaddressed need: to prepare our students for the ubiquitous presence of AI tools, which are on the road to becoming as ubiquitous as the internet itself.

    A teacher and students in class.

    Teachers evaluated the resources as very effective, giving them the opportunity to have authentic and meaningful conversations with their students about the world we live in. The format of the lessons was engaging — one of the teachers was so enthusiastic that she actually managed to keep students away from their phones for the whole lesson. 

    They also appreciated the pedagogical quality of the resources, especially the fact that everything is ready to use in class and that they could access them for free. In interviews, they also appreciated that they themselves also learnt a lot from the lessons:

    “For me it was a wake-up call. I was living in my bubble, in which I don’t really use these tools that much. But the world we live in is no longer the world I knew. … So such a lesson also helps us to learn and to discover the children in another context, – Carmen Melinte, a computer science teacher at the Colegiul Național Grigore Moisil in the small city of Onești, in north-east Romania, one of the EU regions with the greatest poverty risk.

    What our students think about the resources

    Students enjoyed discussing real-world scenarios and admitted that they don’t really have adults around whom they can talk to about the AI tools they use. They appreciated the interactive activities where they worked in pairs or groups and the games where they pretended to be creators of AI apps, thinking about safety features they could implement:

    “I had never questioned AI, as long as it did my homework,” said one student in our focus groups, where the majority of students admitted that they are already using large language models (LLMs) for most of their homework.

    “I really liked that I found out what is behind that ‘Accept all’ and now I think twice before giving my data,” – Student at the end of the ‘Your data and AI’ activities.

    “Activities put me in a situation where I had to think from the other person’s shoes and think twice before sharing my personal data,” commented another student.

    Good starting point

    This is a good first step: there is an acute need for conversations between young people and adults around AI tools, how to think about them critically, and how to use them safely. School is the right place to start these conversations and activities, as teachers are still trusted by most Romanian students to help them understand the world.

    Students use a computer in class.

    But to be able to do that, we need to be serious about equipping teachers with pedagogically sound resources that they can use in class, as well as training them, supporting them, and making sure that most of their time is dedicated to teaching, and not administration. It might seem a slow process, but it is the best way to help our students become responsible, ethical and accountable digital citizens.

    We are deeply grateful to the brave, passionate teachers in our community who gave the AI safety resources a try and of course to our partners at the Raspberry Pi Foundation for giving us the opportunity to lead this pilot.

    If you are a teacher anywhere in the world, give them a try today to celebrate Safer Internet Day: rpf.io/aisafetyromania

    Website: LINK

  • Helping young people navigate AI safely

    Helping young people navigate AI safely

    Reading Time: 5 minutes

    AI safety and Experience AI

    As our lives become increasingly intertwined with AI-powered tools and systems, it’s more important than ever to equip young people with the skills and knowledge they need to engage with AI safely and responsibly. AI literacy isn’t just about understanding the technology — it’s about fostering critical conversations on how to integrate AI tools into our lives while minimising potential harm — otherwise known as ‘AI safety’.

    The UK AI Safety Institute defines AI safety as: “The understanding, prevention, and mitigation of harms from AI. These harms could be deliberate or accidental; caused to individuals, groups, organisations, nations or globally; and of many types, including but not limited to physical, psychological, social, or economic harms.”

    As a result of this growing need, we’re thrilled to announce the latest addition to our AI literacy programme, Experience AI —  ‘AI safety: responsibility, privacy, and security’. Co-developed with Google DeepMind, this comprehensive suite of free resources is designed to empower 11- to 14-year-olds to understand and address the challenges of AI technologies. Whether you’re a teacher, youth leader, or parent, these resources provide everything you need to start the conversation.

    Linking old and new topics

    AI technologies are providing huge benefits to society, but as they become more prevalent we cannot ignore the challenges AI tools bring with them. Many of the challenges aren’t new, such as concerns over data privacy or misinformation, but AI systems have the potential to amplify these issues.

    Digital image depicting computer science related elements.

    Our resources use familiar online safety themes — like data privacy and media literacy — and apply AI concepts to start the conversation about how AI systems might change the way we approach our digital lives.

    Each session explores a specific area:

    • Your data and AI: How data-driven AI systems use data differently to traditional software and why that changes data privacy concerns
    • Media literacy in the age of AI: The ease of creating believable, AI-generated content and the importance of verifying information
    • Using AI tools responsibly: Encouraging critical thinking about how AI is marketed and understanding personal and developer responsibilities

    Each topic is designed to engage young people to consider both their own interactions with AI systems and the ethical responsibilities of developers.

    Designed to be flexible

    Our AI safety resources have flexibility and ease of delivery at their core, and each session is built around three key components:

    1. Animations: Each session begins with a concise, engaging video introducing the key AI concept using sound pedagogy — making it easy to deliver and effective. The video then links the AI concept to the online safety topic and opens threads for thought and conversation, which the learners explore through the rest of the activities. 
    2. Unplugged activities: These hands-on, screen-free activities — ranging from role-playing games to thought-provoking challenges — allow learners to engage directly with the topics.
    3. Discussion questions: Tailored for various settings, these questions help spark meaningful conversations in classrooms, clubs, or at home.

    Experience AI has always been about allowing everyone — including those without a technical background or specialism in computer science — to deliver high-quality AI learning experiences, which is why we often use videos to support conceptual learning. 

    Digital image featuring two computer screens. One screen seems to represent errors, or misinformation. The other depicts a person potentially plotting something.

    In addition, we want these sessions to be impactful in many different contexts, so we included unplugged activities so that you don’t need a computer room to run them! There is also advice on shortening the activities or splitting them so you can deliver them over two sessions if you want. 

    The discussion topics provide a time-efficient way of exploring some key implications with learners, which we think will be more effective in smaller groups or more informal settings. They also highlight topics that we feel are important but may not be appropriate for every learner, for example, the rise of inappropriate deepfake images, which you might discuss with a 14-year-old but not an 11-year-old.

    A modular approach for all contexts

    Our previous resources have all followed a format suitable for delivery in a classroom, but for these resources, we wanted to widen the potential contexts in which they could be used. Instead of prescribing the exact order to deliver them, educators are encouraged to mix and match activities that they feel would be effective for their context. 

    Digital image depicting computer science related elements.

    We hope this will empower anyone, no matter their surroundings, to have meaningful conversations about AI safety with young people. 

    The modular design ensures maximum flexibility. For example:

    • A teacher might combine the video with an unplugged activity and follow-up discussion for a 60-minute lesson
    • A club leader could show the video and run a quick activity in a 30-minute session
    • A parent might watch the video and use the discussion questions during dinner to explore how generative AI shapes the content their children encounter

    The importance of AI safety education

    With AI becoming a larger part of daily life, young people need the tools to think critically about its use. From understanding how their data is used to spotting misinformation, these resources are designed to build confidence and critical thinking in an AI-powered world.

    AI safety is about empowering young people to be informed consumers of AI tools. By using these resources, you’ll help the next generation not only navigate AI, but shape its future. Dive into our materials, start a conversation, and inspire young minds to think critically about the role of AI in their lives.

    Ready to get started? Explore our AI safety resources today: rpf.io/aisafetyblog. Together, we can empower every child to thrive in a digital world.

    Website: LINK

  • The need to invest in AI skills in schools

    The need to invest in AI skills in schools

    Reading Time: 6 minutes

    Earlier this week, the UK Government published its AI Opportunities Action Plan, which sets out an ambitious vision to maintain the UK’s position as a global leader in artificial intelligence. 

    Whether you’re from the UK or not, it’s a good read, setting out the opportunities and challenges facing any country that aspires to lead the world in the development and application of AI technologies. 

    In terms of skills, the Action Plan highlights the need for the UK to train tens of thousands more AI professionals by 2030 and sets out important goals to expand education pathways into AI, invest in new undergraduate and master’s scholarships, tackle the lack of diversity in the sector, and ensure that the lifelong skills agenda focuses on AI skills. 

    Photo of a group of young people working through some Experience AI content.

    This is all very important, but the Action Plan fails to mention what I think is one of the most important investments we need to make, which is in schools. 

    “Most people overestimate what they can achieve in a year and underestimate what they can achieve in ten years.”

    While reading the section of the Action Plan that dealt with AI skills, I was reminded of this quote attributed to Bill Gates, which was adapted from Roy Amara’s law of technology. We tend to overestimate what we can achieve in the short term and underestimate what we can achieve in the long term. 

    In focusing on the immediate AI gold rush, there is a risk that the government overlooks the investments we need to make right now in schools, which will yield huge returns — for individuals, communities, and economies — over the long term. Realising the full potential of a future where AI technologies are ubiquitous requires genuinely long-term thinking, which isn’t always easy for political systems that are designed around short-term results. 

    Photo focused on a young person working on a computer in a classroom.

    But what are those investments? The Action Plan rightly points out that the first step for the government is to accurately assess the size of the skills gap. As part of that work, we need to figure out what needs to change in the school system to build a genuinely diverse and broad pipeline of young people with AI skills. The good news is that we’ve already made a lot of progress. 

    AI literacy

    Over the past three years, the Raspberry Pi Foundation and our colleagues in the Raspberry Pi Computing Education Research Centre at the University of Cambridge have been working to understand and define what AI literacy means. That led us to create a research-informed model for AI literacy that unpacks the concepts and knowledge that constitute a foundational understanding of AI. 

    In partnership with one of the leading UK-based AI companies, Google DeepMind, we used that model to create Experience AI. This suite of classroom resources, teacher professional development, and hands-on practical activities enables non-specialist teachers to deliver engaging lessons that help young people build that foundational understanding of AI technologies. 

    We’ve seen huge demand from UK schools already, with thousands of lessons taught in UK schools, and we’re delighted to be working with Parent Zone to support a wider roll out in the UK, along with free teacher professional development.  

    CEO Philip Colligan and Prime Minister Keir Starmer at the UK launch of Experience AI.
    CEO Philip Colligan and Prime Minister Keir Starmer at the UK launch of Experience AI.

    With the generous support of Google.org, we are working with a global network of education partners — from Nigeria to Nepal — to localise and translate these resources, and deliver locally organised teacher professional development. With over 1 million young people reached already, Experience AI can plausibly claim to be the most widely used AI literacy curriculum in the world, and we’re improving it all the time. 

    All of the materials are available for anyone to use and can be found on the Experience AI website.

    There is no AI without CS

    With the CEO of GitHub claiming that it won’t be long before 80% of code is written by AI, it’s perhaps not surprising that some people are questioning whether we still need to teach kids how to code.

    I’ll have much more to say on this in a future blog post, but the short answer is that computer science and programming is set to become more — not less — important in the age of AI. This is particularly important if we want to tackle the lack of diversity in the tech sector and ensure that young people from all backgrounds have the opportunity to shape the AI-enabled future that they will be living in. 

    Close up of two young people working at a computer.

    The simple truth is that there is no artificial intelligence without computer science. The rapid advances in AI are likely to increase the range of problems that can be solved by technology, creating demand for more complex software, which in turn will create demand for more programmers with increasingly sophisticated and complex skills. 

    That’s why we’ve set ourselves the ambition that we will inspire 10 million more young people to learn how to get creative with technology over the next 10 years through Code Club. 

    Curriculum reform 

    But we also need to think about what needs to change in the curriculum to ensure that schools are equipping young people with the skills and knowledge they need to thrive in an AI-powered world. 

    That will mean changes to the computer science curriculum, providing different pathways that reflect young people’s interests and passions, but ensuring that every child leaves school with a qualification in computer science or applied digital skills. 

    It’s not just computer science courses. We need to modernise mathematics and figure out what a data science curriculum looks like (and where it fits). We also need to recognise that AI skills are just as relevant to biology, geography, and languages as they are to computer science. 

    A teacher assisting a young person with a coding project.

    To be clear, I am not talking about how AI technologies will save teachers time, transform assessments, or be used by students to write essays. I am talking about the fundamentals of the subjects themselves and how AI technologies are revolutionising the sciences and humanities in practice in the real world. 

    These are all areas where the Raspberry Pi Foundation is engaged in original research and experimentation. Stay tuned. 

    Supporting teachers

    All of this needs to be underpinned by a commitment to supporting teachers, including through funding and time to engage in meaningful professional development. This is probably the biggest challenge for policy makers at a time when budgets are under so much pressure. 

    For any nation to plausibly claim that it has an Action Plan to be an AI superpower, it needs to recognise the importance of making the long-term investment in supporting our teachers to develop the skills and confidence to teach students about AI and the role that it will play in their lives. 

    I’d love to hear what you think and if you want to get involved, please get in touch.

    Website: LINK

  • Exploring how well Experience AI maps to UNESCO’s AI competency framework for students

    Exploring how well Experience AI maps to UNESCO’s AI competency framework for students

    Reading Time: 9 minutes

    During this year’s annual Digital Learning Week conference in September, UNESCO launched their AI competency frameworks for students and teachers. 

    What is the AI competency framework for students? 

    The UNESCO competency framework for students serves as a guide for education systems across the world to help students develop the necessary skills in AI literacy and to build inclusive, just, and sustainable futures in this new technological era.

    It is an exciting document because, as well as being comprehensive, it’s the first global framework of its kind in the area of AI education.

    The framework serves three specific purposes:

    • It offers a guide on essential AI concepts and skills for students, which can help shape AI education policies or programs at schools
    • It aims to shape students’ values, knowledge, and skills so they can understand AI critically and ethically
    • It suggests a flexible plan for when and how students should learn about AI as they progress through different school grades

    The framework is a starting point for policy-makers, curriculum developers, school leaders, teachers, and educational experts to look at how it could apply in their local contexts. 

    It is not possible to create a single curriculum suitable for all national and local contexts, but the framework flags the necessary competencies for students across the world to acquire the values, knowledge, and skills necessary to examine and understand AI critically from a holistic perspective.

    How does Experience AI compare with the framework?

    A group of researchers and curriculum developers from the Raspberry Pi Foundation, with a focus on AI literacy, attended the conference and afterwards we tasked ourselves with taking a deep dive into the student framework and mapping our Experience AI resources to it. Our aims were to:

    • Identify how the framework aligns with Experience AI
    • See how the framework aligns with our research-informed design principles
    • Identify gaps or next steps

    Experience AI is a free educational programme that offers cutting-edge resources on artificial intelligence and machine learning for teachers, and their students aged 11 to 14. Developed in collaboration with the Raspberry Pi Foundation and Google DeepMind, the programme provides everything that teachers need to confidently deliver engaging lessons that will teach, inspire, and engage young people about AI and the role that it could play in their lives. The current curriculum offering includes a ‘Foundations of AI’ 6-lesson unit, 2 standalone lessons (‘AI and ecosystems’ and ‘Large language models’), and the 3 newly released AI safety resources. 

    Working through each lesson objective in the Experience AI offering, we compared them with each curricular goal to see where they overlapped. We have made this mapping publicly available so that you can see this for yourself: Experience AI – UNESCO AI Competency framework students – learning objective mapping (rpf.io/unesco-mapping)

    The first thing we discovered was that the mapping of the objectives did not have a 1:1 basis. For example, when we looked at a learning objective, we often felt that it covered more than one curricular goal from the framework. That’s not to say that the learning objective fully met each curricular goal, rather that it covers elements of the goal and in turn the student competency. 

    Once we had completed the mapping process, we analysed the results by totalling the number of objectives that had been mapped against each competency aspect and level within the framework.

    This provided us with an overall picture of where our resources are positioned against the framework. Whilst the majority of the objectives for all of the resources are in the ‘Human-centred mindset’ category, the analysis showed that there is still a relatively even spread of objectives in the other three categories (Ethics of AI, ML techniques and applications, and AI system design). 

    As the current resource offering is targeted at the entry level to AI literacy, it is unsurprising to see that the majority of the objectives were at the level of ‘Understand’. It was, however, interesting to see how many objectives were also at the ‘Apply’ level. 

    It is encouraging to see that the different resources from Experience AI map to different competencies in the framework. For example, the 6-lesson foundations unit aims to give students a basic understanding of how AI systems work and the data-driven approach to problem solving. In contrast, the AI safety resources focus more on the principles of Fairness, Accountability, Transparency, Privacy, and Security (FATPS), most of which fall more heavily under the ethics of AI and human-centred mindset categories of the competency framework. 

    What did we learn from the process? 

    Our principles align 

    We built the Experience AI resources on design principles based on the knowledge curated by Jane Waite and the Foundation’s researchers. One of our aims of the mapping process was to see if the principles that underpin the UNESCO competency framework align with our own.

    Avoiding anthropomorphism 

    Anthropomorphism refers to the concept of attributing human characteristics to objects or living beings that aren’t human. For reasons outlined in the blog I previously wrote on the issue, a key design principle for Experience AI is to avoid anthropomorphism at all costs. In our resources, we are particularly careful with the language and images that we use. Putting the human in the process is a key way in which we can remind students that it is humans who design and are responsible for AI systems. 

    Young people use computers in a classroom.

    It was reassuring to see that the UNESCO framework has many curricular goals that align closely to this, for example:

    • Foster an understanding that AI is human-led
    • Facilitate an understanding on the necessity of exercising sufficient human control over AI
    • Nurture critical thinking on the dynamic relationship between human agency and machine agency

    SEAME

    The SEAME framework created by Paul Curzon and Jane Waite offers a way for teachers, resource developers, and researchers to talk about the focus of AI learning activities by separating them into four layers: Social and Ethical (SE), Application (A), Models (M), and Engines (E). 

    The SEAME model and the UNESCO AI competency framework take two different approaches to categorising AI education — SEAME describes levels of abstraction for conceptual learning about AI systems, whereas the competency framework separates concepts into strands with progression. We found that although the alignment between the frameworks is not direct, the same core AI and machine learning concepts are broadly covered across both. 

    Computational thinking 2.0 (CT2.0)

    The concept of computational thinking 2.0 (a data-driven approach) stems from research by Professor Matti Tedre and Dr Henriikka Vartiainen from the University of Eastern Finland. The essence of this approach establishes AI as a different way to solve problems using computers compared to a more traditional computational thinking approach (a rule-based approach). This does not replace the traditional computational approach, but instead requires students to approach the problem differently when using AI as a tool. 

    An educator points to an image on a student's computer screen.

    The UNESCO framework includes many references within their curricular goals that places the data-driven approach at the forefront of problem solving using AI, including:

    • Develop conceptual knowledge on how AI is trained based on data 
    • Develop skills on assessing AI systems’ need for data, algorithms, and computing resources

    Where we slightly differ in our approach is the regular use of the term ‘algorithm’, particularly in the Understand and Apply levels of the framework. We have chosen to differentiate AI systems from traditional computational thinking approaches by avoiding the term ‘algorithm’ at the foundational stage of AI education. We believe the learners need a firm mental model of data-driven systems before students can understand that the Model and Engines of the SEAME model refer to algorithms (which would possibly correspond to the Create stage of the UNESCO framework). 

    We can identify areas for exploration

    As part of the international expansion of Experience AI, we have been working with partners from across the globe to bring AI literacy education to students in their settings. Part of this process has involved working with our partners to localise the resources, but also to provide training on the concepts covered in Experience AI. During localisation and training, our partners often have lots of queries about the lesson on bias. 

    As a result, we decided to see if mapping taught us anything about this lesson in particular, and if there was any learning we could take from it. At close inspection, we found that the lesson covers two out of the three curricular goals for the Understand element of the ‘Ethics of AI’ category (Embodied ethics). 

    Specifically, we felt the lesson:

    • Illustrates dilemmas around AI and identifies the main reasons behind ethical conflicts
    • Facilitates scenario-based understandings of ethical principles on AI and their personal implications

    What we felt isn’t covered in the lesson is:

    • Guide the embodied reflection and internalisation of ethical principles on AI

    Exploring this further, the framework describes this curricular goal as:

    “Guide students to understand the implications of ethical principles on AI for their human rights, data privacy, safety, human agency, as well as for equity, inclusion, social justice and environmental sustainability. Guide students to develop embodied comprehension of ethical principles; and offer opportunities to reflect on personal attitudes that can help address ethical challenges (e.g. advocating for inclusive interfaces for AI tools, promoting inclusion in AI and reporting discriminatory biases found in AI tools).”

    We realised that this doesn’t mean that the lesson on bias is ineffective or incomplete, but it does help us to think more deeply about the learning objective for the lesson. This may be something we will look to address in future iterations of the foundations unit or even in the development of new resources. What we have identified is a process that we can follow, which will help us with our decision making in the next phases of resource development. 

    How does this inform our next steps?

    As part of the analysis of the resources, we created a simple heatmap of how the Experience AI objectives relate to the UNESCO progression levels. As with the barcharts, the heatmap indicated that the majority of the objectives sit within the Understand level of progression, with fewer in Apply, and fewest in Create. As previously mentioned, this is to be expected with the resources being “foundational”. 

    The heatmap has, however, helped us to identify some interesting points about our resources that warrant further thought. For example, under the ‘Human-centred mindset’ competency aspect, there are more objectives under Apply than there are Understand. For ‘AI system design’, architecture design is the least covered aspect of Apply. 

    By identifying these areas for investigation, again it shows that we’re able to add the learnings from the UNESCO framework to help us make decisions.

    What next? 

    This mapping process has been a very useful exercise in many ways for those of us working on AI literacy at the Raspberry Pi Foundation. The process of mapping the resources gave us an opportunity to have deep conversations about the learning objectives and question our own understanding of our resources. It was also very satisfying to see that the framework aligns well with our own researched-informed design principles, such as the SEAME model and avoiding anthropomorphisation. 

    The mapping process has been a good starting point for us to understand UNESCO’s framework and we’re sure that it will act as a useful tool to help us make decisions around future enhancements to our foundational units and new free educational materials. We’re looking forward to applying what we’ve learnt to our future work! 

    Website: LINK

  • Free online course on understanding AI for educators

    Free online course on understanding AI for educators

    Reading Time: 5 minutes

    To empower every educator to confidently bring AI into their classroom, we’ve created a new online training course called ‘Understanding AI for educators’ in collaboration with Google DeepMind. By taking this course, you will gain a practical understanding of the crossover between AI tools and education. The course includes a conceptual look at what AI is, how AI systems are built, different approaches to problem-solving with AI, and how to use current AI tools effectively and ethically.

    Image by Mudassar Iqbal from Pixabay

    In this post, I will share our approach to designing the course and some of the key considerations behind it — all of which you can apply today to teach your learners about AI systems.

    Design decisions: Nurturing knowledge and confidence

    We know educators have different levels of confidence with AI tools — we designed this course to help create a level playing field. Our goal is to uplift every educator, regardless of their prior experience, to a point where they feel comfortable discussing AI in the classroom.

    Three computer science educators discuss something at a screen.

    AI literacy is key to understanding the implications and opportunities of AI in education. The course provides educators with a solid conceptual foundation, enabling them to ask the right questions and form their own perspectives.

    As with all our AI learning materials that are part of Experience AI, we’ve used specific design principles for the course:

    • Choosing language carefully: We never anthropomorphise AI systems, replacing phrases like “The model understands” with “The model analyses”. We do this to make it clear that AI is just a computer system, not a sentient being with thoughts or feelings.
    • Accurate terminology: We avoid using AI as a singular noun, opting instead for the more accurate ‘AI tool’ when talking about applications or ‘AI system’ when talking about underlying component parts. 
    • Ethics: The social and ethical impacts of AI are not an afterthought but highlighted throughout the learning materials.

    Three main takeaways

    The course offers three main takeaways any educator can apply to their teaching about AI systems. 

    1. Communicating effectively about AI systems

    Deciding the level of detail to use when talking about AI systems can be difficult — especially if you’re not very confident about the topic. The SEAME framework offers a solution by breaking down AI into 4 levels: social and ethical, application, model, and engine. Educators can focus on the level most relevant to their lessons and also use the framework as a useful structure for classroom discussions.

    The SEAME framework gives you a simple way to group learning objectives and resources related to teaching AI and ML, based on whether they focus on social and ethical aspects (SE), applications (A), models (M), or engines (E, i.e. how AI works).

    You might discuss the impact a particular AI system is having on society, without the need to explain to your learners how the model itself has been trained or tested. Equally, you might focus on a specific machine learning model to look at where the data used to create it came from and consider the effect the data source has on the output. 

    2. Problem-solving approaches: Predictive vs. generative AI

    AI applications can be broadly separated into two categories: predictive and generative. These two types of AI model represent two vastly different approaches to problem-solving. 

    People create predictive AI models to make predictions about the future. For example, you might create a model to make weather forecasts based on previously recorded weather data, or to recommend new movies to you based on your previous viewing history. In developing predictive AI models, the problem is defined first — then a specific dataset is assembled to help solve it. Therefore, each predictive AI model usually is only useful for a small number of applications.

    Seventeen multicoloured post-it notes are roughly positioned in a strip shape on a white board. Each one of them has a hand drawn sketch in pen on them, answering the prompt on one of the post-it notes "AI is...." The sketches are all very different, some are patterns representing data, some are cartoons, some show drawings of things like data centres, or stick figure drawings of the people involved.
    Rick Payne and team / Better Images of AI / Ai is… Banner / CC-BY 4.0

    Generative AI models are used to generate media (such as text, code, images, or audio). The possible applications of these models are much more varied because people can use media in many different kinds of ways. You might say that the outputs of generative AI models could be used to solve — or at least to partially solve — any number of problems, without these problems needing to be defined before the model is created.

    3. Using generative AI tools: The OCEAN process

    Generative AI systems rely on user prompts to generate outputs. The OCEAN process, outlined in the course, offers a simple yet powerful framework for prompting AI tools like Gemini, Stable Diffusion or ChatGPT. 

    Three groups of icons representing people have shapes travelling between them and a page in the middle of the image. The page is a simple rectangle with straight lines representing data. The shapes traveling towards the page are irregular and in squiggly bands.
    Yasmine Boudiaf & LOTI / Better Images of AI / Data Processing / CC-BY 4.0

    The first three steps of the process help you write better prompts that will result in an output that is as close as possible to what you are looking for, while the last two steps outline how to improve the output:

    1. Objective: Clearly state what you want the model to generate
    2. Context: Provide necessary background information
    3. Examples: Offer specific examples to fine-tune the model’s output
    4. Assess: Evaluate the output 
    5. Negotiate: Refine the prompt to correct any errors in the output

    The final step in using any generative AI tool should be to closely review or edit the output yourself. These tools will very quickly get you started but you’ll always have to rely on your own human effort to ensure the quality of your work. 

    Helping educators to be critical users

    We believe the knowledge and skills our ‘Understanding AI for educators’ course teaches will help any educator determine the right AI tools and concepts to bring into their classroom, regardless of their specialisation. Here’s what one course participant had to say:

    “From my inexperienced viewpoint, I kind of viewed AI as a cheat code. I believed that AI in the classroom could possibly be a real detriment to students and eliminate critical thinking skills.

    After learning more about AI [on the course] and getting some hands-on experience with it, my viewpoint has certainly taken a 180-degree turn. AI definitely belongs in schools and in the workplace. It will take time to properly integrate it and know how to ethically use it. Our role as educators is to stay ahead of this trend as opposed to denying AI’s benefits and falling behind.” – ‘Understanding AI for educators’ course participant

    All our Experience AI resources — including this online course and the teaching materials — are designed to foster a generation of AI-literate educators who can confidently and ethically guide their students in navigating the world of AI.

    You can sign up to the course for free here: 

    A version of this article also appears in Hello World issue 25, which will be published on Monday 23 September and will focus on all things generative AI and education.

    Website: LINK

  • Impact of Experience AI: Reflections from students and teachers

    Impact of Experience AI: Reflections from students and teachers

    Reading Time: 5 minutes

    “I’ve enjoyed actually learning about what AI is and how it works, because before I thought it was just a scary computer that thinks like a human,” a student learning with Experience AI at King Edward’s School, Bath, UK, told us. 

    This is the essence of what we aim to do with our Experience AI lessons, which demystify artificial intelligence (AI) and machine learning (ML). Through Experience AI, teachers worldwide are empowered to confidently deliver engaging lessons with a suite of resources that inspire and educate 11- to 14-year-olds about AI and the role it could play in their lives.

    “I learned new things and it changed my mindset that AI is going to take over the world.” – Student, Malaysia

    Experience AI students in Malaysia
    Experience AI students in Malaysia

    Developed by us with Google DeepMind, our first set of Experience AI lesson resources was aimed at a UK audience and launched in April 2023. Next we released tailored versions of the resources for 5 other countries, working in close partnership with organisations in Malaysia, Kenya, Canada, Romania, and India. Thanks to new funding from Google.org, we’re now expanding Experience AI for 16 more countries and creating new resources on AI safety, with the aim of providing leading-edge AI education for more than 2 million young people across Europe, the Middle East, and Africa. 

    In this blog post, you’ll hear directly from students and teachers about the impact the Experience AI lessons have had so far. 

    Case study:  Experience AI in Malaysia

    Penang Science Cluster in Malaysia is among the first organisations we’ve partnered with for Experience AI. Speaking to Malaysian students learning with Experience AI, we found that the lessons were often very different from what they had expected. 

    Launch of Experience AI in Malaysia
    Launch of Experience AI in Malaysia

    “I actually thought it was going to be about boring lectures and not much about AI but more on coding, but we actually got to do a lot of hands-on activities, which are pretty fun. I thought AI was just about robots, but after joining this, I found it could be made into chatbots or could be made into personal helpers.” – Student, Malaysia

    “Actually, I thought AI was mostly related to robots, so I was expecting to learn more about robots when I came to this programme. It widened my perception on AI.” – Student, Malaysia. 

    The Malaysian government actively promotes AI literacy among its citizens, and working with local education authorities, Penang Science Cluster is using Experience AI to train teachers and equip thousands of young people in the state of Penang with the understanding and skills to use AI effectively. 

    “We envision a future where AI education is as fundamental as mathematics education, providing students with the tools they need to thrive in an AI-driven world”, says Aimy Lee, Chief Operating Officer at Penang Science Cluster. “The journey of AI exploration in Malaysia has only just begun, and we’re thrilled to play a part in shaping its trajectory.”

    Giving non-specialist teachers the confidence to introduce AI to students

    Experience AI provides lesson plans, classroom resources, worksheets, hands-on activities, and videos to help teachers introduce a wide range of AI applications and help students understand how they work. The resources are based on research, and because we adapt them to each partner’s country, they are culturally relevant and relatable for students. Any teacher can use the resources in their classroom, whether or not they have a background in computing education. 

    “Our Key Stage 3 Computing students now feel immensely more knowledgeable about the importance and place that AI has in their wider lives. These lessons and activities are engaging and accessible to students and educators alike, whatever their specialism may be.” – Dave Cross,  North Liverpool Academy, UK

    “The feedback we’ve received from both teachers and learners has been overwhelmingly positive. They consistently rave about how accessible, fun, and hands-on these resources are. What’s more, the materials are so comprehensive that even non-specialists can deliver them with confidence.” – Storm Rae, The National Museum of Computing, UK

    Experience AI teacher training in Kenya
    Experience AI teacher training in Kenya

    “[The lessons] go above and beyond to ensure that students not only grasp the material but also develop a genuine interest and enthusiasm for the subject.” – Teacher, Changamwe Junior School, Mombasa, Kenya

    Sparking debates on bias and the limitations of AI

    When learners gain an understanding of how AI works, it gives them the confidence to discuss areas where the technology doesn’t work well or its output is incorrect. These classroom debates deepen and consolidate their knowledge, and help them to use AI more critically.

    “Students enjoyed the practical aspects of the lessons, like categorising apples and tomatoes. They found it intriguing how AI could sometimes misidentify objects, sparking discussions on its limitations. They also expressed concerns about AI bias, which these lessons helped raise awareness about. I didn’t always have all the answers, but it was clear they were curious about AI’s implications for their future.” – Tracey Mayhead, Arthur Mellows Village College, Peterborough, UK

    Experience AI students in UK
    Experience AI students in UK

    “The lessons that we trialled took some of the ‘magic’ out of AI and started to give the students an understanding that AI is only as good as the data that is used to build it.” – Jacky Green, Waldegrave School, UK 

    “I have enjoyed learning about how AI is actually programmed, rather than just hearing about how impactful and great it could be.” – Student, King Edward’s School, Bath, UK 

    “It has changed my outlook on AI because now I’ve realised how much AI actually needs human intelligence to be able to do anything.” – Student, Arthur Mellows Village College, Peterborough, UK 

    “I didn’t really know what I wanted to do before this but now knowing more about AI, I probably would consider a future career in AI as I find it really interesting and I really liked learning about it.” – Student, Arthur Mellows Village College, Peterborough, UK 

    If you’d like to get involved with Experience AI as an educator and use our free lesson resources with your class, you can start by visiting experience-ai.org.

    Website: LINK

  • Experience AI: How research continues to shape the resources

    Experience AI: How research continues to shape the resources

    Reading Time: 5 minutes

    Since we launched the Experience AI learning programme in the UK in April 2023, educators in 130 countries have downloaded Experience AI lesson resources. They estimate reaching over 630,000 young people with the lessons, helping them to understand how AI works and to build the knowledge and confidence to use AI tools responsibly. Just last week, we announced another exciting expansion of Experience AI: thanks to $10 million in funding from Google.org, we will be able to work with local partner organisations to provide research-based AI education to an estimated over 2 million young people across Europe, the Middle East and Africa.

    Trainer discussing Experience AI at a teacher training event in Kenya.
    Experience AI teacher training in Kenya

    This blog post explains how we use research to continue to shape our Experience AI resources, including the new AI safety resources we are developing. 

    The beginning of Experience AI

    Artificial intelligence (AI) and machine learning (ML) applications are part of our everyday lives — we use them every time we scroll through social media feeds organised by recommender systems or unlock an app with facial recognition. For young people, there is more need than ever to gain the skills and understanding to critically engage with AI technologies. 

    Someone holding a mobile phone that's open on their social media apps folder.

    We wanted to design free lesson resources to help teachers in a wide range of subjects confidently introduce AI and ML to students aged 11 to 14 (Key Stage 3). This led us to develop Experience AI, in collaboration with Google DeepMind, offering materials including lesson plans, slide decks, videos (both teacher- and student-facing), student activities, and assessment questions. 

    SEAME: The research-based framework behind Experience AI

    The Experience AI resources were built on rigorous research from the Raspberry Pi Computing Education Research Centre as well as from other researchers, including those we hosted at our series of seminars on AI and data science education. The Research Centre’s work involved mapping and categorising over 500 resources used to teach AI and ML, and found that the majority were one-off activities, and that very few resources were tailored to a specific age group.

    An example activity slide in the Experience AI lessons where students learn about bias.
    An example activity in the Experience AI lessons where students learn about bias.

    To analyse the content that existing AI education resources covered, the Centre developed a simple framework called SEAME. The framework gives you an easy way to group concepts, knowledge, and skills related to AI and ML based on whether they focus on social and ethical aspects (SE), applications (A), models (M), or engines (E, i.e. how AI works.)

    Through Experience AI, learners also gain an understanding of the models underlying AI applications, and the processes used to train and test ML models.

    An example activity slide in the Experience AI lessons where students learn about classification.
    An example activity in the Experience AI lessons where students learn about classification.

    Our Experience AI lessons cover all four levels of SEAME and focus on applications of AI that are relatable for young people. They also introduce learners to AI-related issues such as privacy or bias concerns, and the impact of AI on employment. 

    The six foundation lessons of Experience AI

    1. What is AI?: Learners explore the current context of AI and how it is used in the world around them. Looking at the differences between rule-based and data-driven approaches to programming, they consider the benefits and challenges that AI could bring to society. 
    2. How computers learn: Focusing on the role of data-driven models in AI systems, learners are introduced to ML and find out about three common approaches to creating ML models. Finally they explore classification, a specific application of ML.
    3. Bias in, bias out: Students create their own ML model to classify images of apples and tomatoes. They discover that a limited dataset is likely to lead to a flawed ML model. Then they explore how bias can appear in a dataset, resulting in biased predictions produced by a ML model. 
    4. Decision trees: Learners take their first in-depth look at a specific type of ML model: decision trees. They see how different training datasets result in the creation of different ML models, experiencing first-hand what the term ‘data-driven’ means.
    5. Solving problems with ML models: Students are introduced to the AI project lifecycle and use it to create a ML model. They apply a human-focused approach to working on their project, train a ML model, and finally test their model to find out its accuracy.
    6. Model cards and careers: Learners finish the AI project lifecycle by creating a model card to explain their ML model. To complete the unit, they explore a range of AI-related careers, hear from people working in AI research at Google DeepMind, and explore how they might apply AI and ML to their interests. 
    Experience AI banner.

    We also offer two additional stand-alone lessons: one on large language models, how they work, and why they’re not always reliable, and the other on the application of AI in ecosystems research, which lets learners explore how AI tools can be used to support animal conservation. 

    New AI safety resources: Empowering learners to be critical users of technology

    We have also been developing a set of resources for educator-led sessions on three topics related to AI safety, funded by Google.org. 

    • AI and your data: With the support of this resource, young people reflect on the data they have already provided to AI applications in their daily lives, and think about how the prevalence of AI tools might change the way they protect their data.  
    • Media literacy in the age of AI: This resource highlights the ways AI tools can be used to perpetuate misinformation and how AI applications can help people combat misleading claims.
    • Using generative AI responsibly: With this resource, young people consider their responsibilities when using generative AI, and their expectations of developers who release Experience AI tools. 

    Other research principles behind our free teaching resources 

    As well as using the SEAME framework, we have incorporated a whole host of other research-based concepts in the design principles for the Experience AI resources. For example, we avoid anthropomorphism — that is, words or imagery that can lead learners to wrongly believe that AI applications have sentience or intentions like humans do — and we instead promote the understanding that it’s people who design AI applications and decide how they are used. We also teach about data-driven application design, which is a core concept in computational thinking 2.0.  

    Share your feedback

    We’d love to hear your thoughts and feedback about using the Experience AI resources. Your comments help us to improve the current materials, and to develop future resources. You can tell us what you think using this form. 

    And if you’d like to start using the Experience AI resources as an educator, you can download them for free at experience-ai.org.

    Website: LINK

  • Experience AI at UNESCO’s Digital Learning Week

    Experience AI at UNESCO’s Digital Learning Week

    Reading Time: 5 minutes

    Last week, we were honoured to attend UNESCO’s Digital Learning Week conference to present our free Experience AI resources and how they can help teachers demystify AI for their learners.  

    A group of educators at a UNESCO conference.

    The conference drew a worldwide audience in-person and online to hear about the work educators and policy makers are doing to support teachers’ use of AI tools in their teaching and learning. Speaker after speaker reiterated that the shared goal of our work is to support learners to become critical consumers and responsible creators of AI systems.

    In this blog, we share how our conference talk demonstrated the use of Experience AI for pursuing this globally shared goal, and how the Experience AI resources align with UNESCO’s newly launched AI competency framework for students.

    Presenting the design principles behind Experience AI

    Our talk about Experience AI, our learning programme developed with Google DeepMind, focused on the research-informed approach we are taking in our resource development. Specifically, we spoke about three key design principles that we embed in the Experience AI resources:

    Firstly, using AI and machine learning to solve problems requires learners and educators to think differently to traditional computational thinking and use a data-driven approach instead, as laid out in the research around computational thinking 2.0.

    Secondly, every word we use in our teaching about AI is important to help young people form accurate mental models about how AI systems work. In particular, we focused our examples around the need to avoid anthropomorphising language when we describe AI systems. Especially given that some developers produce AI systems with the aim to make them appear human-like in their design and outputs, it’s important that young people understand that AI systems are in fact built and designed by humans.

    Thirdly we described how we used the SEAME framework we adapted from work by Jane Waite (Raspberry Pi Foundation) and Paul Curzon (Queen Mary University, London) to categorise hundreds of AI education resources and inform the design of our Experience AI resources. The framework offers a common language for educators when assessing the content of resources, and when supporting learners to understand the different aspects of AI systems. 

    By presenting our design principles, we aimed to give educators, policy makers, and attendees from non-governmental organisations practical recommendations and actionable considerations for designing learning materials on AI literacy.   

    How Experience AI aligns with UNESCO’s new AI competency framework for students

    At Digital Learning Week, UNESCO launched two AI competency frameworks:

    • A framework for students, intended to help teachers around the world with integrating AI tools in activities to engage their learners
    • A framework for teachers, “defining the knowledge, skills, and values teachers must master in the age of AI”

    AI competency framework for students

    We have had the chance to map the Experience AI resources to UNESCO’s AI framework for students at a high level, finding that the resources cover 10 of the 12 areas of the framework (see image below).

    An adaptation of a summary table from UNESCO’s new student competency framework (CC-BY-SA 3.0 IGO), highlighting the 10 areas covered by our Experience AI resources

    For instance, throughout the Experience AI resources runs a thread of promoting “citizenship in the AI era”: the social and ethical aspects of AI technologies are highlighted in all the lessons and activities. In this way, they provide students with the foundational knowledge of how AI systems work, and where they may work badly. Using the resources, educators can teach their learners core AI and machine learning concepts and make these concepts concrete through practical activities where learners create their own models and critically evaluate their outputs. Importantly, by learning with Experience AI, students not only learn to be responsible users of AI tools, but also to consider fairness, accountability, transparency, and privacy when they create AI models.  

    Teacher competency framework for AI 

    UNESCO’s AI competency framework for teachers outlines 15 competencies across 5 dimensions (see image below).  We enjoyed listening to the launch panel members talk about the strong ambitions of the framework as well as the realities of teachers’ global and local challenges. The three key messages of the panel were:

    • AI will not replace the expertise of classroom teachers
    • Supporting educators to build AI competencies is a shared responsibility
    • Individual countries’ education systems have different needs in terms of educator support

    All three messages resonate strongly with the work we’re doing at the Raspberry Pi Foundation. Supporting all educators is a fundamental part of our resource development. For example, Experience AI offers everything a teacher with no technical background needs to deliver the lessons, including lesson plans, videos, worksheets and slide decks. We also provide a free online training course on understanding AI for educators. And in our work with partner organisations around the world, we adapt and translate Experience AI resources so they are culturally relevant, and we organise locally delivered teacher professional development. 

    A summary table from UNESCO’s new teacher competency framework (CC-BY-SA 3.0 IGO)

     The teachers’ competency framework is meant as guidance for educators, policy makers, training providers, and application developers to support teachers in using AI effectively, and in helping their learners gain AI literacy skills. We will certainly consult the document as we develop our training and professional development resources for teachers further.

    Towards AI literacy for all young people

    Across this year’s UNESCO’s Digital Learning Week, we saw that the role of AI in education took centre stage across the presentations and the informal conversations among attendees. It was a privilege to present our work and see how well Experience AI was received, with attendees recognising that our design principles align with the values and principles in UNESCO’s new AI competency frameworks.

    A conference table setup with a pair of headphones resting on top of a UNESCO brochure.

    We look forward to continuing this international conversation about AI literacy and working in aligned ways to support all young people to develop a foundational understanding of AI technologies.

    Website: LINK

  • Experience AI expands to reach over 2 million students

    Experience AI expands to reach over 2 million students

    Reading Time: 4 minutes

    Two years ago, we announced Experience AI, a collaboration between the Raspberry Pi Foundation and Google DeepMind to inspire the next generation of AI leaders.

    Today I am excited to announce that we are expanding the programme with the aim of reaching more than 2 million students over the next 3 years, thanks to a generous grant of $10m from Google.org. 

    Why do kids need to learn about AI

    AI technologies are already changing the world and we are told that their potential impact is unprecedented in human history. But just like every other wave of technological innovation, along with all of the opportunities, the AI revolution has the potential to leave people behind, to exacerbate divisions, and to make more problems than it solves.

    Part of the answer to this dilemma lies in ensuring that all young people develop a foundational understanding of AI technologies and the role that they can play in their lives. 

    An educator points to an image on a student's computer screen.

    That’s why the conversation about AI in education is so important. A lot of the focus of that conversation is on how we harness the power of AI technologies to improve teaching and learning. Enabling young people to use AI to learn is important, but it’s not enough. 

    We need to equip young people with the knowledge, skills, and mindsets to use AI technologies to create the world they want. And that means supporting their teachers, who once again are being asked to teach a subject that they didn’t study. 

    Experience AI 

    That’s the work that we’re doing through Experience AI, an ambitious programme to provide teachers with free classroom resources and professional development, enabling them to teach their students about AI technologies and how they are changing the world. All of our resources are grounded in research that defines the concepts that make up AI literacy, they are rooted in real world examples drawing on the work of Google DeepMind, and they involve hands-on, interactive activities. 

    The Experience AI resources have already been downloaded 100,000 times across 130 countries and we estimate that 750,000 young people have taken part in an Experience AI lesson already. 

    In November 2023, we announced that we were building a global network of partners that we would work with to localise and translate the Experience AI resources, to ensure that they are culturally relevant, and organise locally delivered teacher professional development. We’ve made a fantastic start working with partners in Canada, India, Kenya, Malaysia, and Romania; and it’s been brilliant to see the enthusiasm and demand for AI literacy from teachers and students across the globe. 

    Thanks to an incredibly generous donation of $10m from Google.org – announced at Google.org’s first Impact Summit  – we will shortly be welcoming new partners in 17 countries across Europe, the Middle East, and Africa, with the aim of reaching more than 2 million students in the next three years. 

    AI Safety

    Alongside the expansion of the global network of Experience AI partners, we are also launching new resources that focus on critical issues of AI safety. 

    A laptop surrounded by various screens displaying images, videos, and a world map.

    AI and Your Data: Helping young people reflect on the data they are already providing to AI applications in their lives and how the prevalence of AI tools might change the way they protect their data.

    Media Literacy in the Age of AI: Highlighting the ways AI tools can be used to perpetuate misinformation and how AI applications can help combat misleading claims.

    Using Generative AI Responsibly: Empowering young people to reflect on their responsibilities when using Generative AI and their expectations of developers who release AI tools.

    Get involved

    In many ways, this moment in the development of AI technologies reminds me of the internet in the 1990s (yes, I am that old). We all knew that it had potential, but no-one could really imagine the full scale of what would follow. 

    We failed to rise to the educational challenge of that moment and we are still living with the consequences: a dire shortage of talent; a tech sector that doesn’t represent all communities and voices; and young people and communities who are still missing out on economic opportunities and unable to utilise technology to solve the problems that matter to them. 

    We have an opportunity to do a better job this time. If you’re interested in getting involved, we’d love to hear from you.

    Website: LINK

  • Why we’re taking a problem-first approach to the development of AI systems

    Why we’re taking a problem-first approach to the development of AI systems

    Reading Time: 7 minutes

    If you are into tech, keeping up with the latest updates can be tough, particularly when it comes to artificial intelligence (AI) and generative AI (GenAI). Sometimes I admit to feeling this way myself, however, there was one update recently that really caught my attention. OpenAI launched their latest iteration of ChatGPT, this time adding a female-sounding voice. Their launch video demonstrated the model supporting the presenters with a maths problem and giving advice around presentation techniques, sounding friendly and jovial along the way. 

    A finger clicking on an AI app on a phone.

    Adding a voice to these AI models was perhaps inevitable as big tech companies try to compete for market share in this space, but it got me thinking, why would they add a voice? Why does the model have to flirt with the presenter? 

    Working in the field of AI, I’ve always seen AI as a really powerful problem-solving tool. But with GenAI, I often wonder what problems the creators are trying to solve and how we can help young people understand the tech. 

    What problem are we trying to solve with GenAI?

    The fact is that I’m really not sure. That’s not to suggest that I think that GenAI hasn’t got its benefits — it does. I’ve seen so many great examples in education alone: teachers using large language models (LLMs) to generate ideas for lessons, to help differentiate work for students with additional needs, to create example answers to exam questions for their students to assess against the mark scheme. Educators are creative people and whilst it is cool to see so many good uses of these tools, I wonder if the developers had solving specific problems in mind while creating them, or did they simply hope that society would find a good use somewhere down the line?

    An educator points to an image on a student's computer screen.

    Whilst there are good uses of GenAI, you don’t need to dig very deeply before you start unearthing some major problems. 

    Anthropomorphism

    Anthropomorphism relates to assigning human characteristics to things that aren’t human. This is something that we all do, all of the time, without it having consequences. The problem with doing this with GenAI is that, unlike an inanimate object you’ve named (I call my vacuum cleaner Henry, for example), chatbots are designed to be human-like in their responses, so it’s easy for people to forget they’re not speaking to a human. 

    A photographic rendering of a smiling face emoji seen through a refractive glass grid, overlaid with a diagram of a neural network.
    Image by Alan Warburton / © BBC / Better Images of AI / Social Media / CC-BY 4.0

    As feared, since my last blog post on the topic, evidence has started to emerge that some young people are showing a desire to befriend these chatbots, going to them for advice and emotional support. It’s easy to see why. Here is an extract from an exchange between the presenters at the ChatGPT-4o launch and the model:

    ChatGPT (presented with a live image of the presenter): “It looks like you’re feeling pretty happy and cheerful with a big smile and even maybe a touch of excitement. Whatever is going on? It seems like you’re in a great mood. Care to share the source of those good vibes?”
    Presenter: “The reason I’m in a good mood is we are doing a presentation showcasing how useful and amazing you are.”
    ChatGPT: “Oh stop it, you’re making me blush.” 

    The Family Online Safety Institute (FOSI) conducted a study looking at the emerging hopes and fears that parents and teenages have around GenAI.

    One quote from a teenager said:

    “Some people just want to talk to somebody. Just because it’s not a real person, doesn’t mean it can’t make a person feel — because words are powerful. At the end of the day, it can always help in an emotional and mental way.”  

    The prospect of teenagers seeking solace and emotional support from a generative AI tool is a concerning development. While these AI tools can mimic human-like conversations, their outputs are based on patterns and data, not genuine empathy or understanding. The ultimate concern is that this exposes vulnerable young people to be manipulated in ways we can’t predict. Relying on AI for emotional support could lead to a sense of isolation and detachment, hindering the development of healthy coping mechanisms and interpersonal relationships. 

    A photographic rendering of a simulated middle-aged white woman against a black background, seen through a refractive glass grid and overlaid with a distorted diagram of a neural network.
    Image by Alan Warburton / © BBC / Better Images of AI / Virtual Human / CC-BY 4.0

    Arguably worse is the recent news of the world’s first AI beauty pageant. The very thought of this probably elicits some kind of emotional response depending on your view of beauty pageants. There are valid concerns around misogyny and reinforcing misguided views on body norms, but it’s also important to note that the winner of “Miss AI” is being described as a lifestyle influencer. The questions we should be asking are, who are the creators trying to have influence over? What influence are they trying to gain that they couldn’t get before they created a virtual woman? 

    DeepFake tools

    Another use of GenAI is the ability to create DeepFakes. If you’ve watched the most recent Indiana Jones movie, you’ll have seen the technology in play, making Harrison Ford appear as a younger version of himself. This is not in itself a bad use of GenAI technology, but the application of DeepFake technology can easily become problematic. For example, recently a teacher was arrested for creating a DeepFake audio clip of the school principal making racist remarks. The recording went viral before anyone realised that AI had been used to generate the audio clip. 

    Easy-to-use DeepFake tools are freely available and, as with many tools, they can be used inappropriately to cause damage or even break the law. One such instance is the rise in using the technology for pornography. This is particularly dangerous for young women, who are the more likely victims, and can cause severe and long-lasting emotional distress and harm to the individuals depicted, as well as reinforce harmful stereotypes and the objectification of women. 

    Why we should focus on using AI as a problem-solving tool

    Technological developments causing unforeseen negative consequences is nothing new. A lot of our job as educators is about helping young people navigate the changing world and preparing them for their futures and education has an essential role in helping people understand AI technologies to avoid the dangers. 

    Our approach at the Raspberry Pi Foundation is not to focus purely on the threats and dangers, but to teach young people to be critical users of technologies and not passive consumers. Having an understanding of how these technologies work goes a long way towards achieving sufficient AI literacy skills to make informed choices and this is where our Experience AI program comes in. 

    An Experience AI banner.

    Experience AI is a set of lessons developed in collaboration with Google DeepMind and, before we wrote any lessons, our team thought long and hard about what we believe are the important principles that should underpin teaching and learning about artificial intelligence. One such principle is taking a problem-first approach and emphasising that computers are tools that help us solve problems. In the Experience AI fundamentals unit, we teach students to think about the problem they want to solve before thinking about whether or not AI is the appropriate tool to use to solve it. 

    Taking a problem-first approach doesn’t by default avoid an AI system causing harm — there’s still the chance it will increase bias and societal inequities — but it does focus the development on the end user and the data needed to train the models. I worry that focusing on market share and opportunity rather than the problem to be solved is more likely to lead to harm.

    Another set of principles that underpins our resources is teaching about fairness, accountability, transparency, privacy, and security (Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education, Understanding Artificial Intelligence Ethics and Safety) in relation to the development of AI systems. These principles are aimed at making sure that creators of AI models develop models ethically and responsibly. The principles also apply to consumers, as we need to get to a place in society where we expect these principles to be adhered to and consumer power means that any models that don’t, simply won’t succeed. 

    Furthermore, once students have created their models in the Experience AI fundamentals unit, we teach them about model cards, an approach that promotes transparency about their models. Much like how nutritional information on food labels allows the consumer to make an informed choice about whether or not to buy the food, model cards give information about an AI model such as the purpose of the model, its accuracy, and known limitations such as what bias might be in the data. Students write their own model cards based on the AI solutions they have created. 

    What else can we do?

    At the Raspberry Pi Foundation, we have set up an AI literacy team with the aim to embed principles around AI safety, security, and responsibility into our resources and align them with the Foundations’ mission to help young people to:

    • Be critical consumers of AI technology
    • Understand the limitations of AI
    • Expect fairness, accountability, transparency, privacy, and security and work toward reducing inequities caused by technology
    • See AI as a problem-solving tool that can augment human capabilities, but not replace or narrow their futures 

    Our call to action to educators, carers, and parents is to have conversations with your young people about GenAI. Get to know their opinions on GenAI and how they view its role in their lives, and help them to become critical thinkers when interacting with technology. 

    Website: LINK

  • Four key learnings from teaching Experience AI lessons

    Four key learnings from teaching Experience AI lessons

    Reading Time: 4 minutes

    Developed by us and Google DeepMind, Experience AI provides teachers with free resources to help them confidently deliver lessons that inspire and educate young people about artificial intelligence (AI) and the role it could play in their lives.

    Tracy Mayhead is a computer science teacher at Arthur Mellows Village College in Cambridgeshire. She recently taught Experience AI to her KS3 pupils. In this blog post, she shares 4 key learnings from this experience.

    A photo of Tracy Mayhead in a classroom.

    1. Preparation saves time

    The Experience AI lesson plans provided a clear guide on how to structure our lessons.

    Each lesson includes teacher-facing intro videos, a lesson plan, a slide deck, activity worksheets, and student-facing videos that help to introduce each new AI concept. 

    It was handy to know in advance which websites needed unblocking so students could access them. 

    You can find a unit overview on the Experience AI website to get an idea of what is included in each lesson.

    “My favourite bit was making my own model, and choosing the training data. I enjoyed seeing how the amount of data affected the accuracy of the AI and testing the model.” – Student, Arthur Mellows Village College, UK 

    2. The lessons can be adapted to meet student’s needs 

    It was clear from the start that I could adapt the lessons to make them work for myself and my students.

    Having estimated times and corresponding slides for activities was beneficial for adjusting the lesson duration. The balance between learning and hands-on tasks was just right.

    A group of students at a desk in a classroom.

    I felt fairly comfortable with my understanding of AI basics. However, teaching it was a learning experience, especially in tailoring the lessons to cater to students with varying knowledge. Their misconceptions sometimes caught me off guard, like their belief that AI is never wrong. Adapting to their needs and expectations was a learning curve. 

    “It has definitely changed my outlook on AI. I went from knowing nothing about it to understanding how it works, why it acts in certain ways, and how to actually create my own AI models and what data I would need for that.” – Student, Arthur Mellows Village College, UK 

    3. Young people are curious about AI and how it works

    My students enjoyed the practical aspects of the lessons, like categorising apples and tomatoes. They found it intriguing how AI could sometimes misidentify objects, sparking discussions on its limitations. They also expressed concerns about AI bias, which these lessons helped raise awareness about. I didn’t always have all the answers, but it was clear they were curious about AI’s implications for their future.

    It’s important to acknowledge that as a teacher you won’t always have all the answers especially when teaching AI literacy, which is such a new area. This is something that can be explored in a class alongside students.

    There is an online course you can use that can help get you started teaching about AI if you are at all nervous.

    [youtube https://www.youtube.com/watch?v=gScgJf289Cs?feature=oembed&w=500&h=281]

    “I learned a lot about AI and the possibilities it holds to better our futures as well as how to train it and problems that may arise when training it.” – Student, Arthur Mellows Village College, UK

    4. Engaging young people with AI is important

    Students are fascinated by AI and they recognise its significance in their future. It is important to equip them with the knowledge and skills to fully engage with AI.

    Experience AI provides a valuable opportunity to explore these concepts and empower students to shape and question the technology that will undoubtedly impact their lives.

    “It has changed my outlook on AI because I now understand it better and feel better equipped to work with AI in my working life.” – Student, Arthur Mellows Village College, UK 

    A group of Year 10 students in a classroom.

    What is your experience of teaching Experience AI lessons?

    We completely agree with Tracy. AI literacy empowers people to critically evaluate AI applications and how they are being used. Our Experience AI resources help to foster critical thinking skills, allowing learners to use AI tools to address challenges they are passionate about. 

    We’re also really interested to learn what misconceptions students have about AI and how teachers are addressing them. If you come across misconceptions that surprise you while you’re teaching with the Experience AI lesson materials, please let us know via the feedback form linked in the final lesson of the six-lesson unit.

    If you would like to teach Experience AI lessons to your students, download the free resources from experience-ai.org

    Website: LINK

  • Celebrating the AI innovators of tomorrow

    Celebrating the AI innovators of tomorrow

    Reading Time: 4 minutes

    As the Experience AI Challenge has closed for submissions, we would like to thank all the talented young people who participated and submitted their projects this year.

    The Challenge, created by us in collaboration with Google DeepMind, guides young people under the age of 18, and their mentors, through the process of creating their own unique AI project. It encourages young people to seek out real-world problems and create possible AI-based solutions. From January to May, participants in the UK were also able to submit their projects for feedback from AI experts.

    In response to the submissions, Richard Hayler, our Director of Youth Programmes commented:

    “In running the Challenge, we have seen an incredible display of creativity, ingenuity, and curiosity about AI among young people. The dedication and innovation they  demonstrated in their submitted projects has been truly inspiring. The Challenge has not only showcased the immense potential of addressing problems using AI tools, but most of all the remarkable talent and dedication of the next generation of innovators.

    We would also like to thank all the mentors who guided and encouraged participants throughout the Challenge for their invaluable support. Their expertise and mentorship were instrumental in the young people’s success.”

    Some Challenge highlights

    These are some examples of the innovative projects young people created: 

    AI creation: River Water Quality Prediction App

    Creator: Shreyas, age 13

    What does it do:

    “The model predicts how good the water quality of a river is based on several factors such as the levels of ammonium, nitrates, and dissolved oxygen.”

    Who is it for:

    ”It can be used to tell if river water is safe to drink, or safe for life. This can also be used by authorities to decide where to deploy limited resources to purify water depending on its toxicity.”

    An image of a river with buildings in the background.

    AI creation: Coeliac Disease

    Creator: Zainev, age 14–18

    What does it do:

    “The model aims to identify foods that contain the allergen gluten.”

    Who is it for:

    “It is for people with gluten allergy and/or people trying to arrange food for those with a gluten allergy, as it will easily help them identify foods that contain gluten and are not safe to eat.”

    An AI tool classifying gluten and gluten free products.

    AI creation: Spacepuppy’s colour adventure

    Creator: Charlotte, age 12

    What does it do:

    “Teaches children about colours.”

    Who is it for:

    “Teachers at primary schools/ nurseries.”

    A blue rocket on a white background.

    AI creation: Nutrify

    Creator: Ishaan, age 14–18

    What does it do:

    “The model identifies the students’ food items through a webcam image, giving its specific nutritional information including calories, carbs, sugars and proteins.”

    Who is it for:

    “This model can be easily used by students to be aware of the nutritional information of their meals.”

    An AI tool classifying different types of food, such as burgers, juice, and pizza.

    AI creation: Flossie

    Creator: Florence, age 11

    What does it do:

    “Identifies dressing gowns, slippers and pyjamas.”

    Who is it for:

    “For young children to learn different clothing.”

    An AI tool classifying different clothing.

    AI creation: Dermalyst

    Creator: Vedant, age 14–18

    What does it do:

    “Dermalyst is an AI-based dermatologist that analyses images of your skin to check if you have any skin infection or disease and also suggests solutions.”

    Who is it for:

    “This app is targeted at young people but anyone could use it. It saves them from having to wait for a GP appointment.”

    A doctor's hands holding a mobile phone.

    AI creation: Bird identifier

    Creator: William, age 13

    What does it do:

    “It is designed to identify common garden birds native to the United Kingdom. It can identify robins, blue tits, great tits and blackbirds by their photograph.”

    Who is it for:

    “Bird watchers may use the app to identify the birds that they see but don’t know what they are.”

    An image of a Robin on a tree branch.

    Save the date for the celebratory webinar

    We would like to invite you to an online webinar on Wednesday 10 July at 4pm BST to celebrate all Experience AI Challenge participants. Click ‘notify me’ on YouTube to be notified when the webinar starts.

    During the webinar, Mark Calleja from the Raspberry Pi Foundation and Matko Bošnjak, Research Scientist at Google DeepMind, will highlight some young people’s AI creations, and discuss all things AI. You can share your questions about AI for Mark and Matko by filling in this form today.

    Download the Experience AI Challenge resources

    Once again thank you to everyone who participated in the Experience AI Challenge and submitted their projects.

    If you’re interested in the Challenge, you can still download the resources and use them to create your own AI projects.

    Website: LINK

  • A teacher’s guide to teaching Experience AI lessons

    A teacher’s guide to teaching Experience AI lessons

    Reading Time: 5 minutes

    Today, Laura James, Head of Computing and ICT at King Edward’s School in Bath, UK, shares how Experience AI has transformed how she teaches her students about artificial intelligence. This article will also appear in issue 24 of Hello World magazine, which will be available for free from 1 July and focuses on the impact of technology.

    I recently delivered Experience AI lessons to three Year 9 (ages 13–14) classes of about 20 students each with a ratio of approximately 2:3 girls to boys. They are groups of keen pupils who have elected to study computing as an option. The Experience AI lessons are an excellent set of resources.

    Everything you need

    Part of the Experience AI resources is a series of six lessons that introduce the concepts behind machine learning and artificial intelligence (AI). There are full lesson plans with timings, clear PowerPoint presentations, and activity sheets. There is also an end-of-topic multiple choice assessment provided.

    Accompanying these are interesting, well-produced videos that underpin the concepts, all explained by real people who work in the AI industry. Plus, there are helpful videos for the educators, which explain certain parts of the scheme of work — particularly useful for parts that might have been seen as difficult for non-specialist teachers, for example, setting up a project using the Machine Learning for Kids website.

    Confidence delivering lessons

    The clear and detailed resources meant I felt mostly confident in delivering lessons. The suggested timings were a good guideline, although in some lessons, this did not always go to plan. For example, when the pupils were enjoying investigating websites that produce images generated by a text prompt, they were keen to spend more time on this than was allocated in the lesson plan. In this case, I modified the timings on the fly and set the final task of this lesson as a homework task.

    Learning about AI sparked the students’ curiosity, and it triggered a few questions that I could not answer immediately. However, I admitted this was a new area for me, and with some investigation, found answers to many of their extra questions. This shows that the topic of AI is such an inspiring and important one for the next generation, and how important it is to add this to the curriculum now before students make their own, potentially biased, opinions about it.

    “I’ve enjoyed actually learning about what AI is and how it works because before I thought it was just a scary computer that thinks like a human.” – Student, King Edward’s School, UK 

    Impact on learners

    The pupils’ feedback from the series of lessons was unerringly positive. I felt the lessons on bias in data were particularly important. The lesson where they trained their own algorithm recognising tomatoes and apples was a key one as it gave students an immediate sense of how a flawed training data set created bias and can impact the answers from a supposedly intelligent AI tool. I hope this has changed their outlook on AI-generated results and reinforced their critical thinking skills.

    Many students are now seeing the influence of AI appearing in more and more tools around them and have mentioned that a career in AI is now something they are interested in.

    “I have enjoyed learning about how AI is actually programmed rather than just hearing about how impactful and great it could be.” – Student, King Edward’s School, UK 

    [youtube https://www.youtube.com/watch?v=D2uOT4MKNDU?feature=oembed&w=500&h=281]

    Tips for other teachers

    Clearly this topic is incredibly important, and the Experience AI series of lessons is an excellent introduction to this for key stage 3 students (ages 11–14). My tips for other educators would be:

    • I delivered these to bright Year 9s and added a few more coding activities from the Machine Learning for Kids website. As these lessons stand, they could be delivered to Year 8s (ages 12–13), but perhaps Year 7s (ages 11–12) might struggle with some of the more esoteric concepts.
    • Before each lesson, ensure you read the content and familiarise yourself with the lesson resources and tools used. The Machine Learning for Kids website can take a little getting used to, but it is a powerful tool that brings to life how machine learning works, and many pupils said this was their favourite part of the lessons.
    • Before the lesson, ensure that the websites that you need to access are unblocked by your school’s firewall!
    • I tried to add a hands-on activity each lesson, e.g. for Lesson 1, I showed the students Google’s Quick, Draw! game, which they enjoyed and has a good section on the training data used to train the AI tool to recognise the drawings.
    • We also spent an extra lesson using the brilliant Machine Learning for Kids website and followed the ‘Shoot the bug’ worksheet, which allowed pupils to train an algorithm to learn how to play a simple video game.
    • I also needed to have a weekly homework task, so I would either use part of the activity from the lesson or quickly devise something (e.g. research another use for AI we haven’t discussed/what ethical issues might occur with a certain use of AI). Next year, our department will formalise these to help other teachers who might deliver these lessons to set these tasks more easily.
    • Equally, I needed to have a summative assessment at the end of the topic. I used some of the multiple choice questions that were provided but added some longer-answer questions and made an online assessment to allow me to mark students’ answers more efficiently.

    “I have always been fascinated by AI applications and finally finding out how they work and make the decisions they do has been a really cool experience.” – Student, King Edward’s School, UK 

    From comments I have had from the students, they really engaged with the lessons and appreciated the opportunity to discuss and explore the topic, which is often associated with ‘deception’ within school. It allowed them to understand the benefits and the risks of AI and, most importantly, to begin to understand how it works ‘under the hood’, rather than see AI as a magical, anthropomorphised entity that is guessing their next move.

    “The best part about learning about AI was knowing the dangers and benefits associated and how we can safely use it in our day-to-day life.” – Student, King Edward’s School, UK 

    As for my perspective, I really enjoyed teaching this topic, and it has earned its place in the Year 9 scheme of work for next year. 

    If you’re interested in teaching the Experience AI Lessons to your students, download the resources for free today at experience-ai.org.

    Website: LINK

  • Teaching a generation of AI innovators in Malaysia with Experience AI

    Teaching a generation of AI innovators in Malaysia with Experience AI

    Reading Time: 4 minutes

    Today’s blog is from Aimy Lee, Chief Operating Officer at Penang Science Cluster, part of our global partner network for Experience AI.

    Artificial intelligence (AI) is transforming the world at an incredible pace, and at Penang Science Cluster, we are determined to be at the forefront of this fast-changing landscape.

    A teacher delivers a lesson in a classroom while students sit at their desks and listen.

    The Malaysian government is actively promoting AI literacy among citizens, demonstrating a commitment to the nation’s technological advancement. This dedication is further demonstrated by the Ministry of Education’s recent announcement to introduce AI basics into the primary school curriculum, starting in 2027. 

    Why we chose Experience AI

    At Penang Science Cluster, we firmly believe that AI is already an essential part of everybody’s future, especially for young people, for whom technologies such as search engines, AI chatbots, image generation, and facial recognition are already deeply ingrained in their daily experiences. It is vital that we equip young people with the knowledge to understand, harness, and even create AI solutions, rather than view AI with trepidation.

    A student uses a laptop in a classroom.

    With this in mind, we’re excited to be one of the first of many organisations to join the Experience AI global partner network. Experience AI is a free educational programme  offering cutting-edge resources on artificial intelligence and machine learning for teachers and students. Developed in collaboration between the Raspberry Pi Foundation and Google DeepMind, as a global partner we hope the programme will bring AI literacy to thousands of students across Malaysia.

    Our goal is to demystify AI and highlight its potential for positive change. The Experience AI programme resonated with our mission to provide accessible and engaging resources tailored for our beneficiaries, making it a natural fit for our efforts.

    Experience AI pilot: Results and student voices

    At the start of this year, we ran an Experience AI pilot with 56 students to discover how the programme resonated with young people. The positive feedback we received was incredibly encouraging! Students expressed excitement and a genuine shift in their understanding of AI. 

    Their comments, such as discovering the fun of learning about AI and seeing how AI can lead to diverse career paths, validated the effectiveness of the programme’s approach.  

    [youtube https://www.youtube.com/watch?v=zWO_xWOEw0k?feature=oembed&w=500&h=281]

    One student’s changed perspective — from fearing AI to recognising its potential — underscores the importance of addressing misconceptions. Providing accessible AI education empowers students to develop a balanced and informed outlook.

    “I learnt new things and it changed my mindset that AI is not going to take over the world.” – Student who took part in the Experience AI pilot

    Launching Experience AI in Malaysia

    The successful pilot paved the way for our official Experience AI launch in early April. Students who participated in the pilot were proud to be a part of the launch event, sharing their AI knowledge and experience with esteemed guests, including the Chief Minister of Penang, the Deputy Finance Minister of Malaysia, and the Director of the Penang State Education Department. The presence of these leaders highlights the growing recognition of the significance of AI education.

    Experience AI launch event in Malaysia

    Building a vibrant AI education community

    Following the launch, our immediate focus has shifted to empowering teachers. With the help of the Raspberry Pi Foundation, we’ll conduct teacher workshops to equip them with the knowledge and tools to bring Experience AI into their classrooms. Collaborating with education departments in Penang, Kedah, Perlis, Perak, and Selangor will be vital in teacher recruitment and building a vibrant AI education community.

    Inspiring the next generation of AI creators

    Experience AI marks an exciting start to integrating AI education within Malaysia, for both students and teachers. Our hope is to inspire a generation of young people empowered to shape the future of AI — not merely as consumers of the technology, but as active creators and innovators.

    We envision a future where AI education is as fundamental as mathematics education, providing students with the tools they need to thrive in an AI-driven world. The journey of AI exploration in Malaysia has only just begun, and we’re thrilled to play a part in shaping its trajectory.

    If you’re interested in partnering with us to bring Experience AI to students and teachers in your country, you can register your interest here.

    Website: LINK

  • Localising AI education: Adapting Experience AI for global impact

    Localising AI education: Adapting Experience AI for global impact

    Reading Time: 6 minutes

    It’s been almost a year since we launched our first set of Experience AI resources in the UK, and we’re now working with partner organisations to bring AI literacy to teachers and students all over the world.

    Developed by the Raspberry Pi Foundation and Google DeepMind, Experience AI provides everything that teachers need to confidently deliver engaging lessons that will inspire and educate young people about AI and the role that it could play in their lives.

    Over the past six months we have been working with partners in Canada, Kenya, Malaysia, and Romania to create bespoke localised versions of the Experience AI resources. Here is what we’ve learned in the process.

    Creating culturally relevant resources

    The Experience AI Lessons address a variety of real-world contexts to support the concepts being taught. Including real-world contexts in teaching is a pedagogical strategy we at the Raspberry Pi Foundation call “making concrete”. This strategy significantly enhances the learning experience for learners because it bridges the gap between theoretical knowledge and practical application. 

    Three learners and an educator do a physical computing activity.

    The initial aim of Experience AI was for the resources to be used in UK schools. While we put particular emphasis on using culturally relevant pedagogy to make the resources relatable to learners from backgrounds that are underrepresented in the tech industry, the contexts we included in them were for UK learners. As many of the resource writers and contributors were also based in the UK, we also unavoidably brought our own lived experiences and unintentional biases to our design thinking.

    Therefore, when we began thinking about how to adapt the resources for schools in other countries, we knew we needed to make sure that we didn’t just convert what we had created into different languages. Instead we focused on localisation.

    Educators doing an activity about networks using a piece of string.

    Localisation goes beyond translating resources into a different language. For example in educational resources, the real-world contexts used to make concrete the concepts being taught need to be culturally relevant, accessible, and engaging for students in a specific place. In properly localised resources, these contexts have been adapted to provide educators with a more relatable and effective learning experience that resonates with the students’ everyday lives and cultural background.

    Working with partners on localisation

    Recognising our UK-focused design process, we made sure that we made no assumptions during localisation. We worked with partner organisations in the four countries — Digital Moment, Tech Kidz Africa, Penang Science Cluster, and Asociația Techsoup — drawing on their expertise regarding their educational context and the real-world examples that would resonate with young people in their countries.

    Participants on a video call.
    A video call with educators in Kenya.

    We asked our partners to look through each of the Experience AI resources and point out the things that they thought needed to change. We then worked with them to find alternative contexts that would resonate with their students, whilst ensuring the resources’ intended learning objectives would still be met.

    Spotlight on localisation for Kenya

    Tech Kidz Africa, our partner in Kenya, challenged some of the assumptions we had made when writing the original resources.

    An Experience AI lesson plan in English and Swahili.
    An Experience AI resource in English and Swahili.

    Relevant applications of AI technology

    Tech Kidz Africa wanted the contexts in the lessons to not just be relatable to their students, but also to demonstrate real-world uses of AI applications that could make a difference in learners’ communities. They highlighted that as agriculture is the largest contributor to the Kenyan economy, there was an opportunity to use this as a key theme for making the Experience AI lessons more culturally relevant. 

    This conversation with Tech Kidz Africa led us to identify a real-world use case where farmers in Kenya were using an AI application that identifies disease in crops and provides advice on which pesticides to use. This helped the farmers to increase their crop yields.

    Training an AI model to classify healthy and unhealthy cassava plant photos.
    Training an AI model to classify healthy and unhealthy cassava plant photos.

    We included this example when we adapted an activity where students explore the use of AI for “computer vision”. A Google DeepMind research engineer, who is one of the General Chairs of the Deep Learning Indaba, recommended a data set of images of healthy and diseased cassava crops (1). We were therefore able to include an activity where students build their own machine learning models to solve this real-world problem for themselves.

    Access to technology

    While designing the original set of Experience AI resources, we made the assumption that the vast majority of students in UK classrooms have access to computers connected to the internet. This is not the case in Kenya; neither is it the case in many other countries across the world. Therefore, while we localised the Experience AI resources with our Kenyan partner, we made sure that the resources allow students to achieve the same learning outcomes whether or not they have access to internet-connected computers.

    An AI classroom discussion activity.
    An Experience AI activity related to farming.

    Assuming teachers in Kenya are able to download files in advance of lessons, we added “unplugged” options to activities where needed, as well as videos that can be played offline instead of being streamed on an internet-connected device.

    What we’ve learned

    The work with our first four Experience AI partners has given us with lots of localisation learnings, which we will use as we continue to expand the programme with more partners across the globe:

    • Cultural specificity: We gained insight into which contexts are not appropriate for non-UK schools, and which contexts all our partners found relevant. 
    • Importance of local experts: We know we need to make sure we involve not just people who live in a country, but people who have a wealth of experience of working with learners and understand what is relevant to them. 
    • Adaptation vs standardisation: We have learned about the balance between adapting resources and maintaining the same progression of learning across the Experience AI resources. 

    Throughout this process we have also reflected on the design principles for our resources and the choices we can make while we create more Experience AI materials in order to make them more amenable to localisation. 

    Join us as an Experience AI partner

    We are very grateful to our partners for collaborating with us to localise the Experience AI resources. Thank you to Digital Moment, Tech Kidz Africa, Penang Science Cluster, and Asociația Techsoup.

    We now have the tools to create resources that support a truly global community to access Experience AI in a way that resonates with them. If you’re interested in joining us as a partner, you can register your interest here.

    (1) The cassava data set was published open source by Ernest Mwebaze, Timnit Gebru, Andrea Frome, Solomon Nsumba, and Jeremy Tusubira. Read their research paper about it here.

    Website: LINK

  • The Experience AI Challenge: Find out all you need to know

    The Experience AI Challenge: Find out all you need to know

    Reading Time: 3 minutes

    We’re really excited to see that Experience AI Challenge mentors are starting to submit AI projects created by young people. There’s still time for you to get involved in the Challenge: the submission deadline is 24 May 2024. 

    The Experience AI Challenge banner.

    If you want to find out more about the Challenge, join our live webinar on Wednesday 3 April at 15:30 BST on our YouTube channel.

    [youtube https://www.youtube.com/watch?v=kH3BI70M0e0?feature=oembed&w=500&h=281]

    During the webinar, you’ll have the chance to:

    • Ask your questions live. Get any Challenge-related queries answered by us in real time. Whether you need clarification on any part of the Challenge or just want advice on your young people’s project(s), this is your chance to ask.
    • Get introduced to the submission process. Understand the steps of submitting projects to the Challenge. We’ll walk you through the requirements and offer tips for making your young people’s submission stand out.
    • Learn more about our project feedback. Find out how we will deliver our personalised feedback on submitted projects (UK only).
    • Find out how we will recognise your creators’ achievements. Learn more about our showcase event taking place in July, and the certificates and posters we’re creating for you and your young people to celebrate submitting your projects.

    Subscribe to our YouTube channel and press the ‘Notify me’ button to receive a notification when we go live. 

    Why take part? 

    The Experience AI Challenge, created by the Raspberry Pi Foundation in collaboration with Google DeepMind, guides young people under the age of 18, and their mentors, through the exciting process of creating their own unique artificial intelligence (AI) project. Participation is completely free.

    Central to the Challenge is the concept of project-based learning, a hands-on approach that gets learners working together, thinking critically, and engaging deeply with the materials. 

    A teacher and three students in a classroom. The teacher is pointing at a computer screen.

    In the Challenge, young people are encouraged to seek out real-world problems and create possible AI-based solutions. By taking part, they become problem solvers, thinkers, and innovators. 

    And to every young person based in the UK who creates a project for the Challenge, we will provide personalised feedback and a certificate of achievement, in recognition of their hard work and creativity. Any projects considered as outstanding by our experts will be selected as favourites and its creators will be invited to a showcase event in the summer. 

    Resources ready for your classroom or club

    You don’t need to be an AI expert to bring this Challenge to life in your classroom or coding club. Whether you’re introducing AI for the first time or looking to deepen your young people’s knowledge, the Challenge’s step-by-step resource pack covers all you and your young people need, from the basics of AI, to training a machine learning model, to creating a project in Scratch.  

    In the resource pack, you will find:

    • The mentor guide contains all you need to set up and run the Challenge with your young people 
    • The creator guide supports young people throughout the Challenge and contains talking points to help with planning and designing projects 
    • The blueprint workbook helps creators keep track of their inspiration, ideas, and plans during the Challenge 

    The pack offers a safety net of scaffolding, support, and troubleshooting advice. 

    Find out more about the Experience AI Challenge

    By bringing the Experience AI Challenge to young people, you’re inspiring the next generation of innovators, thinkers, and creators. The Challenge encourages young people to look beyond the code, to the impact of their creations, and to the possibilities of the future.

    You can find out more about the Experience AI Challenge, and download the resource pack, from the Experience AI website.

    Website: LINK

  • Experience AI: Making AI relevant and accessible

    Experience AI: Making AI relevant and accessible

    Reading Time: 7 minutes

    Google DeepMind’s Aimee Welch discusses our partnership on the Experience AI learning programme and why equal access to AI education is key. This article also appears in issue 22 of Hello World on teaching and AI.

    From AI chatbots to self-driving cars, artificial intelligence (AI) is here and rapidly transforming our world. It holds the potential to solve some of the biggest challenges humanity faces today — but it also has many serious risks and inherent challenges, like reinforcing existing patterns of bias or “hallucinating”, a term that describes AI making up false outputs that do not reflect real events or data.

    A teenager learning computer science.
    Young people need the knowledge and skills to navigate and shape AI.

    Teachers want to build young people’s AI literacy

    As AI becomes an integral part of our daily lives, it’s essential that younger generations gain the knowledge and skills to navigate and shape this technology. Young people who have a foundational understanding of AI are able to make more informed decisions about using AI applications in their daily lives, helping ensure safe and responsible use of the technology. This has been recognised for example by the UK government’s AI Council, whose AI Roadmap sets out the goal of ensuring that every child in the UK leaves school with a basic sense of how AI works.

    Learner in a computing classroom.
    Every young person should have access to learning AI literacy.

    But while AI literacy is a key skill in this new era, not every young person currently has access to sufficient AI education and resources. In a recent survey by the EdWeek Research Center in the USA, only one in 10 teachers said they knew enough about AI to teach its basics, and very few reported receiving any professional development related to the topic. Similarly, our work with the Raspberry Pi Computing Education Research Centre has suggested that UK-based teachers are eager to understand more about AI and how to engage their students in the topic.

    Bringing AI education into classrooms

    Ensuring broad access to AI education is also important to improve diversity in the field of AI to ensure safe and responsible development of the technology. There are currently stark disparities in the field and these start already early on, with school-level barriers contributing to underrepresentation of certain groups of people. By increasing diversity in AI, we bring diverse values, hopes, and concerns into the design and deployment of the technology — something that’s critical for AI to benefit everyone.

    Kenyan children work on a physical computing project.
    Bringing diverse values into AI is critical.

    By focusing on AI education from a young age, there is an opportunity to break down some of these long-standing barriers. That’s why we partnered with the Raspberry Pi Foundation to co-create Experience AI, a new learning programme with free lesson plans, slide decks, worksheets and videos, to address gaps in AI education and support teachers in engaging and inspiring young people in the subject.

    The programme aims to help young people aged 11–14 take their first steps in understanding the technology, making it relevant to diverse learners, and encouraging future careers in the field. All Experience AI resources are freely available to every school across the UK and beyond.

    A woman teacher helps a young person with a coding project.
    The Experience AI resources are free for every school.

    The partnership is built on a shared vision to make AI education more inclusive and accessible. Bringing together the Foundation’s expertise in computing education and our cutting-edge technical knowledge and industry insights has allowed us to create a holistic learning experience that connects theoretical concepts and practical applications.

    Experience AI: Informed by AI experts

    A group of 15 research scientists and engineers at Google DeepMind contributed to the development of the lessons. From drafting definitions for key concepts, to brainstorming interesting research areas to highlight, and even featuring in the videos included in the lessons, the group played a key role in shaping the programme in close collaboration with the Foundation’s educators and education researchers.

    Interview for Experience AI at Google DeepMind.
    Interviews with AI scientists and engineers at Google DeepMind are part of Experience AI.

    To bring AI concepts to life, the lessons include interactive activities as well as real-life examples, such as a project where Google DeepMind collaborated with ecologists and conservationists to develop machine learning methods to study the behaviour of an entire animal community in the Serengeti National Park and Grumeti Reserve in Tanzania.

    Elephants in the Serengeti.
    One of the Experience AI lessons focuses on an AI-enabled research project in the Serengeti.

    Member of the working group, Google DeepMind Research Scientist Petar Veličković, shares: “AI is a technology that is going to impact us all, and therefore educating young people on how to interact with this technology is likely going to be a core part of school education going forward. The project was eye-opening and humbling for me, as I learned of the challenges associated with making such a complex topic accessible — not only to every pupil, but also to every teacher! Observing the thoughtful approach undertaken by the Raspberry Pi Foundation left me deeply impressed, and I’m taking home many useful ideas that I hope to incorporate in my own AI teaching efforts going forward.”

    The lessons have been carefully developed to:

    • Follow a clear learning journey, underpinned by the SEAME framework which guides learners sequentially through key concepts and acts as a progression framework.
    • Build foundational knowledge and provide support for teachers. Focus on teacher training and support is at the core of the programme.
    • Embed ethics and responsibility. Crucially, key concepts in AI ethics and responsibility are woven into each lesson and progressively built on. Students are introduced to concepts like data bias, user-focused approaches, model cards, and how AI can be used for social good. 
    • Ensure cultural relevance and inclusion. Experience AI was designed with diverse learners in mind and includes a variety of activities to enable young people to pick topics that most interest them. 

    What teachers say about the Experience AI lessons

    To date, we estimate the resources have reached 200,000+ students in the UK and beyond. We’re thrilled to hear from teachers already using the resources about the impact they are having in the classroom, such as Mrs J Green from Waldegrave School in London, who says: “I thought that the lessons covered a really important topic. Giving the pupils an understanding of what AI is and how it works will become increasingly important as it becomes more ubiquitous in all areas of society. The lessons that we trialled took some of the ‘magic’ out of AI and started to give the students an understanding that AI is only as good as the data that is used to build it. It also started some really interesting discussions with the students around areas such as bias.”

    An educator points to an image on a student's computer screen.
    Experience AI offers support for teachers.

    At North Liverpool Academy, teacher Dave Cross tells us: “AI is such a current and relevant topic in society that [these lessons] will enable Key Stage 3 computing students [ages 11–14] to gain a solid foundation in something that will become more prevalent within the curriculum, and wider subjects too as more sectors adopt AI and machine learning as standard. Our Key Stage 3 computing students now feel immensely more knowledgeable about the importance and place that AI has in their wider lives. These lessons and activities are engaging and accessible to students and educators alike, whatever their specialism may be.”

    A stronger global AI community

    Our hope is that the Experience AI programme instils confidence in both teachers and students, helping to address some of the critical school-level barriers leading to underrepresentation in AI and playing a role in building a stronger, more inclusive AI community where everyone can participate irrespective of their background. 

    Children in a Code Club in India.

    Today’s young people are tomorrow’s leaders — and as such, educating and inspiring them about AI is valuable for everybody.

    Teachers can visit experience-ai.org to download all Experience AI resources for free.

    We are now building a network of educational organisations around the world to tailor and translate the Experience AI resources so that more teachers and students can engage with them and learn key AI literacy skills. Find out more.

    Website: LINK

  • AI literacy for teachers and students all over the world

    AI literacy for teachers and students all over the world

    Reading Time: 5 minutes

    I am delighted to announce that the Raspberry Pi Foundation and Google DeepMind are building a global network of educational organisations to bring AI literacy to teachers and students all over the world, starting with Canada, Kenya, and Romania.

    Learners in a classroom in Kenya.
    Learners around the world will gain AI literacy skills through Experience AI.

    Experience AI 

    We launched Experience AI in September 2022 to help teachers and students learn about AI technologies and how they are changing the world. 

    Developed by the Raspberry Pi Foundation and Google DeepMind, Experience AI provides everything that teachers need to confidently deliver engaging lessons that will inspire and educate young people about AI and the role that it could play in their lives.

    A group of young people investigate computer hardware together.
    Experience AI is designed to inspire learners about AI through real-world contexts.

    We provide lesson plans, classroom resources, worksheets, hands-on activities, and videos that introduce a wide range of AI applications and the underlying technologies that make them work. The materials are designed to be relatable to young people and can be taught by any teacher, whether or not they have a technical background. Alongside the classroom resources, we provide teacher professional development, including an online course that provides an introduction to machine learning and AI. 

    Part of Experience AI are video interviews with AI developers at Google DeepMind.

    The materials are grounded in real-world contexts and emphasise the potential for young people to positively change the world through a mastery of AI technologies. 

    Since launching the first resources, we have seen significant demand from teachers and students all over the world, with over 200,000 students already learning with Experience AI. 

    Experience AI network

    Building on that initial success and in response to huge demand, we are now building a global network of educational organisations to expand the reach and impact of Experience AI by translating and localising the materials, promoting them to schools, and supporting teacher professional development.

    Obum Ekeke OBE, Head of Education Partnerships at Google DeepMind, says:

    “We have been blown away by the interest we have seen in Experience AI since its launch and are thrilled to be working with the Raspberry Pi Foundation and local partners to expand the reach of the programme. AI literacy is a critical skill in today’s world, but not every young person currently has access to relevant education and resources. By making AI education more inclusive, we can help young people make more informed decisions about using AI applications in their daily lives, and encourage safe and responsible use of the technology.”

    Learner in a computing classroom.
    Experience AI helps learners understand how they might use AI to positively change the world.

    Today we are announcing the first three organisations that we are working with, each of which is already doing fantastic work to democratise digital skills in their part of the world. All three are already working in partnership with the Raspberry Pi Foundation and we are excited to be deepening and expanding our collaboration to include AI literacy.

    Digital Moment, Canada

    Digital Moment is a Montreal-based nonprofit focused on empowering young changemakers through digital skills. Founded in 2013, Digital Moment has a track record of supporting teachers and students across Canada to learn about computing, coding, and AI literacy, including through supporting one of the world’s largest networks of Code Clubs. 

    Digital Moment logo.

    “We’re excited to be working with the Raspberry Pi Foundation and Google DeepMind to bring Experience AI to teachers across Canada. Since 2018, Digital Moment has been introducing rich training experiences and educational resources to make sure that Canadian teachers have the support to navigate the impacts of AI in education for their students. Through this partnership, we will be able to reach more teachers and with more resources, to keep up with the incredible pace and disruption of AI.”

    Indra Kubicek, President, Digital Moment

    Tech Kidz Africa, Kenya

    Tech Kidz Africa is a Mobasa-based social enterprise that nurtures creativity in young people across Kenya through digital skills including coding, robotics, app and web development, and creative design thinking.

    Tech Kidz Africa logo.

    “With the retooling of teachers as a key objective of Tech Kidz Africa, working with Google DeepMind and the Raspberry Pi Foundation will enable us to build the capacity of educators to empower the 21st century learner, enhancing the teaching and learning experience to encourage innovation and  prepare the next generation for the future of work.”

    Grace Irungu, CEO, Tech Kidz Africa

    Asociația Techsoup, Romania

    Asociația Techsoup works with teachers and students across Romania and Moldova, training Computer Science, ICT, and primary school teachers to build their competencies around coding and technology. A longstanding partner of the Raspberry Pi Foundation, they foster a vibrant community of CoderDojos and support young people to participate in Coolest Projects and the European Astro Pi Challenge. 

    Asociata Techsoup logo.

    “We are enthusiastic about participating in this global partnership to bring high-quality AI education to all students, regardless of their background. Given the current exponential growth of AI tools and instruments in our daily lives, it is crucial to ensure that students and teachers everywhere comprehend and effectively utilise these tools to enhance their human, civic, and professional potential. Experience AI is the best available method for AI education for middle school students. We couldn’t be more thrilled to work with the Raspberry Pi Foundation and Google DeepMind to make it accessible in Romanian for teachers in Romania and the Republic of Moldova, and to assist teachers in fully integrating it into their classes.”

    Elena Coman, Director of Development, Asociația Techsoup

    Get involved

    These are the first of what will become a global network of organisations supporting tens of thousands of teachers to equip millions of students with a foundational understanding of AI technologies through Experience AI. If you want to get involved in inspiring the next generation of AI leaders, we would love to hear from you.

    Website: LINK

  • The Experience AI Challenge: Make your own AI project

    The Experience AI Challenge: Make your own AI project

    Reading Time: 4 minutes

    We are pleased to announce a new AI-themed challenge for young people: the Experience AI Challenge invites and supports young people aged up to 18 to design and make their own AI applications. This is their chance to have a taste of getting creative with the powerful technology of machine learning. And equally exciting: every young creator will get feedback and encouragement from us at the Raspberry Pi Foundation.

    As you may have heard, we recently launched a series of classroom lessons called Experience AI in partnership with Google DeepMind. The lesson materials make it easy for teachers of all subjects to teach their learners aged up to 18 about artificial intelligence and machine learning. Now the Experience AI Challenge gives young people the opportunity to develop their skills further and build their own AI applications.

    Key information

    • Starts on 08 January 2024
    • Free to take part in
    • Designed for beginners, based on the tools Scratch and Machine Learning for Kids
    • Open for official submissions made by UK-based young people aged up to 18 and their mentors 
    • Young people and their mentors around the world are welcome to access the Challenge resources and make AI projects
    • Tailored resources for young people and mentors to support you to take part
    • Register your interest and we’ll send you a reminder email on the launch day

    The Experience AI Challenge

    For the Experience AI Challenge, you and the young people you work with will learn how to make a machine learning (ML) classifier that organises data types such as audio, text, or images into different groupings that you specify.

    A girl points excitedly at a project on the Raspberry Pi Foundation's projects site.

    The Challenge resources show young people the basic principles of using the tools and training ML models. Then they will use these new skills to create their own projects, and it’s a chance for their imaginations to run free. Here are some examples of projects your young tech creators could make:

    • An instrument classifier to identify the type of musical instrument being played in pieces of music
    • An animal sound identifier to determine which animal is making a particular sound
    • A voice command recogniser to detect voice commands like ‘stop’, ‘go’, ‘left’, and ‘right’
    • A photo classifier to identify what kind of food is shown in a photograph

    All creators will receive expert feedback on their projects.

    To make the Experience AI Challenge as familiar and accessible as possible for young people who may be new to coding, we designed it for beginners. We chose the free, easy-to-use, online tool Machine Learning for Kids for young people to train their machine learning models, and Scratch as the programming environment for creators to code their projects. If you haven’t used these tools before, don’t worry. The Challenge resources will provide all the support you need to get up to speed.

    Training an ML model and creating a project with it teaches many skills beyond coding, including computational thinking, ethical programming, data literacy, and developing a broader understanding of the influence of AI on society.

    The three Challenge stages

    Our resources for creators and mentors walk you through the three stages of the Experience AI Challenge.

    Stage 1: Explore and discover

    The first stage of the Challenge is designed to ignite young people’s curiosity. Through our resources, mentors let participants explore the world of AI and ML and discover how these technologies are revolutionising industries like healthcare and entertainment.

    Stage 2: Get hands-on

    In the second stage, young people choose a data type and embark on a guided example project. They create a training dataset, train an ML model, and develop a Scratch application as the user interface for their model. 

    Stage 3: Design and create

    In the final stage, mentors support young people to apply what they’ve learned to create their own ML project that addresses a problem they’re passionate about. They submit their projects to us online and receive feedback from our expert panel.

    Things to do today

    1. Visit our new Experience AI Challenge homepage to find out more details
    2. Register your interest so you receive a reminder email on launch day, 8 January
    3. Get your young people excited and thinking about what kind of AI project they might like to create

    We can’t wait to see how you and your young creators choose to engage with the Experience AI Challenge!

    Website: LINK