Earlier this year we announced that after ten years of creative collaboration, we would be closing We Are Open Co-op on May 1st.

May 1st has arrived.

We have spent the last few weeks archiving a decade of work and created a new website to link to our various GitHub repositories and assets around the web. The wonderful Bryan Mathers created some images for us to help us explain our journey and the decision to close.

So long and thanks for all the fish:

How hard can it be?

We started with four of us as founding members, expanded to six, went back to four and are ending with three. It all started with a shared hunch that we’d enjoy working together, and could run a fair and effective organisation.

Three of the four of us didn’t really know what a co-op was when we started. We found out by becoming one and figuring it out as we went along — which, it turns out, is how a lot of co-ops go about things. Like a magpie, you borrow bits of the governance docs from other co-ops, discuss (and argue) about the rest, and then 10 years later, you realise you’ve become one of the places that people are borrowing from!

It has been, as Bryan puts it in the above cartoon, one hell of a journey.

The job under the job

Earning enough money to live on is a skill. As is making good decisions collaboratively, defusing conflict, and learning how to work according to your values. Sometimes you learn these things on purpose, and sometimes you only acquire them by making mistakes.

We’ve had difficult years and good ones. And the good ones were usually built on the difficult ones.

The thing that nobody tells you about starting a co-op is that being cooperative is the best and the worst thing about it. Flat hierarchies don’t magically remove conflict — they just mean that nobody else will resolve it for you. Over time, you learn when to sit in discomfort and when to ask for help. You realise that “shall we start a co-op?” was actually a question with ten years of homework attached…

What we actually did

We turned up continually for organisations who were trying to make the world a better place. Most of them had got themselves tangled up a bit while working on big ideas and big missions. We helped charities who needed help figuring out how to reconnect with their communities, mission-driven tech projects that had outgrown their original mission, and organisations looking for more innovative ways to make an impact.

Rarely did we arrive with a finished answer. We were there to ask the hard questions and hold up a mirror to the client so that they could see the mess. Then, we got to work, in partnership, with them to sort it out. We were often the people behind the curtain, nudging organisations to be bold, think big and make choices that truly adhere with their (and our) values.

What kept us going — right until the end — is that the work didn’t stop when our project ended. We know our collaborators and clients are out there making better decisions, working more openly, and working more in alignment with their values than they did before they met us. You can’t always see this, but we know it’s there.

The books we could write…

When we asked Bryan to help us summarise what a decade of WAO has actually been about, he created these eight books. Some of them are in-jokes, but let’s imagine leafing through three of them.

Radical collaboration

Being ‘radical’ isn’t about being edgy for the sake of it. Instead, it’s about refusing to do the thing that most organisations ask you to do: leave most of yourself at the door, and show up as a smaller, more ‘professional’ version. This is very much not what we are about.

We wanted to work with each other, and with clients, as fully human beings. That made partnership the default, and meant being honest with clients when we thought they were wrong — and listening carefully when they thought we were.

Recipes for Co-operative Living

We’ve learned so much along the way, including some things we didn’t even know we needed until we stumbled across them. Sociocracy (aka consent-based decision-making), non-violent communication, pre-mortems. Checking-in with each other at the start of every meeting and co-working sessions.

Again, like magpies, we picked these things up from people who we realised were better at this kind of stuff than us. We learned heaps from Outlandish, as well as other cooperatives in the CoTech network. We got involved with Workers.coop and found that not only did we have more to learn, we had loads to teach as well.

Spaghetti Untangling for Beginners

For years, we struggled to explain what we did. We’d talk about ‘openness’ or ‘digital transformation’ or offer to run a Thinkathon to help them ‘get underneath’ a problem. We tried to explain that we are generalists at intersections like technology, community and learning. We tried to showcase our collective skills, and it was always difficult because we’re so similar and also so unique. At some point, we realised that we untangled organisations.

Time after time, people would arrive to us with a knotted-up thing. It could be a project, a community, a whole organisation — or even just an idea that got wrapped around itself. We’d figure out the shape of the knot, find an end, and pull gently. Just the tip, and then the rest would unravel itself.

Why now?

Laura’s sabbatical starts today. John’s looking for a job. Doug is carrying on consulting. Right now, we all want and need slightly different things. These are all positive directions, it’s just that they’re not the same direction any more.

We could have kept going anyway. Many of our clients and friends actually asked us to. In all the ways that “business” is supposed to matter — clients, infrastructure, equity — we are ok. And lots of organisations do this — especially co-ops, forcing themselves to keep going because things are just fine. But we didn’t fancy being one of them. We don’t want to limp along while we’re stretching in different directions, having to contort ourselves to continue. Instead, we’re closing intentionally, while we still like one another, before anyone pulls a muscle. It’s hugely emotional, but it feels like the right call.

A quick note on Bryan

Every image in this post, and in most of our posts, is by Bryan Mathers. He has been an inspirational founding member and then collaborator to WAO over the years. Without overdoing it, we want to thank Bryan from the bottom of our hearts for bringing our ideas to life, and for contributing so much energy (“sunshine”) during the past decade.

The visual thinkery he created for WAO is now archived on GitHub. Go and have a look at him, then hire him: he will make whatever you’re doing better.

…and Hannah

Hannah Belshaw was our administrator from the start of the co-op until she changed careers to User Research. She was always a voice of calm, reason, and ensured that during the early days, we remained solvent!

…and Anne

Anne Hilliger joined us as an intern, and to our delight, continued with us as a collaborator until she landed a fantastic job. She worked on so many different projects while she was with us, and was also a source of inspiration and joy.

Thank you Bryan, Hannah, and Anne, our work was better for you being part of it 🙏

Redistribution

The first law of thermodynamics states that energy cannot be created or destroyed, only transformed from one form to another. With that in mind, we like to think that our work is being ‘composted’ to be used as a kind of mulch or fertiliser for the next batch of great ideas to spring from.

The methods and approaches we picked up and developed will find their way into other teams. Practices will continue on into new projects. Friendships will bloom. Openly-licensed resources will turn up in unexpected places, proving useful to people we’ll never meet.

Our domain will be active for another couple of years and then it won’t. Which is fine.

To our clients: thank you for trusting us — especially those at the start when we didn’t really know what we were doing.

To our partner co-ops and the wider co-op community: thanks for the solidarity, the connections, and the learning.

To everyone who attended workshops, commented on our posts, and could be thought of as part of our community: thank you. You were never just an ‘audience’. You were part of the compost heap.

See you on the internet

You can get in touch with us by reaching out personally:

• Doug can be contacted at hello[at]dynamicskillset.com
• Laura can be contacted at hello[at]laurahilliger.com
• John can be contacted at hello[at]johnbevan.com

We Are Composting was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

After ten years of creative cooperation, we’re announcing that We Are Open Co-op (WAO) will close its doors on our 10th birthday: 1st May 2026. This has been a carefully considered, collaborative decision — the kind we’ve always tried to model as a co-op.

But, as you can imagine, we’re a bit emotional about it, and it also feels a bit weird to finally say it out loud and in public.

WAO is a strong, well-respected brand. We continue to have wonderful clients, meaningful work and good relationships with each other. People are finally waking up to the idea that flat hierarchies and consent-driven businesses are the future.

In some ways, this is a continuation rather than an ending, as we’ll be carrying forward the cooperative principles we’ve practised into new systems and relationships.

So what’s going on?

Change. It’s the only thing that stays the same.

Ten years of We Are Open has taught us that openness is less about tools and more about trust. We’ve collaborated with brilliant people, learned from our mistakes, and stayed curious together. That feels like success to us.

We’ve been running We Are Open Co-op for a decade now, and while we remain friends (and probably future colleagues), we’ve decided that it’s time to move on. As a cooperative, we’re known for a particular kind of work. As individuals, we find ourselves looking to expand in directions that impact each other as well as our cooperative:

• John is looking to get into a full-time gig that spotlight his gift for building relationships and trust.. Alternatively, he wants to work outside for a while.
• Laura is taking a sabbatical starting on May 1st. She made no major plans because she’s not sure what happens when a person who has never stopped just…stops. She will write and wander and build things and try to figure out where she wants to point her big brain next.
• Doug is eager to continue the good work of our collective, both on his own and with new collaborators. He will continue working with our current clients while also focusing more on helping organisations deal with complexity.

Closing WAO thoughtfully and responsibly means that each of us gets to reflect on and celebrate what we’ve achieved without leaving any one of us with the current shared burden of responsibilities and accountabilities of running a business.

Open Sourcing our work

We’ve always worked openly. The clue is in the name!

So we want to figure out what to do with all our stuff. We have so many artifacts and resources. There are truly useful things that we want to make sure remain open and accessible.

That means we have some archiving to do. We’ve already started planning and implementing this, and will spend the next couple of months putting things in various places.

Here’s what we’re planning:

• Websites — we’ll be using the Internet Archive’s wonderful Wayback Machine to ensure that our websites and blog posts remain available. Here’s an example blog post so you can see how it works.
• Podcasts and other audio/visual media — these will be collated in lists on the Internet Archive. For example, we’ve uploaded and listed every season of the Tao of WAO podcast.
• Pages, courses, images & other resources — we’ll use GitHub repositories, pages, and wikis to share everything that doesn’t fit elsewhere. For example, we’ve already archived the wonderful visual thinkery that former member Bryan Mathers created for us.

Helpfully, we recently renewed our domain for a couple of years, so weareopen.coop will remain our canonical link until September 2028.

At the start of May this year we’ll upload a redesigned “We Are (no longer) Open” site that serves as an index page to help people find their way through our archives.

But I was about to hire you!

That’s awesome to hear. If you have a project and want to chat about it now, please do get in touch –We may take on *some* new work in the next 10 weeks. However, projects that have timelines that extend out beyond May 1, 2026 will potentially need to have multiple contracts/agreements.

For future work, please get in touch with us individually:

• Doug can be contacted at hello[at]dynamicskillset.com
• Laura can be contacted at hello[at]laurahilliger.com
• John can be contacted at hello[at]johnbevan.com

We Are Closing was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

It’s been a minute, but we’re reminding you we’re no longer on Medium. We were here for 9 (!) years, so this quick post is for our Medium followers who haven’t yet signed up at https://blog.weareopen.coop

We’ve moved to Ghost! was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

Over the past 9+ years, we’ve been working openly and publishing blog posts regularly here in our Medium publication. It’s time for us to move to a platform we have more control over. We’ve transferred all our blog posts to Ghost, an open source alternative to Medium that is more inline with our values. We have already mapped our beloved domain and will no longer be writing on Medium (except for a few posts to remind YOU to subscribe to us on Ghost).

If you’ve followed us on Medium, we really hope you’ll resubscribe. There’s a button on the front page of https://blog.weareopen.coop/ :)

As ever, we are open, so if you want to get in touch here’s a few ways to do so:

• Schedule a chat!
• Reach out on Mastodon
• Hit us up on LinkedIn (not recommended, some of us avoid LinkedIn regularly)

All things change was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

In this post, we continuing to share outputs from a project we’re working with the Responsible Innovation Centre for Public Media Futures (RIC), hosted by the BBC. We’ve already published:

• What does AI Literacy look like for young people aged 14–19?
• What makes for a good AI Literacy framework?
• Core Values for AI Literacy
• AI Literacy or AI Literacies?

This project has involved both desk research and input from experts in the form of a survey, individual interviews, and a roundtable which we hosted a couple of weeks ago. One area we wanted to ensure we understood were gaps in existing provision around AI Literacies for young people.

The gaps we identified were focused on the 14–19 age range in the UK, with a long list of areas with many themes. We have organised and summarised these around the core values identified in a previous post.

The gaps reflect a pattern seen across education, media, and wider society: provision is uneven. It is often shaped by short-term thinking and competing interests. Overall, it is limited by a lack of clear leadership or coordination.

Unfortunately, many interventions around AI Literacies are focused on technical skills or compliance. These do not connect with young people’s real interests or lived experiences, nor do they address the deeper ethical, social, and cultural questions raised by AI.

As a result of this, many learners — especially those already facing disadvantage — are left with fragmented support and few opportunities to develop genuine agency or critical judgement.

Human Agency and Informed Participation

• Lack of systemic, rights-based frameworks: There is little structured provision to help young people shape, question, or influence AI, with most education focused on adapting to technology rather than encouraging agency or clarifying institutional responsibilities.
• Dominance of industry narratives: Commercial interests and tech industry funding often drive the agenda, narrowing the conversation and limiting opportunities for young people to challenge prevailing narratives or understand the political dimensions of AI.
• Insufficient progression and curriculum integration: There is no standardised, dynamic curriculum or progression framework for AI Literacies, especially for post-16 learners, and limited integration across subjects beyond computing or digital studies.
• Teacher confidence and support gaps: Many teachers lack confidence, training, and adaptable resources to support the development of AI Literacies, resulting in inconsistent, sometimes contradictory, messaging and limited support for critical engagement.
• Disconnect between knowledge and action: Awareness of AI bias, manipulation, or power structures does not reliably translate into agency or behavioural change, with motivation and broader social context often overlooked.

Equity, Diversity, and Inclusion

• Persistent digital and social divides: Access to tools and resources to develop AI Literacies is highly unequal, shaped by school policies, family resources, and broader digital divides, with privileged students often able to bypass restrictions.
• Lack of cultural and global adaptation: Most resources are developed in the global north and do not reflect the needs or realities of diverse cultural, socioeconomic, or linguistic backgrounds, including those from in the global south.
• Barriers for marginalised groups: AI tools and resources can disadvantage non-native English speakers, students with disabilities, and those with limited digital access, reinforcing existing inequalities.
• Neglect of visual and multimodal literacy: There is insufficient focus on images, deepfakes, and multimodal content, despite their growing importance for misinformation and manipulation.
• Resource design and authenticity: Overly polished, anthropomorphised, or inaccessible resources can alienate young people; there is a need to co-design authentic, relatable, and context-driven materials that reflect lived experiences with young people from a range of background

Creativity, Participation, and Lifelong Learning

• Short-termism and lack of sustainability: Funding and interventions are often short-lived, with little focus on long-term, joined-up strategies or progression frameworks.
• Imbalance between creativity and consumption: Most young people are consumers, not creators, of AI content; there is insufficient emphasis on participatory, creative, and hands-on engagement with AI.
• Restrictive and risk-averse policies: Overly strict barriers on access to AI tools in schools can limit meaningful learning opportunities and create anxiety or underground use.
• Missed opportunities for experiential and peer learning: There is underuse of hands-on, constructionist, and peer-led approaches, which are effective for this age group and for a rapidly evolving field like AI.
• Failure to address entrenched digital habits: Many interventions come too late to shift established digital habits; young people may have high digital skill but lack guidance on purposeful, critical, or participatory use.

Critical Thinking and Responsible Use

• Overemphasis on technical skills: Current provision is skewed towards prompt engineering and functional tool use, with insufficient attention to understanding different kinds of AI, ethical reasoning, systemic impacts, and critical engagement.
• Insufficient ethical, environmental, and societal focus: Real-world harms, environmental costs, and the broader impact of AI are rarely discussed, leaving gaps in understanding responsible use.
• Media and information literacy gaps: Algorithmic and data literacy gaps: Young people struggle to understand how data shapes AI outputs, how to assess real versus fake (including deepfakes), and how to evaluate, challenge or seek redress for algorithmic decisions or AI-generated content.
• Anthropomorphism and mental models: Many young people, particularly younger teens, misattribute human-like qualities to AI, affecting their critical judgement and ability to interrogate outputs.
• Lack of robust assessment and evidence: There is a shortage of baseline data on AI literacy levels and limited frameworks for evaluating the effectiveness and impact of interventions, especially in terms of behavioural change.

Upholding Human Rights and Wellbeing

• Disconnection from youth interests and lived experience: AI Literacy resources often fail to connect to young people’s real interests (creativity, sports, mental health), focusing instead on employability or compliance.
• Socio-emotional and privacy risks: Young people may use AI for companionship or advice, sharing sensitive information without understanding privacy or data risks; frameworks rarely address identity, trust, or changing markers of adulthood.
• Confusion and inconsistency in terminology: There is no consensus on what “AI literacy” means, and inconsistent definitions can intimidate learners or place excessive responsibility on individuals.
• Unclear responsibility and leadership: It remains unclear who should lead on the development of AI Literacies. Schools, parents, government, industry, and third sector bodies all have a role to play, but the current situation leads to fragmented provision and a lack of accountability.
• Neglect of digital relationships and boundaries: The role of AI as an “invisible third party” in relationships, and the shifting boundaries of privacy and identity, are rarely addressed in current resources.

Next up

We’re still finalising our framework for AI Literacies and will be sharing it soon. Meanwhile, you can follow our work on this topic so far at https://ailiteracy.fyi.

Please do get in touch if you have projects and programmes that can benefit from our experience and expertise in education and technology!

Acknowledgements

The following people have willingly given up their time to provide invaluable input to this project:

Jonathan Baggaley, Prof Maha Bali, Dr Helen Beetham, Dr Miles Berry, Prof. Oli Buckley, Prof. Geoff Cox​, Dr Rob Farrow, Natalie Foos, Leon Furze, Ben Garside, Dr Daniel Gooch, Dr Brenna Clarke Gray, Dr Angela Gunder, Katie Heard, Prof. Wayne Holmes, Sarah Horrocks, Barry Joseph, Al Kingsley MBE, Dr Joe Lindley, Prof. Sonia Livingstone, Chris Loveday, Prof. Ewa Luger, Cliff Manning, Dr Konstantina Martzoukou, Prof. Julian McDougall, Prof. Gina Neff, Dr Nicola Pallitt, Rik Panganiban, Dr Gianfranco Polizzi, Dr Francine Ryan, Renate Samson, Anne-Marie Scott, Dr Cat Scutt MBE, Dr Sue Sentance, Vicki Shotbolt, Bill Thompson, Christian Turton, Dr Marc Watkins, Audrey Watters, Prof. Simeon Yates, Rebecca Yeager

Gaps in AI Literacy provision was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

A couple of months ago, after seeing a UNESCO call for contributions, Doug began wrangling a group of thinkers and educators to respond to the call in a collaborative and open way. Naturally, I got involved, and thus we thought this story would be a good one for the WAO blog :)

There were six of us on that stormy night…

• Bryan Alexander — an internationally known futurist, researcher, writer with this popular blog and newsletter, AI, academia, and the Future.
• ​Helen Beetham — a researcher and consultant in digital education who has edited several standard texts including Rethinking Pedagogy for a Digital Age. Her articles on AI, education, and society can be found at imperfect offerings.
• ​Doug Belshaw — co-founder of We Are Open Co-op, working at the intersection of systems thinking, digital literacies, and Open Recognition. Doug’s writings can be accessed via his website.
• ​Laura Hilliger — concept architect, open strategist, and co-founder of We Are Open Co-op. Her website contains links to her blog and newsletter.
• ​Ian O’Byrne — Associate Professor of Literacy Education at the College of Charleston. He maintains an active presence through his website and weekly newsletter Digitally Literate.
• ​Karen Louise Smith — Associate Professor in the Department of Communication, Popular Culture and Film at Brock University. She teaches courses related to social media, surveillance, and new media policy and her writing can be accessed via her website.

The six of us met up online to chat about how we might collaborate to respond to UNESCO’s call, and decided that we would each write our own think pieces. We then met up regularly to chat about where we were, what ideas were floating around and get inspiration from one another. Once we had drafts, we each read each other’s pieces offering comments and suggestions.

Our finished pieces can be found at this linktree: https://linktr.ee/ai_future_education

After we submitted our think pieces to UNESCO, we decided to do a roundtable event hosted by Doug. Over 100 people signed up, with 50 more on the waitlist. Participants gathered to discuss the transformative potential of Artificial Intelligence (AI) in education. The event brought together educators, tech experts, and policymakers to dissect our six pieces on AI’s future role in learning environments.

This blog post summarises our very nuanced discussion surrounding AI’s role in education. If you’re interested in this type of thing, we’d recommend watching the full session.

1. Personalized Learning

One of the themes discussed was personalized learning facilitated by AI. While AI can functionally analyze student data to tailor curricula and pacing, we talked about the emotional and social dimensions of learning. The lack of empathy in AI systems hinders holistic education, which requires human interaction.

2. Equity and Access

We talked about the theory that AI could democratize access to quality education, but we highlighted significant challenges. Unequal access exacerbates existing disparities in educational opportunities, and it is not just infrastructure that is inequitable in our education system.

3. The Educator’s Role

AI’s impact on educators’ roles was another theme in our conversation. While AI can handle routine tasks like grading, potentially reducing administrative burdens, there are concerns about over-reliance on technology displacing human interaction. We argued for understanding teachers as mentors, facilitators, guardians and creatives to try and make clear that “efficiency” is not a goal in education.

4. Privacy and Bias

We talked a lot about the ethical implications surrounding various aspects of AI. From data privacy concerns, algorithmic bias, and transparency in AI decision-making, we stressed the importance of ethical guidelines and accountability measures.

5. Collaboration

We talked a bit about the potential for collaboration between educators and AI. We tried to think about what a complementary relationship with AI might look like for education. While AI might enhance some of our teaching tools, it cannot be allowed to overshadow the irreplaceable human element.

6. The Future of Education

In conclusion, we know and spoke about the fact that any technology and its implementation in education must be approached with caution and balance. Our conversation underscored that AI is not a panacea but a technology that exists within a particular context, and that like any technology, it’s how we use it that matters.

Go deeper:

• This is the video ​Recording for the full session
• We made an AI generated ​Chat summary
• ​All of our think pieces are worth a close read. Jump in individually:
• Bryan Alexander — Several futures for AI and education
• Helen Beetham — The implications of ‘artificial intelligence’ for the right to education in equality and dignity
• Doug Belshaw — Marching Backwards into the Future: AI’s Role in the Future of Education
• Laura Hilliger — It is not the tool, it is the artist who sparks the revolution: The Importance of Art Education with or without AI
• Ian O’Byrne — Amplifying Human Cognition: Artificial Intelligence as Mirror and Magnifier
• Karen Louise Smith: Building warm expert expertise to mitigate against data harms in AI-powered edtech

Many thanks to Bryan Mathers of Visual Thinkery, who provided the illustrations included in this post. To see all of those that he drew based on the session, visit his website.

Exploring AI’s Role in Education: A Balanced Perspective from Six Think Pieces was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

Over the past couple of months, we’ve been working on an ‘AI Literacy’ project with the Responsible Innovation Centre for Public Media Futures (RIC), hosted by the BBC. We’ve already published:

• What does AI Literacy look like for young people aged 14–19?
• What makes for a good AI Literacy framework?
• Core Values for AI Literacy

In this post, we want to explore the tension we’ve felt between referring to ‘AI Literacy’ in the singular, versus referring to a plurality of ‘AI Literacies’. Ultimately, although our original brief used the singular form (as do many of our peers) we have decided to take the latter, plural, approach — for reasons we will explain below.

One very practical reason to emphasise ‘AI Literacies’ is that it is difficult to talk about ‘delivering’ a literacy. “Literacy” always begs the question of context: What does literacy mean to this particular person in this particular setting at this particular moment? What it means to be ‘AI literate’ is going to look very different to someone working in a corporate office job, compared to a teenager using AI for a creative project. Additionally, there are multiple literate behaviours when we think about AI — for example, understanding the socio-economic reality of the AI landscape versus knowing how to prompt an LLM to get the kind of information or answer you are looking for.

AI Literacies are therefore both plural and context-specific. They are also socially-negotiated. Literate behaviours depend on the community with which an individual is interacting. This becomes evident through a few examples.

If you are a parent of teenagers, you will have experienced a time when they respond in a way which makes sense to them and their friends, but not to you. You are likely to have to ask them what they mean or use a resource like the Urban Dictionary. Other behaviours such as using a particular emoji might be hilarious for reasons you cannot quite comprehend.

These “rhetorics of communication” are an important part of literacy practices, especially in the digital realm. They constitute ways of interacting with other people within a techno-social system which itself privileges and foregrounds certain kinds of behaviours, while either explicitly or implicitly discouraging others. For example, contemporary chat apps allow you to see not only that a message has been delivered, but whether it has been read. The act of not reading a particular message may be seen in multiple lights: Is the person ignoring me? Are they mad at me? Are they offline in the forest?

Any time we are communicating in ways which are mediated by technologies, part of literate behaviour involves understanding the “affordances” that the technology provides as well as understanding how that technology might be shaping our behaviour.

If you were, for example, quickly texting your teenager while at work, you might send your text and then open a workplace chat window which looks and feels very much like the social one which you have just been using. However, because the context is different — as well as perhaps both the demographic makeup and number of people in the chat — you act differently. =Your literate behaviours are thus socially-negotiated, meaning that you vary your behaviour in different situations.

As we start to understand AI Literacies, we need to think about the most common way in which people experience generative AI — by prompting a Large Language Model (LLM) through a chat window. The chat window is a familiar technology, but the fact that there isn’t a human on the other side of it is not. Part of AI Literacies therefore involves exhibiting and modifying our behaviours based on our knowledge and experience of factors that surround this particular chat window.

With personal or workplace chats, what is outside of the frame informs literate behaviours inside the frame. Similarly, when we are interacting with AI, the more we know about what is outside the frame, the more we can develop appropriate literate behaviours inside the frame. Again, these literate behaviours are plural: will others be able to tell that you are using the outputs of an LLM? (will they mind?) They are based on context: should you trust the company behind the technology you are using? And they are socially-negotiated: are there environmental concerns of which you should be aware?

Angela Gunder’s Dimensions of AI Literacies provides a helpful way to think about these issues. Building on my work on the Essential Elements of Digital Literacies, Gunder’s framework sets out a series of overlapping dimensions that shape how people interact with AI. This approach supports the idea that AI Literacies are not a fixed set of skills, but a collection of practices negotiated within communities and shaped by context.

AI Literacies, like Critical Media Literacies, Digital Literacies, Information Literacies, Data Literacies, and a whole host of “new” literacies, should be considered to be fundamentally plural. What counts as “literate behaviours” are socially-negotiated based on context. Words and phrases, however, are important to describe what we mean. And that is why we will be referring to AI Literacies in the project we’re doing with the RIC for the BBC.

Coming soon

We are working on a public version of our landscape setting and framework for AI Literacies. We’ll be sharing that soon. In the meantime, follow our contributions to this space through https://ailiteracy.fyi/ and get in touch if you have projects and programmes that can benefit from our experience and expertise in education and technology.

Thanks to Laura Hilliger for being a fantastic editor of this post.

AI Literacy or AI Literacies? was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

WAO is currently working with the Responsible Innovation Centre for Public Media Futures (RIC), which is hosted by the BBC. The project, which you can read about in our kick-off post, is focused on research and analysis to help the BBC create policies and content to help improve the AI Literacy skills of young people aged 14–19.

We’re now at the stage where we’ve reviewed academic articles and resources, scrutinised frameworks, and reviewed input from over 40 experts in the field. They are thanked in the acknowledgements section at the end of this post.

One of the things that has come up time and again is the need for an ethical basis for this kind of work. As a result, in this post we want to share the core values that inform the development of our (upcoming) gap analysis, framework, and recommendations.

Public Service Media Values

Public Service Media (PSM) organisations such as the BBC have a mission to “inform, educate, and entertain” the public. The Public Media Alliance lists seven PSM values underpinning organisations’ work as being:

• Accountability: to the public who fund it and hold power to account
• Accessibility: to the breadth of a national population across multiple platforms
• Impartiality: in news and quality journalist and content that informs, educates, and entertains
• Independence: both in terms of ownership and editorial values
• Pluralism: PSM should exist as part of a diverse media landscape
• Reliability: especially during crises and emergencies and tackling disinformation
• Universalism: in their availability and representation of diversity

These values are helpful to frame core values for the development of AI Literacy in young people aged 14–19.

AI Literacy Core Values

Using the PSM values as a starting point, along with our input from experts and our desk research, we have identified the following core values. These are also summarised in the graphic at the top of this post.

1. Human Agency and Empowerment

AI Literacy should empower young people to make informed, independent choices about how, when, and whether to use AI. This means helping develop not just technical ability, but also confidence, curiosity, and a sense of agency in shaping technology, rather than being shaped by it (UNESCO, 2024a; Opened Culture, n.d.). Learners should be encouraged to question, critique, adapt, and even resist AI systems, supporting both individual and collective agency.

2. Equity, Diversity, and Inclusion

All young people, regardless of background, ability, or circumstance should have meaningful access to AI Literacy education (Digital Promise, 2024; Good Things Foundation, 2024). Ensuring this in practice means addressing the digital divide, designing for accessibility, and valuing diverse perspectives and experiences. Resources and opportunities must be distributed fairly, with particular attention to those who are digitally disadvantaged or underrepresented.

3. Critical Thinking and Responsible Use

Young people should be equipped to think critically about AI, which means evaluating outputs, questioning claims, and understanding both the opportunities and risks presented by AI systems. In addition, young people should be encouraged to understand the importance of responsible use, including understanding bias, misinformation, and the ethical implications of AI in society (European Commission, 2022; Ng et al., 2021).

4. Upholding Human Rights and Wellbeing

Using a rights-based approach — including privacy, freedom of expression, and the right to participate fully in society — helps young people understand their rights, navigate issues of consent and data privacy, and recognise the broader impacts of AI on wellbeing, safety, and social justice (OECD, 2022; UNESCO, 2024a).

5. Creativity, Participation, and Lifelong Learning

AI should be presented as a tool for creativity, collaboration, and self-expression, not just as a subject to be learned for its own sake. PSM organisations should value and promote participatory approaches, encouraging young people to contribute to and shape the conversation about AI. This core value also recognises that AI Literacy is a lifelong process, requiring adaptability and a willingness to keep learning as technology evolves (UNESCO, 2024b).

Next Steps

We will be running a roundtable for invited experts and representatives of the BBC in early June to give feedback on the gap analysis and emerging framework. We will share a version of this after acting on their feedback.

If you are working in the area of AI Literacy and have comments on these values, please add them to this post, or get in touch: hello@weareopen.coop

Acknowledgements

The following people have willingly given up their time to provide invaluable input to this project:

Jonathan Baggaley, Prof Maha Bali, Dr Helen Beetham, Dr Miles Berry, Prof. Oli Buckley, Prof. Geoff Cox​, Dr Rob Farrow, Natalie Foos, Leon Furze, Ben Garside, Dr Daniel Gooch, Dr Brenna Clarke Gray, Dr Angela Gunder, Katie Heard, Prof. Wayne Holmes, Sarah Horrocks, Barry Joseph, Al Kingsley MBE, Dr Joe Lindley, Prof. Sonia Livingstone, Chris Loveday, Prof. Ewa Luger, Cliff Manning, Dr Konstantina Martzoukou, Prof. Julian McDougall, Prof. Gina Neff, Dr Nicola Pallitt, Rik Panganiban, Dr Gianfranco Polizzi, Dr Francine Ryan, Renate Samson, Anne-Marie Scott, Dr Cat Scutt MBE, Dr Sue Sentance, Vicki Shotbolt, Bill Thompson, Christian Turton, Dr Marc Watkins, Audrey Watters, Prof. Simeon Yates, Rebecca Yeager

References

• Digital Promise (2024). AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology. https://doi.org/10.51388/20.500.12265/218
• European Commission (2022) DigComp 2.2, The Digital Competence framework for citizens. Luxembourg: Publications Office of the European Union. https://doi.org/10.2760/115376.
• Good Things Foundation (2024) Developing AI Literacy With People Who Have Low Or No Digital Skills. Available at: https://www.goodthingsfoundation.org/policy-and-research/research-and-evidence/research-2024/ai-literacy
• Jia, X., Wang, Y., Lin, L., & Yang, X. (2025). Developing a Holistic AI Literacy Framework for Children. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1–16). ACM. https://doi.org/10.1145/3727986
• Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2(100041), 100041. https://doi.org/10.1016/j.caeai.2021.100041
• OECD (2022) OECD Framework for Classifying AI Systems. Paris: OECD Publishing. https://www.oecd.org/en/publications/oecd-framework-for-the-classification-of-ai-systems_cb6d9eca-en.html
• Opened Culture (n.d.) Dimensions of AI Literacies. Available at: https://openedculture.org/projects/dimensions-of-ai-literacies
• Open University (2025) A framework for the Learning and Teaching of Critical AI Literacy skills. Available at: https://www.open.ac.uk/blogs/learning-design/wp-content/uploads/2025/01/OU-Critical-AI-Literacy-framework-2025-external-sharing.pdf
• UNESCO (2024a) UNESCO AI competency framework for students. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000391105
• UNESCO (2024b) UNESCO AI Competency Framework for Teachers. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000391104

Core Values for AI Literacy was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

cross-posted on the Amnesty UK blog

Community-driven change is more important than ever. Whether we are advocating for social justice, environmental sustainability, or political reform, collective action is how we create lasting impact. But how do we build a movement that starts with individual curiosity and grows into sustained activism? That’s where the Amnesty International UK (AIUK) community platform project comes in — a digital hub designed to empower individuals, support collaboration, and drive meaningful change.

This blog post outlines how the platform and community strategy work together to guide people from discovery of the AIUK community to becoming activists within it.

1. Discovery

The journey of community-driven change starts with discovery. This is the stage where individuals first come into contact with AIUK. Maybe they learn about an issue, identify it as important, and begin to consider how they might want to get involved. Or maybe they meet someone at a demonstration, and discover the community first-hand.

AIUK social media, through broadcasting, is just one tool that helps people discover Amnesty International UK. AIUK makes complex issues accessible and relatable. We want to do the same as AIUK highlights grassroots efforts and community initiatives.

We want to encourage posts that show:

• Our dedicated community and highlight key grassroots initiatives and campaigns.
• Signposts to find local groups or events based on interests.
• Digital actions, such as petitions or downloading campaign guides, to help users take their first steps.

Such content ensures that even people who are new can find relevant AIUK communities and take the first steps toward engagement.

2. Intention to Engage

Once someone discovers a cause they care about, the next step is forming an intention to engage. This stage is all about commitment — moving from passive interest to active participation.

By showcasing community on the AIUK website, we both invite people in and celebrate what the community is achieving. We want to present clear pathways for involvement and help community members inspire others to take steps towards action.

We need to figure out processes that help:

• Goal-setting: Encouraging community members to set personal milestones, like committing to attend 100 meetings.
• Sharing success: Telling success stories and finding testimonials that effectively attract new people while celebrating community achievements.
• Balancing information: Showcasing static information about past successes with dynamic, real-time updates on current campaigns from the community.

By making it easy for people to express their intent and take small but meaningful steps, we build confidence and lay the groundwork for deeper engagement.

3. Taking Action: Turning Intent into Impact

With intention comes action, and this is where real change begins. At this stage, people start to feel a sense of belonging and are ready to contribute to a cause they care about.

A knowledge base can help equip users with actionable tools. We’ll need clear resources and learning pathways that:

• Guide people to the right information: Whether it’s organising a protest, writing letters to policymakers, or starting a local campaign, the knowledge hub can provide step-by-step guidance tailored to issues we work on.
• Help people collaborate: People should be able to connect with others who share their interests and work together on projects — whether virtually or in person. Best practices and community policies may also be at home in the knowledge hub.
• Show them into the community: Make sure that people feel supported and seen as they take action. Create an architecture of participation that brings them into the community platform.

This stage is about turning isolated actions into collective power, with the support of the community ensuring that every contribution counts.

4. Sustaining Action: Building Lasting Commitment

Sustained action is the key to creating lasting change. Too often, movements fizzle out after an initial burst of energy, but with a strong community strategy and integrated platform, we can keep momentum going.

To sustain engagement, the community platform needs to help people align with others in the AIUK movement. We need to think about:

• Feedback loops: Regular check-ins with the community to understand their needs and ensure that we are adapting the community strategy and platform accordingly.
• A recognition ecosystem: Using digital badges and shoutouts for individuals or groups who demonstrate consistent commitment to help us make activism more visible.
• Storytelling opportunities: Sharing success stories and lessons learned will inspire others and keep motivation high.

By encouraging a sense of belonging and purpose, we ensure that members find reasons to continue building collective power for human rights.

5. Becoming an Activist: Empowering Future Leaders

The final stage is becoming an activist. At this point, individuals understand that community isn’t one person, but rather all of us. They begin to work on behalf of others, coordinate together and lift people up with their leadership.

These leaders will use other coordination tools and processes and that’s great! We want to empower the development of activist and leadership skills. We’ll need:

• Decentralised coordination best practices: For members who are ready to take on larger roles, such as leading groups or campaigns.
• Mentorship programs: Connecting experienced activists with newcomers to share knowledge and build networks.
• Advocacy training: Workshops, webinars, and resources focused on effective communication, policy advocacy, and community organising.

Through these efforts, we can go beyond nurturing individual leaders to continue building a movement.

The Power of Community Work in Driving Change

The journey from discovery to becoming an activist is a process of gradual engagement and empowerment. There is a system of platforms, processes and content that help AIUK move people towards becoming an activist. Although we use various digital tools, the journey is an emotional and social one.

We are working hard to make sure the community platform project harnesses the collective strength of our community and makes a difference that lasts.

Building Power and Making Change was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.

WAO is currently working on a project with the Responsible Innovation Centre for Public Media Futures (RIC), hosted by the BBC. Our focus is on AI Literacy for 14–19 year olds and you can read more context in our project kick-off blog post.

One of the deliverables for this project is to review AI Literacy frameworks, with a view to either making a recommendation, or coming up with a new one. It’s not just a case of choosing one with a pretty diagram!

Frameworks are a way in which an individual or organisation can indicate what is worth paying attention to in a given situation. Just as the definition of ‘AI Literacy’ varies by context, the usefulness of a framework depends on the situation. In this post, we share the judgements we made using criteria we developed and share our process in case it is useful for your own work.

Narrowing down the list

While there can be some commonality and overlaps between frameworks for different contexts, the diversity of possible situations is huge. There can never be a single ‘perfect’ framework suitable for every situation. For example, just imagine what ‘AI Literacy’ might look like for (adult) engineers and developers compared with children of primary school age. As with our work at Mozilla you can define what a ‘map’ of new literacies might look like, but it can only ever be one of many that describe the overall ‘territory’.

With our work on this project, we had to bear in mind our audience (14–19 year olds) and the mission of the BBC. There is a long history of Critical Media Literacy which is particularly relevant to our research here, and which was one of the factors when reviewing frameworks.

With a relatively short project timeline of three months, we needed a way to quickly classify approximately forty frameworks and related documents we have collected. We shared relevant details with Perplexity AI (using the Claude 3.7 Sonnet model) over multiple conversations. This helped us reduce our initial list of around 40 frameworks to a more manageable 25.

Coming up with criteria

Next, we came up with some criteria by which to judge them. These criteria were informed by our own work in the area for 15+ years, along with either interviews or surveys with over 35 experts in the field. While these criteria are meant as a heuristic for this project, they are also a useful starting point for asking questions about any project relating to new literacies.

1. Definition of AI — ensures everyone has the same starting point
2. Development process — adds transparency and credibility
3. Target audience — helps match the framework to its users
4. Real-world relevance — shows how ideas work in practice
5. AI safety and ethics — addresses both risks and responsible use
6. Skills and competencies listed — clarifies what learners should be able to do
7. Reputable source — increases trust in the framework

We included both safety and ethics because both are needed for using AI in a responsible and trustworthy way.

Categorising the most relevant frameworks

We used a traffic light (red/yellow/green) categorisation system to score each framework on the above criteria. Only one of the frameworks we reviewed, the OECD Framework for Classifying AI Systems, meets all criteria with a ‘green’ rating.

There are several other frameworks which we judge as meeting the criteria as ‘green’ except for one criterion (‘yellow’). Listed alphabetically by organisation, these are:

• Artificial Intelligence in Education (Digital Promise)
• AI Literacy in Teaching and Learning: A Durable Framework for Higher Education (EDUCAUSE)
• Digital Competence Framework for Citizens (European Commission)
• Developing AI Literacy With People Who Have Low Or No Digital Skills (Good Things Foundation)
• AI competency framework for students (UNESCO)

There are other frameworks which we have decided to include which included two or more criterion as ‘yellow’. For example, the Open University’s Critical AI Literacy Framework, Ng, et al’s article, and Prof. Maha Bali’s blog post linked from her framework all do a good job of defining Critical AI Literacies. We would also note that the Digital Education Council’s list of skills and competencies relating to AI Literacy is useful to pair with those from EDUCAUSE, UNESCO, and the European Commission.

Next steps

As mentioned earlier, our brief for this project involves either making an informed recommendation of a framework, or to come up with our own. We’re currently leaning toward the latter, but either choice will be the subject of a future blog post.

If you have questions, concerns, comments, or indeed a particularly useful resource which you think would be useful for this project, please do get in touch. You can leave a comment here, or use the contact details on our main website to get in touch!

What makes for a good AI Literacy framework? was originally published in We Are Open Co-op on Medium, where people are continuing the conversation by highlighting and responding to this story.