Ada Lovelace Institute publishes 'Making good', a deliberative study of what UK publics expect from AI as a public good

The report draws on engagement with 47 people in Belfast, Brixton and Southampton to examine how they connect AI with public good. Participants saw economic growth as only one part of the issue, instead stressing fairness, community, meaningful lives and support for those at greatest risk of harm. It finds that local context influences expectations of AI and calls for governance that accommodates differing needs and gives communities more say over deployment. The study presents four expectations: AI should be equitable, attentive to people and communities, oriented to future generations, and used carefully where it is necessary and effective.

The community researchers were fundamental to shaping the research through co-design, participatory practice and the co-analysis that underpinned the findings presented here. The inputs of Anita Kambo, Natoya Whyte, Rae Turpin, Claudia Murg, Paula Quigley and Patrick Toland collectively and individually are recognised as co-authorship.

How to read this report

For local and national policy and decision-makers: This work is intended to complement insights about public attitudes to AI from quantitative surveys, such as the Ada-Turing AI attitudes survey. It demonstrates the rich and actionable information that can be drawn from publics in communities, and gives indications of public views that can enable a technology regulatory landscape that is in step with public expectations. This will contribute to supporting positive policy decision-making and mitigate the risks of pursuing approaches and policies in relation to AI that do not align with public trust. See in particular:

Executive summary

‘Public good and AI’, particularly the section on ‘AI for public good is not “one thing”’

‘What do publics expect to see?’

For public-interest AI developers: This work exposes the public’s current discomfort with some aspects of corporate technology development and behaviours. It also provides insights into the public’s own sense of what public good means for them, and how it could be operationalised into AI systems. See in particular:

For people and communities: This work represents the experiences, hopes, concerns and views of 47 people living in Belfast, Brixton and Southampton in 2024. These people are a range of ages, genders, ethnic backgrounds and awareness and experience in AI technologies. They are all – to some extent – engaged in making sense of their longstanding feelings about public good in relation to emerging AI technologies. Even though these technologies are mostly not in use in their communities, they already have strong senses of what is and isn’t acceptable to them, and supportive of the societies they want to live in – and want their children and future generations to live in – in the future. See in particular:

‘A place-based enquiry: what’s good for (diverse) communities?’

For public participation practitioners: This study is the first of its kind to look at the role of place and community in relation to people’s expectations of AI. It demonstrates the use of a methodology of a deliberative enquiry to explore people’s experiences, hopes, concerns and views. See in particular:

‘Methodology: our approach to the research’

Description of the process of sense making in ‘Sense-making’

Description of the concept of emergence in the chapter ‘Making sense of AI’

‘Portraits of people and places’: Reporting on place in relation to Belfast, Brixton and Southampton

For academics: This study builds on theories of public benefit, commons and good – as well as sense-making and emergence – to inform a study of the role of place and community in relation to people’s expectations of AI. It makes an important methodological contribution, as well as contributing to the evidence base of publics’ views on the relationship between public good and AI, with a specific relationship to place. See in particular:

‘“Public good AI”: in search of a legitimate definition’

This report is – as far as we know – the first study to look at the role of place and community in relation to people’s expectations of AI. It sets out how three communities of diverse publics think about ‘public good’ and its relationship to AI. It is designed to complement existing empirical quantitative and qualitative studies by understanding how people from diverse communities in the UK are currently encountering the realities of the unfolding ‘AI revolution’. It explored what people feel the opportunities of AI could be for them, and where they see tensions in relation to their experiences of existing products and services, and future vulnerabilities to technological harms.

Through this deliberative engagement with people in Belfast, Brixton and Southampton, we have been able to show something of where the views or assumptions embedded into UK policy or AI research and development currently diverge from public expectations and hopes. Seen from a policy or research and development perspective, AI for public good can mean a range of things, from a suite of civic tech tools to justification for a funding package for AI deployment at scale.

The diverse publics in this study recognise the importance of AI to the UK economy. However, for them, economic growth through technological innovation is just one component of what public good means in relation to AI. They are not convinced that public good will be created by any programme that looks at social problems through the lens of AI-driven technical solutions.

For these people, AI for public good is about the bigger picture, and taking a holistic and interconnected approach across policy, to ensure that AI makes life better, fairer and good for everyone. Getting it right requires deliberate actions to support values-based governance across government, public services, civil society and industry.

It will be vital to address any prospect of public backlash or loss of public trust – which is one of the biggest risks the UK government itself identifies in the delicate balance of creating sufficient safeguards for emerging AI technologies, while enabling space for market-driven innovation.[1] Global examples of when developments have been misaligned with public expectations – from the controversy surrounding the use and unequal impacts of the UK Ofqual algorithm,[2] to the discriminatory effects of the Netherlands’ use of an algorithm to detect benefit fraud[3] – attest to the validity of this concern.

Closing this gap between policy ambition and publics’ expectations is important, so that technology can develop in alignment, rather than to an agenda driven by economically pressured policymakers and commercially driven technology companies. Evidence about publics’ views and expectations can help to bridge these differences.

In presenting the perspectives and lived experience of these people, we are able to signpost where and why public confidence in the current directions of AI policy is low and where trust with publics should be better established. We are also amplifying the creative, generative suggestions that publics have for AI-supported futures and conveying their forceful case for consensual and public-centred policy-making around AI in the UK.

The report presents evidence that centres participant voices, through description or verbatim quotes. The first two sections focus on how participants made sense of public good and AI, respectively. ‘Public good and AI‘ out how they saw the relationship between these two ideas, and the ‘What do publics expect to see?‘ sets out what people expect to see from AI policy and development, for it to support public good in the longer term.

The ability to connect with communities and people who are often underrepresented in AI research was made possible through the work of the community researchers – experts in their own local contexts, who provided physical and relational spaces in which the research took place. Some of the verbatim quotes reflect the views and interpretations of community researchers, who we identify with their names and location. Some represent words expressed by participants; their anonymity has been protected, but we recognise their location in most instances, where possible and where relevant.

Throughout the report, we spotlight specific areas of discussion that participants felt were important, such as the use of facial recognition technologies in policing, or AI in social care. These have been selected to show where sentiments around AI and public good were particularly strong, unexpected or contested. They also enable some explanation of why people feel the way they do – highlighting the intersectionalities in lived experience that a place-based approach helps to bring into view.

The report culminates by setting out four headline expectations regarding AI use and deployment, put together by Ada researchers based on the evidence of participant views and developed with participants in a final workshop (March 2025). These provide indications of where publics are open to AI being used for good in their own lives and the wider communities, whose needs they considered with care. And where they feel AI and public good are in tension, and more consideration is needed before AI emerges into people’s lives in the here and now.

Summary of our insights

AI for public good isn’t ‘one thing’ – for publics, it’s not a programme, initiative or a set of technologies

Public good invites a diverse set of interpretations, but there are core ideas and meanings that people from different backgrounds, politics and life experience hold in common: the importance of fairness and equity, social connection and community, and the structural support and provision of services that allow people to live meaningful and purposeful lives.

The diverse publics that engaged with our research believed AI for public good meant a commitment to centre values. When people considered public good, it was an inherently moral and values-based concept. They did not redraw these moral boundaries for public good when considering AI’s potential uses in society. Rather, they thought AI should harmonise and build on public good not conflict with it. Particularly, they wanted AI to benefit everyone and protect the most vulnerable. They believe that, for AI to work for public good requires action and values-based governance across public services, civil society and industry.

Publics expect AI design, deployment and policy to accommodate pluralism and diversity for these technologies to work in the public good – they know that there isn’t a singular ‘AI revolution’ that is going to work for everyone. When thinking about public good, people expected that some groups, communities or individuals may have different needs, views, expectations and vulnerabilities. They wanted these differences and requirements to be taken into account in AI design, deployment and policy, so everyone can benefit from AI and no one is harmed.

‘Place’ matters to how people thought about AI’s opportunities and availability and how they wanted to make decisions. We should expect publics across the UK to reflect devolved, local or regional expectations and political cultures, which will be a critical component of how people both encounter and make decisions about AI. Research exploring people’s attitudes to and expectations of AI should take the effect of place into account – not just geography but also locality and community.

Communities want more autonomy and control in how AI manifests in their lives – we need better or more diverse models of what devolved choice could mean in AI deployment.

Publics expect the relationship between public good and AI to be managed so that it is:

Pro-social and equitable: public and person-centred, and supporting of an individual’s talents and abilities.

Relational and ethical: AI should care for human and community needs.

Future-focused and ambitious: AI should advance humanity’s needs, recognising children and future generations.

Responsibly deployed: used considerately, and only where necessary and effective.

The research reported here was undertaken as part of Public Voices in AI, a satellite project funded by Responsible AI UK and EPSRC. Support for the Ada Lovelace Institute’s work on the deliberative enquiry was provided by BRAID. BRAID is funded by AHRC (Grant number: AH/X007146/1).

Public Voices in AI was a collaboration between: the ESRC Digital Good Network at the University of Sheffield, Elgon Social Research Limited, Ada Lovelace Institute, The Alan Turing Institute, and University College London.

Other publications produced through this programme include a nationally representative public attitudes survey,[4] which provides complementary quantitative insights.

Introduction

Context: The AI revolution

Some say we are living in the time of an ‘AI revolution’. And that it is predominantly a technological revolution that manifests in a proliferation of AI-enabled tools and consumer products. If its effects are as wide-reaching as the term ‘revolution’ suggests, it will affect how we experience everything, from work, to healthcare, to education, to mental-health support, to relationships.

That the AI revolution can bring rapid societal benefits as well as economic growth has become an article of faith for leaders and decision-makers in the UK government, as well as the global tech industry. The UK government recently announced its commitment to ‘shape the AI revolution’ at both a domestic and global level through the AI Opportunities Action Plan.[5] Meanwhile, technology companies cast the AI revolution as the key to humanity’s survival, provided we can circumvent its existential risk, invoking a vision of technologies seamlessly integrated into societies.[6] [7]

Despite attempts to rein in the rhetoric and frame AI as part of a longer technological change,[8] the discourse of the AI revolution remains one of the most powerful ideas driving UK policy and industry research and development today. At its core is a contested set of ideas about the necessity and inevitability of technology-driven innovation, which mobilises a constellation of different advocates and cautioners in policy, regulation, industry and civil society.

These groups have very different ideas about what this revolution entails and how it should be achieved, such as: the (global) role of regulation and governments; the range and spread of societal applications, benefits and dangers; and the degree to which ‘agentic AI’ should be accepted and adopted. But in the current global governance environment, the power of technology companies to decide the course of the AI revolution seems assured.

In response to the discourses of the AI revolution and its unfolding realities, participatory input and public voice matter more than ever. A substantial body of research has evidenced that public input into policy is intrinsic to building public trust and confidence in decisions about AI.[9] Scholars involved in AI and society research have repeatedly advocated for building evidence of diverse public expectations and interests to ensure that the benefits of AI are shared across society and reduce harm.[10] Yet even as this body of scholarship has grown, the emphasis on public input, which caused considerable optimism that the ‘deliberative wave’ would help shape AI development, has taken a back seat in policy language.[11]

So, nearly a decade on from the first articulations of UK AI policy (2016),[12] we still lack a shared vision for AI and the ‘good society’ – an articulation of an agreed set of ‘good’ outcomes to steer AI investment, development, deployment and adoption.[13] The need for this has not disappeared, nor has the imperative to involve people in deciding these directions.

Indeed, if the AI revolution is as powerful and as consequential as the rhetoric surrounding AI delivery suggests, then who defines the agenda for ‘public good’ is one of the most important questions anyone can ask.[14]

Ensuring these concepts reflect and have meaning for diverse publics is a crucial component of securing public legitimacy for innovation.[15] The UK Secretary of State for Science, Innovation and Technology recently told Parliament: ‘Trust is incredibly important in this whole agenda. We have seen too many times in the past where a fearful public have failed to fully grasp the potential for innovation coming out of the scientific community in this country. We are not going to make that mistake. We understand from the outset that to take the public with us we must inspire confidence.’[16] As the UK government iterates its roadmap for AI development, there will be no bigger roadblock to AI’s transformative potential than a failure in public confidence.[17]

This research set out to build some foundations for a truly public agenda for AI, by asking people from three communities to set out in their own words what public good means to them, and spending time with them to learn how AI interfaces with their lives, values, ambitions and hopes for the future. The aim is to understand better what these people think is needed from local and national government, industry and civil society to create AI that reflects and supports their public good.

‘Public good AI’: in search of a legitimate definition

Existing models of public good

The need to balance (potentially competing) power dynamics between corporate, state and public interests in the AI revolution has long been recognised, and there are also longstanding debates in academia, policy and the technology sector about how to do this. There are many competing models, some of which repurpose or reinvent historically and institutionally situated concepts for the AI ecosystem – such as ‘public interest AI’,[18] [19] ‘public benefit AI’,[20] ‘AI4people’[21] or ‘AI for social good’ (AI4SG).[22] These are proposed as being able to balance AI towards positive societal outcomes and might include, for example, operationalising values of equity or fairness, co-designing governance processes or developing collaborative enterprises or social initiatives between tech companies, AI developers and researchers.[23]

Within these, there are different models for governmental power and private investment. Public interest AI is moving into prominence in government and philanthropic initiatives,[24] where it is framed as a potential solution to pressing social problems across various domains. The French government’s announcement that public interest projects around AI would be funded through a €400 million endowment to a public-private-philanthropic partnership (Current AI) is a new and substantial development in how relationships between private technology companies, corporate interests and government converge in public programmes for AI.[25] By contrast, AI4SG speaks more to endeavours that tech companies can enact to build deeper relationships with communities or grassroots initiatives through public or industry funding, which often envisage participatory input from publics in different ways.[26]

These initiatives can struggle to achieve their objectives.

There is considerable evidence that technology companies in the wider ecosystem have not yet managed to square competing incentives or devised a legitimate or consistent approach to incorporating public voice in decision-making.[27]

Despite a substantial oversight apparatus put in place around the French government’s programme, there is a risk that this, too, will fail to address underlying power imbalances and dominant assumptions towards positive technological progress sufficiently.[28] There are well-founded concerns that programmes for social good can in reality detract from societal needs or undermine pro-social aims.[29] [30]

Contested definitions and understandings

There is no clear evidence that public good offers a robust conceptual route to balance these interests or incorporate publics into decision making, especially when invoked rhetorically in the delivery of funded programmes. In discourses around AI, public good has featured increasingly as a basis for policy-making – most recently, for instance, in the announcements surrounding the UK’s AI Opportunities Action Plan,[31] which promises to ‘harness the power of AI for the public good’.[32] The potential for delivery of this promise is undermined by the fact that there is not one agreed conception of either social or public good.[33] It is a contested term that is used in relation to differing social, political and economic ideas about benefit, ownership, access, community, contribution, inclusion, value, state provision, participation, rights and privileges.

This means that public good cannot be understood as a static reality – it is grounded in work of philosophers and political theorists, brought into being by policymakers and publics, and reshaped through democratic deliberation and negotiation. This means that calling an initiative good, beneficial or in the public interest does not make it so.

While some initiatives produce positive outcomes, there is a recognised need to locate the legitimacy of these enterprises not in an abstract idea of ‘good’, but in the views, concerns, hopes and expectations of publics – and in the contexts in which technologies are deployed.[34] [35]

Across academia, social research and the third sector, there is a growing interest in fostering debate and discussion around what public good means for UK society in relation to AI,[36] building on evidence that definitional work with diverse publics can help create more public-centric policies around data and AI. Deliberative work on publics’ understanding of public interest, public benefit, and public good for data has led to procedural changes in various institutional contexts and helped to embed public perspectives in the way that data is actioned and mobilised.[37] [38] [39] Participatory work with publics over ideas of public good has also helped to strengthen institutional stewardship and nurture legitimacy for public statistics.[40]

This work intersects with a wider and substantial effort to comprehend the range and diversity of people’s views about AI, which can support understanding of what publics believe is most beneficial or concerning about AI. Public attitudes research from a range of disciplines surfaces some consistencies in expectations around AI. This includes optimism around the use of AI in advancing science and some aspects of healthcare, concerns around automated decision-making that affects people’s lives, and a strong belief that regulation is needed.[41] In fact, the most recent wave (2025) of the Ada Lovelace Institute and Alan Turing Institute national survey of UK attitudes to AI, referred to in this report as the Ada-Turing AI attitudes (2025) survey, reveals that desire for laws and regulation has increased in the last two years.[42]

Attitudes work alone cannot help to make clear the multiple possibilities that public good and AI may present to publics. There are consistent limitations in the range of evidence available on public attitudes in this respect: an overarching Western-centricism,[43] and lack of inclusivity of minoritised or excluded groups,[44] despite evidence to suggest some applications of AI may have disproportionate negative impacts on people from these groups.[45] [46]

These limitations can sometimes lead to narratives around AI that do not help decision-makers understand what the public think or want: an example is the prevalence of narratives around public ambivalence towards AI, when in reality some publics have strong views about specific applications of AI that are positive, negative, contradictory or multifaceted.[47]

Often approaching lived experience through the lens of measuring ‘awareness’ or ‘adoption’, survey work can buttress an overarching technological determinism, which leaves little space for scoping what publics really want or need.[48]

A place-based enquiry: what’s good for (diverse) communities?

This research has used a place-based approach to exploring public good, because we argue that geography is an important delineating factor in how publics are located in the AI revolution and how much power they will have to decide its course. Geography is an acknowledged determinant of inequalities, such as social health, because different power, economic and political structures coordinate in different ways on the ground.[49]

These coinciding factors of geography and structural inequalities will have an intrinsic effect on how people can benefit (or not) from AI, and whether and how people’s voices are heard in AI research and policy. A place-based framing is therefore an important consideration for widening participation and access, and informing AI research with evidence of the needs and expectations from diverse people across the UK.

The UK experiences extensive geographical inequalities, which manifest as place-based differences in income, productivity, opportunities and health outcomes.[50] These disparities interact with digital systems and infrastructure in places across the UK, which Ada’s previous work on access to digital health has shown.[51]

Publics perceive and experience geography as a fundamental constituent of inequalities.[52] For example, the geographic differences in outlooks and the strength of localised grievances regarding immigration were clearly visible in the riots that erupted after the 2024 Southport murders, just a few weeks before fieldwork commenced.[53] We can expect, in this context of historic geographic inequalities, that people who live in different locations and situations in the UK may hold different ideas about what AI opportunities mean for them.

A place-based framing therefore invites us to explore how far geographic disparities may shape how people in different communities access – or expect to be able to access – AI’s opportunities, or whether they are – or see themselves as – excluded from its benefits. It may also help to pose a bigger set of questions about, for example, the role of local and regional identity, collective memory or place-based political cultures in both understanding and negotiating AI’s deployment.

Despite the focus on place in UK policy, evident in programmes such as ‘Get Britain Working’[54] and ‘Levelling Up’,[55] consideration of local capabilities and need are not yet forefronted in AI policy. However, the UK government’s focus on economic growth and innovation, which is driving much of AI policy, is also reflected in devolution plans, such as the regionalisation of planning powers and the emphasis on redistribution of power.[56] Place is going to be increasingly important in both how people engage with AI, but also how they negotiate issues that arise from AI deployment.

Devolving more power for – for example – the delivery of public services to local or regional authorities will give them greater influence over how AI intersects with people’s lives. But this will require negotiation: people in the UK may trust local governments slightly more than national government,[57] but experience of services, levels of civic engagement and awareness are unevenly distributed across the country.[58] [59] In the context of the current funding crisis, local bodies may not have capacity to build routes for co-production around AI, or to strengthen already strained civic relationships.[60] In fact, relocating planning powers to local authorities may make it harder for some local communities to contest the construction of AI infrastructure, such as data centres, in their neighbourhoods, as mayors will have increased powers to override local planning decisions.[61]

Recognising the unique ways in which structural, systemic and economic factors combine in different geographies is key to building ethical approaches to finding solutions and mitigations for place-based inequalities.[62] In relation to AI particularly, place-based community models of governance and participatory engagement (sometimes grouped under the umbrella of ‘AI localism’) are seen as an innovative, flourishing and important contribution to the overall ecosystem.[63] This research argues that place is therefore a critical factor in how diverse UK publics will be able to engage with AI, and that examining and building evidence around place will help us unlock pathways towards good AI uses and policies.

Methodology: our approach to the research

Public good and AI

In its ambition to surface more relational or expansive perspectives on AI, this new deliberative enquiry speaks to various existing research programmes and initiatives. It is allied to work that has been underway to test what ‘possibilities, principles, processes and practices’ might help realise ‘what makes a good digital society?’.[64] And it contributes to wider and more recent deliberative efforts, which are currently creating interfaces for communication between publics and decision-makers, such as the Royal Academy of Engineering’s People’s Stewardship Summit[65] or the Children’s AI Summit.[66]

Complementing these studies, and responding to the ambiguity in the current AI policy discourse around the term ‘public good’, our investigation began with a simple question:

‘What does public good mean to diverse publics when it comes to AI?’

By engaging publics themselves to respond to this question, we respond also to work within the AI for social good (AI4SG) field that has emphasised that directions for ‘good’ must be led by communities, who should decide ‘whether and how they would like to use AI’ as a basis for evolving an ‘AI for social good’ framework.[67]

Our investigation, however, has tried to give publics substantial opportunities to centre their own ideas of a good society and make it easier to contest or reject the use of AI in relation to those tenets. Through de-centring the technology, and re-centring people, we aimed to build empirical evidence to understand people’s priorities through a capabilities-based approach, which recognises community strengths to rebalance the power asymmetries that are embedded into AI policy and infrastructure.[68]

Place-based case studies

This research aimed to build some foundations for the consideration of ‘place’ during a time of wider systemic changes in governance, AI delivery and economic policy. It does this through adapting a place-based case study methodology, which is well suited to understanding how interweaving and complex social challenges materialise in people’s daily lives.[69] By engaging diverse publics in Belfast, Brixton and Southampton, we hoped to trace the possible conceptual range, and potential points of divergence, in people’s understanding of public good. This formed a basis for deeper understanding of the interlocking nature of place and inequalities, and how these may be represented in perspectives on AI.

A place-based case studies approach gave us the methodological richness and opportunity to do this, by allowing us to bring techniques together to cast a ‘360 view’ on how people understood the interactions between AI and their lives. This primarily consisted of assembling deliberative and community-led research methods. AI is acknowledged as a complex and ‘wicked’ problem, which is embedded in, and related, to wider societal and structural challenges.[70] Adaptations of deliberative communications theory emphasise the importance of both translating these issues into familiar social and cultural milieu, and spending time to understand how people develop these views ‘behind the scenes’ of one-off deliberative workshops or events.[71]

We chose three communities (case studies) as locales for this research and engaged pairs of community researchers in each site to collaborate with us in codesigning a loose deliberative process. This aimed to deepen understanding of how the interlocking nature of place and inequalities in these areas may convene perspectives on AI. Belfast, Brixton and Southampton – while not recognised as the most deprived areas in the UK, either in the Index of Multiple Deprivation (2019)[72] or in media discourse,[73] – are each locating points for various structural inequalities, and provide gateways into diverse communities and lived experiences of exclusion.

Each area has faced common challenges in recent years: extreme poverty and low social mobility from long-term, structural and historic economic exclusion,[74] worsened by ‘austerity’ (under the UK’s coalition government 2010–15), and more recently the cost-of-living crisis that followed Brexit and Russia’s invasion of Ukraine.[75] These areas suffer from high pollution from port industry or heavy traffic, which has disproportionately affected minoritised and low-income households.[76] They have all witnessed heightened tension from social dislocation and alienation, which have manifested differently in each place, whether in knife crime or paramilitary violence.

In each of these communities, social cohesion and community relationships have been severely tested in recent years. Immigration has proved a flash point for racism and far-right action in Belfast[77] and Southampton;[78] in Brixton, the community action mobilised in the summer of 2024 demonstrates that residents know all too well the experience of riots and violence on the streets, as well as the injustices that lie at their roots.[79]

We worked closely with community researchers to design a process where we became more familiar with participants’ lives, their outlooks, and priorities for public good, and how they thought AI might relate to these ambitions. We know from related work on the sociologies of data and data practices that people’s knowledge of esoteric concepts such as ‘data’ is created through mundane and everyday engagements and interactions.[80] [81] [82] When people mobilise their views about data and data practices, they constitute this knowledge through feelings, imaginings and speculative fictions (‘what ifs’).[83] [84] We therefore balanced a series of structured, arts-based engagement events with more ethnographic approaches that could capture the subjective and contextual nature of meaning-making (interviews, note taking, observations and participant-led inputs).

People and places: who was included in the research

Within each of these ‘place-based’ approaches, there were multiple communities that could be invited into the research. We asked the community researchers to draw together a diverse and inclusive group of people in each place, which reflected important demographic realities, underserved groups and perspectives in the local area. We agreed on six criteria, where participants could self-identify in relation to different forms of exclusion, as part of an application process across all sites – to ensure an inclusive and diverse approach – asking people to self-select from one or more categories: poverty, disability, ethnic identity, citizenship, gender or sexual identity, or (more broadly) being ‘part of a community not listened to by people in power’.

Through operating a community-led recruitment, we gathered diverse cohorts that spoke to experiences usually omitted from AI research. We had a very wide range of minority ethnic representation, for instance, because of the community basis of the approach. The energy and commitment of the community researchers to the equitable principles of our recruitment also ensured inclusivity across other core excluded groups. Some 26% of people self-identified as having a disability, for instance. We also saw small but significant (15%) LGTBQIA+ representation in the workshops. The strength of connections between Belfast community researchers and their local voluntary sector meant that we achieved significant representation of people who have been excluded based on citizenship (19%).

We could not resolve all participatory inequalities through a community-led approach. We did not seek to be representative or to use methods like sortition to ensure a range of characteristics. We struggled to recruit men from lower socio-economic backgrounds, which led to more female-dominant groups in Belfast and Brixton. There were particular concentrations and absences of perspectives: Belfast’s group, on the one hand, congregated people with experiences of migration that other sites did not represent as strongly, but it was also the only site with no declared LGTBQIA+ representation. The ages of participants were concentrated mainly in the 25–54 age groups, although each site had some representation of people under 25 and some had representation above the age of 55.

We aimed to gather groups of people that were reflective of some of the core social and cultural dynamics of these local societies. The people we congregated reflected diverse sections of their community and were each differently placed within the local nexus of structural forces. They each came with their own senses of place – which were global as well as hyperlocal – as well as differing relationships with the community they lived in and what that meant to them.[85] But during the project, through meeting each other and engaging with each other’s views, these multiple and diverse viewpoints coalesced in a sense of themselves as a ‘temporary community’, which was profoundly but uniquely connected to both people and place.[86]

In Brixton, many participants came from the borough’s longstanding Black communities and its Windrush generations; but there were others who spoke to the borough’s multiculturalism, bringing related meanings of Blackness (Black American), or experiences of ethnic minoritisation (Muslim, Eastern European). Some were long term residents, but there were more recent arrivals, too, testifying to Brixton’s high social flux. Two participants came with experience of homelessness; it has been increasingly difficult for long-term locals to afford to stay in the borough, as gentrification hikes rents and the cost of living. And there are a good number of people who advocate for others who are vulnerable in this climate.

In Belfast, most participants learned about the project through the networks of the city’s voluntary sector, a sector facing increasing pressures through rising costs and needs since the COVID-19 pandemic.[87] Some of our participants worked, or had worked until recently, in this sector, supporting children’s mental health or homeless people. Others volunteered for local advocacy groups, campaigning for fairer rent or better support for neurodiversity. Nearly half of participants had connections with charities supporting refugees and migrants to settle in Northern Ireland. Immigration has become an increasingly prominent, but contested, reality of Belfast’s society in recent years. In this, the group distilled unique place-based realities for Northern Ireland.[88]

Southampton, too, has a variegated voluntary and community life and participants came from across the ‘many villages’ of the city’s activist, creative, voluntary and advocacy lives, as well as different parts of its economy. Some were artists, musicians and creatives, sometimes choosing to live their life outside social norms – and balanced their passion for creativity or community life with various strands of precarious income. Others worked in public services or in drug and alcohol rehabilitation or studied at the city’s universities. Two members were ex-military and had learned about the project through the city’s veterans’ networks.[89]

Helping others, and the critical importance of community, were things that participants all held in common, irrespective of place, even if they realised this in different ways. There were other intersecting points in lived experience across our sites, such as the experience of poverty (33% declared they shared this) and the realities of balancing various strands of precarious income. Some people were in full-time work; others had recently lost work, or – with the burdens of caring or managing disabilities – had been unable to meet full-time job commitments for some time. Two participants could not work at all due to the status of their migration settlement application.

Sense-making

We have described this methodology as an ‘enquiry’ because that term references the longer timeframe of the research process and the different routes for dialogue-based communication, listening and feedback we established. Through these, we could see the various processes of signifying and crystallising that we saw participants engage in around the related concepts of public good and AI. We use the concept of ‘sense-making’ to describe these, because it recognises that meaning-making takes place over time, in social contexts, and that individuals draw on various resources (cultural, social and personal) to make sense of unfolding and dynamic contexts, and decide ‘what’s the story’ and how to respond to it.[90]

Qualitative research provides various tools to understand how people make sense in social settings, and how and why they engage cultural templates and shared understandings, in order to enter into negotiation about the significance of a topic.[91] Exploring perceptions and outlooks to this depth, we argue, is crucial for understanding how diverse publics feel about AI tools, systems and infrastructure, and this may shape how views are expressed in, for instance, the attitudinal surveys that are more commonly used to measure public sentiment.

Our enquiry method used various means to create a rounded view of how participants made sense of public good and AI. This meaning-making was not uniformly dispersed or one-directional: people drew from our learning programme differently, depending on their levels of familiarity with AI, their wider needs, differing expectations and lived experience. Some (not all) told us they benefited from each other’s technical, practical or social knowledge and used this to crystallise their thoughts. They drew in resources from outside the workshops to catalyse this process: social intelligence from their family or friends, their social media networks and trusted media.

We have not captured the totality of their sense-making; we see this research as a foundation for further negotiation on the part of publics, researchers and policy-makers, where other views and perspectives will come into view. Sense-making is an ongoing process. As one participant commented when reflecting on her learning about AI, human intelligence is organic – ‘we are also our emotions, our hormones, our senses, we see, we hear, we touch, we feel’ and a ‘lot of input is changing daily and constantly’. Our programme came to an end in December 2024, but participants are still engaged with this process of making meaning in what is an ever-evolving and shifting environment.

For the purposes of this study, understanding people’s sense-making has allowed us to point to what might underpin people’s attitudes towards AI. It also enables us to identify the importance of their relational dynamics with AI, building on an array of sociological research that emphasises the formative role of the ‘everyday’ in shaping people’s views.[92] Through observing participants’ responses during the research, we have been able to identify and investigate, in the section ‘Making sense of AI’, how the wider context of ‘emergence’[93] – a state of feeling on the verge of radical change – is formative in shaping the views of diverse people in the UK and creating a climate of uncertainty, around which a lack of confidence, insecurity and distrust are increasingly likely to coalesce.

Context of the enquiry

All research occurs alongside political and social climates that shape conversations and findings, as well as participants’ emotional engagement with the subject of the research. Because some of the participant comments and discussions represented in this research refer to contemporary events, we offer this timeline of major events around which workshops took place.

The recruitment of community researchers began in mid-September 2024, some six weeks after the Southport murders, and the riots and protests that took place in its aftermath.[94] Questions and concerns about social cohesion featured prominently in our interviews with applicants during interviews, and was referenced by a few participants during the workshop process.

The fieldwork phase, including participant recruitment, onboarding and the start of the workshops, coincided with important geopolitical developments. The re-election of President Donald Trump on 6 November 2024, and the growing presence and intervention of US technology entrepreneur Elon Musk in UK public discourse had a significant impact on domains at various points in the process.[95] Similarly, conversations responded to some of the events in the continuing war in Gaza and its deepening humanitarian crisis.

The workshops also operated under particular political weathers. Belfast’s first workshop, for instance, took place the day after polls opened for the Irish election. As the votes were counted, a process that would take three days, participants checked their phones for the latest news and analysis, waiting to see if a female Sinn Fein leader would win out on both sides of the border.

It is worth noting, too, that participants’ sense-making occurred during a particular moment in the AI ecosystem. Many referenced live news stories about OpenAI’s o1 model and its potential for strategic deception,[96] as well as other references to new tools and technologies, which positioned how they made sense of AI, and related to the context of ‘emergence’. The climates of ambiguity and uncertainty reflect feelings before January 2025, when the announcement of the large language model DeepSeek, developed in China, sent shocks across the global markets. In the findings workshop (March 2025) some people referenced continuingly shifting technological and politico-technical realities, such as President Trump’s AI showreel of Gaza.

The following case studies will enable readers to spend time getting to know the three places that locate participants and the ‘temporary communities’ they formed during the research period. Understanding how these communities view their own places provides an important background to their motivations and the dynamics they created together during this project. This context allows us to better understand the views and outlooks they held in relation to public good and AI technologies. As well as describing the overarching demographic and cultural constituencies of these workshop groups, we also offer short community portraits of people and places, created with the community researchers, which present these temporary communities in the ways we encountered them.

Portraits of people and places

The evidence we generated about ‘public good’ is grounded in the life stories and perspectives of the people that took part in our workshops, as well as the dynamics they created when they interacted and worked together. We have worked with our community researchers to translate these, so the evidence can be understood in reference to these perspectives and relationships. These portraits of people and places are written using community researcher voices and input; they help to contextualise and humanise the views that are presented in the chapters ahead, while acknowledging that they are specific to what took place during this project.

‘Growing a home’ – Belfast

‘It’s this – the ability to grow a home – that’s good – and that’s what I’m doing here, I’m growing a home.’ – Belfast participant

‘It’s this – the ability to grow a home – that’s good – and that’s what I’m doing here, I’m growing a home.’

– Belfast participant

This sentiment – the common need to ‘grow a home’ – summarises the dynamics created in our workshops. The quote above comes from one of our participants, who was sharing what ‘good’ means to her, reflecting on her move to Belfast from Sudan, and beginning again in a new place. She restarted a career in the NHS, and she feels fortunate, although she doesn’t know yet whether her mother can join her in Belfast. Her story is personal to her, but the narrative of resettlement after conflict had many resonances for others in our workshop.

Nearly half of the people in our workshop had personal experience relevant to her story. A few participants resettled in Belfast some years ago – 23 years in one instance. Some were more recent arrivals. Two young men, from Sierra Leone, and South Africa, were still waiting for their settlement applications to go through. They are highly qualified, eager to learn English. One was encouraged by his Mum to take part: he’d get to know more about his new country and build his confidence. Another young man took part because it’s an interesting topic, and he wanted to develop his English language skills. This opportunity felt good for them: it takes a long time for the settlement application process to go through, and it is hard for them to find enriching experiences when they can’t work or take on education.

The experiences in this group speak to the recent history of immigration in Northern Ireland, which has seen a huge rise in asylum and settlement applications since 2022.[97] With increased population has come pressure on services, concerns about division, and a growing voluntary apparatus to manage integration. The reconciliation initiative in Ballycastle, Corrymeela[98], founded to build bridges between divided communities during the Troubles, has been repurposed to help people integrate in this predominantly white society. The voluntary sector has expanded to manage these changes, with a range of small enterprises and networks.[99] This is how many of these participants heard about this project in the first place. One of the participants, who was once an immigrant herself, works for one of these initiatives, helping others to manage integration.

The ‘local-born’ participants also know what it’s like to resettle after conflict. Many of them think of themselves as ‘Post-Troubles’ (they rejected sectarian identifications during the application process), but the legacies of the past remain tangible: gaps in education and pan-generational poverty from years of systemic discrimination and slow economic growth.[100] People don’t talk about it too much, but our community researchers talked about the generational traumas underneath the surfaces of conversation, which rise up here and there: references to growing up in what people describe as ‘brutal’ areas and familial experience of police abuse; the humour used to assess and dissipate threats, a habit ingrained from living with violence.

For both ‘newcomers’ and ‘locals’, we noticed that being together in this room affirmed something important about themselves and how they want to live: they are all ‘growing’ a vision of Northern Ireland that welcomes and feels welcoming; that knows, based on its past, both the consequences of division and how to repair it. The commitment to service to community others was palpable in the room, as people demonstrated care and respect for each other in their interactions. When they shared their life stories, we reflected on how so many help others in one way or another, through trade union work or in the voluntary sector, helping children or homeless people. Two participants advocate for neurodivergent communities, having experienced ADHD and exclusion themselves. This project is a really important initiative for them: AI has been a leveller and they believe it can be so for others.

They all came with hope for Northern Ireland, but they recognise it needs work. The distinctions between ‘newcomers’ and ‘locals’ hung over them, sometimes interrupting the flow of group conversations, as communications break down, or the banter of ‘locals’ dominates. Our community researchers referred to the ‘crouch position of distrust’, which people in Northern Ireland have learned from years living with threat, and which surfaced in conversation. Occasionally, misunderstandings arose due to the complexities and intersections of identities in the room. A young Muslim woman (a second generation immigrant) at one point had to correct assumptions: she’s British; she moved to Belfast from England last year. Others felt misunderstood, too: a white man in his forties talked about his feminism and raising four daughters.

Together, these diverse people worked up a new vision of, and future for, Northern Ireland that is progressive and positive, welcoming and forward thinking; their conversations were their commitment to grow a home they all can live in.

A city of villages – Southampton

Claudia, a community researcher, joked with us about community life in Southampton: ‘It’s a bit like TK Maxx: the jumble can feel overwhelming, but when you dig through it, you find all sorts of treasures and revelations in there that are truly valuable.’

She was describing how community life can feel hidden and dispersed across the city – what her colleague Rae Turpin acknowledged as a ‘city of villages’. The city has evolved over time, pockets of communal action and identity grown from the historical layers of modern and contemporary residential and urban developments, intermingled with sprawl of commercial hubs, ports, green spaces, waterways and nature reserves. Low-income communities inhabit the fringes of ports and industrial sites, suffering the worst effects from pollution. Multigenerational residents live side-by-side with newcomers or transient residents – people who come to work in the city’s big industries, or to study at the university.

The people who joined this project in Southampton came from across these different social, cultural and professional milieus, each bringing unique perspectives on the city and what it means to live here. Some were more ‘typical’ of the broader community – they were students, long-term residents, people working in key local industries. Many were also from groups whose voices and experiences are less heard in mainstream narratives about Southampton, and indeed in public discourse more broadly: creatives and musicians – people who sometimes live day-to-day and often balance precarious work with other commitments; community organisers, and people who have decided to live outside of society’s capitalist norms.

As a group, serving others is something they held in common, whether through health work or caring for people battling addictions, working to eradicate modern slavery, or carrying with them their previous service in the armed forces. Some of them have campaigned to make lives better, holding the city council to account over its pollution targets; others make steady and everyday improvements to communal spaces, through volunteering in community gardens or nature initiatives.

From their conversations, it was clear they had the capacity to hold different ideas about Southampton and what living here means. Life here can feel fragmented, with pockets of grassroots ‘DIY culture’ across the city, but they all often contest the commercialised heritage or touristic discourse that explains Southampton only in reference to its port industry and its docks. The city, they argued, is progressive, energetic, creative and intellectual – it’s not just ‘the place where the Titanic left’ or a gateway to elsewhere.

These differences in narrative between official discourse and community outlooks reflect longstanding tensions: between affluence and innovation, which sit in places like the ports, universities and the hospital, and the significant challenges faced by many communities across Southampton, which many participants had experienced first-hand. They reflect the group’s experience of disconnection between the needs of communities, as they know them, and the commercial imperatives of the private/public partnerships at the docks that increasingly shape the city’s future.

A commitment to social cohesion, as well as shared feelings of fragility, gave this group a common reference point for community. Early in the exercises, the idea of ‘street parties’ emerged in discussions, returning repeatedly as an expression or an intersecting point where these people’s values of community, connection and creativity came together, across different backgrounds and perspectives.

The focus on street parties epitomises some of the dynamics that made this group distinct: it captures their commitment to place-based belonging, shared joy and communal effort in a context where social life is highly fragmented and lacks capital investment. It represents a reclaiming of public space and recentring of human connection in response to isolation, which some participants expressed concerns about. It also reflects a deep longing for informality, joy and spontaneity in civic life. Street parties were an ideal, but also a bitter paradox – speaking to the value of grassroots life, as well as its fragility and transience; expressing a longing for reciprocity and resource sharing, where it often did not exist.

‘I could see people of all colours and backgrounds. I could see people from the local Black community, the LGBT community – some foreigners, people struggling to speak English. There were the plain ordinary moms like myself. I just thought that was a really good representation [of Brixton].’

– Brixton participant

Brixton brings multiple communities together, and the people who took part in this project came from a range of its diverse populations. They had different backgrounds – Caribbean, African, South Asian, European, Portuguese – demographics that feel typical of the area’s diversity. Some were first- and second-generation immigrants and remained deeply connected to their cultural and social roots, especially Brixton’s Windrush generations. The LGTBQIA+ community, which has a proud place in the area’s history and its culture,[101] was also represented.

Communal life here thrives on connections. People from different backgrounds come together – it’s a dynamic blend of cultures, music, food and art, festivals, carnivals. There’s a deep sense of pride in local heritage across Lambeth and south-east London, especially in areas like Brixton, Peckham and Streatham, known for their Afro-Caribbean, African and South Asian influences. Grassroots organisations and local initiatives play a big role in addressing social issues, fostering inclusivity and celebrating diversity. The spirit of collaboration is strong, whether it’s through youth programmes, cultural festivals, or activist or support networks like those for dementia awareness, over-fifties groups, or breastfeeding groups that support mothers facing the isolation of parenting. Two participants were advocates of a local initiative for the social inclusion of girls and women.

Many of our participants shared a commitment to the community through their involvement in local causes, housing rights, and social justice or taking part in advocacy and community support networks. Many were vocal about the challenges they face, including systemic inequalities, and access to mental health support. During our conversations about public good, we heard echoes of some of their past and more recent challenges: references to the Brixton riots in the 1980s and 2011, the Windrush scandal and the effects of hostile environment policies on local people, the overpolicing of Black people in the community, and the disproportionate impacts of COVID-19.

Many of them sensed that the area is changing. Gentrification, alongside the interventions of property developers and estate agents (‘criminals in suits’) is altering the social dynamics that many recognise as particular to Brixton. Long-term residents can no longer afford to live here, as rent and property prices rise, and alter the local economies of the high street and the market. People enjoy the greater amenities and opportunities, but they’re worried about the unique characters of their neighbourhoods and whether this change benefits people like them. Food prices are rising and schools are closing because families can’t afford to stay in the area.