FRAIM: Framing Responsible AI Implementation and Management
Lead Research Organisation:
University of Sheffield
Department Name: Information School
Abstract
Context
Increasing applications of AI technologies have necessitated rapid evolution in organisational policy and practice. However, these rapid changes have often been isolated in individual organisations and sectors, with a lack of shared cross-sectoral learning and accompanying shared values for responsible and ethical AI (RAI). Meanwhile, RAI resources have proliferated, but few effectively address the challenges in implementing shared principles, further hindering best practice development. As policymakers and industry worldwide grapple to guide, regulate, and design RAI, there is a clear need for establishing shared values and knowledge of the factors involved in implementing and managing RAI in practice.
Challenge
The Framing Responsible AI Implementation and Management (FRAIM) project will bring together cross-sector perspectives on organisational RAI policy and process to scope key stakeholders, shared values, and actionable research needs for building the evidence base on implementing and managing RAI. We have partnered with organisations representing example key areas in which AI use will significantly impact people's lives, including local policy, information access, and cultural enrichment. Our scoping work with these partners will provide a strong foundation for future development of practices and interventions to enable an ecosystem approach to RAI, and creatively and critically examine organisational implementation and management of RAI.
Aims and Objectives
The project will focus on organisational policies and processes around using AI technologies, including pre-trained foundation models as well as context-specific machine learning, to help organise information and support decision-making. With this focus and the specific expertise of our partners, the project will address two key aims:
Aim 1: Map the network of key stakeholders and values in organisational policy and process towards RAI implementation and management.
Aim 2: Scope actionable needs for building a stronger evidence base around RAI implementation and management across sectors.
We will achieve these aims by working with our partners to complete three objectives:
Objective 1: To query and collate the values, questions, and implementation and management challenges being described in the current RAI discourse by performing a meta-analysis of RAI resources and literature.
Objective 2: To identify key stakeholders, practices, and values involved in implementing and managing RAI at organisational levels by conducting exploratory interviews with staff from partner organisations.
Objective 3: To scope specific plans for expanding the RAI evidence base to inform RAI implementation, management, and policy via a scoping workshop held in collaboration with project partners.
Potential applications & benefits
The scoping work in this project will establish clear directions and next steps for ecosystem-focused research and shared values to guide RAI policy and process within organisations. By drawing on multi-stakeholder perspectives and creatively engaging with the complex questions of RAI in practice, the project will benefit:
Partner organisations, through shared insights from other organisations' approaches to RAI policy and process.
The RAI research community, through empirically-grounded mapping of values, policies, and processes for RAI use across organisational contexts.
The public, through insights into AI implementation and management and creative reflection on RAI policy and process in the world around them.
Increasing applications of AI technologies have necessitated rapid evolution in organisational policy and practice. However, these rapid changes have often been isolated in individual organisations and sectors, with a lack of shared cross-sectoral learning and accompanying shared values for responsible and ethical AI (RAI). Meanwhile, RAI resources have proliferated, but few effectively address the challenges in implementing shared principles, further hindering best practice development. As policymakers and industry worldwide grapple to guide, regulate, and design RAI, there is a clear need for establishing shared values and knowledge of the factors involved in implementing and managing RAI in practice.
Challenge
The Framing Responsible AI Implementation and Management (FRAIM) project will bring together cross-sector perspectives on organisational RAI policy and process to scope key stakeholders, shared values, and actionable research needs for building the evidence base on implementing and managing RAI. We have partnered with organisations representing example key areas in which AI use will significantly impact people's lives, including local policy, information access, and cultural enrichment. Our scoping work with these partners will provide a strong foundation for future development of practices and interventions to enable an ecosystem approach to RAI, and creatively and critically examine organisational implementation and management of RAI.
Aims and Objectives
The project will focus on organisational policies and processes around using AI technologies, including pre-trained foundation models as well as context-specific machine learning, to help organise information and support decision-making. With this focus and the specific expertise of our partners, the project will address two key aims:
Aim 1: Map the network of key stakeholders and values in organisational policy and process towards RAI implementation and management.
Aim 2: Scope actionable needs for building a stronger evidence base around RAI implementation and management across sectors.
We will achieve these aims by working with our partners to complete three objectives:
Objective 1: To query and collate the values, questions, and implementation and management challenges being described in the current RAI discourse by performing a meta-analysis of RAI resources and literature.
Objective 2: To identify key stakeholders, practices, and values involved in implementing and managing RAI at organisational levels by conducting exploratory interviews with staff from partner organisations.
Objective 3: To scope specific plans for expanding the RAI evidence base to inform RAI implementation, management, and policy via a scoping workshop held in collaboration with project partners.
Potential applications & benefits
The scoping work in this project will establish clear directions and next steps for ecosystem-focused research and shared values to guide RAI policy and process within organisations. By drawing on multi-stakeholder perspectives and creatively engaging with the complex questions of RAI in practice, the project will benefit:
Partner organisations, through shared insights from other organisations' approaches to RAI policy and process.
The RAI research community, through empirically-grounded mapping of values, policies, and processes for RAI use across organisational contexts.
The public, through insights into AI implementation and management and creative reflection on RAI policy and process in the world around them.
Publications
Newman-Griffis D
(2025)
AI Thinking: a framework for rethinking artificial intelligence in practice
in Royal Society Open Science
| Title | Constant Washing Machine |
| Description | Constant Washing Machine was created by Blast Theory (https://www.blasttheory.co.uk/), and includes two elements: 1) sets of eight custom bars of soap, each engraved with a word or phrase related to responsible AI selected by one of the FRAIM researchers; 2) photo series of portraits of the FRAIM researchers with the bars of soap corresponding to their responsible AI word or phrase. |
| Type Of Art | Artwork |
| Year Produced | 2024 |
| Impact | Constant Washing Machine was launched at a live event in Brighton on 10 December 2024, with approximately 30 live attendees and 50 online attendees. It has featured in two media mentions as of January 2025. |
| URL | https://www.blasttheory.co.uk/projects/constant-washing-machine/ |
| Title | Constant Washing Machine launch event |
| Description | This was a live exhibition of the Constant Washing Machine artwork by Blast Theory (reported separately), held at Blast Theory's studios in Brighton on 10 December 2024. The exhibition included: 1) display of the Constant Washing Machine soaps and photo series; 2) panel discussion with two members of the FRAIM research team, lead Blast Theory artist on the project, and curatorial lead from the Open Data Institute; 3) live handwashing performance using the Constant Washing Machine soaps by panellists; 4) live participatory handwashing by attendees. The exhibition was livestreamed and recorded. |
| Type Of Art | Artistic/Creative Exhibition |
| Year Produced | 2024 |
| Impact | The live event was attended by approximately 30 people in person and 50 people online. |
| URL | https://culture.theodi.org/constant-washing-machine-blast-theory/ |
| Description | FRAIM research has shown that: 1) The nature of responsible AI is contingent, context-based, and multiple. Policies and perceptions of responsible AI vary widely in what concepts form part of 'responsible AI' (eg, transparency, fairness, sustainability), and what stakeholder groups are perceived as acting to make responsible AI occur. The motivators that drive responsible AI, barriers to realising it, and the practices that make it happen come from shared concerns, but are often specific to individual organisations. As a result, 'responsible AI' is not one thing nor is it owned by one stakeholder group: it is a distributed and evolving practice rooted in individual contexts. 2) The implementation of responsible AI is therefore local, practice-based, and problem-oriented. What makes AI use responsible, who is exposed to AI risk and AI benefits, are determined in specific, local contexts. Responding to these risks and benefits, and putting general principles of responsible and ethical AI into day-to-day application, requires a focus on everyday practices and decisions. Focusing on AI as a response to specific problems, rather than a solution in search of a problem, enables organisations to respond productively to the needs of their specific contexts and implement practices that will work for them. 3) Achieving responsible AI requires that organisations bridge structural divides and work across competencies. Many different components of organisations motivate, implement, and are affected by AI use, and these must all work in active collaboration to shape it to the organisation's and society's benefit. As well as working across vertical hierarchies and horizontal divisions, this also requires bringing together people with different skill sets (data, operations, strategy, IT, etc) and creating the conditions for them to work together effectively. FRAIM, in collaboration with the arts collective Blast Theory, has also produced Constant Washing Machine (https://www.blasttheory.co.uk/projects/constant-washing-machine/), an artistic reflection on responsible AI that deepens these reflections and supports the public and diverse stakeholders to engage with the discussions and findings in the project. Constant Washing Machine is a new interactive artwork exploring the everyday, changing nature of responsible AI and the unseen, everyday practices that shape it through the metaphor of hand soap. Constant Washing Machine has been showcased at multiple events to date and is part of the ongoing legacy of the research. |
| Exploitation Route | FRAIM findings are already being taken forward and put to use by the project partner organisations across multiple sectors (Sheffield City Council- local government; the British Library- libraries, cultural and heritage; Eviden- digital transformation and consultancy; and the Open Data Institute- data policy). FRAIM research has informed the development of responsible AI policies within these organisations, and can be taken forward by these and other organisations in their respective sectors in shaping new AI policies and their implementation within organisations. We are working with these organisations to produce sector-facing summaries of the FRAIM research and recommendations for putting responsible AI into practice in their contexts. |
| Sectors | Digital/Communication/Information Technologies (including Software) Government Democracy and Justice Culture Heritage Museums and Collections |
| URL | https://sites.google.com/sheffield.ac.uk/fraim/project-outputs |
| Description | BRAID researchers' response to UK Government copyright and AI consultation |
| Geographic Reach | National |
| Policy Influence Type | Contribution to a national consultation/review |
| URL | https://doi.org/10.5281/zenodo.14945986 |
| Description | Influence on British Library AI Strategy & Ethical Guide |
| Geographic Reach | National |
| Policy Influence Type | Contribution to new or improved professional practice |
| URL | https://blogs.bl.uk/digital-scholarship/2024/12/ai-and-machine-learning-etc-with-british-library-col... |
| Description | Written evidence on the Use of AI in Government |
| Geographic Reach | National |
| Policy Influence Type | Contribution to a national consultation/review |
| URL | https://committees.parliament.uk/writtenevidence/134425/pdf/ |
| Description | Data-driven Visions for the Future of AI Skills and Training in the UK |
| Amount | £75,433 (GBP) |
| Funding ID | IF24RBDS\240052 |
| Organisation | The British Academy |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 09/2024 |
| End | 09/2025 |
| Description | Constant Washing Machine |
| Organisation | Blast Theory |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Blast Theory worked with the research team as embedded artists and co-researchers in FRAIM, with curatorial support from the Open Data Institute's Data as Culture programme. The research team conducted research on 1) analysis of responsible AI-related policy documents from a cross-sector sample of 80 organisations; and 2) interviews with staff at project partners regarding their perceptions of responsible AI and its key stakeholders within their organisational contexts. (These research collaborations are described in a separate Collaborations & Partnerships record.) The research team shared the data produced from this research with Blast Theory, subject to participant consent for interview data. This shared data served as the raw material for Blast Theory's research and artistic practice. |
| Collaborator Contribution | The Open Data Institute conducted the recruitment process for selecting the FRAIM embedded artist, with input from the research team. This resulted in appointing Blast Theory as the embedded artist and research collaborator. Curatorial support for the collaboration with Blast Theory was provided by the Open Data Institute, including management of partnership logistics and commissioning of Blast Theory's work, input and support on design and execution of the artistic output, and curation of opportunities to show the artwork after production. Blast Theory worked closely with the research team by attending team meetings, including a workshop held with all project partners in September 2024, and conducting interviews with individual researchers and members of project partner organisations. They also worked with the research data shared by the research team as raw material for their practice. Blast Theory produced the interactive work 'Constant Washing Machine' between November-December 2024, and organised and hosted a launch event for the work at their studios on 10 December 2024. |
| Impact | Outputs: 1) Artwork - Constant Washing Machine; 2) Creative/Artistic Exhibition - Constant Washing Machine launch event. The collaboration is multidisciplinary and includes: 1) data science; 2) science & technology studies; 3) philosophy; 4) creative arts. |
| Start Year | 2024 |
| Description | Constant Washing Machine |
| Organisation | Open Data Institute |
| Country | United Kingdom |
| Sector | Charity/Non Profit |
| PI Contribution | Blast Theory worked with the research team as embedded artists and co-researchers in FRAIM, with curatorial support from the Open Data Institute's Data as Culture programme. The research team conducted research on 1) analysis of responsible AI-related policy documents from a cross-sector sample of 80 organisations; and 2) interviews with staff at project partners regarding their perceptions of responsible AI and its key stakeholders within their organisational contexts. (These research collaborations are described in a separate Collaborations & Partnerships record.) The research team shared the data produced from this research with Blast Theory, subject to participant consent for interview data. This shared data served as the raw material for Blast Theory's research and artistic practice. |
| Collaborator Contribution | The Open Data Institute conducted the recruitment process for selecting the FRAIM embedded artist, with input from the research team. This resulted in appointing Blast Theory as the embedded artist and research collaborator. Curatorial support for the collaboration with Blast Theory was provided by the Open Data Institute, including management of partnership logistics and commissioning of Blast Theory's work, input and support on design and execution of the artistic output, and curation of opportunities to show the artwork after production. Blast Theory worked closely with the research team by attending team meetings, including a workshop held with all project partners in September 2024, and conducting interviews with individual researchers and members of project partner organisations. They also worked with the research data shared by the research team as raw material for their practice. Blast Theory produced the interactive work 'Constant Washing Machine' between November-December 2024, and organised and hosted a launch event for the work at their studios on 10 December 2024. |
| Impact | Outputs: 1) Artwork - Constant Washing Machine; 2) Creative/Artistic Exhibition - Constant Washing Machine launch event. The collaboration is multidisciplinary and includes: 1) data science; 2) science & technology studies; 3) philosophy; 4) creative arts. |
| Start Year | 2024 |
| Description | BBC panel on responsible AI and journalism |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Media (as a channel to the public) |
| Results and Impact | Dr Newman-Griffis discussed FRAIM research in a BBC Academy Fusion panel on 19 February 2025, on the topic of 'AI and Inclusive Journalism.' This reached media professionals in the BBC and around the world via online livestream, and has sparked discussion for future collaborations on AI and the media. |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://www.linkedin.com/feed/update/urn:li:activity:7298143475831570433/ |
| Description | Constant Washing Machine launch |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | We held a public launch event for the artistic output Constant Washing Machine on 10 December 2024, which was attended by approx 30 members of the public in-person and a further 40-50 online. This sparked new insights for the researchers and attendees reported thinking about responsible AI differently after the event. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://culture.theodi.org/constant-washing-machine-blast-theory/ |
| Description | DCMS CSA visit |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Policymakers/politicians |
| Results and Impact | We presented FRAIM research findings and recommendations to the Chief Scientific Advisor of the Department for Culture, Media, and Sport and a senior leader of Building Digital UK on 30 January 2025. This sparked discussion of further opportunities for promotion of Sheffield AI research within government and potential collaborative directions. |
| Year(s) Of Engagement Activity | 2025 |
| URL | https://www.linkedin.com/posts/shefcmi_prof-tom-crick-chief-scientific-adviser-activity-729110288591... |
| Description | Project partners workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | 12 staff from project partner organisations attended a one-day workshop on 12 September 2024 in Sheffield, to learn about project findings and discuss implications and next steps. |
| Year(s) Of Engagement Activity | 2024 |
| Description | Sheffield City Council visit |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Policymakers/politicians |
| Results and Impact | We presented FRAIM research findings and recommendations to the Chief Executive and Council Leader of Sheffield City Council, which sparked discussion and potential future opportunities for collaborative research and training of Council staff. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.linkedin.com/feed/update/urn:li:activity:7270442540263211008/ |
| Description | Sheffield Policy Campus - AI impacts |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | Project team members presented at a 10 October seminar in the Sheffield Policy Campus AI Seminar Series, on the impacts of AI on work and the economy. Approximately 30-40 civil servants and higher education professionals were in attendance. |
| Year(s) Of Engagement Activity | 2024 |
| Description | Sheffield Policy Campus - AI skills |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Professional Practitioners |
| Results and Impact | Project team members presented in the 23 October 2024 Sheffield Policy Campus AI Seminar Series session on AI skills and education. This reached approx 30-40 civil servants, higher education professionals, and business leaders in the Sheffield City Region. |
| Year(s) Of Engagement Activity | 2024 |