Enabling a Responsible AI Ecosystem

Problem Space: There is now a broad base of research in AI ethics, policy and law that can inform and guide efforts to construct a Responsible AI (R-AI) ecosystem, but three gaps must be bridged before this is achieved:

(a) Traditional disciplinary silos, boundaries, and incentives limiting successful generation and translation of R-AI knowledge must be addressed by new incentives and supportive infrastructure.
(b) The high barriers to adoption of existing research and creative work in R-AI must be removed so that public institutions, non-profits and industry (especially SME) can convert and embed R-AI into reliable, accessible and scalable practices and methods that can be broadly adopted.
(c) The primary actors empowered to research, articulate and adopt responsible AI standards must be more broadly representative of, and answerable to, the publics and communities most impacted by AI developments.

Approach: We will develop and deliver a UK-wide infrastructure that lays secure foundations for the bridges across these three gaps so that AI in the UK is responsible, ethical and accountable by default. The programme will be structured around three core pillars of work (Translation and Co-Construction, Embedding and Adoption, and Answerability and Accountability) and four strategic delivery themes that establish programme coherence: (1) AI for Humane Innovation: integrating within AI research the humanistic perspectives that enable the personal, cultural, and political flourishing of human beings, by weaving historical, philosophical, literary and other humane arts into dialogue with AI communities of research, policy and practise (2) AI for Inspired Innovation: activities to infuse the AI ecosystem with more vibrant, imaginative and creative visions of R-AI futures (3) AI for Equitable Innovation: activities directing research and policy attention to the need to ensure that broader UK publics, particularly those marginalised within the digital economy, can expect more sustainable and equitable futures from AI development, and (4) AI for Resilient Innovation: uplifting research, policy and practise that ensures AI ameliorates growing threats to global and national security, rule of law, liberty, and social cohesion.

Team: Co-Directors Vallor and Luger will lead and deliver the programme alongside the Ada Lovelace Institute, with a cross-disciplinary team of Co-Is who will leverage their networks to broaden/diversify the R-AI community and enhance disciplinary engagement with R-AI, acting as translational interfaces to ensure AHRC programme communications speak effectively to underrepresented cohorts within their communities/disciplines. As partner, the BBC will support public engagement activities to ensure trust, breadth of reach and public legitimacy.

Activities: Through a comprehensive programme of translation, research and engagement activities we will:
(1) Support existing and foster new R-AI partnerships, connecting AI researchers, industry, policymakers and publics around the cross-cutting themes.
(2) Build broader responsible AI visions by developing infrastructure for translation of R-AI research, inviting ECRs and new voices from the arts, humanities and civil society, to co-shape, interrogate and enrich visions of flourishing with AI.
(3) Learning from early R-AI work, surface and map barriers, incentives and opportunities to make R-AI research responsive to the needs and challenges faced by policymakers, regulators, technologists, and wider publics.
(4) Embed R-AI in policy and practice by conducting research and building capacity for translation of R-AI research into accessible and usable guidance for policymakers, industry leaders, SMEs and publics.
(5) Build trust in AI by rethinking accountability through three applied lenses: accountability to wider publics, answerability of current systems, and public mechanisms for recourse through consultation, creative mechanisms and synthesis activities.