Data Ethics Group

How will The Alan Turing Institute shape understanding of the ethical and societal implications of data?



Research areas


Understanding the ethical and societal implications of data is one of The Alan Turing Institute’s key research priorities. We have created the Data Ethics Group to lead our research in this area.


Made up of a range of researchers specialising in ethics, social science, law, policy-making, and big data and algorithms, the Data Ethics Group drives the Institute’s research agenda in data ethics and works across the organisation on ethical best practice in data science.

The Group works in collaboration with the broader data science community, supports public dialogue on relevant topics, and sets open calls for participation in workshops, as well as public events.

How to get involved

Click here to join and request sign-up

Recent updates

DEG Theme for 2022: AI, Power, and the Public Interest: Who’s in control?

Despite the current swell of appeals to data science and “AI for the social good’ in the academic literature, the sociotechnical reality of contemporary data scientific practice seems to be telling a very different story. Present-day AI research and development ecosystems are contested fields composed of complex and contending interests, asymmetrical power relations, and prohibitive entry costs.

Notwithstanding their projections of charitable rhetoric, large tech companies are increasingly engaged in a “commercially-driven production of the social good” that, many have argued, produce outcomes which run counter to the public interest. The corresponding rise of phenomena like “data colonialism” and “philanthro-capitalism” are complicating “AI for the social good” narratives. They are heralding the coalescence of high-entry-cost digital innovation ecosystems, multinational corporate business models, and marketing strategies with humanitarian data work, digital development schemes, and market forces.

The result is the proliferation of privately controlled forms of extractionist data work, that are, in fact, often at cross-purposes with inclusive, equitable, and societally beneficial innovation. Trends such as these appear to be signalling “a profound rebalancing of power and governance in the domain of social life, privileging corporations with large-scale data power and making states (and other commercial and civil society actors) dependent on those corporations.” Similarly, incipient forms of data governmentality and commodification ever more infiltrate academic venues and research environments.

In these, large tech companies’ proprietary data sets, seemingly unlimited financial resources, and massive computing power are, in effect, ‘de-democratising’ AI and data science. Several processes and dynamics hasten this. They include the control that corporations possess over access to data and compute resources, their command over labour power through the university-corporate hybridisation of ‘dual-affiliation’ career trajectories, and their manipulation of the terms of open research to protect their own rentiership claims to monopolistic control over intellectual property and infrastructural assets.

The constellations of asymmetrical power relations, private corporate interests, and high entry costs for data innovation seem to establish the terms of engagement for accessing critical digital infrastructure that should otherwise be tightly bound up with the pursuit of the public good. The theme for our DEG dialogues this year, “AI, Power, and the Public Interest: Who’s in control?,” is framed around the difficult questions raised by these trends.

Questions of concern include: Is the current universe of data scientific innovation—that is, the global assemblage of data infrastructures, compute infrastructures, algorithmic infrastructures, funding schemes, and research and delivery capabilities and resources—equipped to actualise responsible and sustainable data work that serves the public good? Or do these infrastructural, resourcing, and human factors operate, in fact, to curtail and elide possibilities for that actualisation?

Is the human and biospheric interest in the realisation of the global public good being fostered by the current national and global configuration of power relations, sociotechnical affordances, platform ecosystems, and infrastructural networks that characterise contemporary data scientific research and innovation environments? How should terms such as “public good,” “social good”, and “public interest” be construed and reinterpreted in the light of the factors that purport to promote their realisation, or are seen as inhibiting them?

What role should states and governments play in the provision of, and the regulation and governance of, critical digital infrastructure? How can, and should, effective technology governance (including laws, regulatory regimes, and other policy instruments) work in the complicated, multivalent, and transnational innovation ecosystems and platform political economy that is dominated by big tech?

Upcoming events

We look forward to engaging with you at the first public dialogue of 2022 in collaboration with the research team at PATH-AI (Privacy, Agency and Trust in Human-AI Ecosystems) on 9 May at 17:00 GMT.  

Dr James Wright will be presenting his research on PATH-AI followed by a discussion chaired by Dr David Leslie and Professor Charles Raab.

The meeting will be open to all approved members. View flyer


Professor David Leslie

Director of Ethics and Responsible Innovation Research at The Alan Turing Institute and Professor of Ethics, Technology and Society, Queen Mary University of London


Contact info

[email protected]