Daniel Bogiatzis-Gibbons
Department: Social Sciences, Birkbeck
UBEL Pathway: Politics: Birkbeck College
Supervisor: Samantha Ashenden, Laszlo Horvath
Contact details: danjamesgibbons@gmail.com
About Me:
I am a data scientist and political philosopher, and previously worked for 7 years across public sector consultancy, third-sector and regulatory roles. I am a Chartered Statistician and sit on the Royal Statistical Society’s Committee on Data Ethics and Governance.
My Research:
My research will examine why states choose to adopt AI systems and the ethical and regulatory implications. It will focus primarily on the use of AI in children’s social care since it is understudied relative to criminal justice yet involves extremely vulnerable individuals. It is an important topic due to the recent proliferation of AI systems in government and developments in AI regulation, such as the Netherlands creating a register of government AI systems. The focus on children’s social care is timely, given the recently published Care Review highlighting the need to make care proceedings more just and to policy research I co-authored showing low accuracy for AI models used in child protection.
In its first theory section, it will analyse the evolution of the choice to use AI systems by agents of the British state. It will argue, using work by Hannah Arendt and Ian Hacking, that AI diminishes the role of expertise within public policy as AI systems advise on individual cases. Further, it will argue that AI changes considerations of risk to be fundamentally prospective and individualised.
Second, in a section drawing on advanced quantitative methods, it will seek to measure using a conjoint online panel experiment whether accurate communication of the risks and benefits drive public servants’ choice to adopt AI systems. This will be examined against alternative explanations like risk aversion and efficiency savings.
Finally, in a theory section, it will argue, using the work of Judith Shklar, there is a need to learn from the historical development of state statistics to focus on the need for preventing the worst injustices rather than relying on technical safeguards. This will also build on the empirical section; it would be concerning if public policymakers were willing to deploy AI systems in areas like children’s social care with emerging evidence of poor functioning.
Impact of My Research:
Despite assurances that AI will improve state decision-making, this is not always evidence-based and rarely publicly debated. For instance, a report I co-authored for the What Works Centre for Children’s Social Care (Clayton, Gibbons, Schoenwald, Surkis, and Sanders 2020) found that if a machine learning model identifies a child is at risk, it is wrong six out of ten times, meaning if deployed a significant number of children and families could suffer the consequences of wrongful intervention. The political stakes of this shift are therefore high and highlight the increasing need for regulation of AI systems used by the state. This is urgently needed to help protect citizens from the negative consequences of misused or inaccurate systems while allowing them to benefit from the appropriate usage of AI.
On a disciplinary level, the rationale for the thesis is to improve understanding of the role of technology in shaping and being shaped by state practice. For instance, in political theory, technology is typically assumed away, often by analysing a given society with, as Gabriel (2022) puts it, a “specific sociotechnical character (that is, one with a functioning legal system, economic division of labor, capacity for taxation, and so on)” (219).
Finally, the timing of this project is opportune as AI systems are starkly in policy focus, with the UK government consulting on releasing new AI principles, the Netherlands creating the world’s first algorithm register, and the European Union passing the Artificial Intelligence Regulation in December 2022. However, all of these efforts fall far short of the World Bank’s (2021) call for a “new social contract for data”, for example because new regulations tend to focus on the safe development of AI systems, rather than regulating purposes for which AI systems might be justly used. Similarly, the focus on social care is apt due to adoption of recommendations in the far-reaching Independent Review of Children’s Social Care by Josh MacAlister published in 2022.