CALL FOR PAPERS

"AI and the Future of Social Welfare: Recent Developments and Future Prospects"

London, United Kingdom | June 4-5, 2026

We are pleased to invite papers for an international conference “AI and the Future of Social Welfare: Recent Developments and Future Prospects” organized by the International Network for Social Policy Teaching and Research (INSP); the London School of Economics (LSE); the University of California Berkeley Center for Comparative Welfare State Research; and the University of Maryland School of Public Policy. The conference will be held at LSE in London, UK.

ORGANIZING COMMITTEE

Chairs: Douglas Besharov (University of Maryland), Timo Fleckenstein (London School of Economics), and Neil Gilbert (University of California, Berkeley).

BACKGROUND

As in so many areas, artificial intelligence (AI) and various other tools of information science generally, hold great promise for increasing the efficiency and quality of policy research and program evaluation. Machine learning, deep learning, and generative AI are already speeding analyses, facilitating the use of innovative methodologies, and lowering costs on various dimensions (which also enables more extensive analysis)—all of which enhances the analytic capacities of organizations. Each day seems to bring another paper that uses AI for mapping, simulation, survey and data collection, data cleaning and organization, qualitative data coding and synthesis, relational databases, visualization, pattern detection, and predictive modeling/models.

PAPER TOPICS

We encourage submissions on themes related to “AI and the Future of Social Welfare,” including but not limited to:

(1) The conduct and administration of research, including the increased speed and efficiency with which research can be conducted (affecting both research quality and quantity), new methods for conducting and synthesizing research, and the effects of uneven take-up of AI among current researchers;

(2) The development of policies and programs, including the detection and description of societal trends that may require a policy response, the identification and assessment of policy options, and predictive modeling of outcomes;

(3) The operation and management of programs, including eligibility determinations, service provision, customer service assistance, and predictive analytics of service provision;

(4) Transparency, protective controls, and limits, including protocols for reporting AI usage in research, detailed logs of AI prompts, replication of analyses using alternate AI systems, oversight of AI implementation in government programs; and fraud/error detection in social assistance programs;

(5) Ethics, and regulation, including ethical frameworks for AI in public administration; transparency and accountability in algorithmic decision-making; bias, discrimination, and fairness in automated welfare systems; human oversight vs. automated decision systems in social policy; and data governance and citizen privacy in digital welfare; and

(6) Teaching, including the use of AI as an educational tool, academic policies regarding use of AI, and creative AI assignments that stimulate critical thinking about social policy.

We encourage contributions from all relevant disciplines, including information science, social policy, economics, sociology, public health, and political science. We welcome comparative as well as case studies, policy evaluations, and academic and applied research.

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