This talk presents my research on how algorithmic systems influence decision-making in AI-driven environments. I investigate scenarios involving compounded automated decisions (e.g., repeated credit denials), automated work scheduling, and recommendation systems that affect what people purchase, how they manage their time, and how institutions set objectives in multi-stakeholder settings. These systems could then potentially affect people’s agency and core values, producing uncertainty and unexpected outcomes. Through economic modeling, simulation, and organizational analysis, I study how these systems shape individual autonomy (e.g., consumer choices), financial outcomes, and behavior over time.

One part of my talk focuses on deterministic systems like optimization processes and examines how they can potentially amplify financial instability in digital economies. I design methods that incorporate feedback, long-term effects, and stakeholder tradeoffs directly into optimization as a dynamic and temporal process (instead of setting a static multi-objective optimization formulation). Another part of my work explores generative AI and its impact on human reasoning and preferences. In combination, the goal of these projects is to contribute to broader inquiries into how algorithmic systems alter human values and agency in terms of economic coordination and human decision-making.