A Participatory Simulation of the Accountable Capitalism Act
Bill Tomlinson, Michael Six Silberman, Andrew W. Torrance, Kurt Squire, Paramdeep S. Atwal, Ameya N. Mandalik, Sahil Railkar, Rebecca W. Black
Abstract
Interactive computing systems increasingly allow for experimental evaluations of fundamental issues in law, government, and society. In this paper, we describe a participatory simulation of the Accountable Capitalism Act, a bill proposed in 2018 by US Senator Elizabeth Warren. We present findings from an empirical study conducted using this system, relating to the impact of 1) interactive visualization and 2) the Accountable Capitalism Act legal framework on the behavior of participants acting as corporate directors. From this study, we draw lessons about research possibilities at the juncture of HCI and legal and policy studies. This study contributes an analysis and evaluation of a design probe used to investigate potential impacts of the Accountable Capitalism Act, experimental evidence from a study conducted using the design probe, and guidance for future participatory simulations that seek to inform the design of social institutions.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get e81c7c4e-cf19-404e-b891-8107d9234402Related papers
- Designing for Proactive Accountability: Lessons on Governing Technology from Detroit's Food Sovereignty MovementJared Lee Katzman, Ben Green, Tawanna R. DillahuntCHI 2026 · 2 citations
- Design Courts: Workshops for Exploring Emerging Technology EthicsNamrata Primlani, Mark Blythe, Justin MarshallCHI 2025 · 3 citations
- Designing to Support Local Stakeholders in Negotiating about Future Sustainable and Healthy Food SystemsAdrian K. Clear, Samantha Mitchell Finnigan, Ryan T. Sharp, Alice E. Milne et al.CHI 2026 · 1 citation
- Left, Right, and Gender: Exploring Interaction Traces to Mitigate Human BiasesEmily Wall, Arpit Narechania, Adam Coscia, Jamal Paden et al.IEEE VIS 2021 · 38 citations
- RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical RolesMarios Constantinides, Edyta Paulina Bogucka, Daniele Quercia, Susanna Kallio et al.CSCW 2024 · 28 citations
