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Massachusetts Institute of Technology

Preserving Human Autonomy in AI-Mediated Negotiations

Abstract

dc:description.abstract

The rapid integration of generative artificial intelligence (AI) into negotiation and conflict resolution processes raises critical ethical concerns about the erosion of human autonomy, particularly when AI systems navigate irreconcilable “sacred” values (non-negotiable moral principles) alongside transactional “mundane” interests. This thesis investigates whether generative AI can be designed to recognize and respect important values and beliefs while preserving human agency in decision-making. Drawing on datasets from a repository of large language model (LLM) prompts tested in simulated negotiation scenarios, this study employs a mixed-methods approach to evaluating AI’s efficacy in balancing efficiency with ethical imperatives in negotiation. Quantitative metrics (enumerating the outcomes of two-party negotiations) are analyzed alongside qualitative assessments of values such as transparency and consent, drawn from Kantian ethical frameworks. My analysis reveals that while AI negotiating bots excel in trades across mundane, tradable interests they struggle to navigate beliefs and values without oversimplifying moral reasoning or obscuring cultural considerations. These findings inform policy recommendations, including a call for human-in-the-loop validation and technical safeguards for protecting important values in efforts to incorporate AI-assistance into negotiations. By bridging technical analysis and ethical theory, I hope this research contributes to improvements in designing autonomy-preserving AI systems for use in a range of negotiating settings, prioritizing human dignity alongside computational efficiency.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Chen, J. Alvin
Advisor dc:contributor.advisor
  • Susskind, Lawrence

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/162422
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/162422

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Chen, J. Alvin. Preserving Human Autonomy in AI-Mediated Negotiations. Massachusetts Institute of Technology, 2025. https://hdl.handle.net/1721.1/162422