Pith. sign in

REVIEW 1 cited by

Social Choice with Changing Preferences: Representation Theorems and Long-Run Policies

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2011.02544 v1 pith:5ZNGNJZ3 submitted 2020-11-04 cs.MA cs.AI

classification cs.MAcs.AI
keywords socialchoicechangingdecisionlong-runmakingoptimalpolicies
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We study group decision making with changing preferences as a Markov Decision Process. We are motivated by the increasing prevalence of automated decision-making systems when making choices for groups of people over time. Our main contribution is to show how classic representation theorems from social choice theory can be adapted to characterize optimal policies in this dynamic setting. We provide an axiomatic characterization of MDP reward functions that agree with the Utilitarianism social welfare functionals of social choice theory. We also provide discussion of cases when the implementation of social choice-theoretic axioms may fail to lead to long-run optimal outcomes.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Can an AI Agent Safely Run a Government? Existence of Probably Approximately Aligned Policies

    cs.AI 2024-11 conditional novelty 6.0 of 10

    Given a sufficiently accurate model of social dynamics, there provably exist policies that are near-optimal for a chosen social welfare function with high probability, plus a safety filter for arbitrary black-box policies.

Pith tools