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Strategic Evaluation: Subjects, Evaluators, and Society
Machine learning literature on strategic behavior has tried to describe these dynamics by emphasizing the efforts expended by decision subjects hoping to obtain a more favorable assessment -- some works offer ways to preempt or prevent such manipulations, some differentiate 'gaming' from 'improvement' behavior, while others aim to measure the effort burden or disparate effects of classification systems.
Fine-Tuning Games: Bargaining and Adaptation for General-Purpose Models
Both entities are profit-seeking and incur costs when they invest in the technology, and they must reach a bargaining agreement on how to share the revenue for the technology to reach the market.
Optimization's Neglected Normative Commitments
Optimization is offered as an objective approach to resolving complex, real-world decisions involving uncertainty and conflicting interests.
Collective Obfuscation and Crowdsourcing
Crowdsourcing technologies rely on groups of people to input information that may be critical for decision-making.
Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning
In 1996, Accountability in a Computerized Society [95] issued a clarion call concerning the erosion of accountability in society due to the ubiquitous delegation of consequential functions to computerized systems.
Feedback Effects in Repeat-Use Criminal Risk Assessments
We show through simulation that risk can propagate over sequential decisions in ways that are not captured by one-shot tests.
Compounding Injustice: History and Prediction in Carceral Decision-Making
Risk assessment algorithms in criminal justice put people's lives at the discretion of a simple statistical tool.
Computers and Society Applications 62M20 (Primary), 62L10 (Secondary), 68U99 (Secondary) K.4.1; K.5.2; G.3; I.6.5; J.4; J.1; F.0
