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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.
Optimization's Neglected Normative Commitments
Optimization is offered as an objective approach to resolving complex, real-world decisions involving uncertainty and conflicting interests.
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.
Computer Vision and Conflicting Values: Describing People with Automated Alt Text
In this paper, we investigate the ethical dilemmas faced by companies that have adopted the use of computer vision for producing alt text: textual descriptions of images for blind and low vision people, We use Facebook's automatic alt text tool as our primary case study.
Interdisciplinary Approaches to Understanding Artificial Intelligence's Impact on Society
Innovations in AI have focused primarily on the questions of "what" and "how"-algorithms for finding patterns in web searches, for instance-without adequate attention to the possible harms (such as privacy, bias, or manipulation) and without adequate consideration of the societal context in which these systems operate.
An Ethical Highlighter for People-Centric Dataset Creation
Important ethical concerns arising from computer vision datasets of people have been receiving significant attention, and a number of datasets have been withdrawn as a result.
