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Found 11 papers, 2 papers with code
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.
On the Actionability of Outcome Prediction
Through a simple model encompassing actions, latent states, and measurements, we demonstrate that pure outcome prediction rarely results in the most effective policy for taking actions, even when combined with other measurements.
Informational Diversity and Affinity Bias in Team Growth Dynamics
Prior work has provided strong evidence that, within organizational settings, teams that bring a diversity of information and perspectives to a task are more effective than teams that do not.
Proactive Moderation of Online Discussions: Existing Practices and the Potential for Algorithmic Support
To address the widespread problem of uncivil behavior, many online discussion platforms employ human moderators to take action against objectionable content, such as removing it or placing sanctions on its authors.
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report
In September 2021, the "One Hundred Year Study on Artificial Intelligence" project (AI100) issued the second report of its planned long-term periodic assessment of artificial intelligence (AI) and its impact on society.
An Uncommon Task: Participatory Design in Legal AI
Despite growing calls for participation in AI design, there are to date few empirical studies of what these processes look like and how they can be structured for meaningful engagement with domain experts.
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.
Artificial intelligence in communication impacts language and social relationships
Artificial intelligence (AI) is now widely used to facilitate social interaction, but its impact on social relationships and communication is not well understood.
Representativeness in Statistics, Politics, and Machine Learning
Today, as the concept crops up in the study of fairness and accountability in machine learning, we need to carefully consider the term's meanings in order to communicate clearly and account for their normative implications.
Fairness
Computers and Society
Accuracy-Efficiency Trade-Offs and Accountability in Distributed ML Systems
Trade-offs between accuracy and efficiency pervade law, public health, and other non-computing domains, which have developed policies to guide how to balance the two in conditions of uncertainty.
Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices
How are algorithmic assessments built, validated, and examined for bias?
