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ACM Journal on Responsible Computing is a peer-reviewed journal published by ACM, covering Ethics and Social Impacts of AI, Privacy-Preserving Technologies in Data, Privacy, Security, and Data Protection. Over its lifetime it has published 64 papers, which have received 773 citations.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. ACM Journal on Responsible Computing 12, 3, Article 45 (2023).
Formats any DOI in ACM Journal on Responsible Computing style. No sign-up. |
| Publishes research in | Ethics and Social Impacts of AI Privacy-Preserving Technologies in Data Privacy, Security, and Data Protection Artificial Intelligence in Healthcare and Education Explainable Artificial Intelligence (XAI) |
| ISSN | 2832-0565 |
| Citation impact (2-yr) | 6.11 |
| h-index | 13 |
| i10-index | 15 |
| Top institutions publishing here | Cornell University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
This article provides a comprehensive survey of bias mitigation methods for achieving fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning bias mitigation for ML classifiers. These methods can be distinguished based on their intervention procedure (i.e., pre-processing, in-processing, post-processing) and the technique they apply. We investigate how existing bias…
We formalize predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals . For example, pre-trial risk prediction algorithms such as COMPAS use ML to predict whether an individual will re-offend in the future. Our thesis is that predictive optimization raises a distinctive and serious…
Generative artificial intelligence systems based on transformers, including both text generators such as GPT-4 and image generators such as DALL-E 3, have recently entered the popular consciousness. These tools, while impressive, are liable to reproduce, exacerbate, and reinforce extant human social biases, such as gender and racial biases. In this article, we systematically review the…
Amidst calls for public accountability over large data-driven systems, feminist and indigenous scholars have developed refusal as a practice that challenges the authority of data collectors. However, because data affect so many aspects of daily life, it can be hard to see seemingly different refusal strategies as part of the same repertoire. Furthermore, conversations about…
Skin tone plays a critical role in artificial intelligence (AI). However, many algorithms have exhibited unfair bias against people with darker skin tones. One reason this occurs is a poor understanding of how well the scales we use to measure and account for skin tone in AI actually represent the variation of skin tones in…
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