mlsanityData to 7 Oct 2026

Ethics Sheets for AI Tasks

arXiv 2107.01183 ↗First posted 2 Jul 2021cs.AI cs.CLcited by 18

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Abstract (arXiv)

Several high-profile events, such as the mass testing of emotion recognition systems on vulnerable sub-populations and using question answering systems to make moral judgments, have highlighted how technology will often lead to more adverse outcomes for those that are already marginalized. At issue here are not just individual systems and datasets, but also the AI tasks themselves. In this position paper, I make a case for thinking about ethical considerations not just at the level of individual models and datasets, but also at the level of AI tasks. I will present a new form of such an effort, Ethics Sheets for AI Tasks, dedicated to fleshing out the assumptions and ethical considerations hidden in how a task is commonly framed and in the choices we make regarding the data, method, and evaluation. I will also present a template for ethics sheets with 50 ethical considerations, using the task of emotion recognition as a running example. Ethics sheets are a mechanism to engage with and document ethical considerations before building datasets and systems. Similar to survey articles, a small number of ethics sheets can serve numerous researchers and developers.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 7 of its 48 references that are in the map. First posted on arXiv 2 Jul 2021.

Builds on

7 of 48 references.

References · 7

  1. 2018Datasheets for Datasetscited by 1,371
  2. 2018Model Cards for Model Reportingcited by 1,068
  3. 2019Green AIcited by 620
  4. 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systemscited by 234
  5. 2018Assessing Gender Bias in Machine Translation -- A Case Study with Google Translatecited by 121
  6. 2016Analyzing the Behavior of Visual Question Answering Modelscited by 119
  7. 2020Debiasing Skin Lesion Datasets and Models? Not So Fastcited by 43

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 5; 2024: 4; 2025: 2; 2026: 1.

18 papers.

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