mlsanityData to 14 Oct 2026

P4AI: Approaching AI Ethics through Principlism

arXiv 2111.14062 ↗First posted 28 Nov 2021cs.LG cs.CYcited by 1

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Abstract (arXiv)

The field of computer vision is rapidly evolving, particularly in the context of new methods of neural architecture design. These models contribute to (1) the Climate Crisis - increased CO2 emissions and (2) the Privacy Crisis - data leakage concerns. To address the often overlooked impact the Computer Vision (CV) community has on these crises, we outline a novel ethical framework, textitP4AI: Principlism for AI, an augmented principlistic view of ethical dilemmas within AI. We then suggest using P4AI to make concrete recommendations to the community to mitigate the climate and privacy crises.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 27 references that are in the map. First posted on arXiv 28 Nov 2021.

Builds on

7 of 27 references.

References · 7

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  3. 2014Going Deeper with Convolutionscited by 4,241
  4. 2018Model Cards for Model Reportingcited by 1,080
  5. 2016Towards the Science of Security and Privacy in Machine Learningcited by 89
  6. 2017Generative Face Completioncited by 79
  7. 2021Reconsidering CO2 emissions from Computer Visioncited by 9

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Citing papers per year: 2022: 1.

1 paper.