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. 2024 Jun 10;30(3):26.
doi: 10.1007/s11948-024-00480-6.

From Pixels to Principles: A Decade of Progress and Landscape in Trustworthy Computer Vision

Kexin Huang  1   2 , Yan Teng  3 , Yang Chen  2 , Yingchun Wang  1
Affiliations

From Pixels to Principles: A Decade of Progress and Landscape in Trustworthy Computer Vision

Kexin Huang et al. Sci Eng Ethics. .

Abstract

The rapid development of computer vision technologies and applications has brought forth a range of social and ethical challenges. Due to the unique characteristics of visual technology in terms of data modalities and application scenarios, computer vision poses specific ethical issues. However, the majority of existing literature either addresses artificial intelligence as a whole or pays particular attention to natural language processing, leaving a gap in specialized research on ethical issues and systematic solutions in the field of computer vision. This paper utilizes bibliometrics and text-mining techniques to quantitatively analyze papers from prominent academic conferences in computer vision over the past decade. It first reveals the developing trends and specific distribution of attention regarding trustworthy aspects in the computer vision field, as well as the inherent connections between ethical dimensions and different stages of visual model development. A life-cycle framework regarding trustworthy computer vision is then presented by making the relevant trustworthy issues, the operation pipeline of AI models, and viable technical solutions interconnected, providing researchers and policymakers with references and guidance for achieving trustworthy CV. Finally, it discusses particular motivations for conducting trustworthy practices and underscores the consistency and ambivalence among various trustworthy principles and technical attributes.

Keywords: AI principles; Computer vision; Ethical AI; Progress and landscape; Trustworthy AI.

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Figures

Fig. 1
Fig. 1
Overview of the paper
Fig. 2
Fig. 2
The evolution of the emergence of value norms in the literature (left) and statistics on the number of occurrences of each dimension’s value norms in the literature (right)
Fig. 3
Fig. 3
Statistics on the proportion of occurrences of each dimension’s value norms in the literature (left) and trends in the proportion of each dimension’s value norms appearing in the literature (right)
Fig. 4
Fig. 4
LDA topic modeling on trustworthy related papers (Filter 2)
Fig. 5
Fig. 5
Life-cycle trustworthiness framework of frontier CV models
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