Designing a Moral Compass for the Future of Computer Vision Using Speculative Analysis

Skirpan, Michael; Yeh, Tom

doi:10.1109/cvprw.2017.179

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…In this respect, we turn to Galloway and Caudwell (2018) who have described the value of design fiction as one approach to envisioning "works of design that imagine, speculate on, and represent alternate visions of design and the worlds it inhabits" (p. 86). One compelling and germane example of design fiction can be found in the scholarship of Skirpan and Yeh (2017) who share fictive scenarios about computer vision technologies to explore potential risk scenarios and analyze discriminatory harms associated with cybersecurity. The authors detail the methodological benefit of speculative fiction given the need to "consider negative aspects often glossed over when reporting new research" (pp.…”

Section: Speculative Methodsmentioning

confidence: 99%

Learning Analytics and the Abolitionist Imagination

Swauger¹,

Kalir²

2023

Learning Analytics

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This article advances an abolitionist reframing of learning analytics (LA) that explores the benefits of productive disorientation, considers potential harms and care made possible by LA, and suggests the abolitionist imagination as an important educational practice. By applying abolitionist concepts to LA, we propose it may be feasible to open new critiques and social futures that build toward equity-oriented LA design and implementation. We introduce speculative methods to advance three vignettes imagining how LA could be weaponized against students or transformed into a justice-directed learning tool. Our speculative methods aim to destabilize where power in LA has been routinely located and contested, thereby opening new lines of inquiry about more equitable educational prospects. Our concluding discussion addresses how speculative design and fiction are complementary methods to the abolitionist imagination and can be pragmatic tools to help build a world with fairer, more equitable, and responsible LA technologies.

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Section: Speculative Methodsmentioning

confidence: 99%

Learning Analytics and the Abolitionist Imagination

Swauger¹,

Kalir²

2023

Learning Analytics

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“…The second piece on the ethics of CV is a conference paper by Skirpan and Yeh, titled 'Designing a Moral Compass for the Future of Computer Vision using Speculative Analysis'. The authors categorize five risks in CV: privacy violations, discrimination, security breaches, spoofing and adversarial inputs, and psychological harms [23].…”

Section: Related Workmentioning

confidence: 99%

The ethics of computer vision: an overview in terms of power

Waelen

2023

AI Ethics

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Computer vision is a subfield of artificial intelligence, aimed at making computers see. Computer vision tools enable a system or device to automatically analyze, interpret, and respond to images and videos. Computer vision tasks range from object detection and tracking, to the recognition of people’s faces and emotional states. While the ethics of AI in general has received significant attention, and the ethics of facial recognition (a computer vision application) too, little of the AI ethics literature focuses specifically on the ethics of computer vision. In this chapter, I create an overview of ethical, social, and political issues related to computer vision, using a critical approach. This means that I identify issues in terms of power and evaluate them in function of their impact on the value of autonomy and the normative goal of emancipatory progress. The aim of this chapter is first and foremost to offer an overview of potential normative implications of computer vision. Additionally, the chapter functions as an example for the use of a critical approach to AI ethics.

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“…It is hard to imagine a person who would feel comfortable in blindly agreeing with a system's decision in such highly consequential and ethical situations without a deep understanding of the decision making rationale of the system. To achieve complete trustworthiness and an evaluation of the ethical and moral standards of a machine [15], detailed "explanations" of AI decisions seem necessary. Such explanations should provide insight into the rationale the AI uses to draw a conclusion.…”

Section: Introductionmentioning

confidence: 99%

What Does Explainable AI Really Mean? A New Conceptualization of Perspectives

Doran,

Schulz,

Besold

2017

Preprint

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We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algorithmic mechanisms; interpretable systems where users can mathematically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached. The paper is motivated by a corpus analysis of NIPS, ACL, COGSCI, and ICCV/ECCV paper titles showing differences in how work on explainable AI is positioned in various fields. We close by introducing a fourth notion: truly explainable systems, where automated reasoning is central to output crafted explanations without requiring human post processing as final step of the generative process.

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Designing a Moral Compass for the Future of Computer Vision Using Speculative Analysis

Cited by 13 publications

References 20 publications

Learning Analytics and the Abolitionist Imagination

Learning Analytics and the Abolitionist Imagination

The ethics of computer vision: an overview in terms of power

What Does Explainable AI Really Mean? A New Conceptualization of Perspectives

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