In this editorial to the Topical Collection “Innovation under Fire: The Rise of Ethics in Tech”, we provide an overview of the papers gathered in the collection, reflect on similarities and differences in their analytical angles and methodological approaches, and carve out some of the cross-cutting themes that emerge from research on the production of ‘Tech Ethics’. We identify two recurring ways through which ‘Tech Ethics’ are studied and forms of critique towards them developed, which we argue diverge primarily in (...) their a priori commitments towards what ethical tech is and how it should best be pursued. Beyond these differences, we observe how current research on ‘Tech Ethics’ evidences a close relationship between public controversies about technological innovation and the rise of ethics discourses and instruments for their settlement, producing legitimacy crises for ‘Tech Ethics’ in and of itself. ‘Tech Ethics’ is not only instrumental for governing technoscientific projects in the present but is equally instrumental for the construction of socio-technical imaginaries and the essentialization of technological futures. We suggest that efforts to reach beyond single case-studies are needed and call for collective reflection on joint issues and challenges to advance the critical project of ‘Tech Ethics’. (shrink)

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. (shrink)