ABSTRACT
Artificial intelligence (AI) is producing highly beneficial impacts in many domains, from transport to healthcare, from energy distribution to marketing, but it also raises concerns about undesirable ethical and social consequences. AI impact assessments (AI-IAs) are a way of identifying positive and negative impacts early on to safeguard AI's benefits and avoid its downsides. This article describes the first systematic review of these AI-IAs. Working with a population of 181 documents, the authors identified 38 actual AI-IAs and subjected them to a rigorous qualitative analysis with regard to their purpose, scope, organisational context, expected issues, timeframe, process and methods, transparency and challenges. The review demonstrates some convergence between AI-IAs. It also shows that the field is not yet at the point of full agreement on content, structure and implementation. The article suggests that AI-IAs are best understood as means to stimulate reflection and discussion concerning the social and ethical consequences of AI ecosystems. Based on the analysis of existing AI-IAs, the authors describe a baseline process of implementing AI-IAs that can be implemented by AI developers and vendors and that can be used as a critical yardstick by regulators and external observers to evaluate organisations' approaches to AI.
ABSTRACT
This article shows that current ethics guidance documents and initiatives for artificial intelligence (AI) tend to be dominated by a principled approach to ethics. Although this brings value to the field, it also entails some risks, especially in relation to the abstraction of this form of ethics that makes it poorly equipped to engage with and address deep socio-political issues and the material impacts of AI. This is particularly problematic considering the risk for AI to further entrench already existing social inequalities and injustices and contribute to environmental damage. To respond to this challenge posed by AI ethics today, this article proposes to complement the existing principled approach with an approach to ethics as attention to context and relations. It does so by drawing from alternative ethical theories to the dominant principled one, especially the ethics of care or other feminist approaches to ethics. Related to this, it encourages the inclusion of social sciences and humanities in the development, deployment and use of AI, as well as in AI ethics discussions and initiatives. This article presents this proposal for an ethics as attention to context and formulates a series of practical recommendations to implement this proposal concretely.
ABSTRACT
This paper provides a systematic literature review, analysis and discussion of methods that are proposed to practise ethics in research and innovation (R&I). Ethical considerations concerning the impacts of R&I are increasingly important, due to the quickening pace of technological innovation and the ubiquitous use of the outcomes of R&I processes in society. For this reason, several methods for practising ethics have been developed in different fields of R&I. The paper first of all presents a systematic search of academic sources that present and discuss such methods. Secondly, it provides a categorisation of these methods according to three main kinds: (1) ex ante methods, dealing with emerging technologies, (2) intra methods, dealing with technology design, and (3) ex post methods, dealing with ethical analysis of existing technologies. Thirdly, it discusses the methods by considering problems in the way they deal with the uncertainty of technological change, ethical technology design, the identification, analysis and resolving of ethical impacts of technologies and stakeholder participation. The results and discussion of our literature review are valuable for gaining an overview of the state of the art and serve as an outline of a future research agenda of methods for practising ethics in R&I.
