Browsing by Author "Kirichenko, Alexey"

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Artificial intelligence for human flourishing – Beyond principles for machine learning
    (Elsevier, 2021) Stahl, Bernd Carsten, 1968-; Andreou, Andreas; Brey, Philip; Hatzakis, Tally; Kirichenko, Alexey; Macnish, Kevin; Laulhe Shaelou, Stephanie; Patel, Andrew; Ryan, Mark; Wright, David
    The technical and economic benefits of artificial intelligence (AI) are counterbalanced by legal, social and ethical issues. It is challenging to conceptually capture and empirically measure both benefits and downsides. We therefore provide an account of the findings and implications of a multi-dimensional study of AI, comprising 10 case studies, five scenarios, an ethical impact analysis of AI, a human rights analysis of AI and a technical analysis of known and potential threats and vulnerabilities. Based on our findings, we separate AI ethics discourse into three streams: (1) specific issues related to the application of machine learning, (2) social and political questions arising in a digitally enabled society and (3) metaphysical questions about the nature of reality and humanity. Human rights principles and legislation have a key role to play in addressing the ethics of AI. This work helps to steer AI to contribute to human flourishing.
  • Thumbnail Image
    ItemOpen Access
    A systematic review of artifcial intelligence impact assessments
    (Springer, 2023-03-24) Stahl, Bernd; Antoniou, Josephina; Bhalla, Nitika; Brooks, Laurence; Jansen, Philip; Lindqvist, Blerta; Kirichenko, Alexey; Marchal, Samuel; Rodrigues, Rowena; Warso, Zuzanna; Wright, David; Santiago, Nicole
    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.