Browsing by Author "Macnish, Kevin"

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    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.
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    The Ethical Balance of Using Smart Information Systems for Promoting the United Nations’ Sustainable Development Goals
    (MDPI, 2020-06-12) Ryan, Mark; Antoniou, Josephina; Brooks, L.; Jiya, Tilimbe; Macnish, Kevin; Stahl, Bernd Carsten, 1968-
    The Sustainable Development Goals (SDGs) are internationally agreed goals that allow us to determine what humanity, as represented by 193 member states, finds acceptable and desirable. The paper explores how technology can be used to address the SDGs and in particular Smart Information Systems (SIS). SIS, the technologies that build on big data analytics, typically facilitated by AI techniques such as machine learning, are expected to grow in importance and impact. Some of these impacts are likely to be beneficial, notably the growth in efficiency and profits, which will contribute to societal wellbeing. At the same time, there are significant ethical concerns about the consequences of algorithmic biases, job loss, power asymmetries and surveillance, as a result of SIS use. SIS have the potential to exacerbate inequality and further entrench the market dominance of big tech companies, if left uncontrolled. Measuring the impact of SIS on SDGs thus provides a way of assessing whether an SIS or an application of such a technology is acceptable in terms of balancing foreseeable benefits and harms. One possible approach is to use the SDGs as guidelines to determine the ethical nature of SIS implementation. While the idea of using SDGs as a yardstick to measure the acceptability of emerging technologies is conceptually strong, there should be empirical evidence to support such approaches. The paper describes the findings of a set of 6 case studies of SIS across a broad range of application areas, such as smart cities, agriculture, finance, insurance and logistics, explicitly focusing on ethical issues that SIS commonly raise and empirical insights from organisations using these technologies.
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    Organisational Responses to the Ethical Issues of Artificial Intelligence.
    (Springer, 2021) Stahl, Bernd Carsten, 1968-; Antoniou, Josephine; Ryan, Mark; Macnish, Kevin; Jiya, Tilimbe
    The ethics of artificial intelligence (AI) is a widely discussed topic. There are numerous initiatives that aim to develop principles and guidance to ensure that the development, deployment and use of AI are ethically acceptable. What is generally unclear is how organisations that make use of AI understand and address these ethical issues in practice. While there is an abundance of conceptual work on AI ethics, empirical insights are rare and often anecdotal. This paper fills the gap in our current understanding of how organisations deal with AI ethics by presenting empirical findings collected using a set of 10 case studies and providing an account of the cross-case analysis. The paper reviews the discussion of ethical issues of AI as well as mitigation strategies that have been proposed in the literature. Using this background, the cross-case analysis categorises the organisational responses that were observed in practice. The discussion shows that organisations are highly aware of the AI ethics debate and keen to engage with ethical issues proactively. However, they make use of only a relatively small subsection of the mitigation strategies proposed in the literature. These insights are of importance to organisations deploying or using AI, to the academic AI ethics debate, but maybe most valuable to policymakers involved in the current debate about suitable policy developments to address the ethical issues raised by AI.
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    Research and Practice of AI Ethics: A case study approach juxtaposing academic discourse with organisational reality
    (Springer, 2021) Ryan, Mark; Antoniou, Josephina; Brooks, Laurence; Jiya, Tilimbe; Macnish, Kevin; Stahl, Bernd Carsten, 1968-
    This study investigates the ethical use of Big Data and Artificial Intelligence (AI) technologies (BD+AI) - using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues, (from the literature), into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety of different social domains, fields, and applications of AI , there is overlap and correlation between the organisations’ ethical concerns. This more detailed understanding of ethics in AI+BD is required to ensure that the multitude of suggested ways of addressing them can be targeted and succeed in mitigating the pertinent ethical issues that are often discussed in the literature.
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    Technofixing the Future: Ethical Side Effects of Using AI and Big Data to meet the SDGs
    (IEEE SmartWorld, 2019-08) Ryan, Mark; Antoniou, Josephina; Jiya, Tilimbe; Macnish, Kevin; Brooks, L.; Stahl, Bernd Carsten, 1968-
    While the use of smart information systems (the combination of AI and Big Data) offer great potential for meeting many of the UN’s Sustainable Development Goals (SDGs), they also raise a number of ethical challenges in their implementation. Through the use of six empirical case studies, this paper will examine potential ethical issues relating to use of SIS to meet the challenges in six of the SDGs (2, 3, 7, 8, 11, and 12). The paper will show that often a simple “technofix”, such as through the use of SIS, is not sufficient and may exacerbate, or create new, issues for the development community using SIS.