Kimon Kieslich promoviert erfolgreich über "The role of public opinion on ethical AI principles and its implication for a common good-oriented implementation"  [01.05.24]

Gutachter

Erstgutachter: Prof. Dr. Jens Vogelgesang

Zweitgutachter: Prof. Dr. Marc Ziegele (HHU Düsseldoff)

Vorsitzender der mündlichen Prüfung: Prof. Dr. Robert Jung

Abstract

Artificial Intelligence (AI) has a tremendous impact on society. While artificial intelligence encompasses a variety of different systems, algorithmic decision-making (ADM) systems in particular are being used to augment or even replace human decision-making. Because ADM systems are susceptible to ethical ramifications, such as fairness issues, opacity, and lack of accountability, how to manage the implementation of ADM is a societal challenge. This is particularly relevant when ADM is used in high impact situations that can potentially affect every member of society, such as in the public sector.

As a way to address the harms of ADM, ethical guidelines have been proposed by companies and policy makers. However, scholars argue that these guidelines lack reinforcement mechanisms and that additional incentives are needed for decision makers to actually invest in ethical systems. In my dissertation, I focus on one potential factor that could contribute to the development of ADM in the public interest or for the common good, respectively – public opinion. Critical public discussions about whether and how society wants ADM to make decisions can put pressure on decision makers to actually develop and implement ADM systems that adhere to ethical standards. The public does this by articulating (political) demands and by legitimizing or critiquing current practices. My research is situated within normative theories of the political public sphere, which propose different approaches for public discourse in the formation of democratic will, as well as the Society in the Loop framework, which emphasizes the need to include citizens’ perceptions in decision-making about ethical trade-offs in the design and implementation of AI systems. This cumulative dissertation consists of four peer-reviewed papers:

Paper 1 critically discusses at a theoretical level the role of public opinion as an influential factor in technology adoption. It argues that given the serious implications that the emergence of AI could have on society, public opinion can be a crucial incentive for both technological and political decision-makers to invest in AI for the common good. However, the paper also acknowledges and discusses the limits of public influence, and outlines potential avenues for greater inclusion of the public voice. Paper 2 presents data from a large-scale survey on public opinion on AI in Germany. In particular, it examines 1) what citizens have in mind when thinking about AI, 2) what role ethical AI issues play in this regard, 3) which demographic and AI-related factors contribute to a higher salience of (ethical) AI issues, and 4) what consequences the salience of ethical AI issues has in terms of AI avoidance and engagement in public discussions about AI. The paper’s main contribution is to provide an empirical database on the engagement of German citizens with AI, thus helping to assess citizen inuence on technological and political decision makers. Paper 3 empirically examines citizens’ perceptions of the ethical trade-os that must be made in the design process of AI systems. It uses a use case of AI in the public sector which, from the normative standpoint of AI development for the common good, requires citizen participation. Paper 3 provides insights into 1) citizens’ ethical preferences for the design of AI systems, 2) shows that there are different publics with different preferences, and 3) describes how these publics are constituted in terms of demographic as well as AI-related factors. The paper’s main contributions are to propose a measurement for evaluating ethical AI principles and to describe different preference patterns of the German public. Paper 4 delves deeper into the topic of the consequences of (non-)compliance with ethical design of AI systems. Again, the paper presents a use case of AI in the public sector and discusses the role of trust in AI as influential factor leading to the legitimization of AI technology. The main contribution of the empirical paper is to elaborate on the role of trust in AI, as it is treated as a major factor in empirical research and policy discussion in light of a widespread implementation of AI.

In summary, my dissertation contributes to the literature on public opinion research, the Society in the Loop framework, and the efforts of the FAccT (Fairness, Accountability and Transparency) community, and specifically discusses the role of the public as a potential critical voice in the design and implementation process of AI systems. On a methodological level, I propose a measure for exploring the preference for trade-offs in ADM systems. On an empirical level, I provide a rich empirical (baseline) data on citizens’ perceptions of ADM on which future studies can build. On a theoretical level, I discuss my findings in terms of normative theories about the role of the public and the Society in the Loop framework. On a practical level, I address the interplay between public opinion and the economic, media, educational, and political & legal sectors, and I elaborate on future steps that can be taken to strengthen the common good orientation in the development and implementation of AI systems.

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