JM
J.J.C. Maas
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1
Freedom in the Digital Age
Designing for Non-Domination
The effects of digital technologies on freedom and democracy have garnered increasing attention in recent years. Many have raised concerns about surveillance capitalism, technofeudalism, and general threats to constitutional democracies—with a special convergence on the worry that uncontrolled power of online platforms undermines people’s freedom. However, it remains unclear how ‘freedom’ should be understood, what the relation is between freedom and uncontrolled power, and to what extent these worries extend beyond online platforms. In this dissertation, I argue that these problems are best answered by appealing to a neo-republican account of freedom as non-domination, where ‘domination’ is understood as a condition of living under an agent’s uncontrolled power. In the context of AI systems used in core societal sectors such as healthcare, I show that domination of a system’s (in)direct end-users by the system’s developers occurs in at least three ways: (1) the distribution of decision-making power, (2) technical limitations of AI systems, and (3) underlying societal structures that empower developers and disempower end-users. To safeguard freedom in the digital age, I propose that AI development requires the explicit intention to 'design for non-domination'. This requires us to consider the broader societal contexts within which these systems operate, such as current regulatory initiatives and the political economy.
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The effects of digital technologies on freedom and democracy have garnered increasing attention in recent years. Many have raised concerns about surveillance capitalism, technofeudalism, and general threats to constitutional democracies—with a special convergence on the worry that uncontrolled power of online platforms undermines people’s freedom. However, it remains unclear how ‘freedom’ should be understood, what the relation is between freedom and uncontrolled power, and to what extent these worries extend beyond online platforms. In this dissertation, I argue that these problems are best answered by appealing to a neo-republican account of freedom as non-domination, where ‘domination’ is understood as a condition of living under an agent’s uncontrolled power. In the context of AI systems used in core societal sectors such as healthcare, I show that domination of a system’s (in)direct end-users by the system’s developers occurs in at least three ways: (1) the distribution of decision-making power, (2) technical limitations of AI systems, and (3) underlying societal structures that empower developers and disempower end-users. To safeguard freedom in the digital age, I propose that AI development requires the explicit intention to 'design for non-domination'. This requires us to consider the broader societal contexts within which these systems operate, such as current regulatory initiatives and the political economy.
Voting Advice Applications (VAAs) are interactive tools used to assist in one’s choice of a party or candidate to vote for in an upcoming election. They have the potential to increase citizens’ trust and participation in democratic structures. However, there is no established ground truth for one’s electoral choice, and VAA recommendations depend strongly on architectural and design choices. We assessed several representative European VAAs according to the Ethics Guidelines for Trustworthy AI provided by the European Commission using publicly available information. We found scores to be comparable across VAAs and low in most requirements, with differences reflecting the kind of developing institution. Across VAAs, we identify the need for improvement in (i) transparency regarding the subjectivity of recommendations, (ii) diversity of stakeholder participation, (iii) user-centric documentation of algorithm, and (iv) disclosure of the underlying values and assumptions.
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Voting Advice Applications (VAAs) are interactive tools used to assist in one’s choice of a party or candidate to vote for in an upcoming election. They have the potential to increase citizens’ trust and participation in democratic structures. However, there is no established ground truth for one’s electoral choice, and VAA recommendations depend strongly on architectural and design choices. We assessed several representative European VAAs according to the Ethics Guidelines for Trustworthy AI provided by the European Commission using publicly available information. We found scores to be comparable across VAAs and low in most requirements, with differences reflecting the kind of developing institution. Across VAAs, we identify the need for improvement in (i) transparency regarding the subjectivity of recommendations, (ii) diversity of stakeholder participation, (iii) user-centric documentation of algorithm, and (iv) disclosure of the underlying values and assumptions.
New technologies are the source of uncertainties about the applicability of moral and morally connotated concepts. These uncertainties sometimes call for conceptual engineering, but it is not often recognized when this is the case. We take this to be a missed opportunity, as a recognition that different researchers are working on the same kind of project can help solve methodological questions that one is likely to encounter. In this paper, we present three case studies where philosophers of technology implicitly engage in conceptual engineering (without naming it as such). We subsequently reflect on the case studies to find out how these illustrate conceptual engineering as an appropriate method to deal with pressing concerns in the philosophy of technology. We have two main goals. We first want to contribute to the literature on conceptual engineering by presenting concrete examples of conceptual engineering in the philosophy of technology. This is especially relevant, because the technologies that are designed based on the conceptual work done by philosophers of technology potentially have crucial moral and social implications. Secondly, we want to make explicit what choices are made when doing this conceptual work. Making explicit that some of the implicit assumptions are, in fact, debated in the literature allows for reflection on these questions. Ultimately, our hope is that conscious reflection leads to an improvement of the conceptual work done.
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New technologies are the source of uncertainties about the applicability of moral and morally connotated concepts. These uncertainties sometimes call for conceptual engineering, but it is not often recognized when this is the case. We take this to be a missed opportunity, as a recognition that different researchers are working on the same kind of project can help solve methodological questions that one is likely to encounter. In this paper, we present three case studies where philosophers of technology implicitly engage in conceptual engineering (without naming it as such). We subsequently reflect on the case studies to find out how these illustrate conceptual engineering as an appropriate method to deal with pressing concerns in the philosophy of technology. We have two main goals. We first want to contribute to the literature on conceptual engineering by presenting concrete examples of conceptual engineering in the philosophy of technology. This is especially relevant, because the technologies that are designed based on the conceptual work done by philosophers of technology potentially have crucial moral and social implications. Secondly, we want to make explicit what choices are made when doing this conceptual work. Making explicit that some of the implicit assumptions are, in fact, debated in the literature allows for reflection on these questions. Ultimately, our hope is that conscious reflection leads to an improvement of the conceptual work done.
Correction to
Technology as Driver for Morally Motivated Conceptual Engineering (Philosophy & Technology, (2022), 35, 3, (71), 10.1007/s13347-022-00565-9)
The original version of this article unfortunately contained mistake. At the end of the reference list, on the last page, the added data has been removed. In footnote 11, we have enclosed parenthesis the reference (O’Shea 2018). The original article has been corrected.
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The original version of this article unfortunately contained mistake. At the end of the reference list, on the last page, the added data has been removed. In footnote 11, we have enclosed parenthesis the reference (O’Shea 2018). The original article has been corrected.
There has been an increased focus within the AI ethics literature on questions of power, reflected in the ideal of accountability supported by many Responsible AI guidelines. While this recent debate points towards the power asymmetry between those who shape AI systems and those affected by them, the literature lacks normative grounding and misses conceptual clarity on how these power dynamics take shape. In this paper, I develop a workable conceptualization of said power dynamics according to Cristiano Castelfranchi’s conceptual framework of power and argue that end-users depend on a system’s developers and users, because end-users rely on these systems to satisfy their goals, constituting a power asymmetry between developers, users and end-users. I ground my analysis in the neo-republican moral wrong of domination, drawing attention to legitimacy concerns of the power-dependence relation following from the current lack of accountability mechanisms. I illustrate my claims on the basis of a risk-prediction machine learning system, and propose institutional (external auditing) and project-specific solutions (increase contestability through design-for-values approaches) to mitigate domination.
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There has been an increased focus within the AI ethics literature on questions of power, reflected in the ideal of accountability supported by many Responsible AI guidelines. While this recent debate points towards the power asymmetry between those who shape AI systems and those affected by them, the literature lacks normative grounding and misses conceptual clarity on how these power dynamics take shape. In this paper, I develop a workable conceptualization of said power dynamics according to Cristiano Castelfranchi’s conceptual framework of power and argue that end-users depend on a system’s developers and users, because end-users rely on these systems to satisfy their goals, constituting a power asymmetry between developers, users and end-users. I ground my analysis in the neo-republican moral wrong of domination, drawing attention to legitimacy concerns of the power-dependence relation following from the current lack of accountability mechanisms. I illustrate my claims on the basis of a risk-prediction machine learning system, and propose institutional (external auditing) and project-specific solutions (increase contestability through design-for-values approaches) to mitigate domination.