The ethics of algorithms: key problems and solutions

Tsamados, Andreas; Aggarwal, Nikita; Cowls, Josh; Morley, Jessica; Roberts, Huw; Taddeo, Mariarosaria; Floridi, Luciano

doi:10.1007/s00146-021-01154-8

Cited by 188 publications

(151 citation statements)

References 122 publications

(168 reference statements)

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“…This is problematic, not least because it could shield these companies from stricter governance requirements of the sort we identify here. This, in turn, could ultimately threaten fundamental EU values, with examples of technology companies already undermining workers' rights, including gig economy companies threatening the ability to collectively bargain (Tan et al, 2020;Tassinari & Maccarrone, 2020), and algorithmic bias leading to discriminatory outcomes (Tsamados et al, 2021).…”

Section: Legitimacymentioning

confidence: 99%

Safeguarding European values with digital sovereignty: an analysis of statements and policies

Roberts¹,

Cowls²,

Casolari³

et al. 2021

Internet Policy Review

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The European Union (EU) has, with increasing frequency, outlined an intention to strengthen its "digital sovereignty" as a basis for safeguarding European values in the digital age. Yet, uncertainty remains as to how the term should be defined, undermining efforts to assess the success of the EU's digital sovereignty agenda. The task of this paper is to reduce this uncertainty by i) analysing how digital sovereignty has been discussed by EU institutional actors and placing this in a wider conceptual framework, ii) mapping specific policy areas and measures that EU institutional actors cite as important for strengthening digital sovereignty, iii) assessing the effectiveness of current policy measures at strengthening digital sovereignty, and iv) proposing policy solutions that go above and beyond current measures and address existing gaps. To do this, we introduce a conceptual understanding of digital sovereignty and then empirically ground this within the specific EU context via an analysis of a corpus of 180 EU webpages that have mentioned the term "digital sovereignty" within the past year. We find that existing policies, in particular those pertaining to data governance, help to achieve some of the EU's specific aims in regard to digital sovereignty, such as conditioning outward data flows, but they are more limited concerning other aims, like advancing the EU's competitiveness and regulating the private sector. This is problematic insofar as it constrains the EU's ability to safeguard and promote its values. The policy solutions we propose represent steps towards the further strengthening of the EU's digital sovereignty and firmer protection of EU values. This paper is part of Governing "European values" inside data flows, a special issue of Internet Policy Review

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Section: Legitimacymentioning

confidence: 99%

Safeguarding European values with digital sovereignty: an analysis of statements and policies

Roberts¹,

Cowls²,

Casolari³

et al. 2021

Internet Policy Review

Self Cite

View full text Add to dashboard Cite

show abstract

“…A similar point has also been made by Thomas Malone, when he suggests that "we should move away from thinking about putting humans in the loop to putting computers in the group" [40]. The above mentioned problems may also be potentially harmful from the point of view of the human-AI fit, because they may trigger negative dynamics such as complacency, deskilling and avoidance of responsibility [8,17,23,66].…”

Section: Introductionmentioning

confidence: 78%

“…We are not the first ones to point out the risks of agential AI in human assemblies [9,17,66,74]. In this paper, however, our aim is to clarify the concept of agential AI as the main source of harm, a point also raised by Shneiderman and Wiens [59,70].…”

Section: From Intelligent Agents To Functions For Human Knowledgementioning

confidence: 98%

The need to move away from agential-AI: Empirical investigations, useful concepts and open issues

Cabitza

Campagner

Simone

2021

International Journal of Human-Computer Studies

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We propose a novel approach to human interaction with artificial intelligence systems (HAII), alternative to the mainstream dyadic one where humans and AI are seen as interacting agents. Through two quantitative experiments and two qualitative in-field case studies, we show that the mainstream HAII paradigm presents potentially harmful design shortcomings as it can trigger negative dynamics such as automation bias and prejudices. Our proposal, on the other hand, is grounded in the Computer-Supported Cooperative Work literature, in which AI can be conceived as a component of a Knowledge Artifact (KA). This consists of an ecosystem of knowledge creation tools whose goal is to support a Ba (after Nonaka), i.e. a collective of competent decision makers. We highlight the cooperative nature of decision making and the AI functionalities that a KA should embed. These include eXplainable AI solutions, aimed at facilitating appropriation, but also functionalities that enable reasoning in a collaborative setting. Finally, we discuss how moving intelligence and agency from individual agents to the human collective can help to mitigate the shortcomings of dyadic HAII (e.g., deskilling), re-distribute responsibility in critical tasks, and revisit the HAII research agenda to align it with the needs of increasingly wide, heterogeneous and complex teams.

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“…Furthermore, the processing of data into real-time representations and predictions raises questions with regard to the transparency, explicability, and fairness of algorithms that compile these representations, and to what extent people can, will, and should trust the software and those designing and distributing it (see, e.g. Wong, 2020;von Eschenbach, 2021;Tsamados et al, 2021). Moreover, when data relates to people, even if indirectly, the data can impact their privacy and establish power relationships based on a knowledge imbalance (see, e.g.…”

Section: Techno-industrial Tendenciesmentioning

confidence: 99%

Steering Representations—Towards a Critical Understanding of Digital Twins

2021

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Digital Twins are conceptualised in the academic technical discourse as real-time realistic digital representations of physical entities. Originating from product engineering, the Digital Twin quickly advanced into other fields, including the life sciences and earth sciences. Digital Twins are seen by the tech sector as the new promising tool for efficiency and optimisation, while governmental agencies see it as a fruitful means for improving decision-making to meet sustainability goals. A striking example of the latter is the European Commission who wishes to delegate a significant role to Digital Twins in addressing climate change and supporting Green Deal policy. As Digital Twins give rise to high expectations, ambitions, and are being entrusted important societal roles, it is crucial to critically reflect on the nature of Digital Twins. In this article, we therefore philosophically reflect on Digital Twins by critically analysing dominant conceptualisations, the assumptions underlying them, and their normative implications. We dissect the concept and argue that a Digital Twin does not merely fulfil the role of being a representation, but is in fact a steering technique used to direct a physical entity towards certain goals by means of multiple representations. Currently, this steering seems mainly fuelled by a reductionist approach focused on efficiency and optimisation. However, this is not the only direction from which a Digital Twin can be thought and, consequently, designed and deployed. We therefore set an agenda based on a critical understanding of Digital Twins that helps to draw out their beneficial potential, while addressing their potential issues.

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The ethics of algorithms: key problems and solutions

Cited by 188 publications

References 122 publications

Safeguarding European values with digital sovereignty: an analysis of statements and policies

Safeguarding European values with digital sovereignty: an analysis of statements and policies

The need to move away from agential-AI: Empirical investigations, useful concepts and open issues

Steering Representations—Towards a Critical Understanding of Digital Twins

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