AI Governance: Digital Responsibility as a Building Block

Thelisson, Eva; Morin, Jean‐Henry; Rochel, Johan

doi:10.21552/delphi/2019/4/6

Cited by 6 publications

(7 citation statements)

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“…Important conceptual and technical work sheds light on foundational issues like algorithmic transparency, explainability, or safety, as well as on related aspects such as data governance or privacy [8][9][10][11]. Similarly, the ethical aspects and their implementation in code, as well as organizational governance, have received many valuable contributions [8,[12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Mapping global AI governance: a nascent regime in a fragmented landscape

Schmitt

2021

AI Ethics

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The rapid advances in the development and rollout of artificial intelligence (AI) technologies over the past years have triggered a frenzy of regulatory initiatives at various levels of government and the private sector. This article describes and evaluates the emerging global AI governance architecture and traces the contours of a nascent regime in a fragmented landscape. To do so, it organizes actors and initiatives in a two-by-two matrix, distinguishing between the nature of the driving actor(s) and whether or not their actions take place within the existing governance architecture. Based on this, it provides an overview of key actors and initiatives, highlighting their trajectories and connections. The analysis shows international organizations’ high levels of agency in addressing AI policy and a tendency to address new challenges within existing frameworks. Lastly, it is argued that we are witnessing the first signs of consolidation in this fragmented landscape. The nascent AI regime that emerges is polycentric and fragmented but gravitates around the Organisation for Economic Co-Operation and Development (OECD), which holds considerable epistemic authority and norm-setting power.

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Section: Introductionmentioning

confidence: 99%

Mapping global AI governance: a nascent regime in a fragmented landscape

Schmitt

2021

AI Ethics

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“…In the absence of adequate formal legal frameworks, selfregulation methods can be valuable for improving digital readiness. Thelisson, Morin, and Rochel [48] argue that "a Digital Responsibility Index" can play a central role in restoring trust in a data-driven economy and creating a virtuous circle, contributing to sustainable growth. Such indexes consider the interests of all stakeholders, including employees, customers, and the broader community and investors.…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence and consumer manipulations: from consumer's counter algorithms to firm's self-regulation tools

Marcellis-Warin

Marty

Thelisson³

et al. 2022

AI Ethics

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The growing use of artificial intelligence (A.I.) algorithms in businesses raises regulators' concerns about consumer protection. While pricing and recommendation algorithms have undeniable consumer-friendly effects, they can also be detrimental to them through, for instance, the implementation of dark patterns. These correspond to algorithms aiming to alter consumers' freedom of choice or manipulate their decisions. While the latter is hardly new, A.I. offers significant possibilities for enhancing them, altering consumers' freedom of choice and manipulating their decisions. Consumer protection comes up against several pitfalls. Sanctioning manipulation is even more difficult because the damage may be diffuse and not easy to detect. Symmetrically, both ex-ante regulation and requirements for algorithmic transparency may be insufficient, if not counterproductive. On the one hand, possible solutions can be found in counter-algorithms that consumers can use. On the other hand, in the development of a compliance logic and, more particularly, in tools that allow companies to self-assess the risks induced by their algorithms. Such an approach echoes the one developed in corporate social and environmental responsibility. This contribution shows how self-regulatory and compliance schemes used in these areas can inspire regulatory schemes for addressing the ethical risks of restricting and manipulating consumer choice.

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“…In line with a CSR pyramid, they constructed the CDR pyramid mode with four levels and illustrated how companies should shoulder different levels of digital responsibility. Likewise, Thelisson, Morin, and Rochel [10] and Wade [34] reckoned CDR as a kind of digital CSR. They mainly elaborated CDR issues in terms of security autonomy and privacy, respecting equality, dealing with data, dealing with algorithms, taking impact on the environment into account, and ensuring a fair transition.…”

Section: Corporate Digital Responsibilitymentioning

confidence: 99%

“…Since then, more and more scholars have studied the concept of CDR. For example, some studies argues that CDR is an extension of CSR [9,10]. In other words, CDR should be studied based on CSR.…”

Section: Introductionmentioning

confidence: 99%

“…Some scholars in information management/operations management fields have tended to illustrate corporate digital responsibilities through concrete forms of digitalization such as artificial intelligence, Machine learning, robotics, etc. [10,14,15]. These research streams focus on the corporate responsibility issues that occur in a specific digital technology scenario (e.g., online banking service, business digital transformation), and neglects the dynamic function of digital technology.…”

Section: Introductionmentioning

confidence: 99%

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Conceptualizing Corporate Digital Responsibility: A Digital Technology Development Perspective

Cheng

Zhang

2023

Sustainability

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Managers and scholars require an appropriate conceptualization, as well as reliable and valid measures of corporate digital responsibility (CDR), to better understand and tackle issues involving CDR. Therefore, by combining insights from extant research on corporate responsibility in the digital realm, this article proposes to distinguish CDR into corporate digitized responsibility and corporate digitalized responsibility. Specifically, corporate digitized responsibility includes unbiased data acquisition, data protection, and data maintenance; corporate digitalized responsibility involves appropriate data interpretation, objective predicted results and tackling value conflicts in data-driven decision-making. Moreover, we also provide a valid measurement for CDR, and the findings demonstrate that a positive relationship exists between CDR and corporate digital performance. Finally, this article offers some suggestions for managers on how to tackle CDR issues and utilize digital technologies in appropriate ways.

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AI Governance: Digital Responsibility as a Building Block

Cited by 6 publications

References 0 publications

Mapping global AI governance: a nascent regime in a fragmented landscape

Mapping global AI governance: a nascent regime in a fragmented landscape

Artificial intelligence and consumer manipulations: from consumer's counter algorithms to firm's self-regulation tools

Conceptualizing Corporate Digital Responsibility: A Digital Technology Development Perspective

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