Three Pathways for Standardisation and Ethical Disclosure by Default under the European Union Artificial Intelligence Act

Laux, Johann; Wachter, Sandra; Mittelstadt, Brent

doi:10.2139/ssrn.4365079

Cited by 13 publications

(8 citation statements)

References 16 publications

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“…Therefore, researchers such as Laux et al. (2023b) predict that it will be hard to negotiate and find a consensus among different interest groups during the standardization process. They also point out that the above questions should be addressed by the Commission and Parliament (i.e., by institutions that can be held democratically accountable) and not pushed down the line to standard‐setting organizations, which are not democratically elected.…”

Section: Discussionmentioning

confidence: 99%

“…Lastly, the AIA does not provide for democratic input on developing technical standards crucial for implementing the proposed regulatory framework (Smuha et al, 2021). 28 Besides input legitimacy (i.e., a lack of stakeholder consultation), those processes might also lack throughput (i.e., a lack of accountable and transparent processes) and output legitimacy (i.e., a lack of standard responsiveness, e.g., with regard to interests of affected stakeholder groups) (Laux et al, 2023b). (Islam et al, 2023;Lim, 2023).…”

Section: 27mentioning

confidence: 99%

“…According toLaux et al (2023b), the AIA pursues a dual purpose: market-making and market regulation. That is, on the one hand, it attempts to create a functioning internal market for AI systems and provide legal certainty to facilitate investments and innovation; on the other hand, it attempts to ensure the safety and trustworthiness of AI systems and the conformity with fundamental rights and European values.…”

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confidence: 99%

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Mitigating the adverse effects of AI with the European Union's artificial intelligence act: Hype or hope?

Wörsdörfer

2023

Glob Bus Org Exc

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In light of the rise of generative AI and recent debates about the socio‐political implications of large‐language models, chatbots, and the like, this paper analyzes the E.U.’s Artificial Intelligence Act (AIA), the world's first comprehensive attempt by a government body to address and mitigate the potentially negative impacts of AI technologies. The paper critically analyzes the AIA from a business and computer ethics point of view—a perspective currently lacking in the academic (e.g., GBOE‐related) literature. It evaluates, in particular, the AIA's strengths and weaknesses and proposes reform measures that could help to strengthen the AIA. Among the AIA's strengths are its legally binding character, extra‐territoriality, ability to address data quality and discrimination risks, and institutional innovations such as the AI Board and publicly accessible logs and database for AI systems. Among its main weaknesses are its lack of effective enforcement, oversight, and control, absence of procedural rights and remedy mechanisms, inadequate worker protection, institutional ambiguities, insufficient funding and staffing, and inadequate consideration of sustainability issues. Reform suggestions include establishing independent conformity assessment procedures, strengthening democratic accountability and judicial oversight, introducing redress and complaint mechanisms, ensuring the participation and inclusion of workers, guaranteeing political independence of the AI Board, providing enhanced funding and staffing of market surveillance authorities, and mandating “green AI.”

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Section: Discussionmentioning

confidence: 99%

Section: 27mentioning

confidence: 99%

mentioning

confidence: 99%

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Mitigating the adverse effects of AI with the European Union's artificial intelligence act: Hype or hope?

Wörsdörfer

2023

Glob Bus Org Exc

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“…Written justifications of using AI and how to oversee the technology must, therefore, beware of creating illusions of normative certainty (cf. also: [Laux et. al 2023a].…”

Section: Six Design Principles For Human Oversightmentioning

confidence: 99%

Institutionalised Distrust and Human Oversight of Artificial Intelligence: Toward a Democratic Design of AI Governance under the European Union AI Act

Laux

2023

SSRN Journal

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“…Cf. also the definition of meaningful human oversight by Brennan-Marquez et al that tracks the debate around Article 22 GDPR (Brennan-Marquez et al 2019: 749).3 On the possible future pathways for standardisation, seeLaux et. al (2023a).4 Cf.…”

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confidence: 99%

Institutionalised distrust and human oversight of artificial intelligence: towards a democratic design of AI governance under the European Union AI Act

Laux

2023

AI & Soc

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Human oversight has become a key mechanism for the governance of artificial intelligence (“AI”). Human overseers are supposed to increase the accuracy and safety of AI systems, uphold human values, and build trust in the technology. Empirical research suggests, however, that humans are not reliable in fulfilling their oversight tasks. They may be lacking in competence or be harmfully incentivised. This creates a challenge for human oversight to be effective. In addressing this challenge, this article aims to make three contributions. First, it surveys the emerging laws of oversight, most importantly the European Union’s Artificial Intelligence Act (“AIA”). It will be shown that while the AIA is concerned with the competence of human overseers, it does not provide much guidance on how to achieve effective oversight and leaves oversight obligations for AI developers underdefined. Second, this article presents a novel taxonomy of human oversight roles, differentiated along whether human intervention is constitutive to, or corrective of a decision made or supported by an AI. The taxonomy allows to propose suggestions for improving effectiveness tailored to the type of oversight in question. Third, drawing on scholarship within democratic theory, this article formulates six normative principles which institutionalise distrust in human oversight of AI. The institutionalisation of distrust has historically been practised in democratic governance. Applied for the first time to AI governance, the principles anticipate the fallibility of human overseers and seek to mitigate them at the level of institutional design. They aim to directly increase the trustworthiness of human oversight and to indirectly inspire well-placed trust in AI governance.

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Three Pathways for Standardisation and Ethical Disclosure by Default under the European Union Artificial Intelligence Act

Cited by 13 publications

References 16 publications

Mitigating the adverse effects of AI with the European Union's artificial intelligence act: Hype or hope?

Mitigating the adverse effects of AI with the European Union's artificial intelligence act: Hype or hope?

Institutionalised Distrust and Human Oversight of Artificial Intelligence: Toward a Democratic Design of AI Governance under the European Union AI Act

Institutionalised distrust and human oversight of artificial intelligence: towards a democratic design of AI governance under the European Union AI Act

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