Amid the rapidly evolving landscape of artificial intelligence (AI) regulation, a significant concern has emerged regarding the predominant focus on preemptive measures aimed at preventing or mitigating potential AI-related harms. While these preemptive measures are undeniably important, they must be complemented by effective redress mechanisms to address and remedy materialized harms. This paper highlights the crucial role of redress in empowering individuals to challenge and rectify the adverse effects of AI systems, emphasizing that access to redress is, in fact, access to justice. We critically evaluate whether current AI governance sufficiently address the need for remedies for AI-related harms, arguing that they fall short in protecting individuals’ rights. To address this gap, we outline four key steps in the redress process: (1) initiating the redress process, (2) determining appropriate avenues for redress, (3) collecting evidence to support claims and (4) receiving and responding to decisions. Each step is explored in detail, presenting distinct challenges and requirements, illustrated with real-world examples. Our findings underscore the urgent need to integrate robust redress pathways into AI governance frameworks to safeguard individual rights as AI technologies become increasingly embedded in society.

This article focuses on the G7’s Hiroshima AI Process (HAIP) and its flagship document, the Hiroshima Code of Conduct, as pivotal elements in shaping global artificial intelligence (AI) governance. By conducting a comprehensive analysis of AI regulations in G7 member states, the article demonstrates a high degree of interoperability between these national frameworks and the Code of Conduct’s principles. The article proposes concrete steps to translate these principles into actionable policies at the G7 level and develops strategic adjustments to incorporate them into national standards. The article then proposes enhancements to the Code of Conduct, including the development of a common AI governance vocabulary, robust risk management frameworks, life cycle standards harmonization, effective stakeholder engagement mechanisms, specific redress mechanisms for AI harms and guidelines for government AI use to ensure democratic principles and human rights are upheld. Ultimately, this research aims to strengthen the G7’s role in leading a global AI landscape characterized by the rule of law, democracy, and human rights.

This paper provides an outline analysis of the evolving governance framework for artificial intelligence (AI) in Singapore. Across the Singapore government, AI solutions are being adopted in line with Singapore’s “Smart Nation Initiative” to leverage technology to make impactful changes across society and the economy. In tandem, Singaporean authorities have been assiduous to release a growing number of governance documents, which we analyse together to chart the city-state’s approach to AI governance in international comparison. The characteristics of Singapore’s AI governance approach include an emphasis on consensus-building between stakeholders (particularly government and industry but also citizens) and voluntary or “quasi” regulation, lately with an emphasis on promulgating standards (AI Standards, n.d.) and audit-like frameworks. Singaporean regulators have also been early movers (globally, and especially in the region) in the promulgation of normative instruments on AI governance including developing the world’s first AI Governance Testing Framework and Toolkit, AI Verify. The Singapore approach may be compelling for other jurisdictions in the region and around the world with an interest in a collaborative, balanced and consensual approach to governing AI outside of strict regulatory mechanisms. However, any jurisdiction adopting aspects of its evolving model would have to duly account for relevant differences in social and institutional conditions.

This commentary explores MENA”s AI governance, addressing gaps, showcasing successful strategies, and comparing national approaches. It emphasizes current deficiencies, highlights regional contributions to global AI governance, and offers insights into effective frameworks. The study reveals distinctions and trends in MENA”s national AI strategies, serving as a concise resource for policymakers and industry stakeholders.

This analysis provides a critical account of AI governance in the modern “smart city” through a feminist lens. Evaluating the case of Sidewalk Labs’ Quayside project—a smart city development that was to be implemented in Toronto, Canada—it is argued that public–private partnerships can create harmful impacts when corporate actors seek to establish new “rules of the game” regarding data regulation. While the Quayside project was eventually abandoned in 2020, it demonstrates key observations for the state of urban algorithmic governance both within Canada and internationally. Articulating the need for a revitalised and participatory smart city governance programme prioritizes meaningful engagement in the forms of transparency and accountability measures. Taking a feminist lens, it argues for a two-pronged approach to governance: integrating collective engagement from the outset in the design process and ensuring the civilian data protection through a robust yet localized rights-based privacy regulation strategy. Engaging with feminist theories of intersectionality in relation to technology and data collection, this framework articulates the need to understand the broader histories of social marginalization when implementing governance strategies regarding artificial intelligence in cities.

Ethical guidelines and policy documents destined to guide AI innovations have been heralded as the solution to guard us against harmful effects or to increase public value. However, these guidelines and policy documents face persistent challenges. While these documents are often criticized for their abstraction and disconnection from real-world contexts, it also occurs that stakeholders may influence them for political or strategic reasons. While this last issue is frequently acknowledged, there is seldom a means or a method provided to explore it. To address this gap, the paper employs a combination of social constructivism and science & technology studies perspectives, along with desk research, to investigate whether prior research has examined the influence of stakeholder interests, strategies, or agendas on guidelines and policy documents. The study contributes to the discourse on AI governance by proposing a theoretical framework and methodologies to better analyze this underexplored area, aiming to enhance comprehension of the policymaking process within the rapidly evolving AI landscape. The findings underscore the need for a critical evaluation of the methodologies found and a further exploration of their utility. In addition, the results aim to stimulate ongoing critical debates on this subject.

Responsible innovation in artificial intelligence (AI) calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitutes a challenge, however, due to the opacity of AI and strong knowledge boundaries between experts and citizens. This undermines trust in AI and undercuts key conditions for deliberation. We approach this challenge as a problem of situating the knowledge of actors from the AI industry within a deliberative system. We develop a new framework of responsibilities for AI innovation as well as a deliberative governance approach for enacting these responsibilities. In elucidating this approach, we show how actors from the AI industry can most effectively engage with experts and nonexperts in different social venues to facilitate well-informed judgments on opaque AI systems and thus effectuate their democratic governance.

This article uses a socio-legal perspective to analyze the use of ethics guidelines as a governance tool in the development and use of artificial intelligence (AI). This has become a central policy area in several large jurisdictions, including China and Japan, as well as the EU, focused on here. Particular emphasis in this article is placed on the Ethics Guidelines for Trustworthy AI published by the EU Commission’s High-Level Expert Group on Artificial Intelligence in April 2019, as well as the White Paper on AI, published by the EU Commission in February 2020. The guidelines are reflected against partially overlapping and already-existing legislation as well as the ephemeral concept construct surrounding AI as such. The article concludes by pointing to (1) the challenges of a temporal discrepancy between technological and legal change, (2) the need for moving from principle to process in the governance of AI, and (3) the multidisciplinary needs in the study of contemporary applications of data-dependent AI.