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Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives

The aim of this position paper is to identify a specific focus and the major challenges related to the human-centered artificial intelligence (HCAI) approach in the field of Industry 5.0 and the circular economy. A first step towards the opening of a line of research is necessary to aggregate multidisciplinary and interdisciplinary skills to promote and take into consideration the different aspects related to this topic, from the more technical and engineering aspects to the social ones and the repercussions in…

Sustainability · Policy

Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives

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From pilots to decision systems: embedding generative AI into strategic decision-making through a socio-technical and governance lens

Generative AI (GAI) promises superior analytics and agility in strategy work, yet organisations struggle to move beyond pilots towards routinised decision inputs. This study investigates how GAI becomes embedded in strategic decision-making (SDM) through a qualitative single-case analysis of a global multi-brand group, based on 27 semi-structured executive interviews triangulated with internal documents and industry reports. Structured inductive coding yields a process model identifying enablers, leadership-driv…

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Regulating AI-powered consumer contracts: risks, remedies, and global legal responses|Regolamentazione dei contratti dei consumatori basati sull’Intelligenza Artificiale: rischi, rimedi e risposte giuridiche globali

Artificial Intelligence (AI) has reshaped consumer contracts by enabling automated drafting, personalization, and enforcement at scale, with limited human intervention. While this increases efficiency, it also introduces risks, including bias, opacity, privacy violations, and power asymmetries. This article offers a comparative legal analysis of regulatory responses and case studies, focusing on the EU AI Act and contrasting it with approaches in the US, Canada, Brazil, and emerging frameworks in Asia-Pacific. T…

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The EU's AI act: A framework for collaborative governance

In February 2024, the Council and the European Parliament (EP) agreed on the Artificial Intelligence Regulation (usually known as AI Act, AIA) .2 This regulation evaluates AI applications to ensure they are used ethically and responsibly, promoting the development of safe and lawful AI across the EU's single market. It establishes a comprehensive legal framework with a risk-based approach, aiming to achieve a balance between protecting the health, safety, and fundamental rights of European citizens and ensuring…

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Advances in artificial intelligence: a review for the creative industries

Artificial intelligence (AI) has undergone transformative advances since 2022, particularly through generative AI, large language models (LLMs), and diffusion models, fundamentally reshaping the creative industries. However, existing reviews have not comprehensively addressed these recent breakthroughs and their integrated impact across the creative production pipeline. This paper addresses this gap by providing a systematic review of AI technologies that have emerged or matured since our 2022 review, examining…

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Artificial intelligence and its ‘slow violence’ to human rights

Abstract Human rights concerns in relation to the impacts brought forth by artificial intelligence (‘AI’) have revolved around examining how it affects specific rights, such as the right to privacy, non-discrimination and freedom of expression. However, this article argues that the effects go deeper, potentially challenging the foundational assumptions of key concepts and normative justifications of the human rights framework. To unpack this, the article applies the lens of ‘slow violence’, a term borrowed from…

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Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective

This paper conducts a systematic review and interdisciplinary analysis of the ethical challenges of generative AI technologies (N = 37), highlighting significant concerns such as privacy, data protection, copyright infringement, misinformation, biases, and societal inequalities. The ability of generative AI to produce convincing deepfakes and synthetic media, which threaten the foundations of truth, trust, and democratic values, exacerbates these problems. The paper combines perspectives from various disciplines…

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AI-driven corporate governance: a regulatory perspective

The use of AI-driven or AI-assisted systems in corporate compliance is a novel topic in the business and management literature, only marginally considered by legal academia. While some scholarly pieces have explored the use of artificial intelligence (AI) systems to support compliance in the financial sector (eg, for anti-money laundering purposes), the legal implications of deploying AI systems to fulfil corporate compliance tasks has not yet received the attention it deserves. This article approaches the use o…

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AI-driven corporate governance: a regulatory perspective

Two peas in two pods? Comparing Sweden and Singapore’s lifelong learning policy and practice response to AI skills demands

Singapore and Sweden invest substantial resources in upskilling their citizens for a digital transition fuelled by advanced technologies such as artificial intelligence (AI). There, the digital transition faces skills shortages and mismatches, leading to increased pressure on lifelong learning (LLL) systems to address these shortages. In this comparative case study, we examine how respective LLL policies and practices address the demands for basic and advanced AI skills. Comparisons are discussed on three levels…

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Decent deepfakes? Professional deepfake developers’ ethical considerations and their governance potential

Abstract Policymakers and societies are grappling with the question of how to respond to deepfakes, i.e., synthetic audio-visual media which is proliferating in all areas of digital life– from politics to pornography. However, debates and research on deepfakes’ impact and governance largely neglect the technology’s sources, namely the developers of the underlying artificial intelligence (AI), and those who provide code or deepfake creation services to others, making the technology widely accessible. These actors…

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Decent deepfakes? Professional deepfake developers’ ethical considerations and their governance potential

Bridging the gap: Towards an expanded toolkit for AI-driven decision-making in the public sector

AI-driven decision-making systems are becoming instrumental in the public sector, with applications spanning areas like criminal justice, social welfare, financial fraud detection, and public health. While these systems offer great potential benefits to institutional decision-making processes, such as improved efficiency and reliability, these systems face the challenge of aligning machine learning (ML) models with the complex realities of public sector decision-making. In this paper, we examine five key challen…

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Elon Musk’s xAI sues Colorado over new rules for artificial intelligence

Elon Musk’s artificial intelligence company, xAI, has filed a lawsuit against the state of Colorado over a new AI law set to take effect in June. The suit seeks to block the state from enforcing the law, which would impose new requirements on AI systems to protect state residents from “algorithmic discrimination” in sectors such as education, employment, healthcare, housing and financial services. Colorado was the first state to pass a comprehensive bill to regulate AI. The company claims the law infringes on it…

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Elon Musk’s xAI sues Colorado over new rules for artificial intelligence

Revisiting the <i>Six Human-Centered Artificial Intelligence Grand Challenges</i> in the Age of Generative AI

Generative AI (GenAI) has shifted AI capabilities from discriminative prediction to creative interaction, offering opportunities to augment productivity and innovation. However, realizing these benefits requires navigating risks where development outpaces governance. This article revisits the Six Human-Centered AI (HCAI) Grand Challenges to analyze their relevance in the generative era. Critical new requirements are identified: preserving human autonomy, ensuring operational safety against non-deterministic outp…

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Co-designing AI systems with value-sensitive citizen science

Abstract As AI systems increasingly influence everyday life, integrating diverse community values is both ethically essential and practically urgent. This paper presents Value-Sensitive Citizen Science (VSCS)—a systematic framework that combines Value-Sensitive Design (VSD) with citizen science to support meaningful public participation in AI development. VSCS addresses gaps in the existing approaches by integrating culturally grounded methods and cognitive scaffolding through the Participatory Value-Cognition T…

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A framework for developing university policies on generative AI governance: a cross-national comparative study

As generative AI (GAI) becomes increasingly embedded in higher education, universities worldwide are developing policies to govern its ethical, pedagogical, and institutional use. However, these policies vary across national and institutional contexts. We undertake a cross-national analysis of GAI guidelines issued by leading universities in the United States, Japan, and China, identifying key policy orientations and proposing a structured framework to support policy development. Using an extended Technology Acc…

Policy

A framework for developing university policies on generative AI governance: a cross-national comparative study