Ethical AI and Data Protection in the Era of Industry 5.0

Ethical Governance of AI-Driven Information Security: Balancing Data Privacy, Cyber Resilience, and Digital Trust in Organizations

Cyber threats represent a critical risk to global organisations, with cybercrime damages projected to exceed USD 10.5 trillion annually by 2025. Consequently, enterprises are rapidly adopting Artificial Intelligence (AI) to augment their security architectures, as traditional, rule based Security Information Systems (SIS) struggle to mitigate sophisticated, multi stage attacks. However, the application of AI in security raises significant ethical questions around data privacy, algorithmic transparency, and the balance between automated surveillance and civil liberties. As a conceptual paper, this study investigates how businesses can govern AI-Driven security solutions by bridging the theoretical divide between technical efficacy and ethical responsibility. To build this theoretical foundation, a systematic review of 32 peer reviewed articles was conducted using the PRISMA paradigm, synthesizing existing evidence across four core governance dimensions: technical performance, stakeholder accountability, regulatory compliance, and organisational process. Our conceptual analysis reveals a persistent "principles to practices gap"; while AI based SIS significantly outperform traditional systems in anomaly detection and incident response, these technological advancements have outpaced the operationalization of ethical norms within organisations. To address this gap, the paper proposes a novel, unified governance framework centred on digital trust. This model distinctly integrates the AI Trust Framework and Maturity Model (AI TMM), the Tiered Ethical Cybersecurity Model (TECM), and privacy preserving technologies such as federated learning to operationalize ethics by design. The article concludes with actionable policy pathways for legislators, organisational leaders, and researchers to increase cyber resilience while strictly respecting individual privacy rights.

Research on Ethical Governance of Relay Protection Engineering in AI ‑ Empowered Power Systems

Hardware is an AI Ethics Problem: Expert Visions for a Sustainable and Equitable Semiconductor Industry

It is argued that considerations of AI ethics must extend beyond models and data to encompass the hardware infrastructures on which they depend, and that embedding stakeholder reflection is critical for anticipatory governance in the physical infrastructure of AI.

A Cross-Sector Review of Ethical Issues in Technology Adoption

Rapid adoption of technologies like Artificial Intelligence, big data, IoT, blockchain, automation, and cloud computing has transformed industries by improving efficiency, innovation, and scalability. However, this growth has also introduced significant ethical challenges, including data privacy breaches, algorithmic bias, surveillance, workforce displacement, lack of transparency, and digital inequality.These issues affect multiple sectors such as healthcare, finance, education, manufacturing, and governance, though their impact varies—for example, patient data security in healthcare, fraud prevention in finance, and job displacement in manufacturing. The study highlights that ethical concerns are interconnected, with problems like privacy linked to cybersecurity and bias tied to transparency.To address these challenges, the research proposes an ethical adoption model based on fairness, accountability, transparency, privacy, inclusivity, and sustainability. It emphasizes the importance of organizational ethics, stakeholder involvement, and regulatory alignment. Overall, the study argues that ethical considerations are essential for sustainable technological progress and should be integrated into all stages of technology development and implementation.

Mapping the fragmented landscape of privacy in the age of generative AI: a bibliometric analysis and future research agenda

This study investigates how privacy has been conceptualized across technical, organizational, behavioral, ethical and governance perspectives and identifies key gaps and emerging challenges within the literature and contributes to the development of a more comprehensive perspective on privacy as a multidimensional issue.

An Analysis of the Digital Personal Data Protection Act 2023

The enactment of the Digital Personal Data Protection Act, 2023 (DPDP Act), is a significant step in India's efforts towards coherent and modern data protection. The Act is a statutory manifestation of the fundamental right to privacy affirmed in Justice K.S. Puttaswamy v. Union of India. The Act attempts to balance two competing necessities- the need to spur economic innovation and growth with the use of data, and the need to maintain the autonomy of persons in the digital or cyber sphere. The paper undertakes a critical study of the Act, considering key dimensions such as state accountability, independence of enforcement mechanisms, algorithmic transparency, and a regulatory role for emerging technologies such as AI, blockchain, and the Internet of Things. These dimensions are not only interrelated but also feed into one another, ranging from cross-border data transfers to surveillance exemptions and data fiduciary obligations. The paper puts the DPDP Act, 2023 in the context of broader privacy frameworks around the world and highlights that although the Act marks a normative development in data regulation, it also reveals enduring tensions in the pragmatics of regulatory governance. The paper concludes by proposing reforms, including the reintroduction of the Sensitive Personal Data, and ensuring robust regulatory protection for Artificial Intelligence and automated decision making, for effective implementation of the DPDP Act, 2023.