Ethics in AI: Responsible and Regulated Development of AI Systems

The field of artificial intelligence (AI) ethics and regulation is gaining urgency as AI systems are deployed across healthcare, education, finance, public services, and other high-impact domains. Although technical progress has been rapid, the operational mechanisms needed to ensure that AI systems are safe, accountable, and compliant remain underdeveloped. Key challenges include the unpredictability of system behavior, limited transparency, risks of misuse, insufficient evaluation of downstream harms, and the absence of widely adopted assurance and auditing practices. While ethical principles and high-level governance frameworks are now well established in the literature, there is a pressing need to move from abstract guidance to concrete methods that can be implemented, tested, and assessed in real-world settings. Recent developments in AI policy and regulation further reinforce the need for practical tools that support compliance, oversight, and continuous monitoring throughout the AI lifecycle.This Research Topic focuses on the practical implementation of trustworthy AI through safety assurance methods, auditing frameworks, and approaches for translating ethical and regulatory requirements into operational practice. Rather than merely revisiting general debates on AI ethics, the topic seeks contributions that show how responsible AI can be embedded into the design, development, deployment, and governance of AI systems. We are particularly interested in work that bridges the gap between principles and practice by proposing concrete methodologies, evaluation procedures, compliance mechanisms, and governance models that can be adopted by researchers, developers, organizations, and policymakers. The goal is to advance actionable, evidence-based approaches that strengthen transparency, accountability, robustness, and human oversight in AI.This Research Topic welcomes original research, methodological papers, case studies, audits, and applied perspectives that address how ethical and regulatory standards for AI can be implemented in practice. Submissions may examine both prospective approaches and retrospective analyses, provided they offer clear lessons for improving assurance, compliance, and governance. Topics of interest include, but are not limited to, the following:o Safety assurance methods for AI systems, including risk assessment, validation, monitoring, and post-deployment oversighto Auditing frameworks for evaluating fairness, robustness, transparency, accountability, and regulatory complianceo Methods for operationalizing ethical principles and regulatory requirements in AI system design and developmento Standards, benchmarks, and certification approaches for trustworthy and human-centered AIo Case studies of AI failures, near misses, or successful interventions that generate practical lessons for safer deploymento Governance models for managing high-risk AI applications across organizational or sectoral contextso Tools and procedures for documenting AI systems, including model cards, impact assessments, and audit trailso Comparative analyses of regulatory implementation across jurisdictions, sectors, or application areaso Interdisciplinary and stakeholder-based approaches that improve oversight, public trust, and responsible innovation Topic editors: Aleksandar Petrovic, Petar Spalevic, Miodrag Zivkovic Source: https://www.frontiersin.org/research-topics/79186/ethics-in-ai-responsible-and-regulated-development-of-ai-systems