AI, optimization and human dignity: Industry 5.0 challenges limits of Industry 4.0

A new research review has offered a comprehensive roadmap for understanding the transition from Industry 4.0 to Industry 5.0, emphasizing a future where artificial intelligence (AI), optimization tools, and human values converge to redefine industrial innovation. The review, titled “AI, Optimization, and Human Values: Mapping the Intellectual Landscape of Industry 4.0 to 5.0,” was published in Applied Sciences.

Conducted by Albérico Travassos Rosário and Ricardo Jorge Gomes Raimundo, the study uses a systematic bibliometric literature review of 53 peer-reviewed publications to analyze how technological progress is evolving toward a more inclusive, ethical, and sustainable industrial paradigm.

What drives the shift from Industry 4.0 to Industry 5.0?

The study chronicles the rapid rise of Industry 4.0, driven by cyber–physical systems (CPS), Internet of Things (IoT), artificial intelligence, and data connectivity, but notes a significant drawback: the limited consideration of human and environmental dimensions. While Industry 4.0 emphasizes automation and efficiency, Industry 5.0 aims to reintegrate human-centric values into industrial systems, recognizing that social well-being, environmental sustainability, and ethical accountability must be prioritized alongside productivity.

Key drivers identified include:

• Human–Machine Collaboration: Industry 5.0 values the unique qualities of human workers, intuition, empathy, and ethical judgment, augmenting rather than replacing them through collaborative robots (CoBots) and intelligent interfaces.

• Ethical Governance: Industry 5.0 responds to growing concerns about data privacy, algorithmic bias, and labor displacement by embedding fairness, explainability, and transparency into AI systems.

• Sustainability and Circular Economy: The transition emphasizes environmentally responsible operations, driven by AI-powered life cycle assessments, digital twins, and energy-efficient optimization strategies.

• Cybersecurity and Resilience: With rising cyber threats and global supply chain disruptions, Industry 5.0 integrates AI-enhanced security models and edge computing to support responsive, self-healing systems.

• Workforce Development: A digitally literate and ethically aware workforce is central to the Industry 5.0 vision, necessitating investments in AI education, lifelong learning platforms, and participatory design frameworks.

These evolving needs reflect a broader philosophical shift in industrial policy: from maximizing profit to maximizing shared value.

How are technologies being reconfigured for human-centric innovation?

The study explores a detailed technological landscape reshaped to align with human-centric values. AI, once focused on automation, is now repurposed for augmentation, ethical oversight, and creative collaboration. Among the highlighted technologies:

• Explainable AI (XAI): Tools that provide transparent, interpretable outputs to build user trust and regulatory compliance.
• Generative AI: Leveraged for real-time design, prototyping, and co-creation, facilitating user-customized and creative industrial outputs.
• Machine Learning (ML): Supports predictive analytics for maintenance, logistics, and customization while adapting to user feedback in real time.
• Cyber–Physical Systems and Digital Twins: These simulate physical systems in digital environments, enabling predictive diagnostics, real-time system optimization, and human-friendly interfaces.
• Wearable Technologies and Sensors: Devices monitor worker health, ergonomics, and fatigue, feeding back into adaptive systems that prioritize well-being.
• Edge Computing and Multi-Objective Optimization: These ensure low-latency responsiveness and balance goals like energy efficiency, cost control, and operational agility.
• CoBots and Human–Robot Collaboration: While early CoBots focused on basic task-sharing, future models are expected to interpret intent, adapt to emotions, and facilitate inclusive workplaces that accommodate diverse capabilities and needs.

These innovations mark a clear departure from task automation to systems designed for co-creation, adaptability, and ethical integration.

What do the trends reveal about the intellectual and policy landscape?

Through citation networks, keyword analysis, and co-authorship patterns, the study reveals a maturing but thematically constrained research field. Despite strong publication growth between 2022 and 2024 and high citation activity, most notably for studies on human–robot collaboration, the analysis identifies a narrow concentration around technology-centric themes such as machine learning, predictive analytics, and smart manufacturing.

Key observations include:

• Limited Conceptual Diversification: Terms like ethics, regulation, and co-production are underrepresented in the research corpus, suggesting a lag in addressing the socio-political dimensions of industrial transformation.

• Geographic and Disciplinary Reach: Italy and China lead in publication volume, and the field spans engineering, computer science, business, and humanities. This reflects an emerging global and interdisciplinary engagement but signals the need for broader integration of philosophical and regulatory discourse.

• Research Clusters: Core journals such as Procedia Computer Science, Applied Sciences, and Springer Series in Reliability Engineering dominate early-stage discourse. However, emerging areas like network security, emotional design, and co-creative systems remain peripheral.

• Metrics and Impact: The reviewed works amassed 1,240 citations collectively, with an h-index of 25. This indicates robust academic engagement but highlights a gap between technological advancement and the integration of human values.

The study concludes that while technical foundations for Industry 5.0 are solidifying, intellectual expansion into ethics, governance, and systemic sustainability is still in nascent stages. Future research must develop metrics to evaluate societal impact, explore sector-specific applications, and examine implementation across diverse cultural and economic contexts.

Toward a future of inclusive and ethical industrial systems

The researchers argue that Industry 5.0 should not be viewed as a replacement for Industry 4.0, but as an ethical, sustainable upgrade that complements its digital infrastructure. By embedding human dignity, resilience, and planetary responsibility into design and policy, the next industrial era may be more than just technologically advanced, it could be socially transformative.

The study calls policymakers, educators, engineers, and business leaders to co-author an industrial future where AI does not just serve economic goals, but also strengthens the social fabric and ecological balance.