[UBU] Trustworthy AI: Decisions, Networks and Human-AI Collaboration in Sociotechnical Systems

I gave the seminar “Trustworthy AI: Decisions, Networks and Human-AI Collaboration in Sociotechnical Systems” at the University of Burgos, as part of the seminarios del programa de doctorado en Ingeniería y Tecnologías Industrial, Informática y Civil.

The talk presented a sociotechnical perspective on trustworthy artificial intelligence, focusing on how AI systems should be understood not only as models, but as systems embedded in data pipelines, human decisions, social structures, institutions, and real-world deployment contexts.

The seminar addressed:

• ⚖️ Trustworthy AI in high-impact decisions: algorithmic fairness, uncertainty, data valuation, and the risks of automated decision-making in sensitive domains.
• 🕸️ AI, graphs, and social networks: how graph-based methods and graph neural networks can help analyze structural inequalities and exposure dynamics in networked systems.
• 🤝 Human-AI collaboration: strategies for designing decision-making systems where humans and AI models complement each other effectively.
• 🧠 Generative AI and LLMs: emerging opportunities and challenges around large language models, including applications in mental health.

The seminar emphasized that trustworthy AI is not only a technical objective, but a sociotechnical challenge requiring rigorous evaluation, human oversight, contextual awareness, and responsible governance.

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