Digital Job Fair

The talk explores complexity as a constitutive dimension of the social and the living, transcending the myths of total control and rationality. In the age of AI, it is necessary to rethink systems of thought and epistemologies, healing the rift between the human and the technological. The future belongs to "hybrid figures" and managers of complexity: professionals capable of inhabiting boundaries and integrating transversal knowledge to govern the unpredictable and generate true innovation.

XR training is no longer just about putting on a headset. The XR2Learn project (Horizon Europe) has built and validated AI systems that detect learners' educational state in real time - adapting challenge, pace, and content dynamically. From no-code authoring tools to open-source affective AI models, discover success stories of how immersive, human-centric learning is becoming accessible to SMEs, educators, and training providers across Europe.

As artificial intelligence increasingly reshapes the workplace, the most urgent challenge is no longer technical adoption but human adaptation. This talk presents a case study in EdTech and higher education that examines how AI can support (definitely not replace) human learning across the lifespan. Drawing from my work as a Full Professor and Academic Program Director for the Master's in Strategic Communications at National University (USA), as well as from multiple international podcast conversations on AI, media literacy, and ethics, this speech explores how AI is already transforming professional education, assessment, and skill development. Rather than focusing on automation or efficiency alone, the case study centers on lifelong learning, critical thinking, and human agency in AI-augmented environments. The talk addresses three core questions: How is AI redefining what it means to “learn for work” over a lifetime? As careers become less linear and skills rapidly expire, education must shift from content delivery to adaptability, reflection, and metacognition. What risks emerge when AI prioritizes engagement, speed, or optimization over understanding? Using examples from EdTech platforms and higher education assessment, the speech highlights ethical tensions around datafication, surveillance, and the commodification of learning. How can educators design AI-supported learning experiences that remain human-centered? The case study presents concrete pedagogical strategies that position AI as a cognitive partner—supporting feedback, reflection, and experimentation—while preserving student agency and responsibility. The speech situates AI within broader debates about the future of work, arguing that the most valuable skills in an AI-driven economy are relational, interpretive, and ethical. By reframing AI as an educational infrastructure rather than a shortcut, this speech invites policymakers, educators, and technologists to reconsider how we prepare learners not just for their next job, but for continuous reinvention across their lives.