The Consent Vacuum presented at IAIL 2026 in Brussels
Paper on what happens to consent when AI agents interact mainly with other agents, co-authored with Osman Gazi Güçlütürk.

Founding Director, Artificial Intelligence Institute
Dr. Mehmet Haklıdır is the founding Director of the TÜBİTAK BİLGEM Artificial Intelligence Institute, Türkiye’s first national AI institute. He holds a Ph.D. in Control and Automation Engineering from Istanbul Technical University and has more than 24 years of experience in AI, autonomous systems, big data, simulation, and technology policy.
He contributed to Türkiye’s first National AI Strategy and led the technical preparation and coordination of the National Artificial Intelligence Action Plan 2026–2030, finalized through consultation with the national AI ecosystem. He serves on the Steering Committee of the Science, Technology and Innovation Policies Council of the Presidency of the Republic of Türkiye and is a member of several international AI governance initiatives, including OECD ONE AI, GPAI, UNESCO AI Ethics, NATO DAIRB, and the European AI Alliance.
His current research focuses on large language models, AI safety with an emphasis on agentic AI systems, deep reinforcement learning, robotics, and autonomous decision-making under uncertainty.
PhD, Control and Automation Engineering
2011–2022
Istanbul Technical University
MSc, Mechatronics Engineering
2003–2006
Istanbul Technical University
BSc, Mechanical Engineering (minor in Computer Science)
1999–2003
Istanbul University
Agentic AI safety and governance, reinforcement learning for autonomous systems, and applied AI for language, health and the geosciences.
How consent, oversight and accountability hold up when AI systems act on people’s behalf and interact with each other.
Decision-making under uncertainty and partial observability for autonomous vehicles, robots and control.
Machine learning and control for geothermal systems: reservoir temperature, contamination and scaling.
Turkish language models, embedding benchmarks and multimodal language analysis.
Privacy-preserving and trustworthy AI for clinical prediction, medical imaging and digital twins.
Applied machine learning with industry and public partners, from livestock tracking to smart appliances.
High-fidelity simulation, computer generated forces and control (2003–2015).
Paper on what happens to consent when AI agents interact mainly with other agents, co-authored with Osman Gazi Güçlütürk.
Consent chain degradation in embodied multi-agent systems (ICRA WoRoBet) and belief-aware privileged distillation for autonomous driving (CVPR WAD).
TR-TEB evaluates 45 open-source embedding models on Turkish tasks.
Why consent breaks when AI acts on your behalf: workshop paper at ACM CHI 2026.
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