Autonomous intelligent transport systems promise to deliver faster, safer and more secure means of transportation. Self-driving cars, drones and autonomous ships and trains are now powered by sophisticated artificial intelligence systems. Recent advances in machine learning driven by the exponential growth of computational power and the wide availability of data have triggered new legal and ethical concerns.
Who “owns” the data stored, processed and generated by these systems?
Who is liable for the unsafe behavior of these systems making decisions based on noisy data if we don’t know who the owner of these data is?
How to make sure these systems are safe and predictable if they are non-deterministic by definition?
As different legal frameworks applicable to data overlap and sometimes contradict each other, developers and investors face growing legal uncertainty which threatens the innovation potential of emerging technologies in safety-critical domains such as transportation. This session will look at some recent developments in machine learning, such as generative adversarial networks, and will provide insight into the legal and ethical implications of the rights on data.
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Ivo Emanuilov is a lawyer and researcher at the Centre for IT and IP Law (CITIP) of KU Leuven. Ivo has acquired significant experience in several international projects advising on a broad range of legal topics spanning the domains of data protection, rights on data, liability, safety and cyber security of distributed and autonomous cyber-physical systems. He has specific experience as a consultant on methodologies for practical implementation of privacy by design measures from a legal perspective in the software development life cycle, legal aspects of unmanned aircraft systems and connected and autonomous vehicles. His research interests are focused on the adaptation and evolution of the regulatory and governance models in distributed and decentralized ecosystems and the impact of new developments in artificial intelligence and blockchain.