Professor Sarvapali Ramchurn (Electronics and Computer Science, University of Southampton, UK) is going to lecture on Towards Responsible Human Agent Collectives at the Auditorium III of Aristotle University Research Dissemination
Center–ΚΕΔΕΑ ΑΠΘ (September 3rd Ave., University Campus) on Wednesday, October 31st , 2018 at 17:00.
ABSTRACT
AI and Machine Learning are driving a number of applications around us. From drones that support emergency responders and the police to machine learning algorithms that monitor our activities in our homes, the value of AI and ML is predicted to add £232Bn to the UK economy alone. In this talk, I will mention some of the issues that need to be addressed to achieve such an impact. Most of these issues have to do with how we design AI/ML that works well for and with humans. This will draw upon my work with the AXA Research fund on Responsible AI where I am investigating methods to implement human-UAV teams and within the A-IoT project where we are investigating human machine interactions that lead to fair and profitable outcomes.
About the speaker
Sarvapali Ramchurn
Professor
Electronics and Computer Science
University of Southampton
email: sdr1@soton.ac.uk
www: http://www.sramchurn.com/
Sarvapali Ramchurn is a Professor of Artificial Intelligence in the Agents, Interaction, and Complexity research group where he carries out research into the design of autonomous agents and multi-agents for real-world socio-technical applications including energy systems, disaster management, and crowdsourcing. He has won multiple best paper awards for his work at AAMAS, IJCAI/JAIR and the AXA Research Fund award on Responsible AI. He works closely with industry and his research touches on a number of fields including Machine Learning, Data Science, and Game Theory. Specifically, he has pioneered the development of agent-based coordination algorithms for distributed task allocation that have been deployed on real-world unmanned aerial vehicles and in the Premier League’s Fantasy Football game where his approach has been shown to outperform more than 5M human players. His papers have been cited more than 4000 times (according to Google scholar) and his work has featured in various media including BBC News, New Scientist, EPSRC Pioneer, and Wired.