Title: Collaborative Artificial Intelligence: Optimisation Problems with Human-Factor based Constraints
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Date & time: 9.00-11.00am, Friday 27th May 2016
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Location: Room 404, SBI building, Quang-Trung Software City (QTSC), District 12, Ho Chi Minh City.
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Abstract:
With the recent fantastic breakthroughs in Artificial Intelligence (AI), such as the latest success of AlphaGo or the advancements in robotics, comes along an increasing number of concerns about the dangers and threats these Ai technologies may bring to our society. These concerns may become so serious in the future that it would cause serious harms to further advancements of AI research. In fact, the root of these concerns lies within the fear of creating a superhuman Artificial General Intelligence (AGI) that one day may decide to destroy the humankind.
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To overcome these concerns, there have been many attempts to position AI as a set of more human-friendly and less threatening technologies.
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A very promising direction of these attempts is the concept of collaborative AI. This concept significantly differs from the AGI approach, as instead of focusing on creating superhuman competitors, it still keeps the human factor at the centre of its objectives. In particular, collaborative AI provides technologies that aim to ease our everyday life in a supportive and ubiquitous way. As ubiquitous systems, such as Internet of Things, and their applications (e.g., smart cities, smart homes, smart cars etc…) are becoming more and more successful, I argue that collaborative AI will also become a dominant concept in the (very) near future.
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However, state-of-the-art collaborative AI is still in its infant stage, and it will have to overcome a number of obstacles in order to achieve maturity. As such, in this talk, I will first describe in detail three major obstacles of the concept, namely: (i) human participation motivation; (ii) user privacy; and (iii) cyber security. In the second part of the talk, I will discuss the state-of-the-art research solutions within each abovementioned topic. In particular, I will mainly focus on the problem of having the human-factor in optimisation problems, a research area I have been working on.
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Short bio:
Long is a Hungarian-Vietnamese computer scientist at the University of Southampton, UK, where he is a Lecturer (Assistant Professor equivalent) in Computer Science. Long did his university studies in Budapest, Hungary (BME-VIK) and obtained his PhD from Southampton in 2012, under the supervision of Nick Jennings and Alex Rogers. He has been doing active research in a number of key areas of AI, mainly focusing on online machine learning, game theory, and incentive engineering. For his work, he has received a number of prestigious awards, such as:
(i) the CPHC/BCS PhD Dissertation Award (for the best Computer Science PhD thesis in the UK in 2012/2013) - Honourable Mention;
(ii) the ECCAI Artificial Intelligence Dissertation Award (for the best European PhD thesis in AI in 2012) - Honourable Mention;
(iii) the Association for the Advancement of Artificial Intelligence (AAAI) Outstanding Paper 2012 Award - Honourable Mention; and
(iv) the European Conference on Artificial Intelligence (ECAI) Best Student Paper 2012 Award - Runner-Up.