IJCAI 2016 Workshop - Closing the Cognitive Loop: Third Workshop on Knowledge, Data, and Systems for Cognitive Computing - overview
As AI techniques are increasingly employed in real world applications and scenarios, their contact with humans is ever-increasing. Traditionally, most AI systems have tended to exclude humans and the problems that accompany interaction with them. This has enabled the development of algorithms and even end-to-end systems that produce “optimal” artifacts that cut humans completely out of the loop, while still operating in a world where the assumption is that humans will be the end-consumers of the artifacts produced by such systems. Cognitive computing is a new paradigm that seeks to replace that diffidence and sometimes even mistrust of humans with a vision of successful cooperation and teaming between humans and AI systems and agents.
The key idea is that human-machine teams can often achieve better performance than either alone. To enable this, AI techniques must not only accommodate humans in the decision-making loop, but to go to great lengths to make such participation as natural and simple as possible. Building such cognitive computing systems and agents will thus require contributions from many areas of AI as well as related fields. We call this process the “closing of the cognitive loop”, and all contributions to the workshop will be evaluated on their ability to demonstrate the successful closing of this loop, or technical extensions to existing work that can close it.
The aim of this workshop is to bring together the work of researchers who are interested in advancing the state-of-the-art not merely in their specific sub-field of AI, but are also willing to engage in technically directed discussions on what is missing currently from their work that is needed to turn it into a deployed service that can gainfully interact with humans and the world at large. Work that is submitted to the workshop will be expected to address this central question, and make some effort towards addressing the challenges involved in taking a stand-alone AI contribution and converting it into a cognitive computing system or service.