Recommender Systems as a Collaborative Form of ASI
Artificial social intelligence is much broader than mere multiagent systems, whether the agents are represented by neural nets or rule-based systems, involving many kinds of partnership between humans and machines. A powerful and well-established example is recommender systems, which are not popularly called AI yet typically involve machine learning of some form, analyzing preferences or behaviors of people in order, commonly, to advise them what movie or other cultural product they might want to experience next.1 A good example is the classic 2006 Netflix dataset of ratings of 17,770 movies by hundreds of thousands of its customers. When computer scientists work on recommender systems, ...
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