The vision of artificial intelligence (AI) is often manifested through an autonomous software module (agent) in a complex and uncertain environment. The agent is capable of thinking ahead and acting for long periods of time in accordance with its goals/objectives. It is also capable of learning and refining its understanding of the world. The agent may accomplish this based on its own experience, or from the feedback provided by humans. Famous recent examples include self-driving cars (Thrun 2006) and the IBM Jeopardy player Watson (Ferrucci et al. 2010). This chapter explores the immense value of AI techniques for collective intelligence, including ways to make interactions between large numbers of humans more efficient.

By defining collective intelligence as “groups of individuals acting collectively in an intelligent manner,” one soon wishes to nail down the meaning of individual. In this chapter, individuals may be software agents and/or people and the collective may consist of a mixture of both. The rise of collective intelligence allows novel possibilities of seamlessly integrating machine and human intelligence at a large scale – one of the holy grails of AI (known in the literature as mixed-initiative systems (Horvitz 2007)). Our chapter focuses on one such integration – the use of machine intelligence for the management of crowdsourcing platforms (Weld, Mausam, and Dai 2011). Read More

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