We naturally think of "intelligence" as a trait belonging to individuals. We're all--students, employees, soldiers, artists, athletes--regularly evaluated in terms of personal accomplishment, with "lone hero" narratives prevailing in accounts of scientific discovery, politics, and business. Similarly, artificial intelligence is typically defined as a quest to build individual machines that possess different forms of intelligence, even the kind of general intelligence measured in humans for more than a century. Yet focusing on individual intelligence, whether human or machine, can distract us from the true nature of accomplishment. As Thomas Malone, professor at MIT's Sloan School of Management and director of its Center for Collective Intelligence notes: "Almost everything we humans have ever done has been done not by lone individuals, but by groups of people working together, often across time and space." Malone, the author of 2004's The Future of Work and a pioneering researcher in the field of collective intelligence, is in a singular position to understand the potential of AI technologies to transform workers, workplaces, and societies. In this conversation with Deloitte's Jim Guszcza and Jeff Schwartz, he discusses a vision outlined in his recent book Superminds--a framework for achieving new forms of human-machine collective intelligence and its implications for the future of work. Can you tell us what a "supermind" is, and how you define collective intelligence? Thomas Malone, director, MIT Center for Collective Intelligence: A "supermind" is a group of individuals acting collectively in ways that seem intelligent, and collective intelligence essentially has the same definition. For many years, I defined collective intelligence as groups of individuals acting collectively in ways that seem intelligent. But I think it's probably more useful to think of collective intelligence as the property that a supermind has.

Artificial intelligence is changing the world of retirement planning. By using improved datasets and algorithms to efficiently deliver solutions tailored to people's needs, AI can help them save, invest and retire better. One of the hottest trends to emerge in this area in recent years is the use of robo-advisors. These are software programs that use the data supplied by clients to create and automatically manage their investment portfolios. They're gaining in popularity, but are they better than human advisors?

I'd guess almost 1,000 people came to hear thought leaders James Guszcza, FCAS, of Deloitte and David Ingram, FSA, of Willis Towers Watson talk about data science and behavioral science at the CAS Annual Meeting in Anaheim. They were talking, at least it sounded to me as I considered it and went back through my notes, about what it means to be an actuary today. That's a topic a lot of us think about as our profession seems encroached upon by artificial intelligence (AI). Once artificial intelligence, whatever it is, (Guszcza noted that the definition of AI is erratically drawn), gets cranking, it will be machines scrubbing, collating, analyzing and concluding -- yes, telling us -- what we humans should think. As actuaries we have always assumed that to the greatest brain goes the truth.

Artificial intelligence technologies could reshape economies and societies, but more powerful algorithms do not automatically yield improved business or societal outcomes. Human-centered design thinking can help organizations get the most out of cognitive technologies. Today's artificial intelligence (AI) revolution has been made possible by the big data revolution. The machine learning algorithms researchers have been developing for decades, when cleverly applied to today's web-scale data sets, can yield surprisingly good forms of intelligence. For instance, the United States Postal Service has long used neural network models to automatically read handwritten zip code digits.