The brains behind Watson

Whenever we talk about preparing kids for the future, we usually include collaboration and teamwork as a valuable skill. Our students also need to realize that science is not conducted by individuals in isolation. Successful scientists and engineers must be able to work effectively with people from different perspectives and backgrounds. In fact, this diversity is often the key for solving complex problems.

From NSTA’s Readings in Science Methods, K–8:

Five or six years ago years ago, I attended a lecture about space shuttle safety by Dr. Jack Bacon, a NASA Engineer. He showed the power of having a diverse workforce by explaining that people with diverse backgrounds (ethnic, gender, socio-economic status, etc.) have different experiences throughout life, they bring different perspectives to the table. In his human differences textbook, Koppleman (2005) explains that diversity is regarded as positive when people engage in solving problems:

If we examine problems the same way, we would generate similar solutions. Williams (2003) described a problem-solving conference where a chemical company invited 50 employees that were women or people of color and 125 predominantly white male managers. When divided into problem-solving teams, half of the groups consisted of white males only and half included diverse members by both gender and race. Afterward, the company CEO said, “It was so obvious that the diverse teams had the broader solutions. They had ideas I hadn’t even thought of… We realized that diversity is a strength as it relates to problem-solving (pp. 442-443).

IBM’s DeepQA team worked together for more than five years to design and build Watson. The team is comprised of men and women working in the United States, Japan, China and Israel. From Jennifer Chu-Caroll’s expertise with designing algorithms to determine the relevant content of a question, to Jaoslaw Cwiklik’s expertise in parallel processing, each team member brought his or her talents to bear on this incredibly complex challenge. “The opportunity to pursue an exploratory project that took an area of science that I was most interested in, and to bring together a team of world class people, and push the limits—it doesn’t get any better than that,” explains David Ferrucci, Principal Investigator of the DeepQA / Watson project.

Read more about the research team here.

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