The entertaining side of data science goes beyond computing - SiliconANGLE

Empathy and creativity might not be the most obvious skill sets for a career in data science, but balancing social science with hard science is what makes data analysis entertaining, according to Margot Gerritsen (pictured), senior associate dean and director of the Institute for Computational and Mathematical Engineering at Stanford University and founder of the Women in Data Science conference.

“As a data scientist, one of the reasons why I think it’s so fun, you’re not just a mathematician or statistician or computer scientist. You are somebody who needs to look at things taking into account ethics and fairness. You need to understand human behavior. You need to understand the social sciences,” Gerritsen said.

Gerritsen spoke with Lisa Martin (@LuccaZara), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the Global Women in Data Science Conference in Stanford, California. (* Disclosure below.)

Gerritsen and Martin discussed the founding and fast growth of the WiDS conference, the need for diversity within data science, and the dangers of subconscious bias when analyzing and presenting data sets.

Planned and executed in less than six months, Gerritsen described the inaugural WiDS event in 2015 as a “sort of a revenge conference” to prove that there were capable women speakers in data science. Livestreaming to scale up virtual attendance has given WiDS true global reach, with 177 events being held in 155 cities in 53 countries during the 2018 conference.

“I think we started the conference just at the right time,” Gerritsen said. “There was a lot of talk about diversity; several of the companies were starting really big diversity initiatives.”

But encouraging diversity takes more than hiring a more diverse workforce: “The whole culture of the company needs to change so that these sort of skills … communication skills, presentation skills, visualization skills, negotiation skills, that they really are developed everywhere,” Gerritsen said. Her goal is to have a workforce that is equal parts male and female, with each sex participating equally and bringing a diverse voice to the field.

Creativity within data science can be a double-edged sword. Although an intuitive approach can bring deeper understanding, it can also allow subconscious bias to influence interpretations. With more and more social, business and political decisions based on data, analysts must be aware of the potential for prejudice in how results are interpreted, presented and perceived, according to Gerritsen.

“Even though we always say we do objective work and we’re building neutral software programs, we’re not. We’re not. Everything that we do in machine learning, data mining, we’re looking for patterns that we think may be in the data because we have to program this data,” Gerritsen concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the Global Women in Data Science Conference. (* Disclosure: TheCUBE is a paid media partner for the Women in Data Science Conference. Neither Stanford University, the event sponsor, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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