UPDATED 21:41 EDT / FEBRUARY 03 2017

BIG DATA

The rise of machine learning: Will the human factor be pushed out of data science? | #WiDS2017

With the rise of machine learning, concerns are being voiced about the future involvement of humans in jobs that computers can handle. But at the same time, alternative views are being offered on ways in which the human element will influence the direction of data science, with passion playing a large role in that survival.

“I think data science is one area in which a woman … will have a huge opportunity to move the needle,” said Stephanie Gottlib-Zeh (pictured), president of Agyleo Sport. In her view, insularity is something more likely to damage an enterprise than to sustain it, and drawing in a diversity of viewpoints is a big step toward protecting against that sort of stagnancy.

Gottlib-Zeh (pictured), president of Agyleo Sport, shared her thoughts on the ways in which data is changing business and how tech workers should aim for jobs that excite them. She spoke with Lisa Martin (@Luccazara), co-host of theCUBE, SiliconANGLE’s mobile live streaming studio, at the Stanford Global Women in Data Science (WiDS) Conference in Stanford, CA. (*Disclosure below.)

“For industries which have been very conservative … moving to this digital setting is a real challenge but achievable by approaching digital transformation in a holistic way,” she noted. And while many are quickly encountering reasons for making that move, realizing that transition in effective ways is no easy task. “Alignment and coherency across all entities and at all levels in the organization is essential to succeed.  The cultural aspect is very important. If you don’t get the culture right … you will likely fade,” Gottlib-Zeh commented.

Given that “the data now is in the center of everything,” as she put it, the need to adapt to today’s realities of service and data oriented business replacing “a product-centric viewpoint” is becoming a very noticeable pressure. And while Gottlib-Zeh felt that many industries, particularly the oil and gas companies, “have been essentially blind” by not understanding how to properly leverage the data at their disposal, the changing state of things is now driving efforts to gain accuracy, predictability and accessibility, or be left behind.

Hands-on and passion

“Time and precision cost a lot of money,” Gottlib-Zeh noted, but that downside in no way diminishes their importance. “There is no recipe, but for sure, I think many industries today are still mired in their old ways. They really need some fresh … insights to drive the products right,” she continued, nodding to women in tech as an underutilized resource in this regard, despite the opportunities “for women to jump into these jobs … with either a technical or a managerial angle.”

What it came down to, she said, was genuine enthusiasm for the work. “Skill-wise, let’s be passionate. If you love the data … I think you would be perfect. It doesn’t matter if you’re a man, woman – you’re just a data scientist at the end.”

And while she recognized that there were some prosaic, day-to-day issues that might stand in the way of achieving those goals of employment accessibility, she urged young people not to let that take away their passion.

“This ability of adaptation, of curiosity, of passion for the sorts of challenges … that you will have to address through the data science world, will be key. … I realize that it’s a luxury, at a point, to have a choice about what you want to do in life, but it’s also one you have to address early in life,” she said.

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

Photo by SiliconANGLE

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