A diverse set of perspectives is important in data science for many reasons, including avoiding unintended consequences of technologies that affect an array of people, Dean Andrea Goldsmith said in delivering the closing talk of the 2021 Women in Data Science Worldwide Conference.
In the final talk of the two-day conference, she noted how the field of data science spans engineering, liberal arts, economics, as well as the arts, and brings in tools from mathematics and statistics. “That is an area where women thrive, doing interdisciplinary activities, and that’s part of the reason I’m so excited about data science as an area that needs diversity,” she said.
The annual Women in Data Science conference, hosted by Stanford University, took place online March 7 to 8.
Goldsmith noted that she is not fully a data scientist in her own research, but has “dabbled” in the field and is surrounded by data scientists in her work, both in academia and at her wireless technology startups. She said she has seen how data science can have a significant impact on a diversity of people, and that people with diverse backgrounds may be able to spot potential harm.
Those harms include privacy violations, election disinformation, discrimination and biases arising from artificial intelligence, she said. “People who have experienced those biases can more clearly recognize the dark sides of data science.”
“Having diverse people create the science and apply the science can help that impact be a positive instead of a negative impact,” she said.
Research has shown, she said, that “diverse organizations and teams are more creative, perform better, and have higher satisfaction of their members.”
Watch the video above for an excerpt from her address or view the full talk here.