Building a Diverse Workforce for Next-Generation Analytics and AI

By Jan Rowell

October 15, 2018

High-performance computing (HPC) has a well-known diversity problem, and groups such as Women in HPC are working to address it. But while the diversity challenge crosses the science and technology spectrum, it is especially acute in areas of HPC where breakthroughs are driven by extracting insights from data. The deluge of data, with the convergence of simulation and artificial intelligence (AI) workloads, and the development of exascale computers, will all increase the opportunities to generate data and derive value from it.

Taking advantage of those opportunities is not just a matter of adding more bodies, although that’s part of the solution. There is also a specific need for a highly diverse workforce to create next-generation data models and design the machine learning (ML) applications that will yield transformative value from the available data. Teams that represent different perspectives are likely to produce more robust ML models that reflect all aspects of a problem. As Trish Damkroger, Intel’s vice president and general manager of extreme computing, says, “Inclusion is the foundation of high performance and innovative teams. We believe that in order to shape the future of emerging fields like data and computational science, we must bring together individuals with a wide range of perspectives, backgrounds, and experiences.”

Research supports Damkroger’s perspective. Teams with diversity across the lines of gender, race, ethnicity, and sexual orientation show higher levels of creativity and produce more innovative solutions, according to Katherine Phillips, a professor at the Columbia University Business School.[1] Phillips has also found that members of diverse teams tend to sharpen their own and each other’s thinking, resulting in more rigorous problem-solving.

Women in Big Data

One group that’s addressing the need to build an inclusive workforce for analytics and AI is Women in Big Data (WiBD). This industry initiative got its start in 2015 at Intel, shortly after the company had established its $300 million Diversity in Technology Initiative. Noting that women were significantly underrepresented in the company’s big data technologies area, an Intel team reached out to some of the company’s big data partners in the Bay Area to see how widespread the problem was.

“Here was this exciting, up-and-coming area, and we had fewer females proportionately than in some of our hardware engineering groups,” recalls Shala Arshi, senior director of technology enabling at Intel Corporation, a former engineer in the company’s Supercomputer Systems Division, and a founder of WiBD. “We wondered whether it was just an Intel problem or an industry problem, and what we could do about it.”

After determining that other technology companies were facing similar scenarios, they convened a planning team with 15 women from SAP, Cloudera, Oracle, IBM, Intel, and others. Today, WiBD has scaled to more than 7,500 members representing 60 companies and universities. It has nearly a dozen chapters across the US, in Europe, and in Latin America. It also has almost two dozen corporate sponsors and partners, ranging from Netflix and Walmart to Hortonworks and the Linux Foundation.

The growth has been driven by grassroots interest, with activities publicized through social channels such as LinkedIn, Meetup, and Twitter “People find us,” adds Arshi. “We haven’t done a big publicity push. The need is there.”

Smart Decision

Chapters hold regular meetings and events focused on evangelism, networking, training, and mentorship. For example, a recent technology panel sponsored by the WiBD Northwest chapter packed an auditorium with both women and men who heard from machine learning experts at Nike, Intel, and Speakers discussed hot topics in big data and AI, from data quality to AI in the cloud to innovative use cases, and fielded almost two dozen substantive questions.

Among other speakers, the audience heard Parham Parvizi, cofounder and architect at, tout the benefits of a workplace with full gender equality is. Parvizi’s Portland-based startup uses AI to identify patterns in real-time data streams from Internet of Things devices. “We decided early on to have a 50/50 balanced workforce of women and men,” Parvizi told the audience. “It’s been one of the smartest decisions I’ve made. We have a great atmosphere, a well-balanced team, and excellent decision making. Any company I lead in the future will have gender equality.”

They also got career advice from Richa Khandelwal, a software engineering manager whose team delivers machine learning systems and large-scale infrastructure for Nike. Noting the broad range of open source materials and other resources available on machine learning, Khandelwal told career-changers and others who want to move into big data/AI, “Start by finding a problem you can solve with data and AI. Use those resources, and learn what you need to know as you work on solving the problem. Focus on what you can learn rather than what you already know, and don’t sell yourself short.”

Practices to Promote Diversity

With the rapid growth in AI and analytics solutions, HPC must compete with other industries and economic sectors to obtain needed talent. The WiBD experience suggests several tactics that can help HPC organizations succeed:

Emphasize HPC’s relevance and importance. Many women and Millennials want to solve real problems. “They are drawn to jobs where they can make a difference,” Arshi says. “HPC has a huge advantage here because there are so many areas where you can have a big impact on lives and society, from curing cancer to addressing climate change. This resonates very strongly.”

Capture workers in transition. Be flexible enough in your job search to recognize potential in non-traditional career paths. “Many women we talk with are ready for a change of direction in their careers, or they’ve taken time for their family and now are ready to jump back into the workforce,” says Soumya Guptha, an Intel marketing manager and former software engineer who helped found  WiBD’s Northwest chapter and led the chapter’s networking activities the past year. “Women with a math or science background can readily transition into big data, analytics, and AI.”

Grow your own. Nurture the talent within your organization. Establish internal mentoring programs, advise underrepresented populations on obtaining needed skills, and encourage their participation as conference speakers. Educate all employees on diversity’s advantages. Support interested women in joining groups such as Women in HPC and Women in Big Data, to grow professionally and to bring in additional women. Keep in mind that women may be less confident than men in putting themselves forward for a job or a speaking opportunity. Help educate women to not underestimate their capabilities.

Highlight the opportunities. In addition to strong projected job growth, analytics and AI offer a chance to join an exciting young industry. They avoid the need to swim upstream, which they are likely to face in a highly traditional industry, and instead can shape a diverse, egalitarian field.

Advancing Analytics and AI

Workplace inclusivity is increasingly recognized as a competitive differentiator for enterprises and a crucial asset for research teams. By fostering diversity in their AI and analytics workforce, HPC organizations position themselves to capture the full value of the rising flood of data and apply ML to critical mission challenges.

They also have a chance to contribute to overall economic growth. A study by McKinsey Global Institute found that if women participated in the economy identically to men, they could add as much as $28 trillion to the world’s annual GDP in 2025.[2] And experience shows that focused efforts can produce meaningful progress: Intel recently announced it expects to reach its 2020 inclusiveness goals by the end of 2018, achieving full representation of underrepresented minorities and women in its US workforce.[3]

Building on the work of Women in Big Data offers a powerful approach to moving forward.

Learn more about Women in Big Data:

Read a blog about the WiBD Big Data/Machine Learning Technology Panel:

Jan Rowell is a freelance writer based in the Portland, Oregon area. She focuses on technology trends and impacts in HPC, healthcare, and other industries.

[1] Katherine W. Phillips, How Diversity Makes Us Smarter, 2014.

[2] Anu Madgavkar, Kweilin Elingrud, and Mekala Krishnan, The Economic Benefits of Gender Parity, Stanford Social Innovation Review, March 8, 2016.

[3] Barbara Whye, 2017 Diversity & Inclusion Annual Report, March 27, 2018.

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