Beware the “Brobot?” The Women of AI
At CES (where AI was the buzzword this year), a group of women gathered to discuss the role of women in technology, and specifically in artificial intelligence. AI is already having an impact on all aspects of the MULO (multi-location) retail and restaurant ecosystem — from real-time analytics to inventory management and security.
According to the World Economic Forum and published in one report, “Women account for less than 25% of AI specialists, only 14% of the cloud computing workforce, and 20% of engineers. The Artificial Intelligence research staff at Facebook is only 15% women, while at Google this figure is just 10%.”
Elisabeth Strenger is Senior Technical author and Director of Content Strategy for RTInsights, Stenger herself has more than 25 years of technology experience, including nine years as Red Hat’s Emerging Technologies Marketing expert.
She recently published a list of the top women in AI. We asked for her criteria and perspective — both as a woman in technology and the author of the list.
Women are under-represented in AI. Why is that?
“It’s a result of the challenge of keeping women in STEM careers or providing enough professional development training.”
According to SHRM (the Society of Human Resources Professionals), the technology sector has a retention problem, with women leaving tech-related jobs at a high rate.
So, why does AI need women?
“The most visible danger of not having women involved at every stage of artificial intelligence development is bias. Because women are one of the groups underrepresented in data sets, they have experience in noticing outright omission of some groups or biased data acquisition methods. That’s not to say that women don’t have their own biases, but a diverse team with a variety of perspectives can avoid many of the obvious biases.”
What compelled you to put together “The Strenger List?” What were some of the criteria?
“The goal behind RTInsights’ list was to showcase women building AI in many different ways. We wanted to include the entrepreneurs and innovators who are driving clear visions of it’s potential and the dedicated engineers who make the software and hardware work.
They too need vision because this technology presents some very new computing challenges that call for inventive solutions–new ways of designing hardware, new ways of making cloud services available, and new programming languages whose boundaries are being pushed.
The third component of making the tech work for our businesses and society in general is ethics. Lists of AI-tech leaders tend to include the first two while the ethicist’s role is presented on its own. All three–the business, the tech, and the guidance–are critical to the success of artificial intelligence.
At the top of the list of criteria for making it onto the list was that the women had to be sharing their knowledge and experience. Some very good candidates didn’t have a strong enough presence at conferences, on YouTube, or in other media to include them. Giving voice is the only way someone can have a real impact, so being silent was a non-starter.”
What can we do to change the representation of women in AI?
“It all goes back to giving voice to our knowledge, making it known, and sharing it. The more women we hear, see, and encounter the more women can serve as examples, role models, and barrier breakers for other women and men alike.
That’s easier said than done. It’s hard for many women to take the mic or stand in front of the camera having been conditioned to keep a lower profile or stay humble. Maybe the realization that we have a responsibility to keep AI moving toward achieving the best outcome for the most people will make some of us bolder, as bold as the women on the RTInsights’ list.”