Women leaders assert: Generative AI needs humans in the loop

Building tools with generative AI has never been easier, but developers must also remember to experiment and focus on human end-users, speakers at the sixth annual Women in AI Breakfast at VB Transform said.

The sold-out breakfast, presented by Capital One, highlighted the importance of bringing in different points of view and expertise in the fast-changing environment of generative AI.

Jessica Gilmartin, chief revenue officer at Calendly, said today that while so much of generative AI is exciting, the technology shouldn’t be the goal at the end of the day.  

“AI is great, but you have to build for humans and work with them. Technology enables change; it cannot be the end result,” Gilmartin said. 

She added that thinking of AI tools as human-first tools brings people of different backgrounds into the development process that not only ensures applications employees and customers actually use, but also brings new ideas for AI projects.

Gilmartin said that at Calendly, the company encourages teams to include people with different expertise to collaborate. Other speakers echoed the idea that AI still needs a human in the loop, especially if the end product is meant to be used by people anyway. 

The problem with not opening up the development of generative AI to other perspectives is that once the product is available, it becomes difficult to build comfort and trust for a wider set of users. Moderator Noelle Russell, founder and chief AI officer of the AI Leadership Institute, used the example of Alexa, Amazon’s home speaker assistant. Russell said that early in the development of Alexa, both and women were invited to help test it. But it was mainly men who showed up. So, Alexa learned to recognize male voices better than female voices, and now research shows women tend to yell at an Alexa to get the assistant to understand them.

However, it isn’t always easy to convince people that they can play a role in bringing generative AI applications to life. 

Encouraging experimentation

A big reason why women, and those without a formal machine learning background, feel apprehension when using AI products is the lack of time. Another reason is fear that their lack of knowledge of the technology means they will not find a use for it or contribute to its development in a meaningful way.

“Lots of people don’t have a generative AI background because it’s new. I believe that you can use your background if it’s in education, English, legal, you can play a role in AI development, you just need to experiment with it and actually use the technology,” said Aparna Sinha, head of AI Product at Capital One. 

Acknowledging the speed of development, LinkedIn‘s head of Data and AI, Ya Xu, said, “There’s no better time to jump into AI” than now, with several tools, podcasts and videos pointing to the best research papers to get up to speed now available. Kari Briski, vice president of AI models, software, and services at Nvidia, pointed out it’s essential to carve out the time to learn tools and play around with AI.

What is clear, the speakers said, is that people have to become comfortable with AI tools and in the process of building applications with the technology, it will only become better if more people of different backgrounds participate in developing it.