As part of TechCrunch’s ongoing Girls in AI collection, which seeks to present AI-focused girls teachers and others their well-deserved — and overdue — time within the highlight, TechCrunch interviewed Marissa Hummon, the chief know-how officer on the vitality firm Utilidata, the place she is working to make the electrical grid extra sustainable.
“The work that I’m doing at Utilidata is pushing towards the established order of the utility business,” Hummon advised TechCrunch, including that AI is poised to assist the utility sector function extra successfully. “It’s going to give utilities the instruments they should function a clear, trendy, and dependable grid that can higher serve the folks and companies linked to it.”
Hummon began her profession on the Nationwide Renewable Vitality Lab, the place she centered on transfer the vitality business away from carbon-intensive options to extra clear sources. She recalled having to take a brand new modeling strategy as a result of sure physics equations have been “unsolvable utilizing conventional analytic strategies.”
“As a substitute we would have liked to make use of numerical strategies and machine studying,” she stated. This was again in 2010.
Recommendation to girls
Hummon moved her manner up, working on the vitality firm Tendril earlier than touchdown the CTO position at Utilidata, a place she’s held since 2018. She obtained a PhD in utilized physics from Harvard and stated that as she made the transition from grad faculty into the engineering subject, she seen a big drop within the variety of girls working within the subject. “I’ve typically felt the stress of being held to the next customary within the office in comparison with my male friends,” she stated.
Hummon stated now as a pacesetter she tries to guide by instance and create alternatives for girls to guide and be acknowledged. On the similar time, males have to be answerable for creating house for extra girls to enter and keep within the subject, she stated.
“The change we’d like isn’t just in follow; it should be systemic and widespread,” she continued. “It begins with recruiting and hiring, continues with mentoring and training, and culminates with truthful and equitable recognition and promotion — all whereas making a protected and inclusive office.”
Her recommendation to girls coming into the AI subject is to at all times do not forget that being a lady may be a bonus. “It’s given you a perspective that’s completely different out of your male friends and breakthroughs in know-how at all times come from distinctive views.”
She says to hunt alternatives with firms which have proven their dedication to variety and which have leaders who’ve showcased their efforts to help girls and minorities. “Choose a possible employer by the way in which they present up within the interview course of, not by the statements or the studies they placed on their web site.”
Constructing moral AI
Hummon stated that customers ought to know that AI is just not one thing that may resolve all issues however fairly is an knowledgeable assistant to boost operations, enhance effectiveness, and assist help.
“Recognizing its limitations and making certain there are correct checkpoints is essential,” she stated.
She stated it’s at all times vital to grasp how generative AI was educated and constructed as a way to perceive any potential biases it may have. “This data is a robust software when working with language fashions for information evaluation and evaluating the feasibility of options,” she continued. “AI is just pretty much as good as the information and data it was educated on.”
She additionally gave some recommendations on construct protected AI, explaining that Utilidata made an early choice to maintain all of its information native. “Approaching mannequin constructing utilizing distributed AI computing reduces the quantity and frequency of data being transmitted to the cloud and subsequently reduces the probabilities of a safety or privateness breach.”
As for traders, she stated — like all the consultants we spoke to — they should consider how an organization desires to make use of AI, particularly since accountable AI appears to be like completely different in each business. “The funding in accountable AI ought to be commensurate with the danger and complexity of any given firm, not an across-the-board customary.”
