Gilmartin also emphasized the value of thinking of AI tools as human-first tools. By involving people with different backgrounds in the development process, not only can applications be created that employees and customers will actually use, but it also brings new ideas for AI projects. Calendly encourages collaboration among teams with diverse expertise to ensure a human-centric approach to AI development.
Other speakers at the event echoed the idea that AI still needs human involvement, especially when the end product is intended for use by people. The problem with excluding other perspectives in the development of generative AI is that it becomes difficult to build comfort and trust among a wider set of users once the product is available. An example was provided using Amazon’s Alexa, where early testing primarily involved men, resulting in Alexa being better at recognizing male voices. Research now shows that women tend to yell at Alexa to get it to understand them.
However, convincing people that they can contribute to the development of generative AI applications can be challenging. Many individuals, especially women and those without a formal machine learning background, feel apprehensive due to a lack of time or fear that their lack of knowledge will hinder their ability to make meaningful contributions. Aparna Sinha, Head of AI Product at Capital One, believes that individuals from various backgrounds can play a role in AI development by experimenting with and using the technology.
The speakers also acknowledged that now is an opportune time to get involved in AI, as there are numerous tools, podcasts, and videos available to help individuals get up to speed. It is important to carve out time to learn and experiment with AI tools, as this will contribute to the overall improvement of the technology. Ultimately, the consensus among the speakers was that more people from diverse backgrounds need to participate in the development of AI applications to ensure their success and effectiveness.
