The output produced by generative AI is only as good as the data the AI tool is trained on. And when that data is sourced from human beings, it always carries a risk of bias—because we, as humans, are inherently biased. This presents a unique ethical challenge for AI users, particularly in healthcare, where the use of AI has the potential to impact client lives. But on the other side of the coin, AI can actually help mitigate bias and act as a catalyst for health equity. The key is understanding how these tools work—and harnessing that knowledge to use AI technology carefully, cautiously, and intentionally.
In this episode of No Notes, our host Denny Morrison, PhD, chats with Alison Cerezo, PhD, Senior Vice President of Research at mpathic AI, about the current state of bias and ethics in AI—and what behavioral health professionals can do to help ensure these tools are used to support, rather than detract from, equitable behavioral healthcare.
