How voice data is being used with AI to generate "predictive" medical diagnoses

A new episode of the podcast In Machines We Trust explores how universities, medical researchers, practitioners, and the private industry use AI as a diagnostic tool for medical issues. "Hidden away in our voices are signals that may hold clues to how we're doing, what we're feeling, and even what's going on with our physical health. Now, AI systems tasked with analyzing these signals are moving into healthcare."

It explains how Menlo College used AI predictive algorithms to detect depression and other psychological issues during the second year of the ongoing COVID-19 pandemic. Then, interviews with leaders of start-up companies explain using voice as data markers to reverse engineer this data to determine the physiological effects of depression, for example, on the body. The episode concludes with a discussion about the bioethical implications of the data collected and patient privacy issues. An insightful point about the power of AI predictors is the number of data sets available for measurement in relation to human memory.

"A podcast about the automation of everything," and a production of the MIT Technology Review, In Machines We Trust "thoughtfully examines the far-reaching impact of artificial intelligence on our daily lives. Hosted by Jennifer Strong, the series explores the rise of AI through the voices of people reckoning with the power of the technology, and by taking listeners up close with the inventors and founders whose ambitions are fueling the development of new forms of AI, with far-reaching implications we're only just beginning to understand."

David Leibowitz writes in Toward Data Science that these news research studies conclude "that causal machine learning models are not only more accurate than previous AI-based symptom checkers for patient diagnosis but, in many cases, can now exceed the diagnosis accuracy of human doctors. That's mainly due to the methods used, which allow for a more 'outside the box' creativity in diagnosis, and even more improved accuracy for more complex patient illness."

The far-reaching implications of AI are mapping new possibilities for healing and challenging existing structures of creativity and culture, profit and business. Check out this NPR report about the striking movie, TV writers, and AI.

Business Insider recently interviewedBjoern Schuller, professor of artificial intelligence at Imperial College London, featured in the podcast episode, about how AI will "soon write better novels than humans."