Podcast Summary: Artificial Intelligence and Mental Health [Part 1]
AI can sound like science fiction, but it’s already part of your daily routine—and it’s rapidly transforming how healthcare works, too. In a fascinating conversation between Dr. Parikh and Dr. Frank Rudzicz, an expert in speech and AI, we get a clear picture of how AI is not just about robots or self-driving cars, but about software that helps us make decisions, save time, and even diagnose illness.
Wait… Am I Already Using AI?
Yes, you are—and you’ve probably been using it for years without realizing it.
From Google searches to the spam filter in your inbox, AI is quietly working behind the scenes. When you ask Siri or Alexa to play your favourite song, you’re engaging with narrow AI—systems trained to do one specific task well. Even tools like Google Search involve AI; it’s just not always as obvious as something like ChatGPT responding with full sentences.
“So it’s not apples and oranges. It’s two different flavours of apples,” Dr. Rudzicz jokes, comparing Google Search to conversational AI tools like ChatGPT.
What exactly is AI?
There’s no single definition of AI, and that’s part of what makes it so complex—and so fascinating. Some experts see it as software that mimics human behaviour, others view it as systems that follow logical rules, and still others focus on its design to reflect human-like thinking using models like neural networks.
But in general, AI refers to software that acts in ways we consider “intelligent.”
“So many definitions, but generally, it’s trying to get software to behave intelligently and perform tasks that normally require what we call intelligence.” — Dr. Rudizicz
Machine Learning: Is it Different from AI?
AI is a big umbrella, and Machine Learning (ML) sits right under it. While traditional AI systems rely on hard-coded rules written by experts, ML allows computers to learn from data automatically.
In healthcare, this means moving from rigid systems that identify conditions based on fixed checklists, to smart models that learn from thousands (or millions) of patient cases to make predictions or offer insights.
AI in the Clinic: From Scribes to Diagnoses
Dr. Rudzicz is especially optimistic about how AI can revolutionize healthcare, particularly in clinical environments where time and attention are stretched thin.
- AI Scribes Imagine a doctor-patient conversation being automatically transcribed and summarized by AI in real time. That’s what AI scribes do. They extract key information and automatically populate electronic medical records. The benefit? Doctors can spend more time with patients and less time on paperwork. In fact, some studies suggest this kind of automation could free up about seven hours per week for family physicians.
- Listening for Illness One of the most compelling areas Dr. Rudzicz discusses is using AI to detect early signs of diseases like Alzheimer’s just by analyzing how someone speaks. By listening to short clips of speech, AI can pick up on subtle patterns—pauses, filler words, vocabulary shifts—that might indicate cognitive decline, depression, or other neuropsychiatric conditions. What’s even more fascinating? These tools sometimes match or outperform human experts in consistency.
“I am very optimistic about the applicability of machine learning across the entire healthcare spectrum. And from the first moment that someone walks into a hospital or is wheeled into a hospital to the moment they’re eventually discharged, I think there’s nothing but opportunities for AI. How we apply AI or machine learning in each of these opportunities is going to differ on a case-by-case basis.” — Dr. Rudzicz on the use of AI in healthcare
Final Takeaway
AI isn’t just coming—it’s already here, quietly helping in ways most people don’t even realize. In healthcare, it holds real promise for reducing burnout, improving early diagnosis, and making care more accessible. The key is understanding how to use it responsibly and effectively.
This summary has been adapted from Part 1 of our special two-part podcast series on artificial intelligence and mental health. Listen to the full episode here, and stay tuned for Part 2!