AI in Healthcare: Teaser Module 15 ( Algorithmic Fairness: What Clinicians Should Understand)

Added: 2026-05-10

[00:00:04]Welcome to the module 50.

[00:00:06]We have two eminent speakers to take us through this.

[00:00:10]Dr. Avnish Kumar, a clinician turned AI educator, researcher, and advisor, actively driving medical AI literacy at scale through his flagship AI uh that is made AI capsule initiative.

[00:00:24]He is a certified AI professional and faculty contributed to the national programs.

[00:00:29]And his clinical insights with the structured AI education, he made significant impact on the societies of many young and budding oncologist.

[00:00:39]We want to understand is it safe, ethical, and what is a orientation at which the AI should be seen? That's what he's going to teach us.

[00:00:50]And to moderate the session, we have another eminent personality, Mr. Rajiv Sharma. He's the founder and CEO of Advize.

[00:00:59]He brings deep expertise in digital ecosystems, AI-enabled decision support, and large-scale system transformations.

[00:01:07]With prior leadership experience at Bayer Crop Sciences, he has driven data-driven interventions impacting millions at grassroots level.

[00:01:15]Welcome, Dr. Avnish and Mr. Rajiv.

[00:01:18]Avnish, what are you going to teach us today?

[00:01:25]Uh hello, Dr. Suresh. So, thank you for the kind introduction.

[00:01:29]I'll be introducing basically what clinicians should understand about fairness and why this topic of fairness becomes so important when we're talking about AI. Uh we are doing fair uh practice in our clinical work from day to day, but when AI comes into the picture, then things like equality, equity, calibration, parity, all those things become very important.

[00:01:53]So, it is very important for clinicians to understand why if I am using AI on particular patient, whether it is going to cause any unfairness for a particular group of patients because see, ultimately we clinicians are are the safeguards of our patients, as as you can see. And it is our duty to be at that point where our clinical judgment becomes central in deciding whether the use of AI is fair or not.

[00:02:25]Uh so, it's a we'll be seeing all the tradeoffs like what happens as as as the world says, you cannot get everything. So, if you if you are trying to focus on one particular metric, then the other metric has to be balanced and also how you should fairness from a comprehensive lens.

[00:02:45]So, not just about accuracy, not just about some metrics like you see, but it should be a comprehensive measure of how you should look at fairness.

[00:02:56]And ultimately, my key message would be that fairness is a clinical decision and not a formula. So, that I will be emphasizing throughout my session on Wednesday.

[00:03:06]That's great, Avnish. Rajiv, you have been in the industry for so long.

[00:03:11]And what the points Dr. Avnish touches is very important. It's always a tradeoff. You gain something at the cost of something else.

[00:03:19]Okay. So, as the industry perspective or as a technocrat, what exactly is your two cents for the listeners?

[00:03:29]Almost 70,000 doctors are listening on the national platform.

[00:03:33]Please, let us know, Dr. Rajiv.

[00:03:36]Yeah, thank you, Dr. Suresh, for the background. And thanks, Dr. Avnish, for providing the context of what you are going to communicate to a very large and relevant audience. So, basically, from my perspective, you know, this is a very important topic.

[00:03:53]Um and this is so relevant in today's world that what I call it's a collaboration and partnership between experience and technology.

[00:04:06]So, these are two things. And from the perspective of you know, from the patient's perspective, I think I'll be more vocal from their side because at the end of the day, the technology has to help, support, and heal leveraging your experience of you know, decades of wisdom which you have been taught as professionals, which you have practiced as practitioners.

[00:04:33]So, I I think from the patient perspective, one of the biggest challenge which you know, professionals need to look at is how do you create trust among your you know, audience, in this case, the patients. That is the biggest challenge. The second one is how do you leverage AI?

[00:04:58]It's kind of bringing thousands and thousands of experts and years of wisdom together and extracting the best out of it. And then through your lens of relevance, your lens of balancing, how do you filter it off and communicate to your patient so that number one, the trust is built.

[00:05:20]Number two, the AI doesn't or the technology doesn't influence in a very different way. It doesn't try to please the doctors or the patient. It should authenticate the data and then provide you the inputs which you can leverage. And the third thing is it should not hallucinate. I mean, it's a very important trap we should try to you know, avoid. And what AI you know, having used AI in various industries, how do you figure out ways of avoiding AI trying to please its user or hallucinate and communicate things which could take the whole treatment in a different direction. So, I think that's the background with which I would you know, like to communicate from the patient's behalf for his particular benefits. Thank you.

[00:06:12]>> Wonderful, Rajiv. That's so precisely put. So, Avnish, we are very very eager to hear you and then learn from you. And most important, probably if you can just touch upon how to avoid hallucination traps as a special topic, maybe one slide or two, is going to really help the audience in a big way. Once again, stay tuned. The meeting is on May 6th. That is Wednesday evening, 4:00 p.m. to 5:00 p.m. Thanks, Rajiv, for accepting to join as a moderator. As usual, Dr. Avnish is always there for AI in medical education. Thanks once again, Avnish, to you know, accept to take this topic forward. Thank you very much. Thank you.