PodcastsRank #18930
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Clinical Changemakers

MedicinePodcastsHealth & FitnessScienceSocial SciencesENnew-zealand
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Clinicians have trained in the art and science of medicine, and yet feel powerless to make a meaningful impact on the healthcare system.Clinical Changemakers is the podcast looking to bridge this gap by exploring inspiring stories of leadership, innovation and so much more.To learn more and join the conversation, visit: www.clinicalchangemakers.com <br/><br/><a href="https://www.clinicalchangemakers.com?utm_medium=podcast">www.clinicalchangemakers.com</a>
Top 37.9% by pitch volume (Rank #18930 of 50,000)Data updated Feb 10, 2026

Key Facts

Publishes
N/A
Episodes
30
Founded
N/A
Category
Medicine
Number of listeners
Private
Hidden on public pages

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Public snapshot
Audience: Under 4K / month
Canonical: https://podpitch.com/podcasts/clinical-changemakers
Reply rate: Under 2%

Latest Episodes

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The Ethics of AI in Healthcare: Beyond the Stochastic Parrot | Dr. Jessica Morley (Yale Digital Ethics Centre)

Wed Sep 24 2025

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"AI has the potential to re-ontologize healthcare—to completely redesign what we consider to be a disease, what we consider to be a disability, and how we organise care. But we need to decide what good healthcare actually means before we AI-ify everything." — Dr Jessica Morley In this episode of Clinical Changemakers, Dr Jessica Morley, an AI ethics expert and researcher from Yale Digital Ethics Centre, challenges our understanding of what large language models actually are and what they mean for healthcare. Drawing from her work on data ethics and her involvement with OpenSafely during the pandemic, Dr Morley explains why viewing AI as "stochastic parrots" is crucial for healthcare implementation, explores the concept of re-ontologizing medicine, and argues why we need ethical frameworks before technological deployment rather than after. Key Takeaways Stochastic Parrots in Medicine: Large language models don't understand medical concepts—they predict the most likely next word based on probability from their training data. This means they can give you different answers to the same medical question and lack the contextual understanding crucial for patient care. Understanding this fundamental limitation is essential for safe healthcare implementation. The Re-ontologizing Power of AI: AI doesn't just replace existing tools like upgrading from a physical to digital stethoscope. It has the power to completely redesign healthcare by redefining what constitutes disease, changing how we organize care, and separating diagnosis from physical patient interaction. This transformation can be powerful and positive, but only if we're intentional about our goals. The Inverse Data Quality Law: Just as the inverse care law states that those who need healthcare most get it least, the inverse data quality law means those who need AI healthcare tools most will have the poorest quality data about themselves. This creates a two-tier system where marginalized populations get inferior AI-driven care. Social License Trumps Legal Permission: Technical feasibility and legal compliance aren't enough for successful AI implementation in healthcare. Projects like the UK's Care.data failed despite being legal because they lacked social acceptance. OpenSafely succeeded by building in privacy protections, transparency, and meaningful public engagement from the start. Where to Find Our Guest Dr Jessica Morley (LinkedIn, Google Scholar) In This Episode 01:27 - Stochastic parrots: Understanding what LLMs actually do 04:27 - Emergent properties: Why LLMs remain sophisticated probability machines 11:57 - Moral worth and parasocial relationships: When humans attach meaning to AI 14:33 - Re-ontologizing healthcare: How AI redesigns medicine itself 19:28 - The ethical traps: What happens when we AI-ify without thinking about outcomes 25:33 - Two-tier systems: How AI could worsen healthcare inequalities 28:44 - Ethics vs. law: Why we need both rules and values 32:31 - Learning from NHS failures: The importance of not making assumptions 47:43 - Global policy tensions: EU regulation vs. US "let it rip" approaches 54:33 - False dichotomies: Moving beyond "some care vs. no care" thinking 59:02 - Current global sentiment: From tech optimism to healthcare caution Referenced * Dr Morley’s Paper - The ethics of AI in health care: A mapping review (link) * Defining a Stochastic Parrot (link) * OpenSafely platform and approach to health data research (link) * Lessons from Care.data project and its failure in the UK (link) Contact If you have any feedback, questions or if you'd like to get in touch, reach out at jono@clinicalchangemakers.com Hey there 🙌 As a small independent podcast, every rating and share makes a real difference in helping us reach more healthcare leaders. If you found value here, please rate us and pass this along to a colleague who needs to hear it. Clinical Changemakers is a podcast that explores inspiring stories of leadership and innovation in healthcare. To learn more and join the conversation, visit: www.clinicalchangemakers.com This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.clinicalchangemakers.com

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"AI has the potential to re-ontologize healthcare—to completely redesign what we consider to be a disease, what we consider to be a disability, and how we organise care. But we need to decide what good healthcare actually means before we AI-ify everything." — Dr Jessica Morley In this episode of Clinical Changemakers, Dr Jessica Morley, an AI ethics expert and researcher from Yale Digital Ethics Centre, challenges our understanding of what large language models actually are and what they mean for healthcare. Drawing from her work on data ethics and her involvement with OpenSafely during the pandemic, Dr Morley explains why viewing AI as "stochastic parrots" is crucial for healthcare implementation, explores the concept of re-ontologizing medicine, and argues why we need ethical frameworks before technological deployment rather than after. Key Takeaways Stochastic Parrots in Medicine: Large language models don't understand medical concepts—they predict the most likely next word based on probability from their training data. This means they can give you different answers to the same medical question and lack the contextual understanding crucial for patient care. Understanding this fundamental limitation is essential for safe healthcare implementation. The Re-ontologizing Power of AI: AI doesn't just replace existing tools like upgrading from a physical to digital stethoscope. It has the power to completely redesign healthcare by redefining what constitutes disease, changing how we organize care, and separating diagnosis from physical patient interaction. This transformation can be powerful and positive, but only if we're intentional about our goals. The Inverse Data Quality Law: Just as the inverse care law states that those who need healthcare most get it least, the inverse data quality law means those who need AI healthcare tools most will have the poorest quality data about themselves. This creates a two-tier system where marginalized populations get inferior AI-driven care. Social License Trumps Legal Permission: Technical feasibility and legal compliance aren't enough for successful AI implementation in healthcare. Projects like the UK's Care.data failed despite being legal because they lacked social acceptance. OpenSafely succeeded by building in privacy protections, transparency, and meaningful public engagement from the start. Where to Find Our Guest Dr Jessica Morley (LinkedIn, Google Scholar) In This Episode 01:27 - Stochastic parrots: Understanding what LLMs actually do 04:27 - Emergent properties: Why LLMs remain sophisticated probability machines 11:57 - Moral worth and parasocial relationships: When humans attach meaning to AI 14:33 - Re-ontologizing healthcare: How AI redesigns medicine itself 19:28 - The ethical traps: What happens when we AI-ify without thinking about outcomes 25:33 - Two-tier systems: How AI could worsen healthcare inequalities 28:44 - Ethics vs. law: Why we need both rules and values 32:31 - Learning from NHS failures: The importance of not making assumptions 47:43 - Global policy tensions: EU regulation vs. US "let it rip" approaches 54:33 - False dichotomies: Moving beyond "some care vs. no care" thinking 59:02 - Current global sentiment: From tech optimism to healthcare caution Referenced * Dr Morley’s Paper - The ethics of AI in health care: A mapping review (link) * Defining a Stochastic Parrot (link) * OpenSafely platform and approach to health data research (link) * Lessons from Care.data project and its failure in the UK (link) Contact If you have any feedback, questions or if you'd like to get in touch, reach out at jono@clinicalchangemakers.com Hey there 🙌 As a small independent podcast, every rating and share makes a real difference in helping us reach more healthcare leaders. If you found value here, please rate us and pass this along to a colleague who needs to hear it. Clinical Changemakers is a podcast that explores inspiring stories of leadership and innovation in healthcare. To learn more and join the conversation, visit: www.clinicalchangemakers.com This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.clinicalchangemakers.com

Key Metrics

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Pitches sent
18
From PodPitch users
Rank
#18930
Top 37.9% by pitch volume (Rank #18930 of 50,000)
Average rating
N/A
Ratings count may be unavailable
Reviews
N/A
Written reviews (when available)
Publish cadence
N/A
Episode count
30
Data updated
Feb 10, 2026
Social followers
612

Public Snapshot

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Country
New Zealand
Language
English
Language (ISO)
Release cadence
N/A
Latest episode date
Wed Sep 24 2025

Audience & Outreach (Public)

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Audience range
Under 4K / month
Public band
Reply rate band
Under 2%
Public band
Response time band
Private
Hidden on public pages
Replies received
Private
Hidden on public pages

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Presence & Signals

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Social followers
612
Contact available
Yes
Masked on public pages
Sponsors detected
Private
Hidden on public pages
Guest format
Private
Hidden on public pages

Social links

No public profiles listed.

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Monthly listeners49,360
Reply rate18.2%
Avg response4.1 days
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Frequently Asked Questions About Clinical Changemakers

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What is Clinical Changemakers about?

Clinicians have trained in the art and science of medicine, and yet feel powerless to make a meaningful impact on the healthcare system.Clinical Changemakers is the podcast looking to bridge this gap by exploring inspiring stories of leadership, innovation and so much more.To learn more and join the conversation, visit: www.clinicalchangemakers.com <br/><br/><a href="https://www.clinicalchangemakers.com?utm_medium=podcast">www.clinicalchangemakers.com</a>

How often does Clinical Changemakers publish new episodes?

Clinical Changemakers publishes on a variable schedule.

How many listeners does Clinical Changemakers get?

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