Dec 27, 2023

John Vervaeke and guest Sam Tideman delve into the
intricate world of artificial general intelligence (AGI) and its
intersection with healthcare. Sam, an expert in biostatistics,
machine learning, and AI, shares valuable insights from his
professional experiences, particularly in healthcare system
optimization. The conversation navigates the ethical and moral
challenges of applying AI in complex environments like emergency
departments, the intricacies of predictive modeling, and the
broader societal implications of AI, including its energy
consumption and public perception. This episode is essential
listening for anyone interested in understanding the nuanced
interplay between technology, healthcare, and ethics, offering a
comprehensive perspective on the current and future potential of AI
to transform lives and systems.

Sam Tideman, an accomplished healthcare data scientist
with an MS in Biostatistics, blends his analytical acumen with a
passion for theology in his podcast, “Transfigured.” The podcast
features long-form discussions exploring the identity of Jesus,
reflecting Sam’s unique intersection of scientific expertise and
spiritual inquiry.

Glossary of Terms

AGI (Artificial General Intelligence): An AI that has
the ability to understand, learn, and apply its intelligence to a
wide range of problems, much like human intelligence.

Biostatistics: The application of statistics to a wide
range of topics in biology.

Resources and References:

Dr. John Vervaeke: Website | YouTube | Patreon | X | Facebook

Sam Tideman: YouTube

The Vervaeke
Foundation

John Vervaeke YouTube

Awakening from the Meaning Crisis – series

Artificial Intelligence – series

The Crossroads
of Predictive Processing and Relevance Realization | Leiden
Symposium

Books, Articles, Publications, and Videos

Mentoring the Machines: Orientation – Part One: Surviving the Deep
Impact of the Artificially Intelligent Tomorrow – John
Vervaeke, Shawn Coyne 

Mentoring the Machines: Origins – Part 2: Surviving the Deep Impact
of the Artificially Intelligent Tomorrow – John Vervaeke, Shawn
Coyne 

Predictive processing and relevance realization: Exploring
convergent solutions to the frame problem. Phenomenology and
the Cognitive Sciences. Andersen, B., Miller, M., & Vervaeke, J.
(2022).

Related Resources

Chicagoland
Bridges of Meaning Meetup

Chapters with Timestamps

[00:00:00] Introduction of Sam Tiedemann and Episode
Overview 

[00:01:15] Sam’s Background and Intersection with
AI 

[00:04:11] The Role of AI in Healthcare and Emergency
Departments 

[00:14:26] The Limitations of AI in Morally Complex
Environments 

[00:24:34] Discussion on AI’s Capability to Predict
vs. Normative Decision-Making 

[00:53:06] The Energy Consumption and Environmental
Impact of Training AI Models 

Timestamped Highlights

[00:00:00] John opens the discussion by welcoming Sam
and introducing the topic of artificial general intelligence
(AGI).

[00:01:15] Sam shares his diverse background, which
spans theology, philosophy, and artificial intelligence.

[00:06:15] The conversation focuses on AI’s potential
and dangers, setting the stage for the day’s discussion.

[00:09:28] Sam reflects on the complexities he faced
while trying to implement AI in emergency department
forecasting.

[00:14:53] Sam points out the practical limitations of
AI in real-world applications.

[00:21:38] Sam criticizes the inflated expectations
surrounding AI in healthcare projects.

[00:26:26] John and Sam discuss how predictive
processing and relevance realization can be integrated into AI.

[00:29:37] They delve into the potential of AI to
emulate human qualities like intentionality and care.

[00:34:11] John emphasizes the need to recognize the
limitations of AI in solving complex real-world problems.

[00:38:30] Sam’s parable features an AI model in
healthcare that prescribes drugs probabilistically and learns from
outcomes, hinting at AI’s emerging agency.

[00:42:10] The feasibility of AI replicating human
intuition and judgment in complex scenarios is questioned.

[00:46:15] John highlights the importance of a
multidisciplinary approach to understanding and developing AI.

[00:49:57] Philosophical aspects of AI, such as
intentionality and consciousness, are explored in-depth.

[00:53:30] Sustainability concerns in AI development,
especially compared to the human brain’s efficiency, are
discussed.

[01:06:40] The episode concludes with a discussion on
AI’s inability to align with human normativity and the limitations
of its social, cultural, and biological understanding.