Morgan P. Lorio, MD, FACS
speaker
125 appearances
1 recordings
1 series
first heard Mar 2026
last heard 27 Mar
Morgan P. Lorio, MD, FACS’s voice in public audio — every appearance, attributed to the second.
Trend
recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Mar 2026 with 1.
Appearances
Complex patients often generate more uncertainty and variability in outcomes, but those are frequently the patients who need the most thoughtful care.
If systems begin to prioritize predictability above all else, there's a risk that the most complex patients may become harder to treat.
Just over a year ago, I had the opportunity to participate in a global 50 roundtable organized by the Dubai Future Foundation, where experts from multiple sectors were asked to consider possible futures roughly five decades from now.
My perspective in that discussion came from two places.
My international policy work in spine surgery through ISS and my experience as a practicing surgeon.
One idea emerging from that initiative is a classification framework describing how humans and artificial intelligence collaborate in the production of knowledge and decisions.
The framework uses simple visual markers to indicate the degree of human involvement
in AI-assisted work ranging from fully human activity to machine-dominant processes, with several intermediate stages representing different levels of collaboration and oversight.
The purpose is transparency.
As artificial intelligence becomes more deeply embedded in research, analysis, and communication, it will become increasingly difficult to determine how much of an output reflects human judgment versus machine computation.
A clear labeling system helps make that relationship visible.
From a clinical perspective, this aligns closely with something we have long emphasized in medicine, surgeon-in-the-loop governance.
Artificial intelligence may assist with analysis, pattern recognition, and data synthesis, but clinical responsibility and decision authority remain human.
In the terminology of the Debye framework, this approach would be classified as human-led AI.
Yeah, there's another dimension to this conversation that we don't always acknowledge.
AI increasingly influences how we write, whether drafting clinical notes, summarizing literature, or producing scientific manuscripts.
When technology influences how we write, it inevitably influences what we write.
Knowing who or what produced it is therefore important.
This can be categorized across six levels, human only, human directed,
human-led, machine-assisted, machine-dominant, and machine-only.
Showing 61–80 of 125 · page 4 of 7
← Previous
Next →