Jay Komarneni

Founder and Chair, Human Dx · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

founderexecutivehumandx.org ↗

Jay Komarneni founded The Human Diagnosis Project (Human Dx), combining physician collective intelligence and machine learning to map clinical symptoms to diagnoses. Prior to Human Dx, he advised healthcare organizations at McKinsey & Company and Bain & Company.

6statements → 3claims → 1claims resolved → 4/5average certainty → 1.83/5average debate potential →

0 supported 1 partly supported 0 contradicted 2 not checkable as stated how the 3 claims stand · each chip opens the sources

3 assertions · 3 insights · every statement was checked. The predictions and assertions are the 3 claims: statements the public record can support or contradict. 1 is resolved, and 2 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Jay argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

How they sound: speaking style how? →

227 words/min while actually speaking · 16.2 um and uh per 1k words

No argument clarity score for Jay Komarneni: no usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 2,600 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Jay Komarneni said on the a16z Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Assertion Partly supported
HumanDX: Physician collectives outperform 90% of individual doctors in diagnostic accuracy
“We're now seeing that a collective of multiple physicians can outperform 90 plus percent of individual physicians.”
Jay Komarneni Jan 2, 2019 ▶ 10:21 a16z Podcast | The Taxonomy of Collective Knowledge
Insight
Jay Komarneni: Human input is required for human-interpretable AI ontologies
“The only way you're going to get the representations that are most valuable to humans is from human beings themselves, right?”
Jay Komarneni Jan 2, 2019 ▶ 4:23 a16z Podcast | The Taxonomy of Collective Knowledge
Insight
Komarneni: Token rewards incentivize decentralized collective intelligence and knowledge creation
“The ability to ultimately compensate people with application specific tokens is a really interesting incentive to use ontologies and distributed knowledge creation, collective intelligence to come to better answers around given issues or given problems.”
Jay Komarneni Jan 2, 2019 ▶ 21:50 a16z Podcast | The Taxonomy of Collective Knowledge
Insight
Jay Komarneni: Human intelligence excels at multi-scale data synthesis
“One place where that you see that natural place that humans are really good is when there's a high number of scales of different types of information or data, right? So, for example, in healthcare, everything from how your mitochondria or the electron transpor…”
Jay Komarneni Jan 2, 2019 ▶ 22:51 a16z Podcast | The Taxonomy of Collective Knowledge
Assertion Not checkable as stated
Jay Komarneni: HumanDX rewards physicians based on medical data demand
“In human DX, we actually like to use what we call impact in the system, and it allows us to differentially provide contributors who contribute more valuable contributions to the system in terms of what contributions the system most needs. So perhaps there's a …”
Jay Komarneni Jan 2, 2019 ▶ 19:33 a16z Podcast | The Taxonomy of Collective Knowledge
Assertion Not checkable as stated
Komarneni: Duolingo inspired HumanDX's gamified clinical case interface
“Louise had actually his work on Duolingo and really kind of this idea of creating these micro interactions that almost have this gamified structure was really a major inspiration also for the way that we built HumanDX to be these brief interactions where you c…”
Jay Komarneni Jan 2, 2019 ▶ 20:05 a16z Podcast | The Taxonomy of Collective Knowledge

Appearances (1)

EpisodeDateSpeaking time
a16z Podcast | The Taxonomy of Collective Knowledge Jan 2, 2019 13m
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 1,000 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.