Pedro Domingos
Professor Emeritus, University of Washington · 1 appearance on the record.
computed by AI from the episodes · how this works → · full disclaimer →
academicscientistauthorexecutive@pmddomingos ↗homes.cs.washington.edu/~pedrod ↗Wikipedia ↗
Pedro Domingos is an artificial intelligence researcher known for introducing Markov logic networks and authoring The Master Algorithm. He co-founded the International Machine Learning Society and previously served as the Head of Machine Learning at D. E. Shaw & Co.
51statements → 33claims → 13claims resolved → 77%fully supported → 3.67/5average certainty → 2.24/5average debate potential → ≈4.5/5argument clarity, estimated →
10 supported 2 partly supported 1 contradicted 2 not yet assessed 18 not checkable as stated how the 33 claims stand · each chip opens the sources
16 predictions · 17 assertions · 2 opinions · 16 insights · every statement was checked. The predictions and assertions are the 33 claims: statements the public record can support or contradict. 13 are resolved, 2 are not yet assessed, and 18 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 Pedro argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.
Their most notable supported claim
Domingos: Some Hedge Funds Are Completely Run by Machine Learning
“So for example, these days there are hedge funds that are completely run by machine learning algorithms for the most part, you know, hedge fund will use machine learning as one of its inputs. But there are some where the machine learning algorithms, they look …”
Their most notable contradicted claim
Domingos: Machine Learning Algorithms Typically Outperform Human Doctors in Medical Diagnosis
“Machines are remarkably better than human doctors at doing all types of medical diagnosis, not just from x-rays, but from, you know, symptoms, right? You have a patient, you have their symptoms, what is the diagnosis? And even very simple machine learning algo…”
Expressed certainty vs assessment result
weighted support: a fully supported claim counts one, a partly supported claim counts half. Each filled bar is clickable and opens exactly those claims; "none yet" means nothing said at that certainty level has resolved yet
How they sound: not measured why? →
We measure speaking style by listening to the audio itself, and a fair number needs at least 2,000 words from one person on tape we have measured. There is too little of Pedro Domingos on measured tape to publish a rate. This says nothing about how they speak.
Everything Pedro Domingos said on the Knowledge Project that made the record, most notable first. Filter by type, assessment or year in the ledger →
Domingos: Doctors Gatekeep Medical AI to Prevent Automating Their Own Jobs
“In the particular case of medicine, it's not used more already because, of course, the doctors are also the gatekeepers Of the system, and they're not very interested in replacing themselves or their job that they like best by machines.”
Domingos: AI Will Plateau Rather Than Experiencing Infinite Runaway Intelligence Growth
“And I think they will be in the case of AI, but I don't think we're going to see this, you know, infinite growth that, you know, goes completely beyond you know, what humans can imagine.”
Domingos: Computers Will Soon Discover and Store Most Knowledge on Earth
“So in the not too distant future, the vast majority of the knowledge on earth
Will be discovered and will be stored in computers.”
Domingos: A Venture Capital Fund Appointed an Algorithm as a Voting Director
“For example, there's this venture fund recently that announced that one of their directors is now going to be an algorithm. There's seven directors on the board, and one of them's an algorithm. So their algorithm doesn't decide anything all by itself, but it d…”
Domingos: Researchers Can Develop a Single Universal Master Algorithm for ML
“But what I and others believe is that we can Develop a true master algorithm, meaning an algorithm that is able to solve all the different kinds of learning problems that these different algorithms can.”
Domingos: Achieving a Universal Master Algorithm Requires Entirely New AI Paradigms
“And my gut feeling is that actually it's more the latter. I do believe that we have made a lot of progress, but I think we are still missing some important ideas.”
Domingos: White-Collar Jobs Like Engineering Are Easier to Automate Than Blue-Collar Work
“So people often think that the easiest jobs to automate are like the blue collar ones. But actually our experience in AI is that it's actually more the opposite. It's often white collar jobs that are easy to automate. For example, things like engineering and, …”
Domingos: Machine Learning Algorithms Typically Outperform Human Doctors in Medical Diagnosis
“Machines are remarkably better than human doctors at doing all types of medical diagnosis, not just from x-rays, but from, you know, symptoms, right? You have a patient, you have their symptoms, what is the diagnosis? And even very simple machine learning algo…”
Domingos: Commercial Airplane Cockpits Will Transition from Two Pilots to Zero
“We already have two people in the cockpit instead of three, and then we'll have one and eventually we'll have zero.”
Domingos: Most Cars Will Be Self-Driving Between 2026 and 2031
“But I, my guess is that, you know, five years from now, there will be a lot of self-driving cars around and, you know, maybe 10 years from now, 15, Most cars will be self-driving.”
Domingos: Incremental Autonomy Wins Short Term, But Full Autonomy Prevails Long Term
“So, but I think that in the short term the approach of the Teslas and the Toyotas and whatnot will be the prevalent one. I think in the longer run, it will be the Google approach that prevails, right?”
Domingos: Basic ML Often Outperforms Highly Trained Human Pathologists
“And the thing that's amazing is that often just by taking a basic machine learning algorithm and applying on a database of, for example, x-rays and diagnosis, you actually wind up with something that is better. That, for example you know, pathology than a high…”
Domingos: Human Common Sense Will Prevent AI From Quickly Replacing Workers
“I think as time goes forward, you know, the machine learning will get better using a broad spectrum of information. I think for a long time, there will still be Types of common sense knowledge that people have. So I don't think for most things you know, the hu…”
Domingos: Outsiders Are More Likely Than AI Researchers to Create Paradigm Shifts
“Part of my goal in writing the book was to try to get people from outside the field interested in these problems, because in some sense they are more likely, ironically, to have these new ideas than the people who are already professional machine learning rese…”
Domingos: Stock Prediction Neural Networks Decay Within Weeks as Rivals Model Them
“And what typically happens when somebody, you know, deploys a neural network to predict, you know, a certain stock, like for example, you might have 3000 networks each predicting one stock in, in, in the Russell 3000 is that it works for a few weeks and then i…”
Domingos: Startups Can Dominate by Applying Basic ML to Untapped Industries
“Precisely because machine learning is something that can be used just about everywhere, right? In every single industry, in every single part of what a company does, So far, it's only been used for a small fraction of the things that it could be used for. So y…”
Domingos: Commercial Aviation Would Be Safer Flown Entirely by Computers
“And in fact, it would be safer if it was completely flown by a computer. You know, pilots tend to take, you know, the controls at landing and takeoff, which are actually the more dangerous moments. And they make more errors than the computers do.”
Domingos: Technology Growth Curves Are S-Curves, Not Perpetual Exponentials
“I think that argument is actually very dubious, because in reality, no exponential goes on forever. Because there's always a limit because the world is finite. So actually what happens with all of these technology curves is that in the beginning they look like…”
Domingos: Machine Learning Algorithms Do Not Have to Be Black Boxes
“Actually, the learning algorithms don't have to be black boxes. There's actually no reason why I shouldn't be able to say to the Amazon recommender system, why did you recommend that book to me? Or, you know, I just bought a watch. Please don't recommend more …”
Domingos: Autonomous Cars Could Compete in the Indy 500 Within Years
“Well, I think we could at this point actually, and it might actually win. I think in the past, the technology wasn't ready. And then once the technology is ready that people have to let it happen, right? So the Indy 500 would have to let a self-driving car com…”
Domingos: Mixed Human-Machine Driving Control Is Inherently Dangerous
“This notion of a mix of mixed control between the human and the car is actually very problematic. If someone is not driving the car and then suddenly the computer says like, oh, shoot, I'm confused. Take over. Then the person will not be very well able to take…”
Domingos: Machine Knowledge Discovery Will Be as Momentous as Evolution
“And I think this emergence of computers as a source of knowledge is going to be every bit as momentous as the previous three were.”
Domingos: Some Hedge Funds Are Completely Run by Machine Learning
“So for example, these days there are hedge funds that are completely run by machine learning algorithms for the most part, you know, hedge fund will use machine learning as one of its inputs. But there are some where the machine learning algorithms, they look …”
Domingos: A Single ML Algorithm Can Master Multiple Domains via Data
“In traditional computer science, you need to write down a different algorithm for everything that you want to do. So if you want the computer to do diagnosis, you need to explain to it what are the rules of that diagnosis. If you wanted to play chess, you need…”
Appearances (1)
| Episode | Date | Speaking time |
|---|---|---|
| #13 Pedro Domingos: The Rise of The Machines | Aug 30, 2016 | 46m |