The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 51 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 2 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
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…”
Domingos: Neural Network Opacity Often Precludes Deep Learning From Practical Deployment
“With some types of machine learning, like, for example, neural networks and deep learning, it's very opaque, right? What is learned is this big jumble of lots of parameters and all near functions, and nobody really understands what's going on. Which, in fact, …”
Domingos: Knowledge Induced From Empirical Data Is Inherently Uncertain
“Any knowledge that you induce from data is necessarily uncertain, because you never know if you generalized correctly or didn't.”
Domingos: Humans Are Systematically Overconfident in Evolutionary and Cultural Knowledge
“Conversely, a lot of the knowledge that we have from evolution and from experience and from culture, we often tend to think of it as much more certain than it really is. We have this great tendency that's been well studied by psychologists to be overconfident …”
Domingos: Machine Learning Masters Single Domains While Humans Synthesize Broadly
“Machine learning today is very good at learning about one thing at a time. The thing that humans have is that they can bring to bear knowledge from all sorts of directions.”
Domingos: Evolutionary Machine Learning Generated Patented Circuits Outperforming Human Designs
“People have developed new types of radios and amplifiers and electronic circuits using this type of machine learning, and they've actually gotten patents for them. So they work better than the ones that were developed by human engineers. They're typically comp…”
Domingos: Automated Robot Scientist 'Eve' Discovered a New Malaria Drug
“A couple years ago, Eve actually discovered the new malaria drug.”
Domingos: Medical AI Diagnosis Will Spread Initially in Low-Resource Settings
“But, you know, eventually it is going to happen, and it is starting to happen, for example, in situations where doctors are not available, and so nurses can use this, or for patients that need, you know, constant monitoring, or in low resource situations where…”
Domingos: Human-AI Centaur Teams Outperform Standalone Computers in Chess
“The best chess players in the world today are what are called centaurs in the community. They're a team of a human and a computer. So a human and a computer can actually, together, can actually beat the computer.”
Domingos: Human-Computer Collaboration Will Work Best for Most Jobs
“But I think for the foreseeable future in most jobs, it will be a combination in human and computer that works best.”
Domingos: The Stock Market Is Largely Algorithms Modeling Each Other
“The stock market is largely a bunch of algorithms trading against each other. And in fact, what these algorithms are doing Whether or not they know it is modeling each other.”
Domingos: Data Network Effects Create Major Competitive Moats for Machine Learning Incumbents
“There's this network effect of data where if you have a good product and people start using it, then you have a lot of use this, for example, you know, how Google has built up such an unassailable position in search, right? Is like you use their search engine.…”
Domingos: Consumer Adoption of AI Will Force Doctors to Adapt
“And once, for example, these machine learning systems become more widely available as they are becoming, people will start using them and the doctors will be forced to catch up.”
Domingos: Machines Will Handle Most Decisions While Humans Retain Key Choices
“Ultimately I think most things will be done by machines, except the really key decisions that people will always want to retain, even though they make them with advice from the machines.”
Domingos: AI Has Not Yet Achieved Continuous Recursive Self-Improvement Loops
“Having said that, this is still quite limited in what it can do, and it's not, we don't have enough at this point for this thing to set up this loop where it just keeps getting better and better. That hasn't happened yet”
Domingos: Machines Will Build Far More Complex Models Than Humans Can
“So what's going to happen is that the machines are going to be able to learn much more complex models of the phenomena than human beings ever could, and this is good, right? Because with those better models, we can make better decisions. With a better model of…”
Domingos: Machine Learning Algorithms Will Get Better at Explaining Themselves
“I think what's going to happen is that partly the learning algorithms are going to have better, to get better at explaining to people what they're doing.”
Domingos: Human Competition Will Endure Despite Superhuman Computers
“I think more likely what will happen is that people will still be playing each other, even though the best is our computers in the same way that, you know, there's race cars that go way faster than people. But we still have people doing, you know, in the Olymp…”
Domingos: Autonomous Vehicles Only Need to Beat Humans, Not Reach Perfection
“The cars don't have to be perfect before we start using them instead of people. They just have to get better than people.”
Domingos: Symmetry Group Theory Could Spark Machine Learning's Sixth Paradigm
“Because I think this is something that has not been exploited in machine learning and might be the origin of that sixth paradigm.”
Domingos: Major ML Algorithms Are Mathematically Proven Universal Function Approximators
“And there are several major such algorithms today that have mathematical proofs that if you give them enough data, they can learn any function.”
Domingos: Understanding Learning Algorithms Differs From Understanding Their Output Models
“Having said that, you know, we, the machine learning researchers and the data scientists, we actually have a good understanding of how the learning algorithm itself works. You know, what is it that it does to learn, and how could you make it learn better? And …”
Domingos: Deploying Machine Learning Causes Subjects to Adapt Adversarially
“So what happens whenever you deploy a machine learning system is that the people who are being modeled Change their behavior in response to the system. Sometimes in benign ways, but sometimes in adversarial ways.”
Domingos: Netflix and IBM Watson Already Use Basic Forms of Meta-Learning
“And this type of meta learning in certain basic forms is actually already widely used today. Like for example, Netflix uses this type of thing to recommend movies. It doesn't just use one learning algorithm. It uses a whole bunch of them. And then another algo…”