why aren't all 33 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
Prediction Not checkable as stated
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.”
Prediction Not checkable as stated
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.”
Assertion Partly supported
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…”
Prediction Not checkable as stated
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.”
Assertion Contradicted
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…”
Prediction Open · timeframe Aug 2021
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.”
Prediction Open · timeframe Aug 2031
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.”
Prediction Not checkable as stated
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?”
Assertion Not checkable as stated
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…”
Prediction Not checkable as stated
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…”
Assertion Not checkable as stated
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.”
Prediction Not checkable as stated
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…”
Prediction Not checkable as stated
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.”
Assertion Supported
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 …”
Assertion Not checkable as stated
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, …”
Assertion Supported
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…”
Assertion Supported
Domingos: Automated Robot Scientist 'Eve' Discovered a New Malaria Drug
“A couple years ago, Eve actually discovered the new malaria drug.”
Prediction Not checkable as stated
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…”
Assertion Supported
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.”
Prediction Not checkable as stated
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.”
Assertion Supported
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.”
Prediction Not checkable as stated
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.”
Prediction Not checkable as stated
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.”
Assertion Not checkable as stated
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”
Prediction Not checkable as stated
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…”
Prediction Not checkable as stated
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.”
Prediction Not checkable as stated
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.”
Assertion Supported
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.”
Assertion Supported
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…”
Assertion Partly supported
Domingos: IBM's Deep Blue Used Classical Search With No Machine Learning
“So Deep Blue was very much classic AI. There was no machine learning involved. Deep Blue essentially, it was just doing a very a clever and very extensive search for the best moves to make.”
Assertion Supported
Domingos: AlphaGo Combined Classical AI Search With Deep Learning Neural Networks
“And so what DeepMind did with AlphaGo was to actually combine some of the classic AI, you know, game search with deep learning, with this type of you know, neural network approach to do the evaluation.”
Assertion Supported
Domingos: AlphaGo Trained on 30 Million Human Moves Before Self-Play
“So AlphaGo, the first thing that AlphaGo did was it learned from all the existing, the entire existing database of Go matches played by human masters. That was the first thing it did was learn from those, right? Thirty million moves or something like that is t…”
Assertion Supported
Domingos: AI Self-Play Dates Back to Arthur Samuel's 1950s Checkers System
“This is actually a very, very old idea in machine learning. It's one of the oldest ideas. It goes all the way back to the fifties. And this researcher at IBM called Arthur Samuel, who actually wrote the first machine learning system to learn to play a game. An…”