I think we will learn a lot from AI. It will reveal inefficiencies and show us better ways to do many things. But it’s people that will find creative ways to utilize the information to create even better knowledge. AlphaZero did not create knowledge, rather it uncovered new efficiencies, and people can learn from that, but it takes a human to use what was uncovered to create new knowledge.
Alpha zero (machine learning) vs problem solving about the nature of reality:
Alpha zero is given the basic rules of the game (people invented these rules).
Then it plays a game with finite moves on a finite board. It finds the most efficient ways to win (this is where Bayesian induction works).
Now graft the game over our reality, which includes a board with infinite squares and infinite new sets of problem arise. For instance, new pieces show up regularly and the rules for them are unknown. How would alpha zero solve these new problems? It can’t, it doesn’t have the necessary problem solving capabilities which people have. What AI needs is rational criticism or creativity with error correction abilities.
Games in general solved a problem for people (this introduces a new topic but it relevant nonetheless):
Imagine if Aphazero wasn’t given the general rules of the game chess. What would happen next? The program needs to be able to identify a problem before continuing.
People had a problem of being bored. We invented games as a temporary solution to boredom.
Does an AI get bored? No. So how could it invent games (if games weren’t invented yet)? It couldn’t, not without us, because it wouldn’t know it had a problem.
The article you linked to:
Yes, we will have many uses for machine learning and AI. And it will help people come up with better hypotheses and to solve complex (mathematical) problems and improve our lives. Notice, these are complex problems, like sifting through big data and combining variables, but no creativity is needed. The problems that I am referring to are problems about understanding the nature of reality. The article refers to a machine which is going though the same trial and error process as the AlphaZero algorithm mention earlier. But, it’s People who created the ranking system of the chemical combinations mention in the article, the same way people created the game and rules of chess which AlphaZero plays. People identified the problems and solved them using conjectures and refutations. After the rules are in place, the algorithm can take over.
Lastly, it’s people that interpret the results and come up with explanations to make any of this useful.
AI—finite problem solving capabilities.(Baysianism works here)
People and AGI- infinite problem solving capabilities. (Popperian works here)
It’s a huge gap from one to the next.
I don’t expect you to be convinced by my explanation. It took me years of carrying this epistemology around in my head, learning more from Popper and David Deutsch, and the like, to make sense of it. It’s a work in progress.
Thanks for your great questions, this is fun for me. It’s also helping me think of ways to better explain this worldview.
Great questions and thank you for asking. I also had these questions come up in my own mind while learning this epistemology.
Here is how I understand the terms you mentioned:
Knowledge Information with influence. Or information that has causal power (ie. genes, ideas). Fundamentally knowledge is our best guesses.
Understanding Is part of a knowledge transfer process, which varies from subject to subject. It is the rebuilding of knowledge in ones own mind. In people it’s an attempt to replicate a piece of knowledge.
Trail and Error—Yes, I agree Alpha zero has more knowledge than Stockfish, but it’s not new knowledge to the world. Please let me try to explain, because this question also puzzled me for a while. A kind of trail and error happens in evolution as well. Genes create knowledge about the environment they live in buy replicating, with different variations (trial), and dying (error). Couldn’t a computer program do the same thing, only faster? I think it can. But in a simulated environment that people created. The difference is, genes have access to a niche in the physical world, where they confront problems in nature. They solve these problems or they go extinct. A computer program doesn’t have the same access to our physical environment. Therefore people must simulate it. But we still don’t know enough about our own environment to simulate it accurately enough, we have huge gaps in our knowledge about the laws of nature.
When a chess program, programs it’s own rules and step out of its’ game, that would hint at AGI.
Creativity in AI art generators—What you are seeing does not involve the creative process. Original art is being displayed and can be misunderstood as creative. It’s an algorithm made by people, to combine a variation of images, based on our inputs. The images are new an have never been seen before. But it’s not a creative, problem solving process that is happening.
I agree, there will be many cases where our AI will be useful and help people solve their problems, like Elisa whom you mentioned. People are still behind the scenes pulling the strings. And when people create new knowledge (like a deeper understanding phycology) we will include it in our programs and Elisa will work much better.
I really appreciate your questions. If you have anymore please don’t hesitate to ask.