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.
You’re welcome, and thanks for the reply. I’m enjoying our conversation.
What about:
ai art as an example of human creativity
ai generating hypotheses that humans could not, seemingly demonstrating human creativity
ai generating theorems (conjectures, refutations), in old systems back in the 60′s
If the concerns are:
creativity in response to real-world events
ability to increase understanding of a novel environment without aid from a predefined ontology, except for testing behaviors learned by mimicry
ability to improve epistemological distinctions
then I think future developments in robotics will satisfy human intuitions of what it takes for an agi to be an AGI. We can see the analogies between robot behavior and human behavior more easily, and they will be an easier proof of AGI functionality of the kind that your worldview denies.
EDIT:When the robots are controlled or communicated with by external AI using input from robot sensors or external sensors, we will have a fuller idea of the varieties of experience and learning that are humanlike that AI can demonstrate.
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.
You’re welcome, and thanks for the reply. I’m enjoying our conversation.
What about:
ai art as an example of human creativity
ai generating hypotheses that humans could not, seemingly demonstrating human creativity
ai generating theorems (conjectures, refutations), in old systems back in the 60′s
If the concerns are:
creativity in response to real-world events
ability to increase understanding of a novel environment without aid from a predefined ontology, except for testing behaviors learned by mimicry
ability to improve epistemological distinctions
then I think future developments in robotics will satisfy human intuitions of what it takes for an agi to be an AGI. We can see the analogies between robot behavior and human behavior more easily, and they will be an easier proof of AGI functionality of the kind that your worldview denies.
EDIT:When the robots are controlled or communicated with by external AI using input from robot sensors or external sensors, we will have a fuller idea of the varieties of experience and learning that are humanlike that AI can demonstrate.