Question: There is something called a goal setting problem. It applies both to humans and artificial intelligence. When a person sets a goal for himself he needs to evaluate whether it is good or bad in a global sense and  whether it brings him closer to something or moves him away from it.

This evaluation is done on both a genetic level and on the basis of moral principles acquired from society and the laws of the state.

When artificial intelligence is being trained, a problem arises in how to evaluate its actions, because if even a single factor is not taken into account, the artificial intelligence might ignore it. Let us assume the task is to plant a field of strawberries without harming any humans. If the factor of not harming humans is ignored and not included in the overall algorithm, it will lead to significant harm. This is an intricate and complex system that is impossible to design perfectly from the start.

How can we determine what is good and what is bad? I understand that this is a higher-order problem. But still, on the basis of what can be done or at least to come closer to the conclusion that it is good and what is not?

Answer: First, if something is done for the benefit of people—not just for one individual or a single group, but for the benefit of all people—then it is considered good. Second, it is considered good if it does not cause irreparable harm to nature in the process. That is all, really.

These two rules are essentially complex, but they encompass a lot within them.

Question: Is this similar to Kabbalistic definitions where seemingly simple definitions contain the entirety of the universe or the whole path of humanity from the beginning to the ultimate goal? How do you operate with such things in practice?

Answer: Only under the condition of proper education for all the inhabitants of the planet. That is, to load the right information into a person in the course of life and work it out with him until it becomes a practical necessity and reality.
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From KabTV’s “Kabbalah Express” 7/31/23

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