There is a debate around the concept of free will and determinism. Some argue that people’s actions are determined by their history and environment, while others argue there is an element of choice and responsibility.
Feelings and emotions play a role in influencing people’s choices and likelihood of taking certain actions. Negative feelings discourage actions while positive feelings encourage actions.
There are probabilistic factors that influence people’s choices, based on their needs, drives and context. But ultimately people still have some level of responsibility for their choices.
Machine learning models can generalize beyond the training data by bringing something new to the table, not just based on their history. This makes it difficult to determine if a model’s behavior was purely determined or involved some intrinsic factors.
Models that generalize in a similar way to how a human would, seem more understandable and responsible for their behavior.
Models built from similar “stuff” as the environment they are trying to understand, are more likely to induce and generalize correctly.
There could be universes where induction and generalization break down because things are built from fundamentally different “stuff”.
Cases of people with brain abnormalities show that the brain can compensate and perform normally through plasticity, as long as the abnormality has been present from an early age.
There are likely limits to the density of information and capacities that the brain can store per unit volume.
The discussion raised interesting questions about free will, determinism, generalization and the nature of intelligence that are worth exploring further.
There is a debate around the concept of free will and determinism. Some argue that people’s actions are determined by their history and environment, while others argue there is an element of choice and responsibility.
Feelings and emotions play a role in influencing people’s choices and likelihood of taking certain actions. Negative feelings discourage actions while positive feelings encourage actions.
There are probabilistic factors that influence people’s choices, based on their needs, drives and context. But ultimately people still have some level of responsibility for their choices.
Machine learning models can generalize beyond the training data by bringing something new to the table, not just based on their history. This makes it difficult to determine if a model’s behavior was purely determined or involved some intrinsic factors.
Models that generalize in a similar way to how a human would, seem more understandable and responsible for their behavior.
Models built from similar “stuff” as the environment they are trying to understand, are more likely to induce and generalize correctly.
There could be universes where induction and generalization break down because things are built from fundamentally different “stuff”.
Cases of people with brain abnormalities show that the brain can compensate and perform normally through plasticity, as long as the abnormality has been present from an early age.
There are likely limits to the density of information and capacities that the brain can store per unit volume.
The discussion raised interesting questions about free will, determinism, generalization and the nature of intelligence that are worth exploring further.
https://www.youtube.com/watch?v=pMTuWL2vDoY