What are some unresolved theories in AI

I made a short list of problems or areas in AI that I struggle to find answers on or simply understand. And I wonder if some of us also have similar issues about AI in general. The field of machine learning is growing so fast to keep track of everything evolving.

1. What is the computational complexity class of problems that humans can solve but artificial intelligence cannot?

2. Can neural nets always solve problems better than social nets (collective of people)?

3. Is there an Ecological Approach to Computer Visual Perception? JJ Gibson proposed a treatise of vision as related with objects around, so is an agent affected by its environment (similar to the concept of phenotropic computing by Jaron Lanier)

4. Does the presence of an agent affect the environment and model in Reinforcement Learning?

4.1 What is the causality of having an agent present in the environment, does its presence affect the reward system. In quantum computing each measurement affects the environment.