AI improvements are not even across the board. While some tasks have become incredibly advanced, other simple tasks still trip them up, showing that not all intelligence is equal.
We should be cautious about assuming that increases in one type of AI ability mean it can do everything we can. Each skill in AI may develop separately, like bagels and croissants in baking.
Understanding what makes intelligence requires looking deeper than just performance. There is a difference between raw capabilities and the contextual, real-life experiences that truly shape how we understand intelligence.
There are two main ways people understand the world: one focuses on strict evidence and science, while the other values common sense and personal experience. Both have their strengths and weaknesses depending on the situation.
The 'fractal ratchet' concept explains how deeper scrutiny often leads to discovering more detail, but it can also make comparisons difficult. When you look at things more closely, you might keep finding more complexity instead of reaching a clear 'true' answer.
When making decisions or forming opinions, it's important to know when to rely on precise measurements and scientific reasoning versus when to trust your intuition and common sense. Balancing both approaches can help you navigate complex issues more effectively.