AI is a Floor Raiser, not a Ceiling Raiser¶
A reshaped learning curve¶
Before AI, learners faced a matching problem: learning resources have to be created with a target audience in mind. This means as a consumer, learning resources were suboptimal fits for you:
You're a newbie at $topic_of_interest , but have knowledge in related topic $related_topic . But finding learning resources that teach $topic_of_interest in terms of $related_topic is difficult.
, but have knowledge in related topic . But finding learning resources that teach in terms of is difficult. To effectively learn $topic_of_interest , you really need to learn prerequisite skill $prereq_skill . But as a beginner you don't know you should really learn $prereq_skill before learning $topic_of_interest .
, you really need to learn prerequisite skill . But as a beginner you don't know you should really learn before learning . You have basic knowledge of $topic_of_interest , but have plateaued, and have difficulty finding the right resources for $intermediate_sticking_point
Roughly, acquiring mastery in a skill over time looks like this:
What makes learning with AI groundbreaking is that it can meet you at your skill level. Now an AI can directly address questions at your level of understanding, and even do rote work for you. This changes the learning curve:
Experts in a field tend to be more skeptical of AI. From Hacker News:
[AI is] shallow. The deeper I go, the less it seems to be useful. This happens quick for me. Also, god forbid you're researching a complex and possibly controversial subject and you want it to find reputable sources or particularly academic ones.
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