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Quality vs. Efficacy: Learning with AI
AI is often described as tireless, structured, and reactive, much like a parrot that can mimic human speech without true understanding. The advancement of technology makes it plausible for AI to appear more capable than it is. Concerns exist about AI's risk in sensitive areas like therapy, with reports of hackers weaponizing AI tools. The author adopted a conservative approach to AI, fearing it would hinder their programming learning and career entry, a fear that proved somewhat valid. Despite an attempt to use an LLM as a surrogate mentor, the author found it could not replace genuine human mentorship. Technological advances, particularly in AI, challenge our understanding of problem-solving and deep thinking. While computers advanced gradually, AI's computational scaling has had an exponentially greater and deeper impact. This impact is compared to the computer revolution, with AI's influence being a thousand times greater. AI is transforming tedious tasks and even replacing earlier software solutions with AI agents. The author experimented with using an AI as a coding mentor, acknowledging that the effectiveness relies on prompting skills.
