Beyond Automation: How to use First Principles to Find AI's Next Big Disruptions?
Hey PH Fam!
We're all seeing AI transform industries, but are we looking deep enough? I've been thinking about applying first-principle thinking to identify areas truly ripe for AI disruption – going beyond automating existing tasks to fundamentally reimagining solutions.
Instead of asking 'How can AI make X better?', what if we ask:
What is the core human need X is trying to solve?
What are the fundamental limitations of current solutions, pre-AI?
If we were to solve this need from scratch today, with current AI capabilities (LLMs, generative models, etc.) as a core building block, what would it look like?
To get the ball rolling, here are a couple of 'first-principle' observations that point to potentially massive opportunities:
First-Principle Observation: Many crucial human needs for guidance, support, or specialized knowledge are constrained by the 24/7 availability and linear scalability of human experts. While the need can arise anytime, access to the right expert in the moment of need is often impractical.
Use-Case Example that highlights this: Think about a person needing a critical, unexpected medical emergency at 2 AM and needing immediate, high-level specialized healthcare-service. Or consider someone needing instant, personalized support to process a difficult emotional situation as it happens, rather than waiting for a scheduled appointment.
The idea here isn't to jump to AI solutions yet, but to use these kinds of fundamental observations to pinpoint areas where current limitations create significant unmet needs or inefficiencies.
What other core human needs, or fundamental limitations in how things are currently done, can we identify that might be completely re-architected if AI capabilities were a foundational assumption?
Replies