The author also introduces the concept of an AI Impact Matrix, which organizes AI models from a use case that optimizes a pain point for an individual to a disruptor that personalizes solutions and impacts communities at a system level. The article concludes by reminding readers that while AI excels in complex activities, it falls short in uniquely human activities like reasoning, judgment, imagination, empathy, creativity, and problem-solving. Therefore, the most useful AI models are those that involve humans and are grounded in the problem they're solving.
Key takeaways:
- AI models should be built with a focus on the most commonly overlooked categories: children and aging adults living in low-income communities, and self-insured employers.
- AI's ability to manage complexity and see connections can unlock personalized care at scale, moving beyond aggregate generalizations to cater to individual needs.
- When assessing an AI solution, it's important to consider whether it's intended to optimize, transform or disrupt the current state, as this will impact how you engage with the solution and the value you derive from it.
- Successful AI models are those that keep humans in the loop and stay grounded in the problem they're solving, excelling in complex activities while falling short in uniquely human activities like reasoning and empathy.