> He argues this type of value judgement is something AI fundamentally cannot do, as it can only pattern match against existing decisions, not create new frameworks for assigning worth.
Counterpoint : That decision has to be made only once (probably by some expert). AI can incorportate that training data into its reasoning and voila, it becomes available to everyone. A software framework is already a collection of good decisions, practices and tastes made by experts.
> An MIT study found materials scientists experienced a 44% drop in job satisfaction when AI automated 57% of their “idea-generation” tasks
Counterpoint : Now consider making material science decisions which requires materials to have not just 3 properties but 10 or 15.
> Redesigning for Decision Velocity
Suggestion : I think this section implies we must ask our experts to externalize all their tastes, preferences, top-down thinking so that other juniors can internalize those. So experts will be teaching details (based on their internal model) to LLMs while teaching the model itself to humans.
Counterpoint : That decision has to be made only once (probably by some expert). AI can incorportate that training data into its reasoning and voila, it becomes available to everyone. A software framework is already a collection of good decisions, practices and tastes made by experts.
> An MIT study found materials scientists experienced a 44% drop in job satisfaction when AI automated 57% of their “idea-generation” tasks
Counterpoint : Now consider making material science decisions which requires materials to have not just 3 properties but 10 or 15.
> Redesigning for Decision Velocity
Suggestion : I think this section implies we must ask our experts to externalize all their tastes, preferences, top-down thinking so that other juniors can internalize those. So experts will be teaching details (based on their internal model) to LLMs while teaching the model itself to humans.