Khan argues the practice ignores uncertainty in foundational processes.
@sebkrier
Notice a trend; apply maximal myopic optimisation pressure (in your finite brain); ignore all possible adaptations, reactions, changing environments, second order effects, cost-motivated adjustments etc; obsess over the 'at the limit + all things equal' outcome and make this your main lens for everything; claim humility because you are uncertain about the outcome, while discarding uncertainty about the process. Many such cases!
Users agree with critiques spotlighting myopic optimization in tech reasoning because it precisely identifies flawed approaches in AI development.
@sebkrier The problem is this is how to be effective in a competitive environment with many high agency people competing for finite resources.
Notice a trend; apply maximal myopic optimisation pressure (in your finite brain); ignore all possible adaptations, reactions, changing environments, second order effects, cost-motivated adjustments etc; obsess over the 'at the limit + all things equal' outcome and make this your main lens for everything; claim humility because you are uncertain about the outcome, while discarding uncertainty about the process. Many such cases!
@bilaltwovec precisely
Khan argues the practice ignores uncertainty in foundational processes.
@sebkrier
Notice a trend; apply maximal myopic optimisation pressure (in your finite brain); ignore all possible adaptations, reactions, changing environments, second order effects, cost-motivated adjustments etc; obsess over the 'at the limit + all things equal' outcome and make this your main lens for everything; claim humility because you are uncertain about the outcome, while discarding uncertainty about the process. Many such cases!
