Hard Things Look Easy / Easy Things Look Hard
The Counter-Intuitive Trajectory of Computers and the Use Cases they Enable
Computers are funny. They naturally know how to compute (obviously), then they learn to read, and then now they are starting to see and hear.
This runs totally opposite to humans, who naturally know how to see and hear, then learn to read, then compute.
That suggests a rule of thumb: tasks that are hard for us are easy for computers, and vice-versa. This is why computers complement us so well, and why they engender so much amazement. This also explains why computers are so damn hard to program.
AI like ChatGPT elevate all these to a whole new level. The amazement is beginning to metamorphose into fear because computers have gotten so good at tasks that challenge and baffle even supposedly smart humans. These are the things that look hard for us but turn out easy for computers:
- Writing poems that rhyme
- Translation
- Navigation
- Playing chess and Go
- Generating code
- Summary and synthesis of key points
- Making music
- Creative visualization
- Crafting essays
- Copywriting
These are tasks that we typically deem ‘intellectual’ — the domain of the creative elite. We are seeing an AI-induced existential crisis because computers are now beating the humans we typically hold in high regard — the poets, musicians, coders, chess players, and copywriters.
Creative was supposed to be the last industry for tech to disrupt. Now it’s turning out to be the first (mainly because it is low-stakes and high tolerance for error). If we extrapolate this trend, it is natural to wonder whether computers will simply beat out humanity, because it is already trouncing the best of us.
But that is a slippery slope, because we have to remember that tasks that are trivial and easy for us are actually hard for computers:
- Dancing and choreography
- Moving up and down the stairs
- Cooking, packing, and serving food
- Driving
- Playing sports
- Massage therapy
- Fishing and farming
- Sales
- Asking questions
- Making decisions
- Reading emotions
So humans are not out just yet. Could it just be a matter of time? That remains to be seen.
Maybe the lesson here is that we should hold these ‘simple’ jobs in equal regard as the ‘smart’ jobs? These elite jobs are turning out to be easy, while the supposedly more humble jobs are turning out to be hard.
AI has upended the equation. Computers are changing our definition of what is smart. Would the wage situation flip as well?
Maybe the other lesson here is that we are heading towards a race of sorts, where the white-collar and creative elites compete on who can maximize AI to augment their core jobs, while the rest get left behind.
My fearless forecast is that we are heading towards a world that looks like a smiling curve — an AI-augmented elite who maximize these tools up on the left, the hard-to-replace manual jobs up on the right, and the mediocre white-collar surplus elites drooping in the middle.
The only sensible path forward is to stay ahead of this curve.
