Beyond Perfection - How AI Unleashes Creativity by Lowering Our Standards - Tiago Forte

author:: Tiago Forte
tags:: #source/article AI Creativity
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The paradoxical conclusion of all this is that, for the highest-performing professionals at the top of their game, the bottleneck to their growth is in learning to lower their standard of quality.

Second, delivering at a lower level of quality is not just a matter of stopping when you reach a certain point. It requires you to understand which dimensions of quality can be sacrificed, and which still need to be maximized.

Third, working at lower levels of quality surprisingly requires more advanced communication and collaboration skills.

Other people and stakeholders have to be ready to receive the “quick and dirty” draft you’ve made, which means you need to prepare them in advance. It’s of no use to deliver it in half the time if they aren’t ready and it will just sit around collecting dust. The way you communicate has to change because you have to calibrate the expectations of your collaborators so they consider the big picture instead of zeroing in on some inconsequential detail.

It turns out that in order to learn faster, you have to expose yourself: to people’s opinions of you and your work, to the consequences of mistakes and failures, to the disappointment of a promising new experiment not working out. You’re going to need more emotional fluidity to be able to pivot abruptly from one promising direction you may already be invested in, to another more promising one.

At every level, our society and politics and economy and culture are all shifting far faster than ever before, and in more unpredictable ways. Quality is no longer about sticking faithfully to a timeless process passed down through the generations. It depends instead on your ability to maintain situational awareness about your environment and adapt your thinking and behavior to match it.

The word “quality” has a moralistic connotation that implies more of it is always better than less.

The word “fidelity” means “faithfulness,” as in “How faithful should this deliverable be to the ultimate version of what it could be?”

But fidelity is also a morally neutral term, conveying that more is not necessarily better.

But there is a lot of value in failed experiments – they reveal what isn’t true, doesn’t work, or isn’t worth pursuing.

this may be the greatest impact of AI tools in the short term: allowing us to quickly create low-fidelity, 80/20 prototypes

Many of the “intermediate” stages of our workflows include this kind of categorization, analysis, chunking, decision-making, and planning of tasks. By replacing these intermediate stages with AI, I think our time and attention will get freed up to spend in two places: the very beginning of our creative process – deciding which information to capture as inputs in the first place – and the very end of our creative process – polishing and refining the final product to perfection as only humans can.