There has never been a better time to live in the better part of North America, i.e. Toronto.
One of the perks you get is to attend talks given by famous people. For example, I saw Ted Chiang in person at one of UofT’s event (in-person only, not live-streamed/recorded) last month where he gave a talk on how written language has changed human cognition.
In Chiang’s view, written language is fundamentally different from oral language. Written language makes human think more clearly and makes it possible to organize thoughts through writing. However, because humans are very accustomed to written language and many of us have received training since an early age, sometimes we forget that written language is not an innate part of human as oral language is.
In other words, if you’re reading this, you have mastered a piece of powerful technology with high expressive power that transformed your cognition to an entire level up. Look at you, a Cyborg.
During the Q&A, the audience inevitably asked about his view on Artificial Intelligence (AI) and how AI would change human cognition, perhaps in a similar fashion written language did.
Since I was inspired by his view on the relationship of human and AI it surprised me that Ted Chiang was not too excited about AI changing human cognition in the near future. Much more down-to-earth and less-philosophical, the strongest impact from technologies like Machine Learning (ML) and AI, in his view, is the power of seeing patterns that are invisible to human eyes.
Just like the impact of electron microscopes on medical science, big data processed via ML is very helpful to fields like biology. In less scientific fields like product management, ML and AI are likely the most useful when employed in areas like data visualization instead of changing human cognition all at once.
It was definitely not Ted Chiang’s intention but the analogy between data visualization and electron microscopes gave me a lightning strike, metaphorically speaking. It challenged everything I thought to be true about the value of analytics.
A couple years ago I wrote about my take on the value of analytics. Through an extreme thought experiment I came to the conclusion that as access to information becomes much easier in the future, the true value of an analyst comes from helping stakeholders asking the right questions.
I assumed that information access would be changed fundamentally. Everything else would stay the same. Stakeholders would be lost in the ocean of information. Analysts would hold onto the right of insights.
Data visualization, along with other data tools and skills are just footnotes. Only the right question matters.
Now I see why my original analysis is flawed.
What I left out is the possibilities of stakeholders working with analysts to become more data fluent throughout the process. Information doesn’t have to form an ocean if there are key metrics as lighthouses. Insights is not a right of analysts but rather for everyone. Decision making is not a once and for all activity but rather a process. Forget about “stakeholders” and “analysts”. There is no you and me.
A less poetic way of putting this is that analytics is not supposed to be transactional. Analysts are not magicians who drag a bunny out of a hat and go “Voila, there you go.” And of course in this case the bunny is the insights, the hat is the data, and the magical word is a link to a well-titled Google Sheet with proper access granted.
If not “just ask questions”, then what? Great question - a question will only exist in written language. See how cleverly I tied the argument back to the first half of this thing.
I don’t know, is the answer. I’m still experiencing the cognitive dissonance Ted Chiang gave me. But fortunately rethinking could be the beginning of a new theory. Until then, you’re still encouraged to just ask questions.
:-D
References:
1. How to Pick a Career (That Actually Fits You)
2. Just ask questions
3. Disband the analytics team
4. A possible future for expanding cognition: Ted Chiang shares thoughts on being a cyborg — Schwartz Reisman Institute