We know more than we can tell

Tacit knowledge as the basis for everything else

Reflect back over your life. Your career. At point X can you describe how you got there with precision? What about point Y? Is it possible to verbalize exactly what decisions contributed to what you’ve become?

No? What about the inflection points? You probably can describe those.

Think about the current organization you work for. Can you pinpoint why its explicitly successful? If you could, could you codify it?

Maybe you were Ben Girard writing “The Google Way”. You outline unique-at-the-time management practices such as: adopting an innovation culture where failing fast is revered, data used to guide decision making, an organizational structure that is largely flat and a premium placed on hiring the best.

Now we “know-that”. And many organizations have since tried to copy the model.

But what about the specific “know-how” cultivated as a by-product of cultural exchange?

The tacit knowledge that dwells in our awareness.

A bit over a decade ago, in an e-mail I sent to friends, I described the Google of then — non-pejoratively — as “adult college”.

A place where we all had names, “noogler”, “greygler”, “spoogler”, etc, ate together, engaged in shared leisure activities and learned from our surroundings and the people in them.

The details themselves are less important than the value signified.

At Google, what you implicitly learned and importantly felt was a sense of shared responsibility through unification towards a common purpose.

This understanding was continuously re-impressed through each personal experience amidst a backdrop of abundance. Even now, it’s hard to explicitly express. And still challenging to replicate.

But those who revere that other mind—the one we all share, as humans and as citizens—aren’t interested in other things. Their focus is on the state of their own minds. —VI. 16

Onto Polyani

Imagine rebuilding a simulation of the Google of 2014. You could codify most of Girard’s identified practices. The raw knowledge is there and can be expressed in propositional form. But to imbue the simulacra inhabiting the representation with sentience untainted by the unmistakable smell of synthetics would be near impossible.

See Michael Polyani risked his reputation as many great thinkers do and committed to a hypothesis.

One with extraordinary relevance even today.

Human knowledge of how the world functions and of our own capability are, to a large extent, beyond our explicit understanding.

Or simply: we know more than we can tell.

This was the premise of his seminal 1966 work “The Tacit Dimension”. And was also explored in “Personal Knowledge”.

The structure identified is that we experience the world by integrating our subsidiary awareness into a focal awareness.

Think about reading. You understand the meaning of a letter with your focal awareness and simultaneously understand grammar, syntax and words with your subsidiary awareness.

MIT Economist David Autor gave a name to the observation: Polyani’s paradox in the context of exploring employment growth and automation — or why there are still so many jobs even despite advances in mechanization, robotization and computerization.

A decade ago it was a truism that the skill of a driver would be difficult to replace through schooling on the history of the motorcar. It still is despite advancements in autonomy.

Explicit and tacit knowledge complement one another. And tacit knowledge is gained through nuanced personal experience which we struggle to describe.

There are many critics of this paradox. Recent advances in machine learning powering current state GPTs provide proof points in the ability for tacit rules to be more readily statistically learned from abundant data and context.

Today

Technological progress marches forward. CAPEX is plunged at extraordinary rates into hardware and infrastructure to continue capitalizing on scaling laws. The bet is that they will continue.

Scaling laws: you get an improvement in quality by spending a lot more. That’s what they mean.

And it’s why, despite Wall Street’s recent myopic focus on ROI, neither Google, META, Microsoft, NVIDIA, etc truly care.

As Larry Page has reportedly said: "I am willing to go bankrupt rather than lose this race” towards generational model improvements leading to AGI. Because as the thinking goes — that competent AGI, even if not sentient (a non-requirement), will be worth 10s or 100s of trillions in value.

Amidst this race, one thing should remain clear to you and I.

Personal knowledge shaping our human intelligence — learned explicitly, descriptively and tacitly — will always be important.

It shapes who we are and what we can do. Individually and collectively.

And has been the basis for most everything else.