A question of power?

One of the core criticisms of platforms is that they have become far too powerful. While this is more of a throw-away comment, it is interesting to examine it up close to see if it can be turned into a hypothesis and tested – and what I am most interested in testing is not if platforms have become too powerful, since that will be a subjective evaluation, but rather if they are more powerful now than 10 years ago.

In order to test this we need an operational definition of power. One of the simplest and best definitions of power is found in Max Weber’s work – he defines power as the probability that you get your way in given the sum total resistance from other parties. This probability then is the measure of power – if 100% you are all-powerful in a social system, and 0% you are utterly powerless.

If you can complete your projects with a high probability, even in the face of resistance from other parties, you have a lot of power.

Weber’s definition of power is probabilistic and operational

Armed with this definition we can now do a counter-factual thought experiment – we can look at projects that platforms and tech companies executed on historically and ask if they would have a higher or lower probability of success today.

  • Take the Google Books-project. Is the probability higher or lower that Google would be able to complete a project to scan all the world’s books today than ten years ago?
  • Or StreetView – if Google announced today that it would travel all the world’s streets and record imagery to enable better navigation, would the probability that they were able to complete that project be higher or lower than ten years ago?
  • Or Libra – is the probability that Facebook succeeds with an alternative crypto currency launch of the same ambitions it had in the first launch lower or higher?
  • Would Facebook be more likely or less likely to be able to acquire Instagram or Whatsapp today than they were when they acquired them?

It seems obvious, then, that tech companies actually have less power today than they did 2, 3 or 10 years ago – at least by the design of this experiment.

Now, you can criticize the design of the experiment, but by this definition of power applied to these counter-factuals, well, it seems as if Big Tech has less – not more – power.

But there is a difference, you may argue, between having more or less power and having too much power. I readily concede that this may be the case, and if we can find an operational way to think about power that shows it I would be interested in what that is.

Power has fascinated social scientists for a long time, and as a result there is a plethora of different definitions of power, but a few interesting forms of power that would reward further exploration, I think, include:

  • Innovation power – this ability is divided into two, and we can use the myth that Plato has Socrates tell about Toth and Thamus to illustrate it. In the myth Toth is the genius inventor that develops new technologies and ideas, and Thamus is the king and ruler that decides if these inventions should be made publicly available. These two forms of power are closely related – Toth’s power to invent and Thamus power to disseminate. We probably undervalue what it means that a lot of both kinds of power reside firmly in the tech sector, and is found in large tech companies. They invent and disseminate the future.
  • Recruiting power – the ability to find the finest and most creative minds and attract them to an organization is a transformative power that also leads to a generative advantage – it strengthens the innovation power referenced above. This, too, I think is severely undervalued.

There is much more to say about this, but any discussion of power would benefit from a closer examination of what we mean by using the term and how we can test our assumptions.

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