John Wang sharing his thoughts on why executives are enamoured by AI.
Executives have always had to deal with non-determinism. That’s par for the course:
- People being out sick or taking time off unexpectedly
- Someone not finishing an important project and not talking about it until far too late in the process
- People reacting to an announcement in an unexpected way
- A feature being built in a way that doesn’t make sense with respect to the rest of the product, but does technically achieve objectives.
More generally, if you’ve ever taken a Chaos Theory class in math, you’ll know that nonlinear, chaotic systems emerge when individual agents in a system are all acting with different inputs, utility functions, etc. Systems become slightly easier to manage if you’re able to make those utility functions consistent (you’re able to get a grasp on system dynamics).
A manager’s job is to create a model of the world and align everyone’s utility functions, knowing that there’s a large amount of non-determinism in complex systems. So it makes sense that as a manager, you’re ok with a decent amount of this.
AI is something that is non-deterministic but has a lot of characteristics of a well behaved chaotic system (specifically a system where you can understand the general behavior of the system, even if you cannot predict the specific outcomes at any point in time).
For example:
- LLMs generally continue their work and provide an output regardless of time of day, how difficult the task is, how much information is available
- LLM’s deficiencies have well defined failure modes (e.g. hallucinations, lack of ability to operate outside of their context, and especially poor outcomes when not given enough context)
- The types of tasks that an LLM can accomplish are relatively well known, and the capability envelope is getting mapped out quickly. This is different than humans, where each person has a different set of strengths and weaknesses and where you need to uncover these over time.
Many of these properties are more deterministic than large human systems, which makes AI incredibly attractive for an executive who is already used to this and likely has put a large amount of effort into adding determinism into their systems already (e.g. by adding processes and structure in the form of levels and ladders, standard operating procedures, etc.).
Intriguing.
He also talks about why individual contributors are sceptical of AI.