Good exploration, but I’m not sure I agree with the thesis. Often there’s a ton of complexity in the search and refinement of a simple result. You can’t start with the simple model and assume away the creation of that model (or if you prefer, the identification of that model in model-space).
Most clinical trials are very simple statistical models. There are not trillions of parameters in a complex neural network architecture. Yet they are still the most effective tools we have at validating and optimising health and recovery in human beings.
Simply wrong. Clinical trials are required for final validation and regulatory compliance, but they’re not effective at all for optimizing health or recovery in human beings. They are a tiny part of the search and development of an intervention. There are multiple complex neural network architectures (many inside peoples’ heads, and many on fairly complicated data-processing systems) required to get to the point of even thinking about the clinical trials.
If there was a piece of content so convincing … would not require a complex statistical model.
Also incorrect. It would almost certainly require a complex model to find/create that content, possibly anew for each susceptible human.
They are a tiny part of the search and development of an intervention.
I agree that there is complexity in healthcare that is not explained by a simple statistical model, my point is that the final layer often is a simple statistical model that drives a lot of the complexity and the outcomes. Making a drug is much more complex than deciding which drug to give, but that decision ultimately drives the outcomes.
Also incorrect. It would almost certainly require a complex model to find/create that content, possibly anew for each susceptible human.
Same point as above. If there were a piece of content that worked for all humans then a simple model would suffice (multi-armed bandit for example) and if the content doesn’t exist, people are incentivised to create it
Good exploration, but I’m not sure I agree with the thesis. Often there’s a ton of complexity in the search and refinement of a simple result. You can’t start with the simple model and assume away the creation of that model (or if you prefer, the identification of that model in model-space).
Simply wrong. Clinical trials are required for final validation and regulatory compliance, but they’re not effective at all for optimizing health or recovery in human beings. They are a tiny part of the search and development of an intervention. There are multiple complex neural network architectures (many inside peoples’ heads, and many on fairly complicated data-processing systems) required to get to the point of even thinking about the clinical trials.
Also incorrect. It would almost certainly require a complex model to find/create that content, possibly anew for each susceptible human.
I agree that there is complexity in healthcare that is not explained by a simple statistical model, my point is that the final layer often is a simple statistical model that drives a lot of the complexity and the outcomes. Making a drug is much more complex than deciding which drug to give, but that decision ultimately drives the outcomes.
Same point as above. If there were a piece of content that worked for all humans then a simple model would suffice (multi-armed bandit for example) and if the content doesn’t exist, people are incentivised to create it