AI at the Intersection: The A16z Investment Thesis on AI in Bio + Health

Agrawal et al. argue that the framing of AI automation versus augmentation is wrong. Rather than being distinct they are often one and the same. They say that AI, initially intended for automating tasks, inadvertently acts as a force for augmentation of the broader workforce. For example, automating diagnostic skills in healthcare could diminish de... See more

Part of the challenge of “AI” is we keep raising the bar on what it means for something to be a machine intelligence. Early machine learning models have been quite successful in terms of real world impact. Large scale applications of machine learning today include Google Search and ads targeting, Siri/Alexa, smart routing on mapping applications, s... See more

An over-dependence on artificial intelligence is often just lethargy disguised as efficiency, and the “outsource everything to AI” crowd ignores the fact that the work is often more valuable than the output.

I have two predictions regarding the broader use of AI as a crutch:

First, folks who are willing to go out of their way to add a human touch to... See more