I’ve been working in the “real world business processes that companies are trying to AI-ify” realm for quite a while now. Pharma, cyber security, oil and gas production, etc.
This article doesn’t mention a really, really straightforward factor for why AI hasn’t invaded these domains despite billions of dollars being dumped into them.
An automated process only has to be wrong once to compel human operators to double or triple check every other result it gives. This immediately destroys the upside as now you’re 1) doing the process manually anyway and 2) fighting the automated system in order to do so.
99% isn’t good enough for truly critical applications, especially when you don’t know for sure that it’s actually 99%; there’s no way to detect which 1% might be wrong; there’s no real path to 100%; and critically: there’s no one to hold responsible for getting it wrong.
This article doesn’t mention a really, really straightforward factor for why AI hasn’t invaded these domains despite billions of dollars being dumped into them.
An automated process only has to be wrong once to compel human operators to double or triple check every other result it gives. This immediately destroys the upside as now you’re 1) doing the process manually anyway and 2) fighting the automated system in order to do so.
99% isn’t good enough for truly critical applications, especially when you don’t know for sure that it’s actually 99%; there’s no way to detect which 1% might be wrong; there’s no real path to 100%; and critically: there’s no one to hold responsible for getting it wrong.