[50CNT]

Even to develop an expert system, you only need some humans who do it quantifiably better than other humans. Despite not all of us being expert Go players, we have AI that can do it. In the less abstract space, we have medical diagnosis systems that hold up in accuracy to domain experts, and beat competent practitioners.

There are potential issues with this: - The accuracy of NLP and Voice recognition used is too low to provide useful input (needs to do speaker differentiation without training on specific speakers. Heavy usage of jargon) - Performance in one domain (say a meeting about oil&gas) does not transfer to another (say a meeting about IT infrastructure), which makes development cost prohibitive. - Ability to encode and link knowledge is too low to be useful.

[astazangasta]

In Go you have a clear set of test cases with fixed outcomes. You don't have the same thing here.

[50CNT]

That is precisely why I quoted the example of medical diagnosis systems within restricted subfields.