Consider me a skeptic.
AI NLP models have way too many false positives and negatives for this to be workable. Maybe in 10 years, but definitely not now.
Perhaps the reason why detecting rascism or hate speech is so hard for an AI is that what is considered racism or hate speech is a moving target.
Off the top of my head, racism is often so casual that stochastic AI models may have difficulty discerning a difference in syntactic structure or other linguistic features compared to a similarly casual statements of a non-racist nature.
But you're right to be sceptical. Hedge funds are largely a sales job. How can you convince gullible investors to overlook the terrible performance of your sector and invest in you anyways, and then take a large slice of the profits when you get lucky? Buzzwords and neat sounding strategies help.
"...we went from a negative growth in Q4 in storage revenue on a year-over-year basis. We now have flat..."
"DELL – Q1 2022 Dell Technologies Inc Earnings Call"
https://investors.delltechnologies.com/static-files/d70442f3...
Some NLP related problems can be solved at a similar level of quality of humans - (humans actually make a lot mistakes as well).
This is just wrong. State of the art NLP models are pertectly able to identify racism and hate speech if they are trained to do so.
The issue is just that most of the times political correctness is not in the training objective. In fact, general language models are trained to reproduce what they read as closely as possible, hence the racism/hate speech.
Again, the problem is how they are trained, not what they could/could not achieve.
> AI NLP models have way too many false positives and negatives for this to be workable.
Citation needed.
why wouldnt it be possible to train on it?