[dailyvijeos]

Nope. I remember when MTurk came out, used the API and tried some of the work units. For the most part, it really is moot though for most tasks now, except for insanely complex ones or new business processes that haven’t been automated yet. This decline of usefulness is due to the fact recent AI/ML/DL, after little training, can complete mundane, repetitive tasks faster and with far better accuracy and precision than all humans.

[bkanber]

I disagree. There are still lots of tasks out there that fit MTurk. Take something like "look at a picture and determine the person's race". Costs five cents for a Turk to do that. You can certainly train an RNN plus a Bayesian network to do this task, but a) there's no public corpus of training data for this so you'll need to generate that anyway and b) this solution still isn't thaaaat accessible to startups that have 1000 other things to worry about. How much time would the engineering team have to spend training, testing, tuning, validating, and deploying the model? If you only ever need to tag 1M images, that $50k on Turk is probably well-spent over the ML solution. If you need to tag 1B images, that's a different story, but if you're looking at that scale you probably already have the resources to do it.

[etaioinshrdlu]

There's already a great variety of cheap demographic recognition API's readily available... https://deepai.org/machine-learning-model/demographic-recogn... is just one.

[dsr_]

Race is a cultural construct.

Quick, what's Barack Obama's race?

(Hint: your answer will depend on your culture and what you know of his ancestry and upbringing.)

[snowpanda]

This literally has nothing to do with what OP was saying.

You took one word out of his entire point and decided to make a statement about that.