This makes me think,why not use trained humans to come up with challenges that can't be solved easily or efficiently with training data. As an example, a team

This makes me think,why not use trained humans to come up with challenges that can't be solved easily or efficiently with training data. As an example, a team of 2,000 humans can come up with about 10,000 challenges an hour to be solved by 1,000,000 visitors an hour. The key being humans trained to generate questions and challenges that they themselves wouldn not have to solve as part of any regular activity or event. The labor cost can obviously be outsourced(or not) and it makes sense to charge as a service to sites. However,this makes me ask one more question - what if popularity in ML creates meanial jobs for humans similar to my theoretical solution? Everyone looks at the benefits of ML,but all good technologies get abused and it's hard to imagine even more ML countering abused ML.