You're in a desert walking along the sand when all of a sudden you look down and see a tortise. You reach down and flip the tortise on it's back. The tortise lays on it's back, it's belly baking in the hot sun but you're not helping. Why is that leon?

* Tortoise

* its back

* its belly

* Leon

(in case the mistakes were not for comedic effect)

Found the simulant.

;)

Or maybe later Android versions know they should turn the Tortoise back on its feet.

* Thank you

* Mr.

* Professor

(in case you want some appreciation for your nitpicking)

Correcting people's mistakes is not nitpicking, it's how people learn.

Correction. It can be.

Nitpicking: looking for small or unimportant errors or faults, especially in order to criticize unnecessarily.

See what I did there? We can keep going, but it adds no value. It's tortises all the way down.

Indeed, and neither you nor the GP were criticising.

fushta!

Sylvania.

Oh, really? So how is one supposed to learn from just getting a list of corrections with no explanation whatsoever?

If you want someone to learn, help them. If you're not willing to do that leave it be. If you can't leave it be, you probably only want to nitpick.

What's it like to hold the hand of someone you love?

People always come at this from an angle of "what can I do that computers can't?". You need to take into account the incredible diversity of people who use the internet, and what they can and can't do. There's already a viral article written by an old lady who can't pass the current captchas. Add to this, people who don't speak english, or don't speak it well; people who battle to read and comprehend text in any language; people who battle with logical reasoning; etc, etc, etc. The lowest common denominator for a task that be easily solved by any human is pretty low.

Just issue the Turing test to every visitor.

It's a good idea, but you would need different languages versions.

When writing such captcha questions for a forum, I generally use google as a validation to see that google can't answer the question in the top listed links. This allow me to easily adjust questions to the point where natural language processing should not be able to answer the question but a human person would.

Yep, Question-Answering Semantic Role labeling is an interesting research project around crowdsourcing NLP datasets. https://dada.cs.washington.edu/qasrl/

> A man is running. A dog is behind him barking and growling. What does the man think might happen?

So what's the correct answer here?

* That's a mean dog

* I hope it's on a leash

* I hope it's not going to start running after me

* I hope I don't get bitten

* Where can I hide?

* OMG, I will get rabies!

This was my first thought, there are many different things a human could think of, and we will probably cycle through them all in a few ms. This would have to be multiple choice and then what? The "AI" would have a baseline 25% chance of getting it correct (assuming 4 options).

Multiple choice doesn't work well for captchas. You can just guess and get it 25% of the time correct. Which is fine for spammers.

You couldn't autogenerate them easily. If you don't have a unique captcha people could store answers