I can see the numbers on the notes and infer that they denote United States Dollars, but have zero idea of what the coins are worth. I would expect that anyone outside United States would have to look up every coin type and so take very much more than 3-4 times longer clicking images with boats. Especially if the coins have multiple variations.
If a system like this were widely deployed online using US currency, people outside the US would need to familiarize themselves with US currency if they are not already familiar with it. But they would only need to do this once and then it should be easy to remember for subsequent instances. There are only 6 denominations of US coins in circulation - $0.01, $0.05, $0.10, $0.25, $0.50, and $1.00 - and although there are variations for some of them, they mostly follow a very similar pattern. They also frequently have words on them like “ONE CENT” ($0.01) or “QUARTER DOLLAR” ($0.25) indicating the value, so it should be possible for non-US people to become familiar with those.
Alternatively, an easier option could be using country specific-captchas which show a picture like this except with the currency of whatever country the internet user is in. This would only require extra work for VPN users who seek to conceal their location by having the VPN make it look like they are in some other country.
If the image additionally included coin-like tokens, it would be a nontrivial research project (on the order of an hour) to verify that each such object is in fact not any form of legal tender, past or present, in the United States.
The idea was they the tokens would only be similar in broad shape and color—but would be different enough from actual legal tender coins that I would expect a human to easily tell the two apart.
Even if all the above were solved, you still need such images to be easily generated in a manner that any human can solve it fairly quickly but a machine vision system custom trained to solve this type of problem, based on at least thousands of different examples, can’t. This is much harder than it sounds.
I agree that the difficulty of generating a lot of these is the main disadvantage, as you would probably have to just take a huge number of real pictures like this which would be very time consuming. It is not clear to me that Dall-E or other AI image generators could produce such pictures with enough realism and detail that it would be possible for human users to determine how much money is supposed to be in the fake image (and have many humans all converge to the same answer). You also might get weird things using Dall-E for this, like 2 corners of the same bill having different numbers indicating the bill’s denomination.
But I maintain that, once a large set of such images exists, training a custom machine vision system to solve these would be very difficult. It would require much more work than simply fine tuning an off-the-shelf vision system to answer the binary question of “Does this image contain a bus?”.
Suppose that, say, a few hundred people worked for several months to create 1,000,000 of these in total and then started deploying them. If you are a malicious AI developer trying to crack this, the mere tasks of compiling a properly labeled data set (or multiple data sets) and deciding how many sub-models to train and how they should cooperate (if you use more than one) are already non-trivial problems that you have to solve just to get started. So I think it would take more than a few days.
If a system like this were widely deployed online using US currency, people outside the US would need to familiarize themselves with US currency if they are not already familiar with it. But they would only need to do this once and then it should be easy to remember for subsequent instances. There are only 6 denominations of US coins in circulation - $0.01, $0.05, $0.10, $0.25, $0.50, and $1.00 - and although there are variations for some of them, they mostly follow a very similar pattern. They also frequently have words on them like “ONE CENT” ($0.01) or “QUARTER DOLLAR” ($0.25) indicating the value, so it should be possible for non-US people to become familiar with those.
Alternatively, an easier option could be using country specific-captchas which show a picture like this except with the currency of whatever country the internet user is in. This would only require extra work for VPN users who seek to conceal their location by having the VPN make it look like they are in some other country.
The idea was they the tokens would only be similar in broad shape and color—but would be different enough from actual legal tender coins that I would expect a human to easily tell the two apart.
Some examples would be:
https://barcade.com/wp-content/uploads/2021/07/BarcadeToken_OPT.png
https://www.pinterest.com/pin/64105994675283502/
I agree that the difficulty of generating a lot of these is the main disadvantage, as you would probably have to just take a huge number of real pictures like this which would be very time consuming. It is not clear to me that Dall-E or other AI image generators could produce such pictures with enough realism and detail that it would be possible for human users to determine how much money is supposed to be in the fake image (and have many humans all converge to the same answer). You also might get weird things using Dall-E for this, like 2 corners of the same bill having different numbers indicating the bill’s denomination.
But I maintain that, once a large set of such images exists, training a custom machine vision system to solve these would be very difficult. It would require much more work than simply fine tuning an off-the-shelf vision system to answer the binary question of “Does this image contain a bus?”.
Suppose that, say, a few hundred people worked for several months to create 1,000,000 of these in total and then started deploying them. If you are a malicious AI developer trying to crack this, the mere tasks of compiling a properly labeled data set (or multiple data sets) and deciding how many sub-models to train and how they should cooperate (if you use more than one) are already non-trivial problems that you have to solve just to get started. So I think it would take more than a few days.