Research Findings:
- reCAPTCHA v2 is not effective in preventing bots and fraud, despite its intended purpose
- reCAPTCHA v2 can be defeated by bots 70-100% of the time
- reCAPTCHA v3, the latest version, is also vulnerable to attacks and has been beaten 97% of the time
- reCAPTCHA interactions impose a significant cost on users, with an estimated 819 million hours of human time spent on reCAPTCHA over 13 years, which corresponds to at least $6.1 billion USD in wages
- Google has potentially profited $888 billion from cookies [created by reCAPTCHA sessions] and $8.75–32.3 billion per each sale of their total labeled data set
- Google should bear the cost of detecting bots, rather than shifting it to users
“The conclusion can be extended that the true purpose of reCAPTCHA v2 is a free image-labeling labor and tracking cookie farm for advertising and data profit masquerading as a security service,” the paper declares.
In a statement provided to The Register after this story was filed, a Google spokesperson said: “reCAPTCHA user data is not used for any other purpose than to improve the reCAPTCHA service, which the terms of service make clear. Further, a majority of our user base have moved to reCAPTCHA v3, which improves fraud detection with invisible scoring. Even if a site were still on the previous generation of the product, reCAPTCHA v2 visual challenge images are all pre-labeled and user input plays no role in image labeling.”
Remember the good old days when it was just malformed text you have to solve? I miss those days. AI was complete garbage and they had to use farms of eyeballs to solve them for bots, making it a costly operation. We’ve now totally gotten away from all of that.
WE ARE THE EYEBALLS AND I AIN’T GETTING PAID IN WOW GOLD TO DO IT EITHER
that was also to train ai.
No it wasn’t… It was human-assisted OCR to help digitize books. Initially for Project Gutenberg, but then for Google Books once Google acquired it in 2009.
OCR is a form of AI.
Traditional OCR isn’t AI; it relies on manually-written rules. Some modern OCR tools use AI concepts (e.g. Tesseract uses a neural network) but they don’t necessarily have to. Getting humans to manually enter words is definitely not AI.