Replacing biased AI with humans, then realizing the new dataset is biased too
Description
Dark-mode screenshot of a verified Twitter post (user name redacted) taken 19 hours after posting. The attached image is the four-panel Anakin - Padme Star Wars meadow meme: Panel 1 shows Anakin with overlaid white text, “We’re using Humans instead of biased AI.” Panel 2 shows Padme asking, “Where do you train them?” Panel 3 zooms on Anakin, silent and expressionless. Panel 4 returns to Padme repeating, “Where do you train them?” All faces are blurred for privacy; a small “imgflip.com” watermark appears bottom-left. Below the meme, Twitter engagement numbers read “6,889”, “10.1 K”, “111.2 K” and “16.4 M.” Technically, the joke highlights that swapping algorithms for human annotators doesn’t remove bias - reminding practitioners of dataset provenance, fairness, and AI ethics considerations
Comments
19Comment deleted
Swapping your biased model for human annotators without touching the dataset is basically `kubectl delete pod`; the container restarts, the bias configmap’s still mounted
The real production incident is when you realize your 'unbiased' human reviewers were trained on Stack Overflow answers from 2012, corporate compliance videos, and that one senior dev who still insists tabs are superior because 'that's how we've always done it.'
Ah yes, the classic RLHF paradox: we'll fix AI bias by having humans label the training data - the same humans whose cognitive biases, cultural assumptions, and systematic prejudices created the problem in the first place. It's like debugging your code by asking the compiler that generated the bug to review it. At least with AI we can version control the bias; with humans, it's just 'legacy wetware' running on millions of years of unpatched evolutionary heuristics
"We replaced biased AI with humans" is just migrating from a system with model cards and audit logs to one with undocumented heuristics, zero observability, and training data called "life."
Swapped biased LLMs for humans trained on Stack Overflow - now with confidently incorrect answers and zero hallucination disclaimers
Human-in-the-loop isn’t a fairness strategy; it’s swapping SGD for SOD - stochastic opinion descent - on the same dataset
What is imposed to be a training source? Comment deleted
*based Comment deleted
both humans and any man-made AI will be inherently biased because only data we can train either of them on is accumulated human knowledge Comment deleted
There is only one solution and total eradication of humanity is unfortunately impossible at current stage of technological development Comment deleted
how about eradicating only those w/ 120IQ(im being generous) and lower? Comment deleted
IQ doesn't mean anything. Almost entire cohort of top NSDAP members & military command of Third Reich scored pretty high on IQ tests. Comment deleted
may be that was the reason they were at the top positions?? Comment deleted
I do think rationally. Problem is that majority of human population is emotion-driven chaotic uber-apes whose consciousness has no proper way to work with from outside Comment deleted
But you wouldn't want those people left alive, would you? Comment deleted
*intelligency Comment deleted
kinda Comment deleted
IQ references how quick humans can recognize patterns and figure out abstractions Comment deleted
High IQ people just learn and analyze life experience faster. Unless they fall into IQ trap of self-reflection and stay in overthinking loop without doing action. Comment deleted