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Seeing a lot of "Well but what if it works" here, and I'll weigh in as someone who does AI - including CV-related applications involving convolutional neural ne
by advael 5y ago
Seeing a lot of "Well but what if it works" here, and I'll weigh in as someone who does AI - including CV-related applications involving convolutional neural networks - professionally and has participated in academic research in that field as well: I would estimate that roughly 80% of all "AI-based inference" that's currently being sold commercially is snake oil. Whether it's ad-tech, malware detection, facial recognition, whatever. There's definitely some promise to these systems, and there are some applications that have already started to bear out, but for the most part the industry is rife with bad data, bad data practices, lack of rigor in the way they scope and define their targets, and rushing products to market well before their claims actually meet even the criteria outlined for the project, let alone any standard of scientific evidence in this field or others. The fact that governments and companies that can make serious decisions with serious consequences are using these systems as-is is a serious problem that is already apparent in several places where they've been deployed.
For systems that claim to make any kind of psychological inference, I doubt there's a single one you should believe the claims of. Nearly half of human-performed psychology studies in the last 70 years have failed to replicate, including ones whose results have become "common knowledge" (As a field as a whole, it fared quite badly in what's called the "replication crisis"), and many of the very best supported of these supposed AI-psychology insights are, if you look into them, built on assumptions made by these results. Most of them fail to even do that, and rush a rigged result that doesn't generalize to market because they can get paid a fortune by their customers who buy the hype
100% of all AI hiring systems, AI proctors, AI recidivism predictors, AI drug-seeking classifiers, and anything that, like this article refers to, purports to infer personality traits from faces are both bullshit and dangerous. Maybe there could exist a reality where this wasn't true, but there is absolutely no solid reason right now to believe we live in that reality.
- pfortuny 5y agoBad data: thanks for saying it out loud. The idea that everything coming from a sensor is data will provoke a lot of harm.
- bojangleslover 5y agoTotally agreed on the snake oil. But you can't deny there are definitely strong signals. For example, NN's can detect with 91% accuracy the sexual orientation of males, with only five images. Also, not saying 91% is good enough for any government or business to commit to. https://www.semanticscholar.org/paper/Deep-Neural-Networks-Can-Detect-Sexual-Orientation-Wang-Kosinski/af30a2394c620132884bb98c78b6b9e46c791482 https://www.semanticscholar.org/paper/Deep-Neural-Networks-C...
- quirkot 5y agoBase rate effect. Also, those NN's are less accurate than a sticky note that just says "straight"
- polm23 5y agoBesides the base rate effect did you not see the article already posted in this thread with the many problems with that paper? https://www.theregister.com/2019/03/05/ai_gaydar/ https://www.theregister.com/2019/03/05/ai_gaydar/
- advael 5y agoHave you read the actual paper? That figure is at best inflated, and their methodology is riddled with confounds, including but not limited to the role of social networking profile pictures as dating signals, intentional signaling such as grooming and makeup, and factors like the the socio-economic status and locale of the people being classified, which can be more predictive of declared sexual orientation than anything resulting from physiological features. Oh right, it's probably worthwhile to note that since there are considerable reasons in many parts of the world to hide one's sexual orientation, and this study's design only conditions on reported sexual orientation on social media, the results are intrinsically skewed just by being from a population of out gay people Also, bear in mind that if we take Wikipedia's reported rate of homosexuality in the general human population, for which 9% would be... pretty generous (The "Demographics of sexual orientation" article lists several statistics and I can't find a world aggregate, but e.g. San Francisco is 15%), a null-classifier that always guesses "straight" would be just as accurate. If the population levels were lower, more accurate Bottom line, that study isn't very convincing
- api 5y agoThe phrases "computer aided superstition" and "computer aided paradolia" come to mind.
- advael 5y agoNah, deep dream was computer-aided pareidolia. This is just regular old computer-aided prejudice
- api 5y agoPrejudice is superstition, paradolia, and statistical undue weight fallacies like "one black person mugged me once, therefore from a sample size of one I am concluding that blacks are criminals."