without discriminating on grounds of protected characteristics
AI classification is trained based on supervised (the right answers are predetermined) learning. MechaHitler for the fascist nationalism’s sake, will rate Obama’s face as a poor employee, and Trump’s as the bestest employee.
Open training data sets would be subject to 1. zero competitive advantage to a model, 2. massive complaints about any specific training data.
For some jobs, psycopaths AND loyalty are desirable traits, even though they can be opposite traits. Honesty, integrity, intelligence can be desirable traits, or obstacles to desperate loyalty. My point is that if there are many traits determined by faces, much more training data is needed to detect them, and then human hiring decision based on 10 or 30 traits matching to a (impossibly unique) position, where there direct manager only cares about loyalty, without being too talented, but higher level managers might prefer a candidate with potential to replace their direct manager, but all of them care about race or pregnancy risk, and then post training based on some “illegal characteristics”.
A Gattaca situation where, everyone has easy time getting great job, and moving to a greater job, OR being shut out of all jobs, creates a self contradicting prediction on “loyalty/desperation” controlability traits. If job duties are changed to include blow job services, then surely those agreeable make a better employee, despite any facial ticks responding to suggestion.
Human silent “illegal discrimination” is not eliminated/changed, but the new capability, you can use a computer to do the interviewing, and waste more interviewees’ time at no human cost to employer is why this will be a success. A warehousing company recently looked at facial expressions to determine attention to safety, and this leads to “The AI punishments to your life will continue until you smile more.” Elysium’s automated parole incident interviews is a good overview of the dystopia.
A classification problem is correlation vs causation. Sunspots and mini skirts have been correlated with stock market returns to some degree, but it tends to be a tenuous connection not guaranteed to hold up over time, or to actually have any meaningful relevance whatsoever. It’s easy to oversell models.
![The Economist on using phrenology for hiring and lending decisions: "Some might argue that face-based analysis is more meritocratic" […] "For people without access to credit, that could be a blessing"](https://lemmy.ml/pictrs/image/14f5a0b4-82b6-498d-a689-36c2824dd296.png){kind=link}
Dystopian neutrality in article.
AI classification is trained based on supervised (the right answers are predetermined) learning. MechaHitler for the fascist nationalism’s sake, will rate Obama’s face as a poor employee, and Trump’s as the bestest employee.
Open training data sets would be subject to 1. zero competitive advantage to a model, 2. massive complaints about any specific training data.
For some jobs, psycopaths AND loyalty are desirable traits, even though they can be opposite traits. Honesty, integrity, intelligence can be desirable traits, or obstacles to desperate loyalty. My point is that if there are many traits determined by faces, much more training data is needed to detect them, and then human hiring decision based on 10 or 30 traits matching to a (impossibly unique) position, where there direct manager only cares about loyalty, without being too talented, but higher level managers might prefer a candidate with potential to replace their direct manager, but all of them care about race or pregnancy risk, and then post training based on some “illegal characteristics”.
A Gattaca situation where, everyone has easy time getting great job, and moving to a greater job, OR being shut out of all jobs, creates a self contradicting prediction on “loyalty/desperation” controlability traits. If job duties are changed to include blow job services, then surely those agreeable make a better employee, despite any facial ticks responding to suggestion.
Human silent “illegal discrimination” is not eliminated/changed, but the new capability, you can use a computer to do the interviewing, and waste more interviewees’ time at no human cost to employer is why this will be a success. A warehousing company recently looked at facial expressions to determine attention to safety, and this leads to “The AI punishments to your life will continue until you smile more.” Elysium’s automated parole incident interviews is a good overview of the dystopia.
A classification problem is correlation vs causation. Sunspots and mini skirts have been correlated with stock market returns to some degree, but it tends to be a tenuous connection not guaranteed to hold up over time, or to actually have any meaningful relevance whatsoever. It’s easy to oversell models.