You end your article with 'Bayesian filters will not outperform a human in hiring'. But that's not the point.
A classifier, and especially a supervised classifier, is really just a tool for intelligence amplification. Make a dumb man perform smarter, and a smart man perform better than almost anyone without the advantage. Similar to providing physicians with a checklist for common procedures which has been developed by iterative analysis of outcomes. It's very hard to become a physician if you're dumb or lazy, but it's quite easy to get fatigued on a 36-hour residency shift, or get complacent if some 'trivial' procedure interrupts your microsurgery specialty. And the stakes are far higher in most surgical interventions.
Naturally, many doctors resist. But the best figure out how to use this to their advantage. It increases the efficiency of the system. Likewise, having the 'advice' of a machine that has been trained on a corpus of good multiple-human-actor decisions, over time, can provide individuals with better judgment than their experience alone. This is more apparent with a larger corpus and finer-grained classification -- eg. multidimensional classification with a huge corpus and eigenclasses of suitability. Game that, and you're smart enough to be in management, most likely ;-)
So, I don't believe you should let your detractors off so easily. Maybe a talented human will outperform an filter with a small corpus. But I'd bet dollars to donuts that, for someone who isn't a full-time interviewer, the assistance of a well-trained filter will increase their acuity and throughput, allowing them to get on with their real jobs and worry less about dumb hires.
You can't really avoid the enthusiasm of junior employees who haven't been burned, and this is another scenario where a filter can help them gauge their judgment by providing a historical perspective. "You know the last guy we hired who interviewed like this, one of your coworkers spent 2 hours a day for 3 months training him, and then we fired him!" That's something you want to avoid, and I have seen this happen at places like Google where you might think they'd be immune. But once you let the dumb or negative folks in, it's all downhill from there.
So -- replace humans? No. Augment them? Yes. It's what computers (and statistical analyses) are meant for!
A classifier, and especially a supervised classifier, is really just a tool for intelligence amplification. Make a dumb man perform smarter, and a smart man perform better than almost anyone without the advantage. Similar to providing physicians with a checklist for common procedures which has been developed by iterative analysis of outcomes. It's very hard to become a physician if you're dumb or lazy, but it's quite easy to get fatigued on a 36-hour residency shift, or get complacent if some 'trivial' procedure interrupts your microsurgery specialty. And the stakes are far higher in most surgical interventions.
Naturally, many doctors resist. But the best figure out how to use this to their advantage. It increases the efficiency of the system. Likewise, having the 'advice' of a machine that has been trained on a corpus of good multiple-human-actor decisions, over time, can provide individuals with better judgment than their experience alone. This is more apparent with a larger corpus and finer-grained classification -- eg. multidimensional classification with a huge corpus and eigenclasses of suitability. Game that, and you're smart enough to be in management, most likely ;-)
So, I don't believe you should let your detractors off so easily. Maybe a talented human will outperform an filter with a small corpus. But I'd bet dollars to donuts that, for someone who isn't a full-time interviewer, the assistance of a well-trained filter will increase their acuity and throughput, allowing them to get on with their real jobs and worry less about dumb hires.
You can't really avoid the enthusiasm of junior employees who haven't been burned, and this is another scenario where a filter can help them gauge their judgment by providing a historical perspective. "You know the last guy we hired who interviewed like this, one of your coworkers spent 2 hours a day for 3 months training him, and then we fired him!" That's something you want to avoid, and I have seen this happen at places like Google where you might think they'd be immune. But once you let the dumb or negative folks in, it's all downhill from there.
So -- replace humans? No. Augment them? Yes. It's what computers (and statistical analyses) are meant for!