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I build AI/ML systems for a living and it's not as big of a deal as you think. Production machine learning systems built by experienced teams will almost always

by rm999 9y ago

I build AI/ML systems for a living and it's not as big of a deal as you think. Production machine learning systems built by experienced teams will almost always have business logic protections built-in to stop the machine from doing something totally stupid. For example, an auto-bidder may have capped velocities or auto-shutoff mechanisms (those examples of bidders spending billions of dollars in minutes are exceedingly sloppy). This is not unlike the human body's deeply-evolved reflexes - before the neocortex can even process that a pan is boiling hot, the nervous system bypasses the brain and and tells the hands to drop it. In the case of driverless cars, DannyBee is absolutely correct: truly driverless cars will not make decisions from a single data point. I have some past experience with unmanned aerial vehicles and those things had insane amounts of redundancy in almost every signal and decision making process; driverless cars are more complex and will come decades later and will probably take this even further.

oneshot908 9y ago
As another such practitioner, why oh why would we ignore hard-learned unambiguous signals and wisdom because we jumped on the machine learning bandwagon? We embraced machine learning to detect and uncover the things we don't see, not to replace the things we already know. There's no conflict here whatsoever.
mannykannot 9y ago
> Production machine learning systems built by experienced teams will almost always have business logic protections built-in to stop the machine from doing something totally stupid. In the case of driving, however, the problem of deciding what behavior to veto is itself a hard problem - perhaps the hardest of all. When the system monitoring the AI is itself AI, the argument becomes circular - which is not to say it cannot be solved, but I think it makes it harder to dismiss the concerns.

by rm999 9y ago

oneshot908 9y ago

As another such practitioner, why oh why would we ignore hard-learned unambiguous signals and wisdom because we jumped on the machine learning bandwagon? We embraced machine learning to detect and uncover the things we don't see, not to replace the things we already know. There's no conflict here whatsoever.

mannykannot 9y ago

> Production machine learning systems built by experienced teams will almost always have business logic protections built-in to stop the machine from doing something totally stupid. In the case of driving, however, the problem of deciding what behavior to veto is itself a hard problem - perhaps the hardest of all. When the system monitoring the AI is itself AI, the argument becomes circular - which is not to say it cannot be solved, but I think it makes it harder to dismiss the concerns.