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The problem with ML/AI is that it almost never provides people with a significant new capability. It can improve and augment, but rarely lets people do somethin
by hooande 6y ago
The problem with ML/AI is that it almost never provides people with a significant new capability. It can improve and augment, but rarely lets people do something that they couldn't do before. There is no "killer app"
It's very difficult to have a transformative impact by adding features or making a process 5% more efficient. It seems like we're very far away from AI enabling the average person to have new opportunities and experiences in the same way as past technological innovations have.
example: email enables me to communicate instantly and asynchronously with someone on the other side of the world. what does ml enable me to do?
- jwilber 6y agoHuh? Here’s one for ya: Communicate instantly and asynchronously with someone who speaks a different language.
- loufe 6y agoI suppose I agree in the sense that it is, really, the killer app. Still I think OP's point still holds, machine translation is undeniably infinitely more practical with ML but it still is just an augmentation. Same going for voice recognition.
- jwilber 6y agoI think OP’s first paragraph sounds like a reasonable framework for viewing the utility of ML, though is a bit too black/white. Bit they lose me completely when they said that we’re “very far away from AI enabling the average person to have new opportunities and experiences in the same way as past technological innovations have”. In any case, I agree with the thread’s larger point that the buzz and hype around the field is exhausting, and certainly not always warranted. Nothing makes my eyes roll more than reading a post from a data “thought-leader” on LinkedIn.
- duderific 6y agoMany, many businesses would gladly take a 5% improvement in efficiency. That can translate to tens or hundreds of millions of dollars for very large companies.
- visarga 6y ago> ML/AI .. rarely lets people do something that they couldn't do before For example, with ML blind people can manage much better than before.