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The difference is that the software or the elevator will work but the statistical model is wrong and doesn't work. It is like the elevator only lift people abov
by jorgemf 11y ago
The difference is that the software or the elevator will work but the statistical model is wrong and doesn't work. It is like the elevator only lift people above 120 and below 90 and for the others it just don't work or take you to the wrong floor.
- chriswarbo 11y ago> The difference is that the software... will work Lots of software doesn't work. Is there a substantial difference between putting an overfitting model in production, and putting a poorly tested program in production?
- photoJ 11y agoI think there might be. When ML fails the only individual capable of noticing is someone who understands the math. When code breaks often the "lay" user notices. The result is obvious to a novice. When ML fails it looks like a duck, quakes like a duck but after multiple years of study its immediately recognizable as an antelope. Though to disagree with my own point, security vulnerabilities have a similar profile. In essence, to all but the highly trained the difference is imperceptible.
- forgetsusername 11y ago>"When code breaks often the "lay" user notices. The result is obvious to a novice." That depends "how" it breaks. As a novice coder myself, I've had things go wrong that I don't notice or can't identify, and it looks like my program is running fine. I think that's the parent's point: it might be stupid to implement crappy macho learning models into production, but it isn't worrisome. It's expected.
- photoJ 11y agoI hear ya. I knew that assertion was going to draw some criticism as its a judgement call about where we draw the line. Who's a novice and what's obvious? However I can't get away from my nagging impression that statistical validity is not inherently clear to the absolute best practitioners. Causality is the goal, and its notoriously difficult, even for world class minds. In my experience the only similar effervescent specter for software development is in security. Such circumstance,seem to me, to require great humility and introspection about ones abilities, but I suppose a little of that would go a long way in general too!
- tmaly 11y agoI would like to see some ML applied to stop lights with a fallback to the PLC with timers if that fails. It would save the nation a lot of gas.
- hugh4 11y agoThat the program is likely to fail loudly and obviously, but the overfitted model will just sit there being subtly yet perniciously much wronger than you think is, forever.
- aficionado 11y agoHow many elevators were failing today? how many were fixed today? and how many have been monitored in real-time to get fixed as they fail? Likewise, statistical models can be monitored and fixed automatically, and, of course, even so they will fail from time to time like elevators do.