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This is baloney. The workings of any machine learning algorithm is not beyond our understanding. Even on an intuitive level, it is easy to watch what it is doin

by ebbv 9y ago

This is baloney. The workings of any machine learning algorithm is not beyond our understanding. Even on an intuitive level, it is easy to watch what it is doing and derive theories about what is going on. If you spend the time to investigate it is possible to map out what is going on. You can determine "This pathway delivers a high signal on pictures of brown cats, this pathway lights up with pictures of black cats." Or whatever. This kind of breathless "Oh we CAN'T understand!" editorializing gets clicks because machine learning is so strange to most people, but it's terrible. We should instead be spreading knowledge about the very simple principles that are underlying the complicated behavior. Our brains are far, far more complicated than even our most advanced machine learning right now. Yet we are constantly making progress on understanding the workings of our brains. This article is just terrible.

hinkley 9y ago
It's not that different than an argument I have at work from time to time: If you don't understand how a thing works, how the hell do you plan to fix it when it doesn't?
spc476 9y ago
Leadup: Dr. Thompson used a genetic algorithm to program a FPGA to detect one of two tones. The result was: > Dr. Thompson peered inside his perfect offspring to gain insight into its methods, but what he found inside was baffling. The plucky chip was utilizing only thirty-seven of its one hundred logic gates, and most of them were arranged in a curious collection of feedback loops. Five individual logic cells were functionally disconnected from the rest— with no pathways that would allow them to influence the output— yet when the researcher disabled any one of them the chip lost its ability to discriminate the tones. (from https://www.damninteresting.com/on-the-origin-of-circuits/ https://www.damninteresting.com/on-the-origin-of-circuits/) Granted, the results were probably due to the quirks of the FPGA gates on that particular chip (and that particular area of the chip) but without further (potentially destructive) investigation, Dr. Thompson (or us for that matter) may never know the actual reason that circuit worked the way it did.
- guskel 9y ago
  Backpropagation doesn't work like genetic algorithms on an FPGA.
jancsika 9y ago
> This kind of breathless "Oh we CAN'T understand!" editorializing gets clicks because machine learning is so strange to most people, but it's terrible. There's also a fringe benefit here. If "we can't understand" what it's doing, then that assumption can appear to weaken the "auditability" argument for deploying FLOSS in life-critical AI systems. (I.e., freedom 1 from the GPL.) I'll bet the argument will be put forward with more frequency over the next few years, especially as self-driving cars become more prominent. Perhaps "appear to weaken" is too strong an assertion. But I can imagine a consumer safety advocate arguing for code to be auditable by outside parties just like Signal can be, and a PR spokesperson deflecting that AI is "beyond our understanding" and therefore not subject to the same standard.

by ebbv 9y ago

hinkley 9y ago

It's not that different than an argument I have at work from time to time: If you don't understand how a thing works, how the hell do you plan to fix it when it doesn't?

spc476 9y ago

Leadup: Dr. Thompson used a genetic algorithm to program a FPGA to detect one of two tones. The result was: > Dr. Thompson peered inside his perfect offspring to gain insight into its methods, but what he found inside was baffling. The plucky chip was utilizing only thirty-seven of its one hundred logic gates, and most of them were arranged in a curious collection of feedback loops. Five individual logic cells were functionally disconnected from the rest— with no pathways that would allow them to influence the output— yet when the researcher disabled any one of them the chip lost its ability to discriminate the tones. (from https://www.damninteresting.com/on-the-origin-of-circuits/ https://www.damninteresting.com/on-the-origin-of-circuits/) Granted, the results were probably due to the quirks of the FPGA gates on that particular chip (and that particular area of the chip) but without further (potentially destructive) investigation, Dr. Thompson (or us for that matter) may never know the actual reason that circuit worked the way it did.

guskel 9y ago
Backpropagation doesn't work like genetic algorithms on an FPGA.

jancsika 9y ago

> This kind of breathless "Oh we CAN'T understand!" editorializing gets clicks because machine learning is so strange to most people, but it's terrible. There's also a fringe benefit here. If "we can't understand" what it's doing, then that assumption can appear to weaken the "auditability" argument for deploying FLOSS in life-critical AI systems. (I.e., freedom 1 from the GPL.) I'll bet the argument will be put forward with more frequency over the next few years, especially as self-driving cars become more prominent. Perhaps "appear to weaken" is too strong an assertion. But I can imagine a consumer safety advocate arguing for code to be auditable by outside parties just like Signal can be, and a PR spokesperson deflecting that AI is "beyond our understanding" and therefore not subject to the same standard.