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>-- Has she calculated the oposite alternatives? People driving to libraries, to search for something? Driving to the library, that is the alternative to train

>-- Has she calculated the oposite alternatives? People driving to libraries, to search for something? Driving to the library, that is the alternative to training these models, really? > -- Ok, basically she is pissed as AI is picking normal language, that people use, and not using the vocabulary that is in vogue on certain political circles. Basically censure, and forced speech. If you had a model trained on a large corpus of data from the pre civil war southern American states, it would have been deeply racist, and would even view black people as possible property. If you had one that was trained on data from the 1950 it would be less racist but still problematic viewed by people from today. Is there really something special with today, that removes these kind of concerns with a model trained with current data? > I think social engineering b.s. should be kept as far away as possible from science. This is turning true ai research into a masquerade to push certain political agendas. It seems to me that it would be impossible to do any social science research, and specifically any research on racism. With this kind of attitude. Some of the concerns brought up in the paper seems less consequential than others. Especially the pollution one seems weak to me, that doesn't make it false, and fair enough that is was brought up. I find the racism issue a lot more problematic, and is something I've run up to working on deep learning solutions myself. Even if it worked fine for my group, and most of our customers, that is definitely not fun, and something practitioners should consider when building these things.

jskajakzkjx 6y ago
> If you had a model trained on a large corpus of data from the pre civil war southern American states, it would have been deeply racist, and would even view black people as possible property. If you had one that was trained on data from the 1950 it would be less racist but still problematic viewed by people from today. Is there really something special with today, that removes these kind of concerns with a model trained with current data? I think this argument applies not just to machine learning, but to learning in general. Any kind of knowledge-acquisition process is going to be biased by the environment in which it occurs. That goes not just for digital neural networks, but also those in our human brains, operating on the same racist data the ML models are. If that means we shouldn’t do machine learning, it also means we shouldn’t do human learning either. Of course, the preceding is absurd. A more reasonable take is that we should adjust the objective function of our learning processes to try to account for the effects of biases. We try to do that subjectively as any decent person operating in a biased society should, but our ML models can do it more accurately. In fact, I’d argue that such techniques are necessary to more carefully analyze and build evidence describing the effects of those biases. They can provide insights that will even improve our ability to correct for biases in the real world.
rualca 6y ago
> It seems to me that it would be impossible to do any social science research, and specifically any research on racism. With this kind of attitude. I think this sort of veiled personal attack resorting to baseless extrapolation is not a productive line of public discourse. You should take a step back and think about a) the field of study, b) how the main argument completely ignores the basis of said technical field and what it studies, c) how the argument being created lies on the idea that a self-annointed elite should have the right to manipulate the public to force it to fall in place with it's goals and desires.
- einarfd 6y ago
  > I think this sort of veiled personal attack resorting to baseless extrapolation is not a productive line of public discourse. I thought that my comment was fitting to the tone of the text I replied too, but fair enough, maybe I shouldn't have included that paragraph. > You should take a step back and think about a) the field of study, b) how the main argument completely ignores the basis of said technical field and what it studies, c) how the argument being created lies on the idea that a self-annointed elite should have the right to manipulate the public to force it to fall in place with it's goals and desires. It is unclear to me what this means, is it arguing that studying bias in AI and specifically deep learning is not germane? Is it arguing that it is not acceptable to institute policies and action to create a level playing field for minorities and repressed group because that would be social engineering, and forcing the common man to do the elites bidding? If that is what it means, I have to disagree, I find both of those things worthwhile.
  - rualca 6y ago
    > I thought that my comment was fitting to the tone of the text (...) Yes, that was one of the problems. > It is unclear to me what this means, is it arguing that studying bias in AI and specifically deep learning is not germane? Let me make it clear for you so that a) we are able to talk about things objectively, b) your options to continue using veiled personal attacks is curtailed. Either your goal is to model reality and real life, or your goal is to model your idealization of what you feel real life should be. If you pick option #2 then your model does not reflect real life. Bias is by definition the way the model returns results that don't match the real world and real life, in frequency and in proportion. If your goal is to use your model to manipulate and control society based on your own personal criteria, by manipulating it to return results that distort the real world and real life, then call it something else, because bias is not it.
vonseel 6y ago
The social engineering and woke culture stuff seems like a moot point honestly. If the large language model analyzes everything, it will veer towards normal. It doesn’t seem so far fetched to think they can build something which also tracks and understands language trends and slang, and how to appropriately use this “special vocabulary”. I don’t know much about how these models work, but I would hope something trained on the entire internet is smart enough to know to speak to me in modern English, not Civil War English or Shakespeare English.

jskajakzkjx 6y ago

> If you had a model trained on a large corpus of data from the pre civil war southern American states, it would have been deeply racist, and would even view black people as possible property. If you had one that was trained on data from the 1950 it would be less racist but still problematic viewed by people from today. Is there really something special with today, that removes these kind of concerns with a model trained with current data? I think this argument applies not just to machine learning, but to learning in general. Any kind of knowledge-acquisition process is going to be biased by the environment in which it occurs. That goes not just for digital neural networks, but also those in our human brains, operating on the same racist data the ML models are. If that means we shouldn’t do machine learning, it also means we shouldn’t do human learning either. Of course, the preceding is absurd. A more reasonable take is that we should adjust the objective function of our learning processes to try to account for the effects of biases. We try to do that subjectively as any decent person operating in a biased society should, but our ML models can do it more accurately. In fact, I’d argue that such techniques are necessary to more carefully analyze and build evidence describing the effects of those biases. They can provide insights that will even improve our ability to correct for biases in the real world.

rualca 6y ago

> It seems to me that it would be impossible to do any social science research, and specifically any research on racism. With this kind of attitude. I think this sort of veiled personal attack resorting to baseless extrapolation is not a productive line of public discourse. You should take a step back and think about a) the field of study, b) how the main argument completely ignores the basis of said technical field and what it studies, c) how the argument being created lies on the idea that a self-annointed elite should have the right to manipulate the public to force it to fall in place with it's goals and desires.

einarfd 6y ago
> I think this sort of veiled personal attack resorting to baseless extrapolation is not a productive line of public discourse. I thought that my comment was fitting to the tone of the text I replied too, but fair enough, maybe I shouldn't have included that paragraph. > You should take a step back and think about a) the field of study, b) how the main argument completely ignores the basis of said technical field and what it studies, c) how the argument being created lies on the idea that a self-annointed elite should have the right to manipulate the public to force it to fall in place with it's goals and desires. It is unclear to me what this means, is it arguing that studying bias in AI and specifically deep learning is not germane? Is it arguing that it is not acceptable to institute policies and action to create a level playing field for minorities and repressed group because that would be social engineering, and forcing the common man to do the elites bidding? If that is what it means, I have to disagree, I find both of those things worthwhile.
- rualca 6y ago
  > I thought that my comment was fitting to the tone of the text (...) Yes, that was one of the problems. > It is unclear to me what this means, is it arguing that studying bias in AI and specifically deep learning is not germane? Let me make it clear for you so that a) we are able to talk about things objectively, b) your options to continue using veiled personal attacks is curtailed. Either your goal is to model reality and real life, or your goal is to model your idealization of what you feel real life should be. If you pick option #2 then your model does not reflect real life. Bias is by definition the way the model returns results that don't match the real world and real life, in frequency and in proportion. If your goal is to use your model to manipulate and control society based on your own personal criteria, by manipulating it to return results that distort the real world and real life, then call it something else, because bias is not it.

vonseel 6y ago

The social engineering and woke culture stuff seems like a moot point honestly. If the large language model analyzes everything, it will veer towards normal. It doesn’t seem so far fetched to think they can build something which also tracks and understands language trends and slang, and how to appropriately use this “special vocabulary”. I don’t know much about how these models work, but I would hope something trained on the entire internet is smart enough to know to speak to me in modern English, not Civil War English or Shakespeare English.