3 ms·

If that is a concern, then perhaps you could go ahead and sample a tiny part of "reality" (whatever that means) and then adjust the weights of the digitized dat

If that is a concern, then perhaps you could go ahead and sample a tiny part of "reality" (whatever that means) and then adjust the weights of the digitized data so that it becomes a more representative sample. Also, being biased or unbiased is not dichotomic, i.e. it's not all or nothing. It's something that you can work towards if you put an effort into it. Basically what I'm saying is: don't just go around saying that the task is impossible. At least, try to make an effort to be unbiased and to improve on that over time, and don't just say "it's impossible" as an excuse for being biased.

Balgair 4y ago
Woah, I mean, this argument (the last few comments here) has been a central one in 'western' philosophy for at least the the last 2400 years, if not the last ~4000. I'm not a philosopher by any means, so I'm unaware of the current state of the great conversation. But as to whether reality is even knowable is still very much up for debate, I believe (please correct me philosophy peepz!). In physics we're still woefully unaware of what ~70% of the universe's stuff is doing (negative energy) and if it effects us at all. In neuroscience we still debate what % of your brain neurons make up vs. things like glia. Etc. Like, even trying to capture 'reality' with our quite primitive eyes and sensors and optical engineering is really really hard to do (Abbe' diffraction limit, entropy, Lens maker's equation, etc)
- wizeman 4y ago
  Fortunately, I think "reality" in this context doesn't have the same meaning as "the physical universe". I think the important goal is for as many people as possible to feel like the AI isn't being too biased against them, while still not crippling the AI too much. I will leave the exact mathematical formula for that measure (along with the methods for gathering that input) for debate among researchers who know more about that than I do.
  - entropicdrifter 4y ago
    I mean, define "biased against", right? Because some people will argue that anything that's not explicitly in full agreement with them is "biased against" them. It's a narcissistic, dishonest take, but plenty of people do take that stance nonetheless in order to try to shift all arguments into their narrow worldviews/definitions in order to "win" as many conversations as they can. Right? I mean I've met people online and off who do this from almost every part of the political spectrum. So, do we filter those people out from consideration to begin with, or do we have to cater to those with extreme views in order to get as many "not biased against me" ratings as possible? I guess the point I'm trying to make is that trying to optimize for any single metric is a fool's errand because as soon as you do so, it will be gamed/exploited. Then you can either try diversifying your optimization data points (who gets to choose those? How could they possibly be unbiased, when they literally define the system's bias?) or you can try filtering out bad actors from the data, which is very directly an attempt to bias the system away from insincere bad actors. And all of that's not even accounting for the lack of incentive to try to find neutrality when more biased views are more lucrative in the attention economy.
    - wizeman 4y ago
      I think all of your points are valid. But I still think we should make an effort and strive to solve these problems. I don't think this is being done with ChatGPT, for example. But also, note that an AI doesn't have to be in complete agreement with someone for that person to not feel "biased against". As long as an AI does make some effort to not be prejudiced/biased, that could work. For example, if someone asks: "is climate change real"? An AI does not have to give a simple yes/no answer, or represent a single viewpoint. It could give an answer that is mostly representative of the major thought streams. For example, it could answer something like: "The vast majority of scientists/governments/people have reached the conclusion that climate change is real, bla bla bla. [Here's some good, convincing evidence]. That said, there is a minor fraction of scientists/government/people who believe that climate change is not caused by human action. [They criticize the above evidence in this way]. [Here's also some counter-evidence]. That said, many scientists believe these studies are flawed for this reason or another." I mean, sure, there is still going to be a lot of people who don't agree with this answer. But I think, on a scale of 0-10 they would agree a lot more with this answer than one that completely ignores their viewpoints. And even for those of us who believe in climate change, we can still consider this answer somewhat reasonable. Thus, increasing the total amount of points would probably be a somewhat effective way of eliminating a large deal of bias, I think. Although, yes, you couldn't do this for every possible viewpoint. And it would be a challenge to figure out how to weigh these points in a way that makes the most amount of people happy. But I still think we should make efforts in this direction.
coldtea 4y ago
>If that is a concern, then perhaps you could go ahead and sample a tiny part of "reality" (whatever that means) and then adjust the weights of the digitized data so that it becomes a more representative sample. Who is doing the "adjusting the weights"? Why would they be "unbiased"? The real answer is those who make the AI (or people who have power over them) get to chose the training data or to adjust the weights. And the rest have to put up with it, whether the former are biased or not.

Balgair 4y ago

Woah, I mean, this argument (the last few comments here) has been a central one in 'western' philosophy for at least the the last 2400 years, if not the last ~4000. I'm not a philosopher by any means, so I'm unaware of the current state of the great conversation. But as to whether reality is even knowable is still very much up for debate, I believe (please correct me philosophy peepz!). In physics we're still woefully unaware of what ~70% of the universe's stuff is doing (negative energy) and if it effects us at all. In neuroscience we still debate what % of your brain neurons make up vs. things like glia. Etc. Like, even trying to capture 'reality' with our quite primitive eyes and sensors and optical engineering is really really hard to do (Abbe' diffraction limit, entropy, Lens maker's equation, etc)

wizeman 4y ago
Fortunately, I think "reality" in this context doesn't have the same meaning as "the physical universe". I think the important goal is for as many people as possible to feel like the AI isn't being too biased against them, while still not crippling the AI too much. I will leave the exact mathematical formula for that measure (along with the methods for gathering that input) for debate among researchers who know more about that than I do.
- entropicdrifter 4y ago
  I mean, define "biased against", right? Because some people will argue that anything that's not explicitly in full agreement with them is "biased against" them. It's a narcissistic, dishonest take, but plenty of people do take that stance nonetheless in order to try to shift all arguments into their narrow worldviews/definitions in order to "win" as many conversations as they can. Right? I mean I've met people online and off who do this from almost every part of the political spectrum. So, do we filter those people out from consideration to begin with, or do we have to cater to those with extreme views in order to get as many "not biased against me" ratings as possible? I guess the point I'm trying to make is that trying to optimize for any single metric is a fool's errand because as soon as you do so, it will be gamed/exploited. Then you can either try diversifying your optimization data points (who gets to choose those? How could they possibly be unbiased, when they literally define the system's bias?) or you can try filtering out bad actors from the data, which is very directly an attempt to bias the system away from insincere bad actors. And all of that's not even accounting for the lack of incentive to try to find neutrality when more biased views are more lucrative in the attention economy.
  - wizeman 4y ago
    I think all of your points are valid. But I still think we should make an effort and strive to solve these problems. I don't think this is being done with ChatGPT, for example. But also, note that an AI doesn't have to be in complete agreement with someone for that person to not feel "biased against". As long as an AI does make some effort to not be prejudiced/biased, that could work. For example, if someone asks: "is climate change real"? An AI does not have to give a simple yes/no answer, or represent a single viewpoint. It could give an answer that is mostly representative of the major thought streams. For example, it could answer something like: "The vast majority of scientists/governments/people have reached the conclusion that climate change is real, bla bla bla. [Here's some good, convincing evidence]. That said, there is a minor fraction of scientists/government/people who believe that climate change is not caused by human action. [They criticize the above evidence in this way]. [Here's also some counter-evidence]. That said, many scientists believe these studies are flawed for this reason or another." I mean, sure, there is still going to be a lot of people who don't agree with this answer. But I think, on a scale of 0-10 they would agree a lot more with this answer than one that completely ignores their viewpoints. And even for those of us who believe in climate change, we can still consider this answer somewhat reasonable. Thus, increasing the total amount of points would probably be a somewhat effective way of eliminating a large deal of bias, I think. Although, yes, you couldn't do this for every possible viewpoint. And it would be a challenge to figure out how to weigh these points in a way that makes the most amount of people happy. But I still think we should make efforts in this direction.

coldtea 4y ago

>If that is a concern, then perhaps you could go ahead and sample a tiny part of "reality" (whatever that means) and then adjust the weights of the digitized data so that it becomes a more representative sample. Who is doing the "adjusting the weights"? Why would they be "unbiased"? The real answer is those who make the AI (or people who have power over them) get to chose the training data or to adjust the weights. And the rest have to put up with it, whether the former are biased or not.