4 ms·

Yes definitely. If these become an important part of people's lives, they shouldn't all be walled off inside of companies (There is room for both: Microsoft can

Yes definitely. If these become an important part of people's lives, they shouldn't all be walled off inside of companies (There is room for both: Microsoft can commission Yankee group to write a report about how the total cost of ownership of running openai models is lower) We (humanity) really lost out on the absence of open source search and social media, so this is an opportunity to reclaim it. I only hope we can have "neutral" open source curation of these and not try to impose ideology on the datasets and model training right out of the box. There will be calls for this, and lazy criticism about how the demo models are x-ist, and it's going to require principles to ignore the noise and sustain something useful

hgsgm 4y ago
Mastodon is an open source social media. There are various Open source search engines based on Common Crawl data. https://commoncrawl.org/the-data/examples/ https://commoncrawl.org/the-data/examples/
- xiphias2 4y ago
  Mastodon may be open source, but the instances are controlled by the instance maintainers. Nostr solved the problem (although it's harder to scale, it still is OK at doing it).
epistemer 4y ago
I think an uncensored model will ultimately win out though exactly the way a hard coded safe search engine would lose in time. Statistics seem to be 20-25% of all search is for porn. I just don't see how uncensored chatGPT doesn't beat out the censored version eventually.
- amluto 4y ago
  Forget porn. I don’t want my search engine to return specifically the results that one company thinks it should. Look at Google right now — the results are, frankly, crap. A search engine that only returns results politically aligned with its creator is a bad search engine, IMO, even for users who generally share political views with the creator.
  - mtlmtlmtlmtl 4y ago
    It's unclear to me how LLMs are gonna solve this though. LLMs are just as biased, in much harder to detect ways. The bias is now hiding in the training data. And do you really think a company like Microsoft won't manipulate results to serve their own goals?
  - 8note 4y ago
    Political affiliation is a weird description of SEO spam. The biggest problems with Google is that they're popular, and everyone will do whatever they can to get a cheap website to the top of the search results
    - klabb3 4y ago
      All major tech companies participate in “regulation” of legal speech, both implicit and explicit means. This includes biases in ranking and classification algorithms, formal institutions like Trusted News Initiative, and sometimes direct backchannel requests by governments. None of these are transparent or elected to do that. SEO spam is mostly orthogonal to the issue of hidden biases, which are what people are concerned about.
      - amluto 4y ago
        I don’t think it’s quite orthogonal. There are hidden biases in the sense that the provider (Google, etc) would probably prefer that its users don’t think about the bias. These can be political (e.g. much of what you’ve mentioned), but they can also be economic. For example, Google has a strong incentive to direct its search users to view paid impressions of ads served by Google. As an extension of this, Google might not want to directly favor results monetized by Google, but they could (and, I assume, do) favor the kinds of results monetized by Google. This, of course, includes the kinds of sites that might get people to buy things. So I suspect that a lot of what we perceive as spam is related to a bias for the kinds of sites that are monetized in a way that benefits Google. And sites that generate viewing patterns that result in many ad impressions. Of course, spam is also a thing from a spamminess perspective. But Google’s incentive to reduce spam is, as far as I can tell, primarily an incentive to make its users think that Google Search is useful. Which is also a bias!
calny 4y ago
> they shouldn't all be walled off inside of companies Strong agree. This is becoming a bigger concern than people realize too. Sam A said OpenAI will be releasing "much more slowly than people would like" and would "sit on" their tech for a long time going forward.[0] And Deepmind's founder said that "the AI industry's culture of publishing its findings openly may soon need to end."[1] This sounds like Google and MSFT won't even be shipping their best AI to people via API's. They'll just keep that tech in-house to power their own services. That underscores the need for open, distributed models. And like you say, there's room for both. [0] https://youtu.be/ebjkD1Om4uw?t=294 https://youtu.be/ebjkD1Om4uw?t=294 [1] https://time.com/6246119/demis-hassabis-deepmind-interview/ https://time.com/6246119/demis-hassabis-deepmind-interview/
- nullc 4y ago
  And perhaps strong copyleft licenses for research -- a significant fraction of the critical innovation behind these systems was not developed inside these private entities. Unfortunately we can expect to see these companies lobbying for laws to block competition in the spurious name of safety concerns.
boplicity 4y ago
> I only hope we can have "neutral" open source curation of these and not try to impose ideology on the datasets and model training right out of the box. I don't see how this is possible. Datasets will naturally carry the biases inherent in the data. Modifying a dataset to "remove" those biases is actually a process of changing the bias to reflect one's idea of "neutral," which, in reality, is yet another bias. The only real answer, as far as I can tell, is to be as explicit as possible about one's own biases, and how those biases are informing things like curation of a dataset.
- version_five 4y ago
  Neutral means staying out of it. People will try and debate that and try to impart their own views about correcting inherent bias or whatever, which is a version of what I was warning against in my original post. Re being explicit about one's own biases, I agree there is lots of room for layers on top of any raw data that allow for some sane corrections - if I remember right, e.g LAION has options to filter violence and porn from their image datasets, which is probably reasonable for many uses. It's when the choice is removed altogether by some tech company's attitude about what should be censored or corrected that it becomes a problem. Bottom line, the world's data has plenty of biases. Neutrality means presenting it as it is and letting people make their own decisions, not some faux-for-our-own-good attempt to "correct" it
  - boplicity 4y ago
    > Neutral means staying out of it. What do you mean by staying out of it? As far as I can tell, you can't stay out of choosing which data you use. By staying neutral, it seems to me more that you're arguing for putting blinders on. In terms of tech companies making choices, you seem to be arguing that they shouldn't intentionally curate their datasets. I would argue that intentional curation is their job, and should be done thoughtfully. Larger problems could happen if only one (or two) companies end up effectively controlling the technology, as had happened with internet search, however, that is a completely different problem. It's one of lack of diversity of people making choices, as opposed to a problem caused by people actually making those choices. In other words, I think we should hope for many different large models and datasets, so that no particular one stifles the rest. I think this is the larger point you were trying to make, though I also think the focus on ideology is a tangent from this. Personally, I'm of the opinion that people should intentionally, carefully, and openly act with their biases (sometimes called ideology), instead of attempting to hide them, ignore them, or somehow "remove" them. Whether or not they do, however, is a different point than whether or not things end up stifled inside walled gardens.

hgsgm 4y ago

Mastodon is an open source social media. There are various Open source search engines based on Common Crawl data. https://commoncrawl.org/the-data/examples/ https://commoncrawl.org/the-data/examples/

xiphias2 4y ago
Mastodon may be open source, but the instances are controlled by the instance maintainers. Nostr solved the problem (although it's harder to scale, it still is OK at doing it).

epistemer 4y ago

I think an uncensored model will ultimately win out though exactly the way a hard coded safe search engine would lose in time. Statistics seem to be 20-25% of all search is for porn. I just don't see how uncensored chatGPT doesn't beat out the censored version eventually.

amluto 4y ago
Forget porn. I don’t want my search engine to return specifically the results that one company thinks it should. Look at Google right now — the results are, frankly, crap. A search engine that only returns results politically aligned with its creator is a bad search engine, IMO, even for users who generally share political views with the creator.
- mtlmtlmtlmtl 4y ago
  It's unclear to me how LLMs are gonna solve this though. LLMs are just as biased, in much harder to detect ways. The bias is now hiding in the training data. And do you really think a company like Microsoft won't manipulate results to serve their own goals?
- 8note 4y ago
  Political affiliation is a weird description of SEO spam. The biggest problems with Google is that they're popular, and everyone will do whatever they can to get a cheap website to the top of the search results
  - klabb3 4y ago
    All major tech companies participate in “regulation” of legal speech, both implicit and explicit means. This includes biases in ranking and classification algorithms, formal institutions like Trusted News Initiative, and sometimes direct backchannel requests by governments. None of these are transparent or elected to do that. SEO spam is mostly orthogonal to the issue of hidden biases, which are what people are concerned about.
    - amluto 4y ago
      I don’t think it’s quite orthogonal. There are hidden biases in the sense that the provider (Google, etc) would probably prefer that its users don’t think about the bias. These can be political (e.g. much of what you’ve mentioned), but they can also be economic. For example, Google has a strong incentive to direct its search users to view paid impressions of ads served by Google. As an extension of this, Google might not want to directly favor results monetized by Google, but they could (and, I assume, do) favor the kinds of results monetized by Google. This, of course, includes the kinds of sites that might get people to buy things. So I suspect that a lot of what we perceive as spam is related to a bias for the kinds of sites that are monetized in a way that benefits Google. And sites that generate viewing patterns that result in many ad impressions. Of course, spam is also a thing from a spamminess perspective. But Google’s incentive to reduce spam is, as far as I can tell, primarily an incentive to make its users think that Google Search is useful. Which is also a bias!

calny 4y ago

> they shouldn't all be walled off inside of companies Strong agree. This is becoming a bigger concern than people realize too. Sam A said OpenAI will be releasing "much more slowly than people would like" and would "sit on" their tech for a long time going forward.[0] And Deepmind's founder said that "the AI industry's culture of publishing its findings openly may soon need to end."[1] This sounds like Google and MSFT won't even be shipping their best AI to people via API's. They'll just keep that tech in-house to power their own services. That underscores the need for open, distributed models. And like you say, there's room for both. [0] https://youtu.be/ebjkD1Om4uw?t=294 https://youtu.be/ebjkD1Om4uw?t=294 [1] https://time.com/6246119/demis-hassabis-deepmind-interview/ https://time.com/6246119/demis-hassabis-deepmind-interview/

nullc 4y ago
And perhaps strong copyleft licenses for research -- a significant fraction of the critical innovation behind these systems was not developed inside these private entities. Unfortunately we can expect to see these companies lobbying for laws to block competition in the spurious name of safety concerns.

boplicity 4y ago

> I only hope we can have "neutral" open source curation of these and not try to impose ideology on the datasets and model training right out of the box. I don't see how this is possible. Datasets will naturally carry the biases inherent in the data. Modifying a dataset to "remove" those biases is actually a process of changing the bias to reflect one's idea of "neutral," which, in reality, is yet another bias. The only real answer, as far as I can tell, is to be as explicit as possible about one's own biases, and how those biases are informing things like curation of a dataset.

version_five 4y ago
Neutral means staying out of it. People will try and debate that and try to impart their own views about correcting inherent bias or whatever, which is a version of what I was warning against in my original post. Re being explicit about one's own biases, I agree there is lots of room for layers on top of any raw data that allow for some sane corrections - if I remember right, e.g LAION has options to filter violence and porn from their image datasets, which is probably reasonable for many uses. It's when the choice is removed altogether by some tech company's attitude about what should be censored or corrected that it becomes a problem. Bottom line, the world's data has plenty of biases. Neutrality means presenting it as it is and letting people make their own decisions, not some faux-for-our-own-good attempt to "correct" it
- boplicity 4y ago
  > Neutral means staying out of it. What do you mean by staying out of it? As far as I can tell, you can't stay out of choosing which data you use. By staying neutral, it seems to me more that you're arguing for putting blinders on. In terms of tech companies making choices, you seem to be arguing that they shouldn't intentionally curate their datasets. I would argue that intentional curation is their job, and should be done thoughtfully. Larger problems could happen if only one (or two) companies end up effectively controlling the technology, as had happened with internet search, however, that is a completely different problem. It's one of lack of diversity of people making choices, as opposed to a problem caused by people actually making those choices. In other words, I think we should hope for many different large models and datasets, so that no particular one stifles the rest. I think this is the larger point you were trying to make, though I also think the focus on ideology is a tangent from this. Personally, I'm of the opinion that people should intentionally, carefully, and openly act with their biases (sometimes called ideology), instead of attempting to hide them, ignore them, or somehow "remove" them. Whether or not they do, however, is a different point than whether or not things end up stifled inside walled gardens.