5 ms·

We are getting to a point where "trust" is the biggest issue. Can you trust govt, big corporations, universities? It's like everyone is optimizing for their ga

by nojvek 10y ago

We are getting to a point where "trust" is the biggest issue. Can you trust govt, big corporations, universities? It's like everyone is optimizing for their gain and deceiving the other side with what they need to hear. We are in the era of information overload without a good way of filtering fact from dogma. I hope there is some development of good AI that helps the average Joe hunt this facts down for him/her. Google's fact verification algorithm is in the right direction. Can we trust it? I hope Facebook implements something similar but that's unlikely since they're in the entertainment and ads business. I really hope orgs like openai are able to create something like this for the world.

leereeves 10y ago
How would an AI know the truth? In the short term, only by comparing an article under review to "trusted" sources. But if there were any such sources available to tell us the ground truth, we wouldn't need the AI.
- TeMPOraL 10y ago
  I can totally imagine AI knowing the truth, by the virtue of throwing lots of compute at Bayesian inference. The more difficult question, I think, is: why should an average Joe trust the (presumably government or corporate) AI over their favourite worldview-confirming sources?
  - leereeves 10y ago
    Bayesian inference based on what evidence?
    - TeMPOraL 10y ago
      Observational. Reality has to add up to a coherent whole, so I imagine a sufficiently smart AI getting a good picture of it through just observing a lot.
      - deleted 10y ago
        [deleted]
      - coldtea 10y ago
        There's no truth in most matters, just perspectives and interests. Truth is not an inherent reality of the universe. There is matter and energy in various juxtapositions, but no 'truth', except if by truth we mean correctly describing a physical order of things. But that's hardly the interesting part or what we usually want to know when we speak of truth. At best, truth in things like politics and such requires a definition first, and so the problem of what's true is just moved to "according to whose definition?". Is "wealthfare harmful", for example, is not about knowing or not knowing its cost, but more about whether you think the costs are justified. One can legitimately believe that poor people should be left to rot if they can't afford healthcare, for example. Second, why would an "advanced AI" stick to the truth any more than a human would? Especially if distorting it brings large benefits for it?
        TeMPOraL 10y ago
        That's how the world goes downhill. Instead of getting at the truth, people are - well, literally - playing politics. When I ask someone if "welfare is harmful", I ask for their opinion on the relative impact it has on various issues we want to optimize for, which mostly boil down to short and long-term happiness of people. It's a difficult question, but still a factual one. The list of things we want to optimize for is finite, there is some ordering to it, and the impact of various actions on those things is, in principle, calculable. Even the question of "can welfare be justified" is an objective one. There is some model for "justified" that you have, and the data either lets you justify welfare or does not (and tells you the degree to which it is so, if your thinking process is worth anything). It's only when people start pushing their stupid agendas and start putting their personal interests in focus that the whole thing gets "difficult". -- Either way, I only said that a sufficiently smart AI could know the truth (or at least a good approximation of it). I didn't say it will necessarily tell it to people who ask. But an AI that can't correctly from data would be a pretty shitty AI. It's enough that human brains have this problem.
- dredmorbius 10y ago
  https://en.m.wikipedia.org/wiki/Criteria_of_truth https://en.m.wikipedia.org/wiki/Criteria_of_truth This isn't a greenfield.
- Elrac 10y ago
  > How would an AI know the truth? There's been some research on this. I think I even saw at least one article about it here on HN, though I can't find a link any more. What I remember seeing is a kind of world (?) map of the Internet with a set of different-colored interconnecting webs of sites. There is one set that deals mostly in verifiable facts, usually based on genuine, usually academic research. Universities are major nodes in this net, but you get some overlap with "mainstream" news sources, Wikipedia and so on. There's another major set that includes InfoWars, Collective Evolution, Natural News, Deepak Chopra, Mercola and other Anti-Vaxxers, various AGW deniers, and other well-known sources of bullshit. Both of those networks have many more connections within themselves than to the other clouds, and have their own frequent-viewer audiences who will frequent the one set more than the other. There were, as I remember, other sets that were less significant. Purely on probability, a story will be dramatically more likely to be true if originated and/or propagated in the first of those clouds than the second. Mapping these webs is a pretty mundane mechanical task, yet it can provide an excellent filter for some classes of information. Other stuff is "squishier" because it's more opinion than fact. Politics and policies will be found here, and you're likely to see (I don't remember if the article I have in mind showed this) "conservative" vs. "liberal" networks rather than "fact" vs. "bullshit". On the other hand, there are experts on many aspects of politics, and if you're looking for ideas on policy that are informed by history and research, you're more likely to get them from professors of history, economics and law than from Fox News or televangelist channels. I suspect there are a lot more inferences that can be drawn, via probability or Bayes, from the Internet sources of information, its propagation behavior, and the shape of the networks it travels. Similarly, there's a wealth of information to be gained from analyzing the language of an individual page. Emotional words vs. dispassionate ones; weasel words like "probably" or "it was said" as opposed to "according to" or links to other sources. Bullshit is often simplified for consumption by simple people, while academics often carelessly lapse into "high-bred" or technical language. Some of those features could be gamed, simulated, faked, and certainly will be. Many bullshit articles in the health, field, for instance, now link to "outlier" or discredited papers in PubMed to enhance their credibility. But like our grandparent poster, I think AI, working patiently and dispassionately, will be able to continue to find hints to distinguish the wheat from the chaff.

by nojvek 10y ago

leereeves 10y ago

How would an AI know the truth? In the short term, only by comparing an article under review to "trusted" sources. But if there were any such sources available to tell us the ground truth, we wouldn't need the AI.

TeMPOraL 10y ago
I can totally imagine AI knowing the truth, by the virtue of throwing lots of compute at Bayesian inference. The more difficult question, I think, is: why should an average Joe trust the (presumably government or corporate) AI over their favourite worldview-confirming sources?
- leereeves 10y ago
  Bayesian inference based on what evidence?
  - TeMPOraL 10y ago
    Observational. Reality has to add up to a coherent whole, so I imagine a sufficiently smart AI getting a good picture of it through just observing a lot.
    - deleted 10y ago
      [deleted]
    - coldtea 10y ago
      There's no truth in most matters, just perspectives and interests. Truth is not an inherent reality of the universe. There is matter and energy in various juxtapositions, but no 'truth', except if by truth we mean correctly describing a physical order of things. But that's hardly the interesting part or what we usually want to know when we speak of truth. At best, truth in things like politics and such requires a definition first, and so the problem of what's true is just moved to "according to whose definition?". Is "wealthfare harmful", for example, is not about knowing or not knowing its cost, but more about whether you think the costs are justified. One can legitimately believe that poor people should be left to rot if they can't afford healthcare, for example. Second, why would an "advanced AI" stick to the truth any more than a human would? Especially if distorting it brings large benefits for it?
      - TeMPOraL 10y ago
        That's how the world goes downhill. Instead of getting at the truth, people are - well, literally - playing politics. When I ask someone if "welfare is harmful", I ask for their opinion on the relative impact it has on various issues we want to optimize for, which mostly boil down to short and long-term happiness of people. It's a difficult question, but still a factual one. The list of things we want to optimize for is finite, there is some ordering to it, and the impact of various actions on those things is, in principle, calculable. Even the question of "can welfare be justified" is an objective one. There is some model for "justified" that you have, and the data either lets you justify welfare or does not (and tells you the degree to which it is so, if your thinking process is worth anything). It's only when people start pushing their stupid agendas and start putting their personal interests in focus that the whole thing gets "difficult". -- Either way, I only said that a sufficiently smart AI could know the truth (or at least a good approximation of it). I didn't say it will necessarily tell it to people who ask. But an AI that can't correctly from data would be a pretty shitty AI. It's enough that human brains have this problem.
dredmorbius 10y ago
https://en.m.wikipedia.org/wiki/Criteria_of_truth https://en.m.wikipedia.org/wiki/Criteria_of_truth This isn't a greenfield.
Elrac 10y ago
> How would an AI know the truth? There's been some research on this. I think I even saw at least one article about it here on HN, though I can't find a link any more. What I remember seeing is a kind of world (?) map of the Internet with a set of different-colored interconnecting webs of sites. There is one set that deals mostly in verifiable facts, usually based on genuine, usually academic research. Universities are major nodes in this net, but you get some overlap with "mainstream" news sources, Wikipedia and so on. There's another major set that includes InfoWars, Collective Evolution, Natural News, Deepak Chopra, Mercola and other Anti-Vaxxers, various AGW deniers, and other well-known sources of bullshit. Both of those networks have many more connections within themselves than to the other clouds, and have their own frequent-viewer audiences who will frequent the one set more than the other. There were, as I remember, other sets that were less significant. Purely on probability, a story will be dramatically more likely to be true if originated and/or propagated in the first of those clouds than the second. Mapping these webs is a pretty mundane mechanical task, yet it can provide an excellent filter for some classes of information. Other stuff is "squishier" because it's more opinion than fact. Politics and policies will be found here, and you're likely to see (I don't remember if the article I have in mind showed this) "conservative" vs. "liberal" networks rather than "fact" vs. "bullshit". On the other hand, there are experts on many aspects of politics, and if you're looking for ideas on policy that are informed by history and research, you're more likely to get them from professors of history, economics and law than from Fox News or televangelist channels. I suspect there are a lot more inferences that can be drawn, via probability or Bayes, from the Internet sources of information, its propagation behavior, and the shape of the networks it travels. Similarly, there's a wealth of information to be gained from analyzing the language of an individual page. Emotional words vs. dispassionate ones; weasel words like "probably" or "it was said" as opposed to "according to" or links to other sources. Bullshit is often simplified for consumption by simple people, while academics often carelessly lapse into "high-bred" or technical language. Some of those features could be gamed, simulated, faked, and certainly will be. Many bullshit articles in the health, field, for instance, now link to "outlier" or discredited papers in PubMed to enhance their credibility. But like our grandparent poster, I think AI, working patiently and dispassionately, will be able to continue to find hints to distinguish the wheat from the chaff.