I can think of a few directions for technology aiding in fact checking:
1. Much of finding out what’s true or false is about finding consistency amongst lots of observations. So this is the science direction. If you can analyze lots of data, say from first-hand direct measurements like from a scientific instrument, or analyzing second hand observational data, say from many news sources reporting on a political event. One could also imagine multimodal analysis combining these first and second-hand kinds of data to arrive at a consensus estimate of a “true” perspective. E.g. analyzing video and audio streams recorded at said political event, combined with many text reports of the event. So this point is about data mining, and jointly estimating semantic meaning from natural language and other kinds of data, in a way that’s consistent with everything else considered factual.
2. Provenance-tracking: Think block chain - if we can provably trace a piece of data back to its primary sources, tracking all its modifications along the way, this could help with establishing provenance, and verifying legitimacy of any modifications along the way.
3. Consensus, staking/voting, etc. A lot of deciding what’s true is about seeking consensus. One thing I’m generally optimistic about here is that, for any given fact “out there,” there are many more ways to describe it incorrectly than correctly. So even though it sounds scary for consensus to be an aspect of truth finding, it always will be, and at the very bottom it’s all we can hope for. One way that’s already getting traction to make consensus mean something, is the idea of staking. So you have to put something down on the table when you claim you believe something to be true. Software can (and already is) helping to build confidence behind some claims more than others by backing claims with value (money).
4. Humans are insanely bad at reasoning rationally, because of lots of reasons. Pick your favorite fallacy. We evolved to survive long enough to reproduce and rationality is a happy accident. One could imagine software being less susceptible to simple tricks, could be less incentivized to outright lie for personal gain or power seeking, or claiming to represent their actual beliefs when they are actually pursuing other goals by conveying something they don’t actually believe.
1. Much of finding out what’s true or false is about finding consistency amongst lots of observations. So this is the science direction. If you can analyze lots of data, say from first-hand direct measurements like from a scientific instrument, or analyzing second hand observational data, say from many news sources reporting on a political event. One could also imagine multimodal analysis combining these first and second-hand kinds of data to arrive at a consensus estimate of a “true” perspective. E.g. analyzing video and audio streams recorded at said political event, combined with many text reports of the event. So this point is about data mining, and jointly estimating semantic meaning from natural language and other kinds of data, in a way that’s consistent with everything else considered factual.
2. Provenance-tracking: Think block chain - if we can provably trace a piece of data back to its primary sources, tracking all its modifications along the way, this could help with establishing provenance, and verifying legitimacy of any modifications along the way.
3. Consensus, staking/voting, etc. A lot of deciding what’s true is about seeking consensus. One thing I’m generally optimistic about here is that, for any given fact “out there,” there are many more ways to describe it incorrectly than correctly. So even though it sounds scary for consensus to be an aspect of truth finding, it always will be, and at the very bottom it’s all we can hope for. One way that’s already getting traction to make consensus mean something, is the idea of staking. So you have to put something down on the table when you claim you believe something to be true. Software can (and already is) helping to build confidence behind some claims more than others by backing claims with value (money).
4. Humans are insanely bad at reasoning rationally, because of lots of reasons. Pick your favorite fallacy. We evolved to survive long enough to reproduce and rationality is a happy accident. One could imagine software being less susceptible to simple tricks, could be less incentivized to outright lie for personal gain or power seeking, or claiming to represent their actual beliefs when they are actually pursuing other goals by conveying something they don’t actually believe.