The trustworthy reputation of the media has taken a hit.  Over, and over, and over again.  While that trust fell into the abyss around the 2016 US election, the industry has never been able to recover.  The extraordinary drivers of this dip have been two, nearly unrelated things.  First, the decision by certain figures to start calling any news stories they don’t like “fake news”, which was repeated so often by hardcore followers that other figures globally quickly coined the term as well (with mixed results).  Second, the very real mis- and dis- information campaigns started on social media to drive specific opinions but also general discord; and because of the attention these campaigns received, traditional news outlets more than once picked up the social media posts and ran them as news with little due diligence.  The result was both real news that was labelled fake because it made certain people look bad; and truly fake news that was believed by some and debunked by others, but even factual debunking simply led to cries of “fake news”.  This cycle continues at various stages even today, but has been made even worse by the evolution of AI slop.  This allows just about anyone to make news stories that, so long as they are not absolutely outlandish, at least some people will believe them.  It also allows real news stories to be labelled as “AI fake news,” repeating a disturbing cycle.

Believe it or call it fake news, but a recent Gallup Poll shows that Americans’ trust in overall media remains near that record low, with plenty of momentum to dip it to record lows in the near future.  While 34% have either a high or fair amount of confidence in the media, a full 38% place zero trust in what they hear on official news channels.

One more driver likely helps put a dent in these numbers: news pundits are more and more expressing their opinions on events rather than focusing on impartiality.  This is exacerbated by top social media personalities making a living from this, and traditional outlets following the trend in order to stay relevant.  What earns clicks and therefore revenue isn’t the truth, it is the ability to sensationalize a story, and truth is simply not a driving factor to make that happen.  Either way, the word “truth”, even in what should be a mostly impartial industry, is losing value.

And all of this is paving the way for prediction markets to take a large chunk of our attention.  It’s not even that prediction markets have better sources or even more impartial sources.  It’s simply that prediction markets, by their nature, have a strong financial incentive to root out the truth, rewarding those who contribute to correct predictions.  If anything can be trusted, it is a financial incentive.  Let’s take a look at prediction markets to see how they are operating, why they have recently become so relevant, and what we can expect from the “truth” in the near future.

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The Rise (and Stall) of Prediction Markets

Prediction markets in some form have been around for centuries, but their modern form came onto the stage in the 1980s and 1990s, where early electronic markets were able to demonstrate that an accumulated betting behavior, driven by rewards, was able to accurately forecast events at least as well as traditional methods.  For certain events such as elections and economic indicators, the accuracy could rise above traditional means as the pieces of the engine itself consisted of those who were voting with their ballot or dollar to make events happen.  By taking the idea of voting on some event and tying to it the direct financial incentive, a large grouping of inputs could produce a statistically stable (and fairly accurate) forecast.  Why didn’t this just become “the market”?  Because regulations and heavy centralization of the platforms limited prediction markets to little more than academic experiments.

And then came Web3, allowing decentralization to reinvent the entire model, and the world is starting to notice.

Web3 Is The Key

The ability to take a model like prediction markets and fully decentralize it eliminates some of the strongest barriers that restricted their use to date.  Aside from the obvious elimination of insider fixing and various types of fraud, a decentralized platform upgrades a prediction market instantly.  First, it turns a tightly controlled market into a globally accessible opportunity to predict events of any size, the bigger the better.  Second, the borderless aspect and use of digital assets prevents a regulatory body from suddenly shutting down a prediction market without notice, a risk for which created dampening effects for those centralized prediction markets.  Third, the ability of a trustless third party such as a smart contract operating with an oracle ensures that the human element of bad actors is taken out of play.  The truth is sought and revered through the probabilities that arise, and the trustless system makes sure that the truth is captured without having any incentives to do otherwise.  Web3’s unique aspects all seem to enhance the prediction market, as if the model was simply waiting for the invention of Web3 for it to be complete.  Platforms like Myriad, Polymarket, Augur, and Omen are driving these markets, and their intuitive alignment of incentives and truth are speaking out to a fast-growing audience.  It will not be long, and in some cases could be possible today, for prediction markets to play a role in traditional news stories as those outlets make an effort to slowly regain all the trust they have lost with their audiences.

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