You are right that by default prediction markets do not generate money, and this can mean traders have little incentive to trade.
Sometimes this doesn't even matter. Sports betting is very popular even though it's usually negative sum.
Otherwise, trading could be stimulated by having someone who wants to know the answer to a question provide a subsidy to the market on that question, effectively paying traders to reveal their information. The subsidy can take the form of a bot that bets at suboptimal prices, or a cash prize for the best performing trader, or many other things.
Alternately, there could be traders who want shares of YES or NO in a market as a hedge against that outcome negatively affecting their life or business, who will buy even if the EV is negative, and other traders can make money off them.
In theory, there can be information-seekers who subsidize either the operation of the market, or the payout pool for specific questions, or provide bonuses for profitable investors/market-adjusters.
But fundamentally, there's no "outside" source of income to participants, like there is for stock ownership (theoretically; there's a LOT of companies who've never paid a dividend).
It’s not zero net value because there’s information produced, and also it’s fun. A more rational alien species that does not find risk enjoyable would have less accurate prediction markets (although without such thing as “gambling” maybe their markets are actually legal and thus more accurate.)
At manifold we haven’t really found a good way to use the information value yet. Subsidization doesn’t lead to increased activity in practice unless it makes the market among the top best trading opportunities. Pay for views has been much more effective as a “pay for information” method than subsidy. Most users are bettors rather than viewers. It’s good that we’re good at converting people, but without a long tail of lurkers we aren’t generating a lot of value from the information itself.
There is a situation in which information markets could be positive sum, though I don't know how practical it is:
I own a majority stake in company X. Someone has proposed an action A that company X take, I currently think this is worse than the status quo, but I think it's plausible that with better information I'd change my mind. I set up an exchange of X-shares-conditional-on-A for USD-conditional-on-A and the analogous exchange conditional on not-A, subsidised by some fraction of my X shares using an automatic market maker. If, by the closing date, X-shares-conditional-on-A trade at a sufficient premium to X-shares-conditional-on-not-A, I do A.
In this situation, my actions lose money vs the counterfactual of doing A and not subsidising the market, but compared to the counterfactual of not subsidising the market and not doing A I gain money because the rest of my stock is now worth more. It's unclear how I do compared to the most realistic counterfactual of "spend $Y researching action A more deeply and act accordingly".
(note that conditional prediction markets also have incentive issues WRT converging to the correct prices, though I'm not sure how important these are in practice)
In a good prediction market design users would not bet USD but instead something which appreciates over time or generates income (e.g. ETH, Gold, S&P 500 ETF, Treasury Notes, or liquid and safe USD-backed positions in some DeFi protocol).
Another approach would be to use funds held in the market to invest in something profit-generating and distribute part of the income to users. This is the same model which non-algorithmic stablecoins (USDT, USDC) use.
So it's a problem, but definitely a solvable one, even easily solvable. The major problem is that prediction markets are basically illegal in the US (and probably some other countries as well).
Also, Manifold solves it in a different way -- positions are used to receive loans, so you can free your liquidity from long (timewise) markets and use it to e.g. leverage. The loans are automatically repaid when you sell your positions. It is easy for Manifold because it doesn't use real money, but the same concept can be implemented in the "real" markets, although it would be more challenging (there will be occasional losses for the provider due to bad debt but it's the same with any other kind of credit, it can be managed).
A lot of the money comes from the bad traders. If you have no bad traders, the prices are correct.
A better mechanism though is to "subsidize the market", meaning the person who wants the information incentives the market to collect it. In particular, you can set up subsidy schemes where the average cost to the subsidizer is proportional to the number of bits of information they gained.
I've only watched some prediction market news from the outside, so forgive my basic question, but are prediction markets supposed to bring in money besides having new entrants bring in cash?
I've often seen prediction markets compared to stock markets, but the stock market is generally positive-sum because you're investing money in profitable businesses that pay dividends. In contrast, if a prediction market begins with 1000 people with $1000 each (and no one else joins or brings in more money), can it ever have more than $1,000,000 in the market?
If the answer is "no, it doesn't generate money", isn't that a big problem for prediction markets as a long-term concept? It means everyone will be fighting over a limited pie, and there will be no reason for the average person to join the prediction market (they just stand to lose their money to the experts). Is this a problem holding back prediction markets now, and are there ideas to fix it?