This isn't a particularly deep or informed take, but my perspective on it is that the "misinformation problem" is similar to what Scott called the cowpox of doubt:

What annoys me about the people who harp on moon-hoaxing and homeopathy – without any interest in the rest of medicine or space history – is that it seems like an attempt to Other irrationality.

It’s saying “Look, over here! It’s irrational people, believing things that we can instantly dismiss as dumb. Things we feel no temptation, not one bit, to believe. It must be that they are defective and we are rational.”

But to me, the rationality movement is about Self-ing irrationality.

It is about realizing that you, yes you, might be wrong about the things that you’re most certain of, and nothing can save you except maybe extreme epistemic paranoia.

10 years ago, it was popular to hate on moon-hoaxing and homeopathy, now it's popular to hate on "misinformation". Fixating on obviously-wrong beliefs is probably counterproductive to forming correct beliefs on important and hard questions.

Excerpt from Deepfakes: A Grounded Threat Assessment - Center for Security and Emerging Technology (I haven't read the whole paper):

This paper examines the technical literature on deepfakes to assess the threat they pose. It draws two conclusions. First, the malicious use of crudely generated deepfakes will become easier with time as the technology commodifies. Yet the current state of deepfake detection suggests that these fakes can be kept largely at bay. 

Second, tailored deepfakes produced by technically sophisticated actors will represent the greater threat over time. Even moderately resourced campaigns can access the requisite ingredients for generating a custom deepfake. However, factors such as the need to avoid attribution, the time needed to train an ML model, and the availability of data will constrain how sophisticated actors use tailored deepfakes in practice.

Based on this assessment, the paper makes four recommendations:

• Build a Deepfake “Zoo”: Identifying deepfakes relies on rapid access to examples of synthetic media that can be used to improve detection algorithms. Platforms, researchers, and companies should invest in the creation of a deepfake “zoo” that aggregates and makes freely available datasets of synthetic media as they appear online.
• Encourage Better Capabilities Tracking: The technical literature around ML provides critical insight into how disinformation actors will likely use deepfakes in their operations, and the limitations they might face in doing so. However, inconsistent documentation practices among researchers hinders this analysis. Research communities, funding organizations, and academic publishers should work toward developing common standards for reporting progress in generative models.
• Commodify Detection: Broadly distributing detection technology can inhibit the effectiveness of deepfakes. Government agencies and philanthropic organizations should distribute grants to help translate research findings in deepfake detection into user-friendly apps for analyzing media. Regular training sessions for journalists and professions likely to be targeted by these types of techniques may also limit the extent to which members of the public are duped.
• Proliferate Radioactive Data: Recent research has shown that datasets can be made “radioactive.” ML systems trained on this kind of data generate synthetic media that can be easily identified. Stakeholders should actively encourage the “radioactive” marking of public datasets likely to train deep generative models. This would significantly lower the costs of detection for deepfakes generated by commodified tools. It would also force more sophisticated disinformation actors to source their own datasets to avoid detection

Is it tractable?

1. One might argue that the amount of misinformation in the world is decreasing, not increasing. Maybe we're much more aware of it, which would be a good thing.
2. Lesswrong and the EA Forum are making progress on this, no? This is one of my top ideas for how tech can help our causes
3. Wikipedia also helps a lot, I think. There might be other such ideas (because of inadequate equilibria), so if we find them, it might be a worthy use of EA founders+funds: A relatively easy way to provide a ton of value to society in a way that is hard (or maybe impossible) to monitize.

Regarding deep fakes:

Scott Alexander wrote about it:

https://slatestarcodex.com/2020/01/30/book-review-human-compatible/

This part stuck with me:

Also, it’s hard to see why forging videos should be so much worse than forging images through Photoshop, forging documents through whatever document-forgers do, or forging text through lying. Brookings explains that deepfakes might cause nuclear war because someone might forge a video of the President ordering a nuclear strike and then commanders might believe it. But it’s unclear why this is so much more plausible than someone writing a memo saying “Please launch a nuclear strike, sincerely, the President” and commanders believing that. Other papers have highlighted the danger of creating a fake sex tape with a politician in order to discredit them, but you can already convincingly Photoshop an explicit photo of your least favorite politician, and everyone will just laugh at you.