But as you point out, there’s reason to think Amazon’s search engine is imperfect, especially for new products. Ads are the messy, side-effect-laden solution for that problem.

That can be annoying, but it also happens in debates between people, and sometimes the implicit assumptions are real and (sorry) load-bearing. So it can be an appropriate conversational tack.

I think government should work more on helping people find alternatives to social media. The “town square effect” that makes people feel forced to use these apps is real and pernicious. That feels like a better target for regulation and taxation than content. If your business moat is based on network effects, perhaps there should be the equivalent of a land value tax on your network.

https://en.wikipedia.org/wiki/Signalling_(economics)

https://en.wikipedia.org/wiki/Costly_signaling_theory_in_evo...

Republicans are an anti-tax and to some extent anti-debt constituency. Liberals are also fairly anti-tax, unless it’s limited to taxing the rich. There’s opposition now to all forms of new energy infrastructure: to oil/gas/nuclear from the left and many liberals, to wind/solar from the right.

There are no “easy ways.” Only hard fights, against both sometime allies and longtime political opponents.

You have an audience willing to give you the benefit of the doubt to learn something they’re unfamiliar with.

It’s specifically the fact that you chose to highlight a topic that makes your audience pay attention. Perhaps nobody else could have gotten their attention and adjusted their perspective the way you can. Not necessarily because you’re intrinsically better, but because they’ve chosen to pay attention to you.

I’m scrolling Hacker News and this post happened to be on the front page. Your comment happened to be the first comment. Im in the audience for OP and for you. If this post or your comment hadn’t been here, I’d have been doing and thinking about something else. Is that good or bad? I don’t know. But it is different. The human tendency to be receptive to convenient information sources, regardless of their novelty or whether they’re of maximum quality, may be adaptive.

Charles P Pierce https://en.wikipedia.org/wiki/Charlie_Pierce

Conservatives don’t have as much of a problem with science when it avoids “impact science” and sticks to topics that don’t conflict with church teachings or business interests.

But trust in science has never been universal. Trust in institutions and experts had to be built painstakingly over generations. The Social Transformation of American Medicine is a great account of this process for American doctors.

“Leaving nothing on the table” would mean selling few enough shares at the IPO that you have to overpay to get shares at the IPO. Previous valuations are known, as is that implied by each choice of IPO price when looking at the book. So the skill is just in the company not needing all that much money and being great at generating hype.

I would fully expect that a monotonous diet leads to a heavy skew in the gut microbiome as specific bacterial species that thrive on that diet are selected for, others against. It makes some sense that a fecal transplant could repair the damage. If the diet has shifted or expanded, the transplant could lead to long term benefits by restoring newly-viable bacterial species, perhaps by facilitating digestion of the new types of food.

I’d be curious to see a factoring out of the diet composition, gut microbiome, genetics, and severity of autism symptoms.

But when making decisions about a real patient’s care, a doctor will be operating under different motivations.

They can also refer patients to a specialist, defer a diagnosis until they have more information, use external resources, consult with other doctors.

Doctors aren’t chatbots. They are clinical care directors.

Presuming there are no issues with information leakage, it’s genuinely impressive AI can perform this level of success at a specific doctoring skill. That doesn’t make it a replacement for a doctor. It does make it a useful tool for a doctor or a patient, which is exactly what we’re seeing in practice.

For PCR, one of the innovations I’m excited about is the development of PCR that preserves chemical properties of the input DNA, like CG methylation. This is a critical epigenetic mark on cytosines (C DNA bases). When cytosine’s followed by guanine (G base), forming the sequence CG, its complement is also CG. There’s an enzyme called a maintenance methyltransferase that copies CG methylation from the template ssDNA strand to the new reverse strand during DNA replication.

Normally this mark gets diluted into invisibility during PCR, because there’s no maintenance methyltransferase to preserve it as the input DNA is copied. A thermostable maintenance methyltransferase can preserve CG methylation throughout PCR. This is brand new technology that’s just making its way into the scientific marketplace now. It’s the kind of PCR innovation my lab’s excited about.

https://www.cbc.ca/news/canada/trump-canada-yukon-1.3235254

We can react to the fact that mothers can do more to protect their children from abuse in many ways. We can give them better access to information and support in getting away from abusers. We can create better links between police and communities they serve. We can create more pathways for children to be exposed to healthy adult behavior and connections with healthy adults, even when the family is dysfunctional.

But when we find evidence that existing supports have failed, deeply investigating why is critical.

AI and humans are labor that can be put to work designing and vetting such systems. The problem with AI isn’t that it builds things we don’t understand. It’s that we do not have much experience with its failure modes, limitations and risks. There are many unknown unknowns.

It’s directly analogous to the problem of hiring, management, outsourcing and contacting. Sure, we know that labor can produce massive, highly reliable systems nobody fully understands. But how do we coordinate labor, AI and human, to successfully produce the systems we actually need? What failure modes and advantages does AI introduce into the mix for specific projects?

That’s where the uncertainty comes from, not the lack of comprehensive knowledge of the systems themselves.

But Tyler Cowen’s calling in particular is ABSOLUTELY to suck up to power.