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This article includes interviews from multiple experts, citing data from both retrospective and case control studies, plus the pandemic which effectively provided an even broader, country-wide study that again matched their data.

I’d love to understand why you would post such a dogmatic dismissal without so much as a citation. Are you an ophthalmology researcher yourself who is familiar with contrary and well-vetted research? Are you someone with a strong personal experience that you have a hard time squaring with the data? Or are you someone who forms strong beliefs, firmly held, regardless of whatever new information life offers?



> I’d love to understand why you would post such a dogmatic dismissal without so much as a citation

Is this your first time on hacker news?


Indeed.

As someone with an education in healthcare, nothing goes off the rails, and I mean really off the rails like a health related thread on HN.

You get some of the most ardent believers in some of the wildest hypotheses who are quick to dismiss a century or more of actual data.

That’s not to say that some early hypotheses won’t turn out to be correct, but there is a big difference between “I read this interesting paper with an interesting hypothesis” and “Hey guys, all of current medicine is 100% wrong and your doctor is conspiring to keep the truth from you (or so inept they probably can’t tie their own shoe).”


Emmitropization is a fact. Peripheral over focus causing myopia is well documented and peripheral defocus is also well studied. Peripheral defocus lenses and low dose atropine are well studied. The mechanism is understood, and proved by multiple different ways to interfere with the mechanism.

Optometrists are clothing salespeople. Only some ophthalmologists even know about atropine as an option.


Yup. If you spend time all day at a computer but never wear glasses, I can magically guess that your prescription is around -2. That's not a coincidence, just calculate the focal length and it comes out to exactly the computer screen distance.

And when you wear your full prescription without correcting for target distance, you just restart the process all over again. For some lucky people the axial length seems to be fixed after some point, but for most people that sets them on the path of increasing power.


At this valuation and given the strength of the team, it’s not hard to imagine a future acquisition yielding a significant ROI.

Besides, we don’t know what future opportunities will unfold for these technologies. Clearly there’s no shortage of smart investors happy to place bets on that uncertainty.


Dunning himself addressed this back in 2011:

> 4.1. Regression to the mean

> The most common critique of our metacognitive account of lack of self-insight into ignorance centers on the statistical notion of regression to the mean. Recall from elementary statistics classes that no two variables are ever perfectly correlated with one another. This means that if one selects the poorest performers along one variable, one will see that their scores on the second variable will not be so extreme. Similarly, if one selects the best performers along a variable, one is guaranteed to see that their scores on the second variable will be lower…

His full response is longer than is appropriate to quote here, but you can easily find the chapter online.

Dunning, David (1 January 2011). "Chapter Five – The Dunning–Kruger Effect: On Being Ignorant of One's Own Ignorance". Advances in Experimental Social Psychology. Vol. 44. Academic Press. pp. 247–296. doi:10.1016/B978-0-12-385522-0.00005-6. ISBN 9780123855220


The author continues,

> Some scholars observe that Fig. 5.2 looks like a regression effect, and then claim that this constitutes a complete explanation for the Dunning–Kruger phenomenon. What these critics miss, however, is that just dismissing the Dunning–Kruger effect as a regression effect is not so much explaining the phenomenon as it is merely relabeling it. What one has to do is to go further to elucidate why perception and reality of performance are associated so imperfectly. Why is the relation so regressive? What drives such a disconnect for top and bottom performers between what they think they have achieved and what they actually have? [...] As can be seen in the figure, correcting for measurement unreliability has only a negligible impact on the degree to which bottom performers overestimate their per-formance (see also Kruger & Dunning, 2002). The phenomenon remains largely intact.

The DK effect says roughly, "low performers tend to overestimate their abilities." Yet when researchers analyzed the data, they found that high and low performers overestimate and underestimate with the same frequency. [0] It's just that high performers are more accurate than low performers (note how this statement differs from the DK effect). Since you can completely explain the "X graph" by the random noise combined with the ceiling effect, and since beginners' self evaluations are noisier than experts', you don't even need regression to the mean to explain why you get the "X graph."

0. Nuhfer, Edward, Steven Fleisher, Christopher Cogan, Karl Wirth, and Eric Gaze. "How Random Noise and a Graphical Convention Subverted Behavioral Scientists' Explanations of Self-Assessment Data: Numeracy Underlies Better Alternatives." Numeracy 10, Iss. 1 (2017): Article 4. DOI: http://dx.doi.org/10.5038/ 1936-4660.10.1.4


> I built some software that ran on a cellphone used by LEO (law enforcement officers) to determine if the person they are quizzing is inebriated or impaired through controlled substances by examining the person's eyes and having them focus on images displayed on the phone screen.

Is this used in the field, and what level of testing and validation was required?

This is coming from a skeptical POV, but I’m genuinely curious to hear about the process. Historically, of course, law enforcement technology has a history of being anything but evidence based. It’s good that there’s finally progress away from pseudoscience like fiber analysis and smoke patterns.

But from your experience is there anything to stop LEOs from adopting new tools and technologies without adequate evaluation and standards, aside from the courts, which have such a poor track record in this space?


What’s with all the comments stating that the intersection could fool some human drivers too?

First, looking at it on 2D video shot at night is very different than actually being there. But more importantly, the acceptable threshold for autonomous vehicles is not and never will be “Better than the worst drivers.”


Definitely not a fly-by-night scam. It’s been around for almost a decade:

https://www.nytimes.com/2016/02/25/fashion/a-robot-that-has-...


It’s the original wiki (and coined the term):

https://en.m.wikipedia.org/wiki/WikiWikiWeb

Has a bit of a focus on coding, with pages/discussions for various programming patterns and terms, like:

https://c2.com/xp/YouArentGonnaNeedIt.html


A foal can stand shortly after birth. It doesn’t learn that from its environment. Say we train a quadruped AI, then what is our training simulating if not evolutionary development? It’s no different for an AGI and whatever analogue it ultimately has for our evolutionarily derived neocortex.


Walking and having feelings are two very different things though. Walking is simple enough that we can program a robot to do it without even having to resort to a NN. The concept of having feelings is so difficult that we barely understand how it works in humans, let alone how we could train a computer to have them.


Maybe emergent algorithms like biological evolution never “understand” the thing they have made, but the thing still has been made. The same might apply to our steps toward AGI.

We can’t even predict all the emergent patterns in current AI much less future, more complex systems.

Maybe there never has to be a time where someone sits down to create some sort of “feelings module” for something akin to feelings to emerge in a complex system. Same, presumably, even for sentience.


You’re focusing on the specific numbers in the example, but missing the point. Imagine the salary difference is larger.

Basically, you have one company that has already paid $250K recruiting the doc and another company that paid close to $0. So if it comes to a bidding war over salary, the former company will always be at a financial disadvantage. And budgets always have limits.


No, I'm not focusing on numbers. In fact, if I focus on the numbers they seem suspect: $250k is the cost to recruit, not the relocation costs[0]. A good chunk of that (upwards of $220K) is going to occur even with a local recruitment, which makes the disadvantage of the initial recruiter much smaller.

Further, as others have mentioned, there are other ways to contractually recoup relocation costs without a non-compete. A "you must pay back your relocation costs if you leave within a year" clause is far more justifiable than a "you can't work as a physician within 30 miles for at least 1 year if you ever leave us ever" clause.

(The same type of payback clause could apply if you did something drastic like pay off their entire student loans in one lump sum, though I am assuming that in most cases practices don't do that.)

All that said, my point had nothing to do with the numbers and everything to do with the principles: non-compete clauses are an extremely blunt instrument and are inappropriate in most cases. Firms should be required to come up with more limited contracts that accomplish their stated goals and nothing more, rather than throwing in something that is so damaging to the worker because it's easier for their lawyers.

[0] https://healthrecruitlink.com/blog/what-will-it-cost-to-recr...


You omitted the link that has a lot more detail about why they chose to license it this way:

http://sweetango.com/wp-content/uploads/2016/10/ruralcoopera...

> 44 apple growers… are members of “Next Big Thing, A Growers’ Cooperative” (NBT)… across the United States and Canada. Their ranks include both small and large producers…

> NBT was the brainchild of Minnesota apple grower Dennis Courtier, owner of Pepin Heights Orchards Inc. While Minnesota is a small player in the U.S. apple industry, ranked 20 out of 29 commercially producing states in 2014, Courtier is well known in the industry for new variety innovation. He was one of the first commercial producers to grow and market Honeycrisp apples in the 1990s. Honeycrisp — a “fruit phenomenon” produced by the University of Minnesota’s (UMN) apple-breeding program — has turned the apple category on its head. By 2014, it had rocketed to become the No. 6 apple variety in the United States, based on production.

> Honeycrisp saved [Courtier’s] orchards, but soon it was being grown in geography it wasn’t suited to, and, arguably, being overgrown. The university had released it as an “open variety” — meaning that after paying a small royalty to a variety’s developer, any grower can buy Honeycrisp trees and sell the fruit as they wish.

> If apple growers were to be financially healthy in the long term, Courtier felt that apple production and marketing would have to change.

There is also this description about one of the co-op members (which may explain why other commenters have different opinions about Red Delicious)…

> The Clarks watched the decline of the Red Delicious (Reds) variety from a front-row seat. Chelan was historically known for producing prime-quality Reds. Then the variety was “bred to grow red” in parts of the state that weren’t good “terroir” (or growing territory) for it. That fruit didn’t taste as good or store as well.

> The variety’s popularity with consumers fell far and fast…

> “As consumers ourselves, we know that if we consumers don’t get a good apple, we don’t come back for a while,” says Bill Clark. “NBT is managing who grows an apple, where it grows, what the eating experience is. That’s paramount to the variety’s sustainability

Edit: formatting


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