goopthink's comments

I worked in three different healthcare technology companies (for doctors, pharma, and insurance).

1. In not a single case was compliance with HIPAA rules ever a cost center beyond the initial project to implement controls, and that itself wasn’t a huge project. For most organizations, compliance with the guidelines is simply good data security. It’s like calling any internet security expensive and unnecessary.

2. Doctors can share data. They have tools to share it in their EMRs, and there are no restrictions to sharing it with other healthcare providers during the course of care.

3. The security and privacy rules are almost entirely about the preventive of public, accidental, or unauthorized disclosure, and also about giving patients access whatever data you hold on them.

4. Why would newspapers want to publish random people’s healthcare information? Unless it was part of a piece targeting a famous/influential person or medical practice, in which case yes, if they access and publish individuals’ healthcare information without consent, that’s a breach of privacy that can be challenged in court. The law isn’t about the damages per se, it’s about the breach of privacy and confidentially.

This includes primarily heavily excerpted copies of the papers. While some editorial choices may make a lot of sense, you don’t know what you don’t know between the ellipses.

Yes, and you should read “The Mom Test”. Key takeaway, focus your questions on the problems customers are trying to solve and details therein, rather than talking about your solution or trying to be on pitch mode.

I completely agree - this is nearly verbatim a personal frustration I recorded in my work log from a few days ago:

Extremely frustrated with Google Shopping ads. I can’t understand how they make money. Spent an hour trying to figure out how to:

- Add custom UTM parameters (can’t unless with a manual feed, it looks like) because Google doesn’t doesn’t seem to track shopping ads unless you install extra JS events and modify google analytics

- Change search queries that products come up for (after deeper research, look like you can’t - again, handled by the data feed but your product title must be now SEO’d to all heck to hit the right keywords. Good luck if you have an original product name)

- Fix the product disapprovals (their bot was too dumb to understand how to navigate native shopify variants, it keeps seeing a mismatch between a variant and its price… and this is the data feed that Googles own app in Shopify generates!)

- Understand why the shopping ads dashboard in Google and the in-Shopify google shopping ads dashboard show different product disapprovals... just why? Genuinely confused here.

It’s ridiculous. It wasn’t this hard a few years ago. In the quest to add more ‘automation’ and ‘smartness’ they’ve made it so dumb and so bad it drives me up the wall.

It reminds me of the time when a friend tried to do Google’s recommendations for “smart” ads and it optimized his local North Carolina health store ads to ads for dieticians targetting neighboring states, because of a few logical algorithmic leaps of “well this is what other users see success with, with ads like yours.” He wasted a few hundred dollars and time fielding confused calls, until we reverted the campaign, turned all the recommendations off and made it a simple, dumb but effective campaign.

What a joke. A horribly infuriating joke played by a group of product managers and engineers. They are literally leaving so much money on the table because the platform is so unusable (speaking for experience: I regularly have people turn to me asking for help setting up their ads because they can’t make heads or tails of it).

Google’s Ad Products have - over the last few years, in the pursuit of “smartness” —gotten progressively dumber and harder to use, making all sorts of bad and often unchangable decisions on your behalf, and having really awful interfaces for trying to make any sorts of edits and apply them anywhere. And I say this as a technical marketer. Facebook’s ads products are a godsend compared to the awful nonsense that is Google Ads.

SimpleNote from Automattic is simple, markdown based, local and cloud synced. It doesn’t get too many updates because it’s pretty feature complete for what it does.

I recently wrote about my learning strategy under a post called “How Learning Works: Components, Loops, Systems”: https://romandesign.co/how-learning-works-components-systems...

> It's like Charlie Munger once said about mental models: “All this stuff is really quite obvious and yet most people don’t really know it in a way where they can use it.”

The long and short of it is that you go through a cycle of Knowing, Doing, Assessing. Each of those has sub sucked and pieces but they fit together really well and work generally across different types of things you’re trying to learn (intellectual, skill,ms, physical).

Correct - Either Sony/Universal launching their own service off the backs of making their catalogs exclusive, or Spotify cutting deals with existing artists to make their catalogs exclusive and then growing into being a music publisher themselves.

Here’s a good visual of that in action: https://twitter.com/ShaulTurner/status/1476722513195405315?s... #

But really, any #MarshallFire twitter post right now.

I live in the neighborhood, but we are just outside of the evacuation zone. This part of Colorado is — in other times — a really nice mixed-use set of communities. It has a lot of open fields, farms, businesses, and “old town” town centers right alongside very dense apartment buildings and single family homes. We haven’t had snow or rain in almost two months, and everything is very dry. I saw the wind bringing flames along these open fields (like kindling) right into Louisville and Superior, and then it lights up the neighborhood, spreading house to house, fueled by wind that has brought down trees and power lines (friends in Boulder getting some rolling blackouts earlier). These nice parks and open fields are like turbo boosts from neighborhood to neighborhood. Any other combination - not as dry, not as windy, and it would have been a small localized fire. Everyone is packing their cars even if outside of the mandatory or pre-evacuation zones. We are supposed to have a massive snowstorm tomorrow morning as well, which makes this very painful - large fires normally burn in loosely populated areas, but this is as dense as any major suburban center.

For the record here, in addition to the fines, there is an additional unreported price of legal costs to fight this and compliance costs to fulfill obligations as per settlement. It's not quite an iceberg costs, but I guarantee they hired expensive lawyers to fight this beyond usual retainers.

I think that's absolutely and cynically correct. For example: there is a concept of parking tickets with fines. The fines are set to discourage certain behaviors while also not being cruel and unusual. Some people will never park "illegally" while others consider parking tickets to be the unfortunate risk or consequence of how they live their lives and do their jobs. The same is true for all penalties, period.

This cynical calculus should be separated from how we feel about the organizations that commit things that result in fines. It's really easy to hate on banks and believe that every fine is justified and should actually be way bigger. Pitchforks and burning down the barn, ya know? But someone somewhere decided that calculus of appropriateness based on a variety of factors, and it is the lowercase-p political process to push for changes based on outcomes we see. But the pendulum swings both ways. China is an example of a country where if a company goes against government rules it can be dissolved, its leaders arrested and thrown in prison, based on criteria they have calibrated politically. Or in some other countries, you may be beheaded for social infractions. Not trying to reduce this to absurd (but real) logical extremes, but highlighting that this is precisely the difficult balance folks try to find, and our sense of proportionality is often affected by the current popular conception of them as an industry or as an individual company/person. I.e., just as many people hate on banks and think they should be punished higher, they turn around express complete disbelief at "unfair" fines and laws that are broken by innovators that run faster than regulations allow (read: tesla, uber, airbnb, etc). Sometimes we collectively feel fines are justified, sometimes not, sometimes too high, sometimes too low. Your calibration may vary.

One of the recurring themes in comment sections around fines for banks and large businesses is that "the fine is not in proportion to the size of the business".

I guess it makes sense to ask then, do we want to have fines that are proportional to the revenue/profit/"X"-value of a business (and how might that get gamed)? Where if a small business is sued for something like this, it will only pay $100 while a larger business for the same infraction will pay $100,000,000? And if we're ok with that, are we ok then also acknowledging that we completely disincentive any sort of legal enforcement of small businesses, from a cost/benefit perspective?

I actually think the inverse is true: if the SEC has decided that the correct penalty for recordkeeping failures is $125M, it is likely a balance of proportionality to the crime, cost of enforcement, and proportion to victimhood of the crime. The question I always wonder around this is, how much of this $125M goes back towards victims (if any) and how much goes towards further agency enablement to pursue criminal activity? Is $125M enough for the SEC to open X more cases (knowing how overcapacity they and every other government agency are)?

In addition to the points raised by BMJ and in the comments below, there is a limit to what independent fact checking can accomplish. For example, are their fact checkers conducting their own scientific experiments validating claims and outcomes of a scientific paper? Are fact checkers reaching out to sources from a news article and verifying quoted information? When “breaking news” or “scoops” are reported presenting totally new information about the world, how can that be verified against other information that - by virtue of something being new - cannot be verified by other preexisting sources?

If the fact checking process is limited to verification based on other information that is currently available, and if the fact checking process cannot distinguish between factual information and the opinions people hold as a result of that information, the outcome will be an inevitable echo chamber that reinforces currently dominant views or whatever preexisting biases are present.

In short, fact checking is hard and there is a reason why reputable publishing outlets have their own internal fact verification processes before something gets published (including safeguards and retractions, because they make mistakes too), and why news is separated out from opinion-editorial pages... even if it is in style to add opinions (read: “perspective”) to every article.

YMMV, but a significant amount of real-world and statistically significant contributions can be made to average human longevity by focusing on paths of least resistance, such as tackling gun and car related deaths, then on the individual+average longevity by looking at preventable-but-chronic conditions (such as diabetes) by regulating things like common pollutants, added sugars to foods, and having better access to the outdoors and exercise/activity. Then you can enjoy a long life that will - on average - be healthy and long enough and with decreased risk of dying early. Past that, a lot of the research feels like “solutionism”.

The thing is, in many cases you don't need to know if the diagnosis is correct, so long as the results are directionally correct. If the outcome is an improvement in health, that meets your threshold for value delivered, hence payment rendered. I think there are many cases when you don't need to be smarter than the other person to benefit from their expertise. You can take it a step further and make the distinction between absolute value versus perceived/relative value -- if we have a patient with cancer, absolute value might mean destroying all cancer cells (which is an absolute metric but extremely hard to model). But perceived value might be "feeling better". It's important to make this distinction particularly in healthcare because absolute benefits and relative benefits are extremely important. Hospice/end-of-life care is a good example of this (as is the cancer example above). Most people would prefer relative or perceived comfort as opposed to absolute results that only end up prolonging a painful process.

Outside of healthcare, for another example example, you don't need to understand engineering and tension dynamics in order to appreciate that the second floor of your home support you and your roof doesn't cave in on itself. I don't have examples on hand, but in medicine we've had cases where people do some logical variation of "the right thing for the wrong reasons." I.e., rituals that correlate with healthy outcomes because there is some not-yet-understood principle at play (i.e, you don't need to understand germ theory to benefit from cleanliness rituals).

I think this is one of those logical conundrums which falls into the trap of "in theory, in practice". The artificial constraints around the problem space result in artificial logical conundrums.

The article proposes prepayment options. Why not go to the "other, other obvious" solution, which is results-based payments? In healthcare, that's value-based care. In other industries w/ agent-principle problems, it's called "taking on risk". You're incentivizing results and outcomes, rather than whatever specific actions lead up to those results. It means that the focus is no longer on the activity provided by the agent, but on the desired outcomes from the principle. Pure alignment and it helps filter out those who are good at getting results from those who are good at doing the actions.

From experience in DTC retail, this is more of an AR (not VR) benefit. I think (because I can’t remember the exact examples) that Amazon, IKEA, and a few others already do a “See it in your room!” feature. With smartphones with LiDAR/equivalent scanning this becomes really easy. Other retailers like H&M already use digital human models and clothes so it’s a short leap there as well.

Author here! I didn’t even think about it from an organizational learning perspective - this was written with individual learning in mind. I run a product team and this is a challenge we have as well - I think that requires a balance between building processes, ownership, and visibility efforts that keep organizational learning growing. All together that creates a culture - it’s not the processes themselves, but shared enforcement and encouragement that keeps organizational learning going. Ben Horowitz’a book “What you do is who you are” is good on that as well. Worth a deeper dive :)

This is not a criticism of the work done, but I think the top 20-40 mentions are extremely obvious and a regular reader might be able to guess a good portion of these recommendations. What is really interesting - and started at with the “categories” — is tying the recommendations to explicit context. I didn’t dive too deep into the recommendations, but are the categories by book category, or by originating topic of conversation? It’s a narrow distinction, but a useful one. I’d love to see deep learning pull up a hierarchy of conversational topics on hacker news and match recommendations to those trees.