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This is how I think it roughly works where I live: You get a per-user token directly at the bank or via mail (not email, but a physical envelope). Your banking app can use this token once to get a secret key. Secret key + user name + password allows you to use the banking app.

Any way to circumvent this requires app isolation to be broken somehow.

PAXLY (https://www.paxly.eu) | Vienna, Austria | Full-Time | ONSITE+PART REMOTE | €50k-100k salary

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We're a small (10-person) team disrupting the packaging industry. Large companies like Media Markt use our software to manage their purchasing materials and all processes surrounding it.

Currently we are looking for a fullstack developer with a focus on frontend.

Our tech stack includes Dropwizard (Java + Hibernate + Guice) in the backend and Angular (+ Angular Material + TailwindCSS) in the frontend.

If you are interested, you can see a detailed job offering and apply under the following link: https://www.paxly.eu/jobs/fullstack-developer-java-typescrip...

I heard of state tenders where they basically have some minimum requirements that have to be met and otherwise choose the cheapest option. For a large amount of vehicles it is probably cheapest to design one that meets all the minimum requirements exactly.

They actively discourage its use: "Die Deutsche Gesellschaft für Gastroenterologie, Verdauungs- und Stoffwechselkrankheiten (DGVS) rät davon ab, Stuhltests zur Untersuchung des Mikrobioms zu nutzen."

In my opinion there being no evidence in either direction does not mean that you should not try it, especially if there is no downside and you have a chronic condition.

I assumed lack of evidence + non mainstream opinion = alternative medicine. Maybe there is a better word for cases like this where there is some evidence but no clear indication of causality.

In german speaking countries gut microbiome analysis is considered alternative medicine by many medical professionals and is actively discouraged by some interest groups. [1]

There always is a gap between medical research and application which people have different opinions on. For example when it was found out that high cholesterol was bad for you, doctors recommend patients with high cholesterol to eat less cholesterol. Later it turned out that there was little correlation between eating cholesterol and having high cholesterol. The correct opinion supported by scientific evidence was considered alternative medicine for decades.

[1] https://www.dccv.de/aktuelles/nachricht/teuer-und-sinnlos-dg...

I was wondering the same thing! I always assumed that payment processing was one of the most "winner-takes-it-all" business models out there.

People dislike PHP because its standard library had many inconsistencies and interesting design decision that no sane programmer would ever even think off, like all random numbers being odd (https://stackoverflow.com/questions/31612082/why-does-mt-ran...).

Many of these decisions revolve around the authors not wanting their functions to fail under any circumstances. This is nice for beginners but quickly hurts more than it helps in larger projects as it obfuscates bugs.

"The best and brightest built a state of the art forecasting model and it says I should do X" sells much better than "I assume this year will be exactly like last year and last year we should have done X".

Basing your decisions on complicated scientific methods inspires confidence in many people, even when there is no benefit.

It also mitigates responsibility for decision makers, because they can claim that they would have made the perfect decision if only the model's predictions would have been perfect as well.

The main problem that I and many others have is not the policy of the month but how targets are shifting. When the measels vaccine was introduced it was clear that after one or two shots you were safe for many years if not for life. Seatbelts are not an irreversible medical procedure.

So my problem and the problem of many others is not focused on the policies in effect right now, but the direction in which the policies evolve.

If I had thought one or two years ago how the CCP was going to handle the pandemic, it would be pretty much the way the US, Germany and France handle it right now.

Many of these people are heavily traumatized. Charles Manson for example was mistreated by his mother and in prison. If there were better child protective services and a more humane prison system in place, he might never have done what he did.

Most people doing evil things are in part doing these evil things as a result of their circumstances. By changing their circumstances through social programs you reduce violence and make everyone happier as a result.

You can argue that blaming violence on circumstances ignores people's own responsibility, but I believe that better social and medical programs are still worth it because they attack the part of the root cause society can influence most easily.

While violence is sometimes justified, I think it's still better to build a society that tries to solve its problems without violence or prevents problems that can only be solved with violence.

When you have reckless people attacking the elderly you need better psychological healthcare and a better social system to prevent that.

I understand your point and in a narrow context it's definitely true, but in a larger context you can prevent most violence by changing society.

Science can be used to analyze subjective experiences, but analyzing something and being the one and only all-knowing oracle is a big difference. Science is always constrained to an ideal world, but reality is messy. There is no one correct way to pull out a piece of egg shell that got into the pan by mistake while cooking.

Also I believe predicting things like favorite meals is possible to a high degree of certainty, but there is always a gap between the nice theoretical world and the real world. Maybe it's your favorite meal because your grandmother always cooked it for you. How do you define a meal? How much egg can you add or remove before it becomes a different meal?

If my arguments seem too hand wavy, consider the incompleteness theorem. There are truths in mathematics that cannot be shown to be true. Why should messy real life give you stronger guarantees than the clean world of mathematics? Why should there always be one correct way of doing things that we can deduce?

Or let's say I bet that a certain Turing machine doesn't halt. What does science say about this? Is this rational? Should I have bet that it does halt?

Science is one of the best tools available, but it will not solve all of humanity's problems.

> > science alone can never legitimate itself

> Nether anything else, religion is based on faith and dogma. It can never be legitimised by facts as it will not be based on faith anymore.

> So what's the point of your statement then?

That the author of the article uses this argument to show that science alone is not enough. In comparison, like you mentioned, religion can legitimize itself through dogma. Science needs another system that promotes values and goals that can be achieved through science.

> > scientific process itself involves subjective decisions

> Yes, you can use imagination, try/fail approaches but those are then put to the test. And if my magical stone that keeps away tigers was found not to work, then its just a stone. Thats where the non-tangible and mistic claims come to die, or live (ie placebo effect, we don't understand it yet, but we know it exists).

I completely agree with you on this. Given enough time you get more and more knowledge. The interesting cases in my opinion are where there is conflicting evidence from different studies or sources and maybe not enough time to do further studies.

For example you have stomach cancer due to a genetic defect. Your doctor recommends you a medication which works for stomach cancer, but it has strong side effects. In all available studies there was no distinction made between patients with that defect and without. You reduce your survival chances if you take the medication and it doesn't work, but you also reduce your chances when you don't take it and it does work. So whats the rational thing to do?

> In my opinion the author desperately flails their arms in an attempt to obscure the murky argument. And it feels like convoluted god of gaps argument without mentioning god.

The author does not present a very coherent argument, but I still think he makes some good points.

Science works very well for things like not getting sick, understanding physical phenomena or getting to the moon. But for some goals like being happy, finding meaning in life or cooking a tasty meal science is only of limited use.

Also I don't think the author necessarily proposes to replace science, but rather being aware of the limits of science. There is no one scientific or rational way of coming up with scientific hypotheses or determining how to apply scientific discoveries best to the real world. There is always a gap between the ideal world of science and reality.

The article is written in a convoluted way, but the main points it makes are valid in my opinion. The first being that science alone can never legitimate itself as being the only true way of doing something. This legitimization must come from somewhere else like philosophy and can never be part of science itself.

The second point is that there is will always be a gap between science, reality, human understanding and application of science. Even the scientific process itself involves subjective decisions not derivable from science, e.g. what hypotheses to test.

I think the author wants to convey that doing everything "the rational way" is not objectively superior than doing everything according to some other set of principles.

There is a middle ground that exists only when you combine science with common sense.

Let's say a chemical X is used in baby food production. There are no studies that show that it is harmful, because no studies have been done yet. Many chemicals with similar structure have been shown to be harmful.

Scientifically speaking you would be correct to say that there is no evidence that chemical X is harmful. There is no way yet to accurately model the interaction of any chemical with your body without any actual experimentation. You can make an argument that chemical X might be harmful because similar chemicals are harmful, but that would not be science.

I would not buy that baby food with chemical X if given a choice. Best case I don't lose.

Finding conclusive evidence in science often takes lots of time to gather enough data because there are so many different variables to consider. So absence of evidence means a lot more when you have been looking for a long time and invested lots of resources.

I think scientism relates to beliefs that equate the current state of scientific knowledge with absolute truth and ignoring unknown unknowns and limits of scientific methods like statistics.

A common fallacy is that "absence of evidence is evidence of absence". For a government this might mean "There is no definite scientific evidence that substance X causes cancer, so we do not ban it.".

I missed a _not_ in that sentence. I and most other people on HN obviously want to know everything.

There are 4 things he could have done: 1. Don't reveal any secrets. 2A Reveal secrets that harm candidate A. 2B Reveal secrets that harm candidate B. 3. Reveal all secrets that harm candidate A and candidate B.

I don't think anybody on HN argues that option 3 is preferable over all the other options. You seem to think option 1 is preferable to both options 2A and 2B. GP and I seem to think the opposite.

I can understand your argument that half the truth can be worse than no truth at all. But as there are very few sources for information like WikiLeaks I think in cases like this, half the truth might be all the public can get and it at least gives you a basic idea of what is happening when nobody is looking.

4 years ago at work we compared Kafka to alternatives and ended up using it. In my opinion the only reason for using Kafka is that you need a very very highly performant message queue. It had bad usability at the time and some very annoying undocumented behaviour (e.g. there was no official guide or feature to permanently remove a node).

It feels like whenever Kafka developers had to make any tradeoffs they chose performance over everything else. I would only ever use it again if I the sheer data volume makes it impossible to use an alternative.

Yes, but those are different people that might be killed, which makes it an ethical dilemma.

Depending on the type of adverse reaction, it might be safer for young people to not get vaccinated at all or with a different vaccine. (For example if the adverse reaction affects mostly young people, while COVID affects mostly older people.)

The ethical issue is that the people dying from COVID and the people who might have an adverse reaction from the vaccination are not the same people.

If mostly old people die from COVID but the adverse reaction of the vaccine is independent of age, then for very young people the risk of an adverse reaction of the vaccination might outweigh the risk of permanent damage from COVID.

I think software quality in research has nothing to do with the problems themselves. It's more like article suggests that nobody cares about your software. The only goal is to get published and be cited as many times as possible. Your coding mistakes don't matter if they cannot be found out or hurt your reputability.

How many tests would be written for business software if it had only to run for one meeting and then never be looked at again?

It just shows that I, you and the average person is much closer to them than we think.

If you put enough money on the table I'm sure many more people would do the same thing as those currently in power. It's just that most people don't have the opportunity to sell out.

That's the scary truth I think.

Great article! I also found that the aim to be objective in everything and use metrics as truth and not just another input is pretty harmful over the long run in business and science. Things that are hard to measure are ignored most of the time.

The best example are apples. When you breed apples to be 3% larger each year but taste slightly worse, you can weigh them and see that they got slightly larger. As you cannot accurately measure taste you will notice that they basically taste the same. After years of breeding you have giant apples with bad taste.

The author's proposition of using as many metrics as possible and talking to real people is a good solution to make better decisions.

I would add that for some decisions you should actually just focus on the few facts that truly matter. The classic example being a potential business partner with a bad reputation. If somebody is not trustworthy everything else probably doesn't matter.

I found the book "The Power of Now" by Eckhart Tolle helpful in controlling or getting rid of harmful inner dialog.

In my part of the world offices were the last places to shut down due to COVID and are still partially open. Losing social interactions at your workplace happened after heavy restrictions were placed on meeting friends, family and going anywhere except supermarkets.

Maybe you are just lucky that the office is the only place where you lost regular social interactions.

I think the issue is not that the changes don't matter but that they end up being a substitute for addressing the real problem of structural racism.

A CS analogy: Using a linter is good, but it doesn't fix bugs in your code. Pretending it does keeps you from fixing them.

Asking how long a feature will take is like asking how much it will cost to renovate an old house. Nobody can know for sure but you as an expert can give a better estimate than most other people. Nobody just asks a structural engineer to just build a house and that costs don't matter.

Why is that "wrong" estimate so important? Because business people do not see the real cost associated with features. They can only guess how many buttons you need to add to the UI. In order to build good products they need to weigh feature benefits against engineering costs. Even if the cost is wrong, it's about the magnitude compared to other options.

If business people get annoyed by missed estimates they don't understand engineering estimates and how to use them properly.

I do that partially by focusing explicitly on a single objective like performance or test coverage.

In reality you need to compromise, but by keeping the scope of learning projects artificially small you learn a lot about that one aspect and the trade offs involved.

For example when I wanted to learn more about testing for front end applications in Angular, I wrote all types of different tests for a small sample project. By doing that and reflecting on how I could incorporate all those tests at work, I learned a lot about structuring my code to be more testable, when and how to use mocks, Angulars built-in testing utilities and much more.

By going very narrow it's easier to go deep. You won't learn about all the side effects and interactions with decisions in other areas, but at least you know more options and can try to find a better optimum.