- Dishonesty expert is dishonest
- Politicians who constantly talk about freedom want to restrict anything that doesn't fit their world view
- Militant anti-gay preachers hire call boys
- Diversity teams are the least diverse
See also: every freedom fighter that launches a coup to overthrow a dictator, then becomes a dictator themselves within a decade. Or cops that get caught stealing child porn from the evidence locker, despite not being pedophiles by any definition.
Not all these types start this way, or are inherently hypocrites. Repeat exposure to something tends to rub off. You can't rail against the evils of prostitution as the basis of your career without being forced to spend cycles processing what about them is so awful. Thinking about round tits on display, the mechanics of sex, etc. The unthinkable is literally on your mind 24/7, which effectively normalizes the behavior and makes it less outrageous over time. It's a weird cycle of grooming yourself to accept what you purport to hate.
I'm an anti-fraud professional. I'm surrounded by so much of it (seemingly without consequence) that I'm frequently tempted to break bad myself. I never will, but it's a "conscious" decision (as an extremely stubborn Slav) and not because I'm a saint. Temptation just comes with the territory. It wears you down until you fail and make headlines in the most humiliating way.
CGP Grey made great recap in one of his videos [2] called Rules for Rulers.
[1]https://en.wikipedia.org/wiki/The_Dictator%27s_Handbook [2] https://youtube.com/watch?v=rStL7niR7gs&feature=share8
TL;DR: If you were a public person, watch your actions during bad times.
Has this happened? He thought it was normal porn?
IME DEI is usually a function rolled into HR (although they often contract with diversity training firms), rather than a separate team, except at large companies. Where there are separate DEI teams, they tend to be the most diverse, at least among the white-collar workforce - the requirements for these jobs tend to be quite nonspecific, because they don't really need to do much besides write stuff and give presentations related to diversity. These tasks can, at a pinch, be mostly handed off to interns and ChatGPT, or else involve cribbing from preexisting presentation templates. The actual engineering, PM, etc., teams tend to be less diverse - graduates of specific university programs tend to be less diverse, in the non-euphemistic sense, than university graduates as a whole.
That's not my observation at all.
Someone can likewise have every intention of being ethical, but just be bad at it. Conversely, someone could know ethics well and simply choose to disregard them and do unethical things anyways. An ethicist isn't necessarily someone who practices ethics particularly well, it's someone who understands the concepts of ethics well.
What studying ethics offers the individual is the tools to analyze their moral beliefs and ensure they are at least internally consistent. That "and why?" is probably the most valuable takeaway from studying ethics. Rather than saying "that act was wrong", a student of ethics can explain, down to axiomatic beliefs, why that wrong. If a disagreement between two people boils down to axiomatic beliefs, then you're never going change each others minds. But a difference in interpretation can be argued with the potential for persuasion.
It also gives you a lot of practice justifying your own actions. Useful, but perhaps not exactly altruistic.
Try the trolley problem. Is it okay to divert a trolley to kill 1 innocent person to save 10? What about 5? What about 1? And this is just an abstract thought problem. Now try war, nukes, abortion, death penalty, etc. Everyone has a simplistic and superficial idea of ethics. An ethics class helps you develop a deeper and broader understanding of ethics. To develop the what and why of ethics.
That being said, some work in practical ethics has had a huge impact. Peter Singer's work on animal ethics started the modern animal rights movement, and his essay "Famine, Affluence, and Morality" has inspired many people to donate a lot more to charity than they otherwise would.
Why do people use the term "ethical" as though there were a single agreed-upon "right" system of ethics?
My understanding is that there are numerous concepts of right and wrong, some of which are very divisive.
So i.e. there are people who would be widely detested for being "ethical" in unfashionable frameworks.
As you might expect, it's among "one of the most popular" courses offered at Harvard.
e.g. Innovation Managers have most likely never done an innovative thing in their life
I worked in this area (at Harvard as well) a bit as a grad student and can absolutely understand the temptation for the lighter version of this. If you can drop one outlier group, you get a cool story and a job at a top 10 b-school. Or keep it, get a muddled result, and try again for a better paper next year. I ended up just leaving the field entirely as the whole "our system massively rewards dodgy practices" vibe really bummed me out.
This creates a strong incentive to fudge the results and never ship anything. I knew of one scientist who figured out you could just fake the entire thing and skip the work part. He coasted for 5 years doing this.
It’s funny how greedy, for-profit companies are strict about honest accounting, while non-profit universities are fine with dodgy research.
I joined academia for the pursuit of truth, and forth the glory of Knowing. But it turned out that academia doesn’t really do this anymore, it just sells itself as doing these things.
Academia is entirely a “reputation” system, as it turns out, from paper publishing to student-evaluations to “public rankings.” As it turns out, the capitalist marketplace must also contend with these issues, but imho (and somewhat counterintuitively), it does so somewhat more honestly.
As someone in academia (very different field than Behavioral psych), I'm very cautious of people who say overgeneralised hyperbole such as:
> I joined academia for the pursuit of truth, and forth the glory of Knowing.
Because doing science is not clear concise straight forward exercise people envision.
(Science has major systemic issues but that's besides my point)
"academia doesn’t really do this anymore"
I've heard this from more than one current or former academic. Some argue it's due to market logic entering academia. It sounds like you take a different view?
However as a PhD student I decided that science academia wasn't for me - not because of out and out fraud - but because I could see success depended on marketing, networking and self-promotion - simply doing excellent quality work was required, but not sufficient.
Some of this is fair - part of an academics job is not just to discover new stuff, but to educate about it's discovery.
Anyway I decided I didn't have a loud enough trumpet and sharp enough elbows.
I'd agree that you find less politics in industry.
People only care about lines on the CV - and are willing to do anything to add another under the “peer reviewed” column. Including, lie, cheat, and steal (ideas).
What do you mean by 'anymore'. Was there some golden age of bygone glory?
Provided that there are valuable things to discover in the field of quirky marketing psychology.
But if all they want to do is provide a regular supply of ammo to both sides of internal corporate conflicts on marketing strategy, and promote the consulting brand of their profs, their current approach is optimal.
The first two of these blog posts are:
> students approached this “Year in School” question in a number of different ways. For example, a junior might have written “junior”, or “2016” or “class of 2016” or “3” (to signify that they are in their third year). All of these responses are reasonable.
> A less reasonable response is “Harvard” [...] Nevertheless, the data file indicates that 20 students did so. Moreover, and adding to the peculiarity, those students’ responses are all within 35 rows (450 through 484) of each other in the posted dataset
In addition, of these 20 very suspicious rows, most were strongly confirming the hypothesis of the authors.
Likewise the first link shows that, in a spreadsheet containing outcomes sorted by treatment group, someone had manually moved rows from the span of rows containing one kind of treatment to a span containing outcomes from a different treatment. These provably manually reordered rows also contained most of the strong evidence for the predicted effect...
Ladies and gentlemen, this is my friend, Doctor Kimble…
> It is worth reiterating that to the best of our knowledge, none of Gino’s co-authors carried out or assisted with the data collection for the studies in this series.
I'm confused; I thought 109 described a paper in which Ariely was the sole person to handle the data. How is this not contradictory?
An earlier Data Colada post -- https://datacolada.org/98 -- is about Study 3 in the same article. It seems that Ariely is the only co-author who might have handled the data for that study.
Certainly https://en.wikipedia.org/wiki/Judith_Miller and https://en.wikipedia.org/wiki/Robert_Novak have massive journalistic ethical errors: the former fabricating news for the US Government and the latter blowing a CIA agent's cover (the Plame Affair). Yet, they are celebrated journalists.
It seems that you have to:
- not be hypocritical (it is a greater sin to preach and sin; than simply to sin)
- be younger (established powerhouses can steamroll these accusations)
And to GP: thank you! The number of times Dan Ariely is involved in this data fabrication stuff does make the whole thing seem a bit fishy. At best, he is bad at trusting people, which makes any claims he makes low-coefficient since they could be from data from fabricators.
I was feeling guilty for besmirching Johann Hari's reputation in my own mind until looking at his wiki page and finding the HE TOO was involved in both plagiarism and fabrication scandals like Jonah Lehrer.
Weird. Explains the mental merger I guess.
I am curious to know more on this one. Odd to see so much pointing fingers happening. I'm guessing that isn't as rare as I would assume it is?
She is the best-selling author, most recently, of “Rebel Talent: Why it Pays to Break the Rules in Work and Life.”
Someone writing a book arguing for breaking the rules is exactly who I would expect to break the rules.
Or is the irony here that someone actually took an idea seriously and followed through on it?
I think the general thesis is questionable, for work especially, because in business contrary to the stereotype being honest and following the rules does pay off in the long run.
What has changed in the past 2000 years is the availability of information. Nothing is 100% true other than defined Universal constants. Everything else is on a spectrum. Those that want to get closer to 100% truth have many tools to get them along. Those that don't care can ask ChatGPT and get something 25% true. You can lead a horse to water, but you can't make them drink. That's just how people are, and AI isn't really changing that.
this gave us the illusion that we were in a world of Truth, because why would these centralized corporations ever lie to us, or massage the facts in any way? it's The News, of course it's inherently trustworthy.
then the Web came about, causing some to see cracks in the foundations. then the iPhone was released, social media took off, and now the news monoculture is almost (but not quite) dead, and we're back to fending for ourselves in this onslaught of information.
Nicely put, because it explains the widespread disappointment in journalism, media, academia that don't even seem to try anymore.
(Anyway, what do you mean by "truth"?[0])
[0] https://en.wikipedia.org/wiki/Tarski's_undefinability_theore...
I suspect most lies are just short term convinces.
On the contrary, I think we should expect them to be dishonest, and they are. They literally have a book named “Why It Pays to Break the Rules at Work and in Life”, what did you expect? Of course they're dishonest.
The story is just entertaining.
- "That's not how X works." <comment ends with no explanation>
- "Anyone back in ___ who was paying even the slightest attention could have seen that ___ was going to happen."
- "This subreddit / board / field has gone to sh_t"
> Also, who cares if they did lie
They didn't just lie, they tampered with collected data used for scientific research, harming their co-authors' work and reputation and giving fake leads to their field of study, thus wasting their peers' time spent on reproducing the case. It may also have had an effect on promotions that their peers should have gotten and on the way people got managed, based on these behavioral studies.
Also the evidence collection displayed in another reply is technically interesting.
"Harvard dishonesty expert dishonestly accused of dishonesty"
We saw a widely publicized and long career of false data in biology over the past couple of years following roughly the same structure (just sticking garbage data into excel spreadsheets). Methodological errors and publication bias are also widespread in CS. When I was in grad school, the method I was told to use to choose tools was to choose the second best tool in a paper, since the authors' tool was invariably the best but their evaluations were inherently less likely to transition into my work.
Drawing a further conclusion that whole entire fields of research are simply untrustworthy based on media coverage of bad actors, especially as a nonexpert, is throwing the baby out with the bathwater.
The field that is actually tackling the reproducibility crisis even in a small way is Psychology. This is one reason why there are so many "X doesn't actually replicate" headlines. Yes, replication studies should be even more common. But it is hard to conclude that the social sciences are uniquely horrible when Psychology is actually ahead of the curve here.
physics has a good reputation, but then you hear of things like apparent fraud in that quantum computing paper about Majorana fermions...
computer science actually seems relatively okay as far as avoiding outright fraud, probably because there's such a strong norm of sharing code. plenty of questionable research practices though.
Public health is in even worse shape. During COVID I was forced to conclude nobody in power was actually reading the papers that were driving policy. They'd regularly have major errors in them, like model code that was full of bugs or where things were stated about the real world as if they were clearly 100% true but the underlying paper stated the models had unrealistic assumptions! (same people making both statements). Universities didn't care about any of this.
I never saw outright fraud in CS but I've seen things that were getting close to the line in cryptography research. Some years ago there were a spate of research papers on Intel SGX that kept claiming they'd broken the security. When examined closely they all used an identical version of GNUtls in the enclaves for their proofs of concept. I got curious about why this specific version of this not very popular cryptography library kept cropping up as the reason for using it never seemed to be mentioned in the papers. Turns out that it's an ancient version, the last version before side channel mitigations were added. The techniques they were claiming broke SGX only worked if you ignored basic cryptographic best practices and used obsolete libraries. And last year there was a non-SGX case where the researchers claimed to be able to extract private keys over the network via side channel attack. The demonstration required the use of a very specific algorithm nobody actually uses, and required the target server to not be doing anything else, and for it to be saturated with traffic that did nothing except invoke this specific obscure algorithm and even then it took days. So this wasn't a realistic scenario anyone needed to worry about but it was presented as if it was.
This guy's speciality is Applied Dishonesty, so he's not the abstract sort with just theory and no practise. ;)
Does this implicate Ariely or did I read that wrong?
I agree that one of the problems is that we've sometimes been given reason not to expect an institution to have integrity.
One of the other problems is that public discourse is often lacking in integrity, as well.
In Comments ... Don't be snarky. ... Please don't sneer ... Avoid generic tangents. Omit internet tropes.... Please don't post shallow dismissals, especially of other people's work.... Please don't complain about tangential annoyances—e.g. article or website formats, name collisions, or back-button breakage. They're too common to be interesting.
<https://news.ycombinator.com/newsguidelines.html>
And finally, that would be her expertise.
I was mostly making fun of the language we humans tend to use sometimes: a car expert would be applying their expertise on cars, a botany expert would do it in botany, but it's not an "honesty expert" but a "dishonesty expert"?
I do believe that's an interesting point to make, even if — obviously — at least someone has misread the joke as something else.
I told the person I was working with about the data and suggested it was fraudulent and she became concerned and raised it with her supervisor. Within about 24 hours I no longer had access to the data sets. And the friend of a friend just said that she didn't need help anymore.
I suppose I could have raised a fuss and contacted a journalist but all I had was columns of data without context. Plus at the time I'm ashamed to say I was playing a lot of World of Warcraft and not inclined to do much else that required effort.
Policy always represents somebody's interests. "Data driven" is an excellent cover when you control the data. You get to eat the cake and look good while doing it.
https://statmodeling.stat.columbia.edu/2023/06/21/ted-talkin...
https://statmodeling.stat.columbia.edu/2023/06/23/its-worse-...
/s
"We understand that Harvard had access to much more information than we did, including, where applicable, the original data collected using Qualtrics survey software. If the fraud was carried out by collecting real data on Qualtrics and then altering the downloaded data files, as is likely to be the case for three of these papers, then the original Qualtrics files would provide airtight evidence of fraud. (Conversely, if our concerns were misguided, then those files would provide airtight evidence that they were misguided.)"
It does not appear that Harvard found any evidence that they were misguided...
Great example that highlights the balance of presumption of innocence with the asymmetrical bullshit principal. This person should be referred to criminal prosecution for fraud as a deterrent to others. 1,200 page reports to provide proof beyond a reasonable doubt is not scalable.
To anyone who has worked in research, the various strategies it shows would be tragically familiar.
Seems possible.
(and if you didn't catch that reference, have a look at Prof. Gino's photo.)
