Censorship is always abused. Maybe this time or maybe not. But it's always abused.
And yes, it's worse than misinformation.
And yes, it's worse than misinformation.
But I suppose it will depend on the circumstances, and I'd honestly be interested to hear your thoughts on why censorship is worse.
As for the inevitability of abuse? When it comes to corporate interests, that seems to be nearly axiomatic. The Verge's list of fascinating & horrifying exchange at Apple about app approvals & secret deals makes for a great case-study in this. [0]
[0] https://www.theverge.com/22611236/epic-v-apple-emails-projec...
A statement of "I don't know' clearly indicates a lack of knowledge.
A statemnt of "I have no opinion" clearly indicates that the speaker has not formed an opinion.
In each case, a spurious generated response:
1. Is generally accepted as prima facie evidence of what it purports.
2. Must be specifically analysed and assessed.
3. Is itself subject to repetition and/or amplification. With empirical evidence suggesting that falsehoods outcompete truths, particularly on large networks operating at flows which overload rational assessment.
4. Competes for attention with other information, including the no-signal case specifically, which does very poorly against false claims as it is literally nothing competing against an often very loud something.
Yes: bad data is much, much, much, much worse than no data.
Outlier exclusion is standard practice.
It's useful to note what is excluded. But you exclude bad data from the analysis.
Remember that what you're interested in is not the data but the ground truth that the data represent. This means that the full transmission chain must be reliable and its integrity assured: phenomenon, generated signal, transmission channel, receiver, sensor, interpretation, and recording.
Noise may enter at any point. And that noise has ... exceedingly little value.
Deliberately inserted noise is one of the most effective ways to thwart an accurate assessment of ground truths.
1) You can have an empty dataset.
2) You can have an incomplete dataset.
3) you can have a dataset where the data is wrong
All of these situations, in some sense, are "bad"
What I'm saying is that, going into a situation, my preference would be #2 > #1 > #3.
Because I always assume a dataset could be incomplete, that it didn't capture everything. I can plan for it, look for evidence that something is missing, try to find it. If I suspect something is missing but can't find it then I at least know that much, and maybe even the magnitude of uncertainty that adds to the situation. Either way, I can work around it understanding the limits if what I'm doing or if there's too much missing, make a judgement call and say that nothing useful can be done with it.
If I have what appears to be a dataset that I can work with, but the data is all incorrect, I may never even know it until things start to break or, before that if I'm lucky, I waste large amounts of time to find out that the results just don't make sense.
It's probably important to note that #2 and #3 are also not mutually exclusive. Getting out of the dry world of data analysis, if your job is propaganda & if you're good at your job, #2 and #3 combined is where you're at.
It's a scientist who removes outliers in the direction that refute his ideas, but not ones in the direction that support it.
These aren't entirely dissimilar, but they have both similarities and differences.
Data in research is used to confirm or deny models, that is, understandings of the world.
Data in operations is used to determine and shape actions (including possibly inaction), interacting with an environment.
Information in media ... shares some of this, but is more complex in that it both creates (or disproves) models, and has a very extensive behavioural component involving both individual and group psychology and sociology.
Media platform moderation plays several roles. In part, it's performed in the context that the platforms are performing their own selection and amplification, and that there's now experimental evidence that even in the absence of any induced bias, disinformation tends to spread especially in large and active social networks.
(See "Information Overload Helps Fake News Spread, and Social Media Knows It". (https://www.scientificamerican.com/article/information-overl...), discussed here https://news.ycombinator.com/item?id=28495912 and https://news.ycombinator.com/item?id=25153716)
The situation is made worse when there's both intrinsic tooling of the system to boost sensationalism (a/k/a "high engagement" content), and deliberate introduction of false or provocative information.
TL;DR: moderation has to compensate and overcome inherent biases for misinformation, and take into consideration both causal and resultant behaviours and effects. At the same time, moderation itself is subject to many of the same biases that the information network as a whole is (false and inflammatory reports tend to draw more reports and quicker actions), as well as spurious error rates (as I've described at length above).
All of which is to say that I don't find your own allegation of an intentional bias, offered without evidence or argument, credible.
Well, it's rare that I know of. The nature of things is that I might never know. But most people that don't work with data as a profession also don't know how to create convincingly fake data, or even cherry pick without leaving the holes obvious. Saying "Yeah, so I actually need all of the data" isn't too uncommon. Most of the time it's not even deliberate, people just don't understand that their definition of "relevant data" isn't applicable. Especially when I'm using it to diagnose a problem with their organization/department/etc.
Propaganda... Well, as you said there's some overlap in the principles. Though I still stand by more preference of #2 > #1 > #3. And #3 > 2&3 together.
I've worked with scientific, engineering, survey, business, medical, financial, government, internet ("web traffic" and equivalents), and behavioural data (e.g., measured experiences / behavour, not self-reported). Each has ... its interesting quirks.
Self-reported survey data is notoriously bad, and there's a huge set of tricks and assumptions that are used to scrub that. Those insisting on "uncensored" data would likely scream.
(TL;DR: multiple views on the same underlying phenomenon help a lot --- not necessarily from the same source. Some will lie, but they'll tend to lie differently and in somewhat predictable ways.)
Engineering and science data tend to suffer from pre-measurement assumptions (e.g., what you instrumented for vs. what you got. "Not great. Not terrible" from the series Chernobyl is a brilliant example of this (the instruments simply couldn't read the actual amount of radiation).
In online data, distinguishing "authentic" from all other traffic (users vs. bots) is the challenge. And that involves numerous dark arts.
Financial data tends to have strong incentives to provide something, but also a strong incentive to game the system.
I've seen field data where the interests of the field reporters outweighed the subsequent interest of analysts, resulting in wonderfully-specified databases with very little useful data.
Experiential data are great, but you're limited, again, to what you can quantify and measure (as well has having major privacy and surveillance concerns, often other ethical considerations).
Government data are often quite excellent, at least within competent organisations. For some flavour of just how widely standards can vary, though, look at reports of Covid cases, hospitalisations, recoveries, and deaths from different jurisdictions. Some measures (especially excess deaths) are far more robust, though they also lag considerably from direct experience. (Cost, lag, number of datapoints, sampling concerns, etc., all become considerations.)
It's complicated.
>Self-reported survey data is notoriously bad
This is my least favorite type of data to work with. It can be incorrect either deliberately or through poor survey design. When I have to work with surveys I insist that they tell me what they want to know, and I design it. Sometimes people come to me when they already have survey results, and sometimes I have to tell them there's nothing reliable that I can do with to. When I'm involved from the beginning, I have final veto. Even then I don't like it. Even a well designed survey with proper phrasing, unbiased likert scales, etc can have issues. Many things don't collapse nicely to a one-dimensional scale. Then there is the selection bias inherent when by definition you only receive responses from people willing to fill out the survey. There are ways to deal with that, but they're far from perfect.
A: "I've conducted a survey and need a statistician to analyse it for me."
(I've seen this many, many, many times. I've never seen it not be the sign of a completely flawed aproach.)
I show some aggregated moderation history on reveddit.com e.g. r/worldnews [2]. Since moderators can remove things without users knowing [3], there is little oversight and bias naturally grows. I think there is less bias when users can more easily review the moderation. And, there is research that suggests if moderators provide removal explanations, it reduces the likelihood of that user having a post removed in the future [4]. Such research may have encouraged reddit to display post removal details [5] with some exceptions [6]. As far as I know, such research has not yet been published on comment removals.
[1] https://www.reddit.com/r/pushshift/
[2] https://www.reveddit.com/v/worldnews/history/
[3] https://www.reveddit.com/about/faq/#need
[4] https://www.reddit.com/r/science/comments/duwdco/should_mode...
[5] https://www.reddit.com/r/changelog/comments/e66fql/post_remo...
[6] https://www.reveddit.com/about/faq/#reddit-does-not-say-post...
As the saying goes, it's not what you don't know that gets you into trouble. It's what you know for sure that just ain't so.
You may be ignorant, but you know it, and can deal with it. Let's call is starting from 0.
When you have bad data, you frequently don't know that you have bad data until things go very very wrong. You aren't starting from 0. 0 would be an improvement.
In the known-knowns model, you have knowledge and metaknowledge (what you know, what you know you know):
K U -- What you know
K KK KU
U UK UU
\
What you know you know
TT TF FT FF (Truth & belief of truth)
---- ---- ---- ----
KK | KKTT KKTF KKFT KKFF
KU | KUTT KUTF KKFT KKFF
UK | UKTT UKTF UKFT UKFF
UU | UUTT UUTF UUFT UUFF
In both the TF and FT columns, belief of the truth-value of data is incorrect.
In both the KU and UU columns, there is a lack of knowledge (e.g., ignorance), either known or unknown.
(I'm still thinking through what the implications of this are. Mapping it out helps structure the situation.)
Both exist. But the larger effort is put into distraction.
The recent Russian model is more on bullshit and subverting notions of trust entirely.
American propaganda seems largely based on a) what sells and b) promoting platitudes, wishful thinking, and c) (at least historically) heart-warming (rather than overtly divisive) notions of nationalism.
The c) case is now trending more toward divisive and heat-worming.
Yes, censorship and propaganda go hand in hand. In 1922 Walter Lippmann wrote in his seminal work, Public Opinion,
> Without some form of censorship, propaganda in the strict sense of the word is impossible. In order to conduct a propaganda there must be some barrier between the public and the event. [1] [2]
[1] https://www.gutenberg.org/cache/epub/6456/pg6456.html
[2] https://en.wikipedia.org/wiki/Public_Opinion_(book)#News_and...
Both are also tied inherently to monopoly, along with surveillance and both general and targeted manipulation.
https://joindiaspora.com/posts/7bfcf170eefc013863fa002590d8e...
If gamma rays randomly excluded one post in a thousand, that would be mussing data. Censors excluding one post in ten thousand is worrying because they have motivations of their own, which gamma rays do not.
This is 'some bad data' vs 'systemically biased data' and the latter is much worse. Most datasets will contain some bad data but it can be worked around because the errors are random.
https://twitter.com/degenrolf/status/1261164727486615559?lan...
https://twitter.com/degenrolf/status/1067780924014772224
Whereas censorship is lindy among things that have bad effects on society.
https://en.wikipedia.org/wiki/Lindy_effect
So give the most caution against the proven bad thing and not the one you're in a trendy moral panic about.
I'm going to adopt this style of argument from now on.
"Oh, you think that X is a big problem? Well, it isn't, because you have problem X, and only think that way because of it! It's your cognitive distortions talking! Zing!"
On a similar note, I somehow doubt if people broke through the doors to enter your home, assaulted people trying to protect it, yelled about how they want you dead, and then took some of your stuff you'd be calling it an "unguided tour".
1. Don't say anything because my neighbour tapes your mouth shut
2. Lie and say, "They were brutally murdered by your neighbour", resulting in a dead neighbour followed by my kids showing up unharmed from school
...can you explain in this scenario how censorship is worse than misinformation.
I'm not trying do be a jerk. I hear your argument a lot (especially on tech-heavy web sites) and I want to understand it.
Concretely to your hypothetical: don't attribute to misinformation the issue that is most like your barbaric reaction. Not to say that the liar should not be punished, it should bear a big responsibility in the consequences of the actions. But at the end of day it was not the liar the one that killed your neighbor, you were.
It's not as if folk AREN'T acting on misinformation or showing that they aren't really capable of distinguishing between the two. Tons can. And tons won't realize that The Boston Tribune isn't real.
We're having to deal with almost literally shouting "fire!" in a crowded theater when there's no fire, only there's special effects and major campaigns to convince people there's fire, not just taking some guy at their word and stampeding because of it.
If I am the father of the missing children and I see the "family and friends" sharing their condolences, I would go talk to them first. If someone comes with pictures trying to accuse someone of something, no matter how shocking the accusations, there would still be the question of (a) why is someone bothering with taking pictures and not taking to the authorities beforehand and (b) what are the consequences for me if I went on a rampage attack based on bogus evidence.
To get a little bit on topic: the reason that censorship is worse than misinformation is that we should always operate on the premise that our information is incomplete, inaccurate or distorted by those controlling the information channels.
Without censorship, I can listen to different sources (no matter how crazy or unsound they are) and I can try to discern what makes sense and does not. With censorship, any dissent is silenced, so we get one source of information - who can never get questioned - or worse we get to see many sources of information but only the ones that are aligned with the censors and gives us a false consensus and the illusion of quality in information.
Only idiots can walk around in the world of today and confidently repeat whatever they hear from "official" sources as unquestionable truths.
The extremes of my example were only to show that there could be real and serious consequences from misinformation rather than silence. If we dial it back from "killing my neighbour" to "lost my job" or even "missed my bus", I believe my point still stands. In many scenarios that we experience every day, we would be better served by accepting censure over misinformation.
You claim "we should always operate on the premise that our information is incomplete, inaccurate or distorted by those controlling the information channels" and I agree with you in theory. But in practice this is impossible. The human brain is physically unable to work everything through from first principles. This makes sense conceptually and has been verified in research.
And this to me is the fundamental issue of our time:
In theory, social media and unrestrained free speech are a boon for all society.
In practice they have turned people against each other with very real and serious consequences.
No. Not at all. I refuse your premise. Not only you are begging the question here (what scenarios? Your example was terrible and I really don't think you can come up with a good one), I honestly worry more about those that believe this rhetoric than the "victims" of misinformation.
Also, it's curious how those that so easily accept censorship never think that they will eventually be on the wrong side of the taser gun.
> I agree with you in theory. But in practice this is impossible. The human brain is physically unable to work everything through from first principles.
Good thing then that this is NOT WHAT I AM SAYING.
There is no need to "work though things from first principles". The idea is NOT to determine a priori what is "right" or "safe" and then make a binary decision. The base idea is to decide on what action to take (or to refuse to take) by asking yourself what is the worst possible thing that can happen if the information I have is wrong? What are the odds of me being wrong?.
I'd suggest you get acquainted with Nassim Taleb and Joe Norman to understand better how to deal with complexity and uncertainty.
> In practice they have turned people against each other with very real and serious consequences.
Bullshit. There was no Facebook during the time of the Crusades. There was no Twitter during the Cold War and no smartphones during WW1 and WW2. None of these things would be avoidable if only we could censor wrongthink.
On the other hand, THERE ARE video records of Tienanmen Square who have been successfully hidden from an entire country for an entire generation.
(Sorry for the harsh language, but I start reading any kind of censorship-apologetic and fighting instincts kick in. If you don't see how much of a sign of being morally bankrupt it is to casually defend the hellish things like state-sponsored censorship, I see no point in continuing the "debate")
To think that is okay to have one all-too-powerful entity controlling information channels is stepping into fascism and totalitarianism. This is a lesson that we should have learned already: no possible good comes out of that.
"If there be time to expose through discussion, the falsehoods and fallacies, to avert the evil by the processes of education, the remedy to be applied is more speech, not enforced silence"
However, I think it's also important to recognize that in today's algorithmically driven content presentation, "more speech" is often comically ineffective because it is never consumed in the emergent content bubbles that silo people from contradictory information. Not to mention the fact that misinformation that confirms your preconceptions is a much more powerful influence than actual information that contradicts them. Given this, an important caveat embedded in the above quote is: "If there be time". A recognition of the fact that, in some circumstances, there will not be an opportunity for more speech to prevail.
I don't have a solution to this. There may be no good solution to this, except lesser degrees of bad solutions.