Tuesday, September 03, 2024
Why AI ‘misinformation’ algorithms and research are mostly expensive garbage
If ever there was a case of ‘garbage in, garbage out’ then this is it.
And, ultimately it has all been driven by the objective of censoring information that does not fit the politically correct narrative.
The Hunter Biden laptop story is just one of many stories which were deemed by the Main Stream Media (and most academics) to be ‘misinformation‘ but which were subsequently revealed as true.
Indeed Mark Zukerberg has now admitted that Facebook (Meta), along with the other big tech companies, were pressured into censoring the story before the 2020 US election and also subsequently pressured by the Biden/Harris administration to censor stories about Covid which were wrongly classified as misinformation.
The problem is that the same kind of people who decided what was and was not misinformation (generally people on the political Left) were also the ones who were funded to produce AI algorithms to ‘learn’:
a) which people were ‘spreaders of misinformation’; and
b) what new claims were ‘misinformation’.
Between 2016 and 2022, I attended many research seminars in the UK on using AI and Machine Learning to ‘combat misinformation and disinfomation’.
From 2020, the example of Hunter Biden’s laptop was often used as a key ‘learning’ example, so algorithms classified it as ‘misinformation’ with subclassifications like ‘Russian propaganda’ or ‘conspiracy theory’.
Moreover, every presentation I attended invariably started with (and was dominated by) examples of ‘misinformation’ that were claimed to be based on “Trump lies” such as those among what the Washington Post claimed were the “30,573 false or misleading claims made by Trump over 4 years”.
But many of these supposed false or misleading claims were already known to be true to anybody outside of the Guardian/NYT/Washington Post reading bubble.
For example, they claimed that Trump said “Neo-Nazis and white supremacists were very fine people” and that anybody denying was pushing misinformation, whereas even the far Left-leaning Snopes had debunked that in 2017.
Similarly, they claimed “evidence that Biden had dementia” or that “Biden liked to smell the hair of young girls” was misinformation despite multiple videos showing exactly that – so, don’t believe your lying eyes; indeed as recently as one week before Biden’s dementia could no longer been hidden during his live Presidential debate performance, the mainstream media were adamant that such videos were misinformation ‘cheap tricks’.
But the academics presenting these Trump, Biden, and other political, examples ridiculed anybody who dared question the reliability of the self-appointed oracles who determined what was and was not misinformation. At one major conference taking place on zoom I posted in the chat:
“Is anybody who does not hate Trump welcome in this meeting”. The answer was “No. Trump supporters are not welcome and if you are one you should leave now”.
Sadly, most academics do not believe in freedom of thought, let alone freedom of expression when it comes to any views that challenge the ‘progressive’ narrative on anything.
In addition to the Biden and Trump related ‘misinformation’ stories which turned out to be true, there were also multiple examples of covid related stories (such as those claiming very low fatality rates and lack of effectiveness and safety of the vaccines) classified as misinformation that also turned out to be true.
In all these cases anybody pushing these stories was classified as a ‘spreader of misinformation’, ‘conspiracy theorist’ etc. And it is these kinds of assumptions which drive how the AI ‘misinformation’ algorithms that were developed and implemented by organisations like Facebook and Twitter worked.
Let me give a simplified example The algorithms generally start with a database of statements which are pre-classified as either ‘misinformation’ (even though many of which turned out to be true), or ‘not misinformation’ (even though many of which turned out to be false). For example, the following were classified as misinformation:
“Hunter Biden left a laptop with evidence of his criminal behaviour in a repair shop”
“The covid vaccines can cause serious injury and death”
The converse of any statement classified as ‘misinformation’ was classified as ‘not misinformation’.
A subset of these statements are used to “train” the algorithm and others to “test” the algorithm.
So, suppose the laptop statement is one of those used to train the algorithm and the vaccine statement is one of those used to test the algorithm.
Then, because the laptop satement is classified as misinformation, the algorithm learns that people who repost or like a tweet with the laptop statement are ‘misinformation spreaders’. Based on other posts these people make, the algorithm might additionally classify them as, for example, ‘far right’.
The algorithm is likely to find that some people already classified as ‘far right’ or ‘misinformation spreader’ – or people they are connected to – also post a statement like “The covid vaccines can cause serious injury and death”.
In that case the algorithm will have ‘learnt’ that this statement is most likely misinformation. And, hey presto, since it gives the ‘correct’ classification to the ‘test’ statement, the algorithm is ‘validated’.
Moreover, when presented with a new test statement such as “The covid vaccines do not stop infection from covid” (which was also pre-classified as ‘misinformation’) the algorithm will also ‘correctly learn’ that this is ‘misinformation’ because it has already ‘learnt’ that the statement.
“The covid vaccines can cause serious injury and death” is misinformation and that people who claimed the latter statement- or people connected with them – also claimed the former statement.
The way I have outlined how the AI process is designed to detect ‘misinformation’, is also the way that ‘world leading misinformation experts’ set up their experiment to “profile” the “personality type” that is susceptible to misinformation.
The same methods are also now used to profile and monitor people that the academic ‘experts’ claim are ‘far right’ or racist.
Hence, an enormous amount of research was (and is still) spent on developing ‘clever’ algorithms which simply censor the truth online or promote lies. Much of the funding for this research is justified on the grounds that ‘misinformation’ is now one of the greatest threats to international security.
Indeed, in Jan 2024 the Word Economic Forum declared that “misinformation and disinformation were the biggest short term global risks”.
European Commission President Ursula von der Leyen also declared that “misinformation and disinformation are greater threats to the global business community than war and climate change”. In the UK alone, the Government has provided many hundreds of millions of pounds of funding to numerous University research labs working on misinformation.
In March 2024 the Turing Institute alone (which has several dedicated teams working on this and closely related areas) was awarded £100 million of extra Government funding – it had already received some £700 million since its inception in 2015.
Somewhat ironically, the UK HM Government 2023 National Risk Register includes as a chronic risk:
“artificial intelligence (AI). Advances in AI systems and their capabilities have a number of implications spanning chronic and acute risks; for example, it could cause an increase in harmful misinformation and disinformation”
Yet it continues to prioritise research funding in AI to combat this increased risk of ‘harmful misinformation and disinformation’!
As Mike Benz has made clear in his recent work and interviews (backed up with detailed evidence), almost all of the funding for the Universities/research institutes world wide doing this kind of work, along with the ‘fact checkers’ that use it, comes from the US State Dept, NATO and the British Foreign Office who, in the wake of the Brexit vote and Trump election in 2016, were determined to stop the rise of ‘populism’ everywhere.
It is this objective which has driven the mad AI race to censor the internet.
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Harris’s empty words an insult to US voters and democracy
Did you see that interview with Kamala Harris on CNN? Wasn’t it amazing?
As things stand, Harris, and her vice-presidential running mate, Tim Walz, are marginally ahead in the presidential race. If the polls are accurate, and the election were held today, she’d probably be president. On the basis of the epic, fatuous emptiness of her first major television interview, this is a potentially disastrous development.
This column is no unqualified admirer of Donald Trump. America has presented itself with a terrible choice. But on the basis of that CNN interview, it stands ready to elect one of the most spectacularly incompetent and unqualified candidates in its history.
Of course, we must be careful about polls. Trump tends to outperform his poll numbers on election day. So it’s possible that even with the current opinion poll numbers, Trump could win.
The other paradox is that Trump leads Harris over who can better manage most of the key issues, but Harris leads Trump overall in the polls. In other words, a lot of people think Trump can do the job, but don’t like him much.
People are still unconvinced that Harris can do the job, but the Democrat machine, running a Hollywood movie star celebrity image promotion job, has marketed her as a likeable and normal American.
The CNN interview was unintentionally revealing. Harris, in striking contrast to professional politicians of the past such as Barack Obama or Bill Clinton, has avoided doing any unscripted interviews or live exchanges on camera. No one suggests she’s suffering cognitive decline like Joe Biden, but she is unbelievably hopeless at explaining her policies, or even just talking in sensible English about policy issues.
As Vice-President, she did a disastrous TV interview early in the life of the Biden administration, in which the interviewer was mean enough to ask some polite but modestly insistent questions about her performance in trying to clean up the illegal immigration disaster on the Mexican border.
She made such a mess of it that she virtually went into hiding afterwards, and was never again given primary responsibility for any serious issue by the Biden administration.
But back to the CNN show. The journalist, Dana Bash, did ask some of the obvious and mildly tough questions, but when Harris didn’t answer Bash didn’t press the matter. Instead there was a suffocating atmosphere of glutinous fluff.
Even on the softest possible questions, Harris had the greatest difficulty constructing a normal English language sentence that actually related to the question.
Bash asked Harris what she would do on day one of her presidency and got this reply: “Well, there are a number of things. I will tell you first and foremost one of my highest priorities is to do what we can to support and strengthen the middle class. When I look at the aspirations, the goals, the ambitions of the American people, I think that people are ready for a new way forward in a way that generations of Americans have been fuelled by – by hope and optimism.”
There followed another similar paragraph of mind-deadening word confetti about how Trump had caused divisions.
Bash was polite, but still no clearer on what Harris planned for day one, which is one the absolutely compulsory cliche questions of all American presidential campaigns. So she tried again. Day one?
Harris replied: “Day one, it’s gonna be about one, implementing my plan for what I call an opportunity economy. I’ve already laid out a number of proposals in that regard, which include what we’re gonna do to bring down the cost of everyday goods, what we’re gonna do to invest in America’s small businesses, what we’re gonna do to invest in families.”
Harris seems like the fictional portrayal of Sara Palin in the movie, Game Change. In that film her handlers couldn’t get Palin to fully grasp certain policy issues, so instead they got her to learn by rote a series of topic-specific answers.
It’s tempting to think Harris has done something similar, although it’s hard to believe anyone would actually write, and the get someone else to memorise, such content-free, syntax-mangling, meandering, pointless word assemblages as Harris uttered.
When later in the interview Harris was asked about the causes of inflation, the best she could come up with was alleged “price gouging” by greedy corporations. There was no mention of the budget deficit approaching $US2 trillion, more than 6 per cent of GDP. Nor of the vast regulatory complexity, and accompanying cost, the Biden administration has added to business.
Bash gently asked Harris why she had reversed herself on her passionate opposition, as recently as 2019, to fracking. She got no answer so asked again.
Harris replied: “Well, let’s be clear. My values have not changed. I believe it is very important that we take seriously what we must do to guard against what is a clear crisis in terms of the climate. And to do that, we can do what we have accomplished thus far.”
George Orwell could not have produced a more exquisite newspeak parody, the object of which is to give the appearance of substance to pure wind.
Consider one more immortal Harrisism, as to her radical policy reversals as she, temporarily at least, abandons her ultra-liberal past for a more centrist presentation for the election: “Dana, I think the – the – most important and most significant aspect of my policy perspective is my values have not changed. You mentioned the Green New Deal. I have always believed and I have worked on it that the climate crisis is real, that it is an urgent matter to which we should apply metrics that include holding ourselves to deadlines around time.”
There were also some wonderfully brazen straight-out lies. Did Biden offer to endorse you in the phone call when he told you he was standing down? Harris: “Well, my first thought was not about me, to be honest.”
Walz was if anything worse than Harris. Bash asked him about several blatant lies he’s told, for example claiming he carried weapons in battle whereas during his service in the National Guard he was never deployed anywhere near a battle zone. He responded, Prince Andrew-like, by praising his own exemplary honesty.
CNN did the right thing asking these questions. But Bash responded to the non-answers as if she’d heard a masterful declamation from Cicero. CNN certainly decided not to make an issue of lies or evasions.
Harris’s handlers are hoping she can be anything any voter wants, that she can win just by not being Trump.
That’s partly why they won’t define her program or let her define herself. But refusing to outline any policies, refusing to engage in any serious debate, that’s an insult to democracy. In her own way, Harris embodies the serious, hopefully temporary, decline of America’s political culture.
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Also see my other blogs. Main ones below:
http://jonjayray.com/covidwatch.html (COVID WATCH)
http://edwatch.blogspot.com (EDUCATION WATCH)
http://antigreen.blogspot.com (GREENIE WATCH)
http://pcwatch.blogspot.com (POLITICAL CORRECTNESS WATCH)
http://snorphty.blogspot.com (TONGUE-TIED)
https://immigwatch.blogspot.com (IMMIGRATION WATCH)
https://australian-politics.blogspot.com (AUSTRALIAN POLITICS)
https://john-ray.blogspot.com/ (FOOD & HEALTH SKEPTIC -- revived)
http://jonjayray.com/select.html (SELECT POSTS)
http://jonjayray.com/short/short.html (Subject index to my blog posts)
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