AI is Expensive Garbage
If ever there was a case of 'garbage in, garbage out' then this is it. Ultimately it has all been driven by the objective of censoring information that does not fit the politically correct narrative.
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'.
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.
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.
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. Look at this video in which Mike Benz walks us through an event that took place in 2019.
It was hosted by the Atlantic Council (a NATO front organisation) to train journalists from mainstream organisations all around the world on how to 'counter misinformation'. Note how they make it clear that 'misinformation' includes for them 'malinformation' which they define as information that is true but, but which might harm their own narrative. They explain how to muzzle such 'malinformation’, especially from the (then) President Trump's social media posts in advance of the 2020 election. Despite claims that this did not happen (and indeed any such claims were themselves classified as misinformation) the journalists involved in this subsequently boasted very publicly that they not only did it but that it prevented Trump's re-election in 2020.