The biggest fakes.
1. Artificial
Intelligence.
There is nothing
really intelligent about it.
I have written
numerous papers on the matter and address everyone to this page.
What “AI”
represents and will be representing for a long time ahead is an advanced
pattern-recognition system with limited ability to self-adjustment. Nothing
more. It’s not a trivial matter, but it is not going to get close to human
intelligence any soon. Of course, AI-called systems will penetrate many
different practices, because they can significantly speed up any
pattern-recognition process. But that’s that. Writers who write about AI do not
even have a definition of intelligence (I do). They do not even
know the difference between “a definition” and “a description”. The core of intelligence is not pattern recognition but imagination (google - “Einstein on intelligence”), because imagination is the source of creativity (e.g. Confessions of a Creative Brain). The only option
for a breakthrough in the field of actual artificial intelligence is to
initiate a deep and targeted research into human intelligence, its functioning,
its structure. But that would mean hiring people who have a deep knowledge in
the field of human intelligence; how it functions, how it is developed. But
that would need people who (a) have the access to top level of decision making,
and (b) already have such knowledge. It will take another decade to have that
people at those levels, hence – a decade of faking is upon of us.
Naturally, media tells a very different stories. It's because people in the field use a very powerful tool – reduction/reducing. They say “artificial intelligence” but then ignore the true meaning of intelligence (because they do not know it) and reduce intelligence to pattern recognition and then say - we can do that. They say “machine leaning” but then ignore the true meaning of learning (because they do not know it) and reduce learning to animal training and then say - we can do that. They say “data science” but then ignore the true meaning of science (because they do not know it) and reduce science to statistical analysis of correlations and then say - we can do that. Many of the methods for correlation analysis have been around for decades and well used in many fields beyond statistics (e.g. physics). All developed sciences are based on the detailed analysis of a vast amount of data and use the same method of reasoning - a scientific method of thinking. Data science requires first and foremost an ability to apply that method for establishing a strategy for the future search of relevant/important correlations. And only then apply a specific statistical method. It's like coding - first a coder needs to establish a set of actions (in a from of commands), and then to choose a programming language and apply it (of course, an experienced coder does it almost at the same time). But media do not tell public about all this. Media just fakes the level of achievements in all those fields.
Naturally, media tells a very different stories. It's because people in the field use a very powerful tool – reduction/reducing. They say “artificial intelligence” but then ignore the true meaning of intelligence (because they do not know it) and reduce intelligence to pattern recognition and then say - we can do that. They say “machine leaning” but then ignore the true meaning of learning (because they do not know it) and reduce learning to animal training and then say - we can do that. They say “data science” but then ignore the true meaning of science (because they do not know it) and reduce science to statistical analysis of correlations and then say - we can do that. Many of the methods for correlation analysis have been around for decades and well used in many fields beyond statistics (e.g. physics). All developed sciences are based on the detailed analysis of a vast amount of data and use the same method of reasoning - a scientific method of thinking. Data science requires first and foremost an ability to apply that method for establishing a strategy for the future search of relevant/important correlations. And only then apply a specific statistical method. It's like coding - first a coder needs to establish a set of actions (in a from of commands), and then to choose a programming language and apply it (of course, an experienced coder does it almost at the same time). But media do not tell public about all this. Media just fakes the level of achievements in all those fields.
2. Educational
Technologies.
Computers,
tablets, smart-phones, the Internet, MOOCs, online home-work systems, online
lab systems, etc. – you name it. They all have failed to make any visible difference in
education (except making tons of money for some players), and will be failing again and again. Granted, above the K12 level some technologies brought some convenience to some students. But that's that. Technologies have failed for K12 schools. Imagine bringing in a
kindergarten the most advanced computers and just giving them to kids saying - learn! If you expect
the kids would really benefit from that – you have no idea what learning is,
and how it happens. But in this example, computers represent all technologies
that are being pushed on to teachers, and kids represent teachers. Not all of
them but the vast majority. In order to be able to use any technology
effectively, a teacher has to be good at teaching in the first place. Otherwise
no technology will make any difference. Of course, if we had robots as smart as
good teachers, that would allow to replace bad teachers with machines. But this
is not going to happen any soon (see the first fake). Hence, the only way
technologies will make any difference if – first and foremost – schools will be
getting lots and lots of good teachers.
Some additional publications on the matter:
3. Education
Reform.
Reforming education has come to it’s failing end. EdReform is dead! Hail to EdReform! Naturally, politicians, the government, the NSF will revile very soon a new approach to reforming education. And that will be a fake. America simply does not have yet enough people who understand what education is and how should it function, hence have a sense of the change required by the new paradigm. The Department of Education is not responsible for reforming schools, it is responsible for establishing stable functioning. Reformation is the duty of the NSF. As I pointed out in How much of the NSF funded fundamental scientific educational research is really fundamental? and Publicity v. The Mission; a tough decision For The NSF., the NSF does not have people who are capable to envision bold approaches and approve ideas that do not fall into work of already existing groups. For decades every single “innovator” was advocating for an “evidence-based approach” to reforming education. What they all really meant, though, “our evidence-based”. Since the end of the WWII America was draining the brains from all over the world in science and technology, but not in education. Even after JFK's talks about education, CIA would steal secrets of the latest Russian missile, but no one wanted and still wants to “steal” the latest math and physics textbooks (and here is the result).
Take physics, for example. If an experiment is done in one country, physicists in other countries do not reject it because of the territorial difference. In education there is plenty of evidence coming from Russia, China, Finland and many other countries for what works in education. But American “scientists” (in the field of education) simply ignore all that data. Despite the fact that all human are equally human independently of the place of living. And will keep ignoring, because that is the only way for them to defend their own turf, and to keep all those grant money (millions of dollars) they use to do the “research”, that is absolutely trivial (as described in this paper), and does not make any impact. American “scientists” (in the field of education) do not even know what “science” is. If they did, they would follow the scientific method of reasoning, including “deriving from the first principles”. Take physics, again. No one needs to perform more experiments with weights and springs to prove the second Newton’s law – that law now is the first principle, and is used to arrive at other conclusions about mechanical systems. Humans (in all countries) function according to the same physiological and psychological laws. Imagine an experiment with two groups of people who have similar physical abilities. For a month, one group will exercise both arms, and another just a left one. If in a month we measure the strength of the people’s arms – what do you expect to observe? The answer is trivial. And does NOT require conducting of an actual experiment, because it is based on a simple fundamental principle – when a muscle is being exercised, it gets stronger, otherwise it is not (or even gets atrophic). The same principle (that I've been successfully using in my classes for more than twenty years) describes a brain development. In education, it leads to a simple rule – when a learner is immersed in a learning process learning happens; the absence of learning is an indicator of the absence of a learning process. Period. There are many similar rules that do not require exhausting specific experimentation – they require mass implementation (using a specific strategy, called Professional Designing for Teachers). The knowledge and the use of those fundamental principles makes the vast amount of the NSF “research” in education useless. But no one will ever confirm this as a fact. For at least two decades the “reform” was based on the
“idea” that schools are factories with assembly lines, and teachers are workers who have to be punished for every mistake and paid extra for something that reformers did not even know how to assess. But when Henry Ford developed his assembly line, he did not just open doors to workers and told - go, figure out how it works. No, he trained them. American teachers are badly trained, en masse. There is virtually no system of teacher professional development. It could exists, but no one wants it. Because if smart, educated, and powerful people would wanted it, it would exist already (another example of reasoning from the first principle). There is a specific governmental unit that is responsible for technological breakthroughs to keep America ahead of the world – DARPA. I have been advocating for such an “agency” in the field of education – since 2004 (Perimeter Institute for Learning and Teaching (PILT): the future of the future of education reform.). In fact, since 2004 (when my English became OK) I have been reaching out to politicians, officials, educators, philanthropists, venture capitalists, the NSF, altogether hundreds of people, not once I was able to elicit any response. From about 40,000 American visitors (from total of more than 87,000) of my blog no one found anything interesting to write a logical response to any conclusion, project, proposal. Despite the fact that the vast majority of my publications offer more than just a critical analysis of the issues, but also specific steps to resolve them. No one reflects on the logic of the publication; everyone dismisses it based on a simple fact – the author has no name. With this level of anti-curiosity and self-absorbedness the next stage of “reforming” will be just a next stage of fighting for the slice of the money-pie. And there will be no help from philanthropy. As I described in Seven Reasons Why Rich Philanthropists Fail at Making Systemic Changes in Education, philanthropists like surrounding themselves with the people who like them. So, no room for “the team of rivals”, no competition of ideas. Till these days, philanthropy has never spurred any innovation. The best it can do is to preserve the status quo. Hence – stagnation. And the last possible force, venture capital, will not be able to make the turn in EdReform. As I described (in part) in “Will Artificial Intelligence Save, Replace or even Affect Education Practices? (a venture capitalist’s view)”, those people so strongly believe in their own powers, so they are absolutely convinced that their primitive view on education is the only way to approach education. My long-term experiment demonstrates that, although America has individuals who truly want improve mass education, she does not have people who want to do that. People (who belong to different social circles) want participate in continuous endless improvement of education. The end game does not interest anyone.
Maslow pyramid is a good working model that explains a lot. Nowadays working in STEM may become very profitable for people who know the right people and say the right words. Doing the right things is not required. Money goes not to one who makes STEM better, but to one who promises(!) to make STEM better in the future. Without real measurability accountability is a fiction. So, the main criterion for support is the name, the list of citations, and a new intriguing term (forget STEM, let’s erase any differences and do STEAM!).
In reality, these days, we do not need new ideas on how to teach - we need to ensure broad and effective implementation of ideas that have been known for decades. But things will not change any soon, because the NSF likes the things the way they are.
“I am very good at teaching, I can teach more students”. “Thanks, but, no, thanks.” “I have a unique experience that I can offer to help instructors and teachers teach better”. “Thanks, but, no, thanks.” This way of management is everywhere in education – all areas, all levels. For the next decade.
4. American
Democracy.
Vast majority of
Americans believe that “voting” is an equivalent of “democracy”. Of course,
educated Americans know the difference, but the number of those people have
been gradually decreasing for the last 30 years. The result is that three
pillars of democracy – separation of powers (a.k.a. check and balances), free
speech, and the rule of law – have been significantly corrupted. This corruption
demonstrates the fact that American is in the stage of the elite change: the old elites have
degraded and have become out of touch with the reality, the new elite does not
yet exist, it is just in the process of being created. America is entering
the period of ethnic battles; people on the conservative
side have been preparing this for a long time, and now use all options to
install their supporters to as many official places as possible (e.g. the
judges who will not use their power to uphold the law, but will use the law to
increase the power of the social group they belong to). America has now its own
“state media” (e.g. FOX), and social media only strengthen that type of
influence leading to further clusterization of American society. That will lead
to even stronger polarization. The period of political and social chaos (plus
the market crash in 2021/22) inevitably leads to the further weakening of
democratic institutions and strengthening
authoritarian tendencies.
The biggest breakthroughs.
1. Ability to grow
and regenerate biological tissues and organs.
2. Ability to
interpret electric impulses of a mind (“mind reading”).
3. Ability to use
electromagnetic waves/beams to induce different states of mind. Combined with #2 it brings an ability to share states of mind directly between individuals.
4. Developing of a
vast database of correlations between different teaching and learning actions
and outcomes (the strategy for such approach is described here).
5. Brain Augmenting Technologies
5. Brain Augmenting Technologies
Note: this post is a part of the
series:
China v. The U.S.: The Battle Of Strategic Thinking
China v. The U.S.: The Battle Of Strategic Thinking
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