AI for Teachers, An Open Textbook: Edition 1

Teaching AI

At this point we are considering the teacher, with respect to AI, as being savvy enough to use it safely and in a way that adds value to the education process.

The teacher may also want to share with its pupils some insider knowledge, explain how some tool that the pupil is using works. But that doesn't give the teacher the role and task of teaching AI.

Nevertheless the question will be raised at some point. Is there a case for educating everyone to AI? And in such a case, what should be taught? Who should do the teaching? How much more will the teacher need to learn?

What we have learnt from teaching coding

Ten years ago most European countries reached the conclusion that teaching "how to use a computer" wasn't good enough and that it was necessary to teach all children to code (or sometimes, with more ambition, computing, informatics). The arguments used then are probably valid today for artificial intelligence:Arguments can be found in 1 and 2. So coding was introduced. As shown in 3, not very well: in particular, insufficient resources were allocated to the human aspect: training the teachers. It is true that there was a complicated problem here: training too well the teachers could lead to these abandoning the teaching profession to work for the computing industry where the salaries are much higher! Reports from Informatics Europe and other organizations all show this (but there are some exceptions, of course).

Training teachers has been a complex task in all countries and in 2022 the results are still heterogeneous. In most countries the feeling is that there are not enough properly trained teachers. This makes it specially difficult to envisage training teachers to AI, at a level sufficient for them to teach AI (rather than teach with AI).

AI Literacy

The first goal could be to introduce some form of digital literacy in schools. But there is no agreement on what this literacy should contain? Do we want to explain how AI works or just what the results of using AI can be? These questions need to be addressed. Perhaps, in order to know what should be taught in a course of AI literacy, the first question is: what do we want to achieve?
If AI literacy is what will allow people to make a difference between magic and science, to be able to consider a new AI solution and have some intuition of how it works (and not just what it does) then some practical training will need to take place: Pupils and students will have to be able to test systems and have some model of how these work.

Paradigms

AI isn't only about some algorithms. There are many human aspects, but also questions to be thought out. For example, most AI methods will rely, to a certain extent, on randomness. This may seem strange for techniques who are supposed to help us make some drastic decisions (or, in the case of the stock exchange, who make the decisions directly).

Yet if AI is going to play a key role in the future, should we not at least start?

In a report for UNESCO in 20184 it was suggested that the following 5 questions, mostly absent today in the education system, need to be addressed:
  1. Coding is one of these. Even if tools seem to avoid direct coding, the reasoning behind the AI tools follows the rules which can be learnt through coding.
  2. Randomness matters. It often comes as a surprise, but AI makes mistakes. And these mistakes are in many ways unavoidable: they can be due to the quality of the data or of the sensors; they will also be due to the statistical nature of the algorithms which are used: most AI algorithms are not aiming at obtaining an absolutely correct.
  3. The world is no longer deterministic. This is a consequence of the above point, but also to the fact that most -if not all- data driven AI methods use some form of randomness to make their decisions. This is not new: in his 1950, Alan Turing6 wrote: RANDOMNESS QUOTE BY TURING "It is probably wise to include a random element in a learning machine."
  4. Critical thinking is essential but it has become necessary to know how to use the right tools. AI tools are getting better and better at creating fakes: images, videos and now texts. Tomorrow probably fake lectures. Common sense alone is no longer able to allow us to make informed decisions when it comes to deciding if an image, a voice, a text is a fake.
  5. The values we cherish, those that contribute to us analysing the world, to make moral decisions, those helping us make decisions as to why we will spend time studying or working, these all need to be scrutinized in the light of the progress Artificial Intelligence is making. Truth has a grey zone which is growing wider every day ; experience is perhaps not going to be of value when AI is able to refer to the collective experience and crunch the numbers. Understanding these questions, or at least asking them, is a necessity.

Some proposed curricula

There are some curricula available today. Unesco has started to survey these and present them[REF88].
Some papers are [REF4]4 and [Ref5]5
---------------------------------------------------------
1Royal Society (2012). Shut down or restart? Report of the Royal Society. 2012 https://royalsociety.org/topics-policy/projects/computing-in-schools/report/T
2Académie des Sciences (2013). L'Académie des Sciences : L'enseignement de l’informatique en France – Il est urgent de ne plus attendre. http://www.academie-sciences.fr/fr/activite/rapport/rads_0513.pdf
3 Informatics Europe (2017)  Informatics Education in Europe: Are We All in the Same Boat?
4 Colin de la Higuera. Report on Education, Training Teachers and Learning Artificial Intelligence. Unesco  report, 2018.
https://www.k4all.org/project/report-education-ai/
5Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019). Envisioning AI for K-12 : What Should Every Child Know about AI ? Proceedings of the AAAI Conference on Artificial Intelligence, 33, 9795-9799. https://doi.org/10.1609/aaai.v33i01.33019795
6A. M. Turing (1950)—Computing Machinery and Intelligence, Mind, Volume LIX, Issue 236, October 1950, Pages 433–460, https://doi.org/10.1093/mind/LIX.236.433
7Howell, E. L., & Brossard, D. (2021). (Mis) informed about what? What it means to be a science-literate citizen in a digital world. Proceedings of the National Academy of Sciences, 118(15), e1912436117. https://www.pnas.org/doi/abs/10.1073/pnas.1912436117
8Unesco (2022) K-12 AI curricula: a mapping of government-endorsed AI curricula. https://unesdoc.unesco.org/ark:/48223/pf0000380602

This page has paths: