Beguiled by Artificial Intelligence.

Experienced educators know the importance of using good quality teaching aids to deliver effective lessons to students. If tasked to introduce shapes to small children, the teachers could start off with initially cutting out different coloured shapes such as a triangle, circle or a square. Next, they could visibly hold one shape at a time towards the students and announce its name. So, initially, they could display the blue triangle and loudly say 'triangle'. Then, they could pick up the red circle and call out 'circle', and finally, they could lift the green square and announce 'square'. This process can be repeated a few times to ensure that the shapes and their associated names are well registered with the students.

However, if the above steps are carefully evaluated, we will observe an underlying problem that results in teaching wrong concepts to the students. As the shapes consist of different colours, and as the teacher holds shape and loudly calls out its name, some students are likely to relate the name of the shape to its respective colour. For example, in the above scheme of things, it is completely reasonable for students to learn that triangle means the colour blue, whereas, circle means red and that the square is referred to the colour green. Although these are incorrect conclusions, nevertheless, in this instance they are logical since the called-out name can be linked to either a shape or a colour. Of course, good instructors also know how to avoid this issue in the first place by simply ensuring that all the shapes have the same colour. This small modification in ensures that the children will correctly associate the name with its appropriate shape and not confuse it with the colour.

In summary, if different colours were indeed used for the shapes, the training could result in students developing two distinctly opposite but consistent types of understanding. The first type of conclusion would associate the name with its correct shape, whereas, the second type of learning could relate the name of the shape to its colour. The key observation is that both outcomes are rational with respect to the data that was presented to the students, but only the first one is correct.

Incidentally, what is true for humans is also true for AI systems which are equally prone to draw wrong conclusions that are albeit consistent with data. To highlight this point, Marvin Minsky, a leading cognitive psychologist who is considered one of the...