Operant Chickens

As with chickens, humans can learn through reinforcement AKA operant conditioning.

In this video clip, we see a chicken learning that pecking a red circle yields a payload of food. Yet there is a problem with this algorithm. I don’t expect this study was meant to elucidate this point, but I’ll continue.

Except for one instance where the blue circle was pecked to yield nothing, the chicken learned that packing the red yielded a treat and so became fixed on seeking the red. What the chicken did not explore where the other colours—beige, green, and yellow. Perhaps these might have had a larger payout or a ‘better’ reward. Perhaps even a penalty or punishment, but I’ll ignore that eventuality.

The point is that through operant conditioning, the chicken is habituated. I feel that this is a metaphor for many such habituations in humans. People are indoctrinated (habituated) into all sorts of beliefs and behaviours, from the organisation of social and political systems to economic systems.

When I see people defending Democracy as Churchill did as “the worst form of government, but the best so far,” I can’t help but consider the parallels: Democracy is the red dot; capitalism is the red dot.

This not being a self-help blog, I’ll mention is passing the routines we get ourselves into that are analogous to this chicken—wandering through the world as if with blinders. The difference between a rut and a grave is the depth or dimensions. Are you in a rut on your way to the grave?

This is all I wanted to say. No chickens were harmed during the production of this blog entry.

Houston, we have a problem

EDIT: Since I first posted this, I’ve discovered that computer algorithms and maths are not playing well together in the sandbox. Those naughty computer geeks are running rogue from the maths geeks.

In grade school, we typically learn a form of PEMDAS as a mnemonic heuristic for mathematical order of operations. It’s a stand-in for Parentheses, Exponents, Multiplication, Division, Addition, and Subtraction. This may be interpreted in different ways, but I’ve got bigger fish to fry. It turns out that many (if not most) programming languages don’t implement around a PEMDAS schema. Instead, they opt for BODMAS, where the B and O represent Brackets and Orders—analogous to Parentheses and Exponents. The important thing to note is the inversion of MD to DM, as this creates discrepancies.

And it doesn’t end here. HP calculators interject a new factor, multiplication by juxtaposition, that mathematician and YouTuber, Jenni Gorham, notates as J resulting in PEJMDAS. This juxtaposition represents the implied multiplication as exemplified by another challenge;

1 ÷ 2✓3 =

In this instance, multiplication by juxtaposition instructs us to resolve 2✓3 before performing the division. Absent the J, the calculation results in ½✓3 rather than the intended 1/(2✓3). As with this next example, simply adding parentheses fixes the problem. Here’s a link to her video:

And now we return to our originally scheduled programming…

Simplifying concepts has its place. The question is where and when. This social media war brings this back to my attention.

As depicted in the meme, there is a difference of opinion as to what the answer is to this maths problem.

6 ÷ 2 ( 1 + 2 ) =

In grade school, children are taught some variation of PEMDAS, BOMDAS, BEDMAS, BIDMAS, or whatever. What they are not taught is that this is a regimented shortcut, but it doesn’t necessarily apply to real-world applications. The ones defending PEMDAS are those who have not taken maths beyond primary school and don’t use maths beyond some basic addition and subtraction. Luckily, the engineers and physicists who need to understand the difference, generally, do.

Mathematicians, scientists, and engineers have learned to transform the equation into the form on the left, yielding an answer of 1. If your answer is 9, you’ve been left behind.

Why is this such a big deal?

When I taught undergraduate economics, I, too, had to present simplifications of models. In practice, the approach was to tell the students that the simplification was like that in physics. At first, you assume factors like gravity and friction don’t exist—fewer variables, fewer complexities. The problem, as I discovered in my advanced studies, is that in economics you can’t actually relax the assumptions. And when you do, the models fail to function. So they only work under assumptions that cannot exist in the real world—things like infinite suppliers and demanders. Even moving from infinite to a lot, breaks the model. Economists know this, and yet they teach it anyway.

When I transitioned from undergrad to grad school, I was taken aback by the number of stated assumptions that were flat out wrong.

When I transitioned from undergrad to grad school, I was taken aback by the number of stated assumptions that were flat out wrong. Not only were these simplifications flat out wrong, but they also led to the wrong conclusion—the conclusion that aligned with the prevailing narratives.

This led me to wonder about a couple of things

Firstly, if I had graduated with an English degree and then became a PhD candidate in English, would I have also learnt it had mostly been a lie for the purpose of indoctrination?

Secondly, what other disciplines would have taught so much disinformation?

Thirdly, how many executives with degrees and finance and management only got the fake version?

Fourthly, how many executives hadn’t even gotten that? Perhaps they’d have had taken a class or two in each of finance and economics and nothing more. How many finance and economics courses does one need to take to get an MBA? This worries me greatly.

To be honest, I wonder how many other disciplines have this challenge. I’d almost expect it from so-called soft sciences, but from maths? Get outta here.

Half-life of knowledge

This also reminds me of the notion of the half-life of knowledge. What you knew as true may eventually no longer be. In this case, you were just taught a lie because it was easier to digest than the truth. In other cases, an Einstein comes along to change Newtonian physics into Oldtonian physics, or some wisenheimer like Copernicus determines that the cosmic model is heliocentric and not geocentric.

If you’ve been keeping up with my latest endeavour, you may be surprised that free will, human agency, identity, and the self are all human social constructs in need of remediation. Get ready to get out of your comfort zone or to entrench yourself in a fortress of escalating commitment.