Tag Archives: science

The Two Main Theories of Brain Evolution

brain evolution

Fossil records (skull size) and archeology (tools) show a clear evolution in our species’ cognitive abilities.

But, when you think about it, our current level of intelligence is far from being necessary for survival. Hunter-gathers could easily get by without abstraction, reasoning and even language.

So where does human intelligence come from? Why has our brain size tripled in the course of our journey?

Two main reasons can account for this spectacular brain expansion. In other words, humans have developed larger brains to deal with either one of the following elements or a combination of both:

  1. Their physical environment
  2. Their fellow humans

In turn, this has led to two sets of hypotheses, namely

  1. Ecological theories
  2. Social theories

Ecological theorists argue that learning to master the environment gradually caused human intelligence to evolve. Without getting into specific theories, here are four factors that might have played a role in this increase.

  1. Food: A positive correlation exits between diet quality and brain size in primates.
  2. Foraging: The increase of food sources required a better memory.
  3. Bipedalism: Tool use increased the demands on cognitive abilities.
  4. Climate: The challenges of climate change called for better problem-solving skills.

The problem with ecological theories is that these factors aren’t unique to humans, which may explain why social theories have become more popular.

Social theorists, on the other hand, argue that living in complex social grouping is what provoked cognitive development in our species. Here again, instead of going over different theories, let’s look at three important (and interrelated) factors.

  1. Social complexity: The wide range of social rules required high-level cognitive skills.
  2. Sexual selection: The choice of intelligent mates created a positive feedback loop.
  3. Language: A symbolic system fosters conceptualization and inference skills.

At the moment, the predominant model explaining the emergence of human intelligence is the ecological dominance-social competition (EDSC) theory, which is a mix of ecological and social theories.

In short, it says that an initial growth of intelligence was enough to overcome ecological pressures, which caused population to increase. This, in turn, forced humans to compete and collaborate with each other, which led to larger brains and higher intelligence.

So humans became peak learners through collaboration and competition.

Here there may be an interesting parallel with knowledge workers, whose success in the organization often comes from their high level of emotional intelligence.

People don’t naturally think like scientists (but peak learners should)

learners as scientists

One of my close friends definitely prefers “being right” than being accurate. He has lots of opinions and theories on everything, but if you show him evidence that contradicts one of them, he’ll put the full weight of his reasoning power to discount your evidence.

As it turns out, we’re all like him to a lesser or greater extent, and this flies in the face of the popular theory of discovery-based learning, which posits that students intuitively learn like scientists.

What does it mean to learn like a scientist?

It means you’re an active creator of your own learning, and you do this by

  1. exploring your environment,
  2. generating ideas about how things work,
  3. testing those ideas and
  4. changing your model accordingly.

In other words, scientific thinking is about coordinating evidence (things you observe) and theory (ideas about how those things work).

So, for people to think like scientists, they need at least to be able

  1. to distinguish theory and evidence and
  2. to update their theory in the light of new evidence.

As many studies have found, untrained people are bad at both.

After reading Researcher Deanna Kuhn’s study, you’ll indeed notice that people easily blur the difference between theory and evidence in everyday life.

Let me give you the simplest example. When you see people smile, you probably take this as evidence that they’re happy, right? But the thing is, you can’t see happy; happy is a theory. It may look like a safe theory, but it’s still a theory.

But even when theories don’t get confused with facts, shifting theories to match facts doesn’t come naturally for most people. As Lord, Ross and Lepper’s classic study showed, when they come across a fact that contradicts their theory, people will often ignore it or interpret it in a biased way (confirmation bias).

Of course, as evidence accumulates, people will eventually adjust their theory accordingly, but that process often occurs unconsciously; unlike scientists, people don’t actively review their models (Kuhn).

With information currently flowing from all directions, critical thinking is more needed than ever. But thinking like a scientist is an acquired skill, and a difficult one at that. And if you want to become a peak learner, you have no choice but to develop that skill.

The best first step you can take in that direction is to set your ego aside and ask yourself: “What would show me I’m wrong?”

The Path from Belief to Knowledge: 5 Levels of Certainty

how to think like a scientist

An old friend of mine recently told me that video games are harmful for my kids’ brain. When I asked him why he thought that, he didn’t bring up some scientific data or research. Instead, he pointed to an acquaintance of ours whose kids are gifted and guess what? They never play video games.

I was flabbergasted.

How can a university-educated man show so little critical thinking and make such unbridled inference? Of course, I quickly made him admit that a ton of other variables could play a role here. And even if a correlation existed, as any college freshman knows, it wouldn’t imply causation.

This story highlights one important fact about belief and knowledge.

As Gary Marcus shows in Kluge, humans often believe first and think later, rather than the other way around. In other words, once we decide that something is true (for whatever reason), we’ll look for reasons to support that belief. The conclusion comes before the premises.

This is a fascinating topic, which I’ll explore in a future post, but today I want to talk about the truth. No less.

How can we make sure that A causes B? How do I know if video games will really damage my kids?

Here are 5 degrees of certainty.

  1. Anecdotes. People just love anecdotal evidence (ex: this cured my brother-in-law), because it’s vivid and personal. But understand this, it’s the weakest kind of proof you can offer.
  2. Experts’ opinion. Experts’ knowledge is more comprehensive, but it often suffers from biases.
  3. Empirical research. This is where beliefs start becoming knowledge, but its reliability level greatly varies due to the presence or not of controls (variables and groups) and peer review.
  4. Meta-analysis. When findings of several independent studies point in the same direction, your claim rests on a solid foundation.
  5. Mega-analysis. When meta-analyses say the same thing, this is as good as it gets. A good example is Hattie’s Visible Learning, which is a synthesis of 800 meta-analyses including 80 million students.

As a peak learner, assessing the validity of new data and current beliefs should become a reflex. Using the 5 levels of certainty presented here can be an excellent start.