I previously talked about how scores on an IQ test are developed, and what they mean mathematically. Now, I’ll look at what they can mean for individuals.
IQ could be described as the BMI of the mind. Although both numbers can provide useful information for a typical mind or body, they should still be regarded with caution especially in an atypical mind or body. BMI is near-useless for athletes, who will often score as overweight or obese due to their increased muscle mass. Similarly, IQ measurements may be helpful to understand a neurotypical person in a familiar situation, but they are flawed for people with neurodevelopmental disorders, or people who are unfamiliar with standardised testing.
3) IQ tests cannot always measure someone’s ability accurately. Health conditions and neurological differences result in people having uneven patterns of ability, which confuse IQ tests.
The Intelligence Quotient- or IQ- is one of the most popular subjects in psychology. Yet despite us often using IQ as a shorthand for intelligence, and even using it to define others, misconceptions about IQ are often louder than explanations.
So how do IQ tests work, and what does an IQ score mean?
1) An IQ test does not directly measure your ability. It uses maths to estimate your ability in relation to other people.
This post is much later than intended, as I wasn’t able to watch all six episodes at the time and had to wait for reruns. Late enough, in fact, that the unfortunate news of its cancellation has already had its 15 minutes of angry tweets. So consider this a retrospective look at Season 10 rather than a live response. Also, spoiler warnings for the finalists and winner of Season 10.
Going into Season 10, I had been concerned about a few aspects of the show, such as the low profile of female team members, the robot reliability issues, and the focus on professionally-built robots. Rule changes ahead of Season 10 promised to bring in more diverse robots, and to counteract the dominance of spinners. So, how well did Season 10 live up to those promises?
Robots and Weapons
Episode One started well by introducing clusterbot The Swarm, built by Ian Watts of Team Big Brother fame. Clusterbots have often been failed experiments in previous series, mostly due to their weight limits and elimination rules. Clusterbots were either equally-sized pairs, or a near-heavyweight bot accompanied by a distraction minibot. As they were ruled out if either piece was immobilised, minibots were merely a liability, while paired bots were weaker than standard competitors without many corresponding advantages. However, due to advances in materials and weapons, The Swarm was made of five featherweight robots with individual working weapons. The Swarm could use four robots in each fight, and they would remain in if at least two robots (>40% by weight) were moving. This approach meant they could carry out the roles clusterbots were designed for, and generate tactical advantages like distractions and multiple angles of attack.
I was introduced to “The Two Cultures” during the first lecture of my scicomm MSc. When we were talking about scicomm history, “The Two Cultures” stood proudly on our timeline alongside documents which were fundamental to the field. So I wanted to read it for myself.
Originally “The Two Cultures” was a lecture, presented by scientist-turned-fiction-author C. P. Snow in 1959. Snow’s titular cultures were “people of the humanities and literature” and “people of the sciences”. In the lecture, Snow sketched out divisions between these cultures, with anecdotes from his experiences as a novelist amongst scientists and a scientist amongst literary intellectuals. He blamed this cultural divide on Britain’s education system, which forced people to specialise in one subject too early and prioritised humanities at the expense of science and engineering.
Books which ask the question “what’s wrong with our brains” are a current pop-psychology staple. Cordelia Fine’s A Mind of Its Own was ahead of this trend, as it was first published in 2005.
A Mind of Its Own explores some ways in which our brains don’t make sense, and the cognitive biases which funnel us down faulty mental shortcuts. The books starts with the bias equivalent of little white lies, detailing how almost all of us are biased to see things as a little easier, happier, and less flawed than they really are. From this gentle introduction, Fine talks us through the progressively larger mental failings discovered through social psychology studies.
I first became interested in reading Sapiens because of its polarising reviews; readers seemed divided over whether it was one of the greatest books in existence or one of the most pretentious. With my curiosity piqued, Sapiens jumped to the top of my to-buy list.
As I haven’t studied much biology or early history, I expected that Sapiens might be a challenging read. However, I was surprised by Yuval Harari’s clear writing style- Harari generally restricts his use of jargon, and uses conversational language rather than adding unnecessary complexity. The challenge in reading Sapiens comes from its ideas , not its communication.
“imagined orders are not evil conspiracies or useless mirages. Rather, they are the only way large numbers of humans can cooperate effectively”
“This is why today monogamous relationships and nuclear familes are the norm in the vast majority of cultures, why men and women tend to be possessive of their partners and children, and why even in modern states such as North Korea and Syria political authority passes from father to son” .
Although I’m both a science nerd and a video game fan, those interests don’t intersect often. Scientist characters in video games are often feared (or laughed at) from a distance, rather than being understandable or sympathetic. Worse, they are usually locked into two narrow roles:
The “Mad scientist” – a friendly yet distant and absent-minded tinkerer, whose inventions take on a life of their own or wind up as destructive rather than helpful.
The “Bad scientist”- a character who focuses entirely on their intellect and considers themselves superior to non-scientists. They can be obsessed with finishing their research or completing their next latest invention, regardless of its use or consequences. Many take utiliarianism to an extreme, seeing no problem with immoral or hurtful acts if they might achieve a greater good.