A study published last week in the British Medical Journal states simply that, “Childhood intelligence was inversely associated with all major causes of death.”
The study focused on some 65,000 men and women who took the Scottish Mental Survey in 1947 at age 11. Those students are now 79 years old and many of them have passed away. By and large, those who scored lower on the test in 1947 were more likely to have died – from all causes — than those who registered higher scores.
This is certainly not the first study to link intelligence with longevity. (Click here, here, and here, for instance). But it raises again a fundamental question: why would smarter people live longer? There seem to be at least two competing hypotheses:
Hypothesis A: More intelligent people make better decisions about their health care, diet, exercise, etc. and — as a result — live longer.
Hypothesis B: whatever it is that makes people more intelligent also makes them healthier. Researchers, led by Ian Deary, call this hypothesis system integrity. Essentially, the theory suggests that a healthy system generates numerous positive outcomes, including greater intelligence and longer life. The theory derives from a field of study known as cognitive epidemiology, which studies the relationships between intelligence and health.
Hypothesis A focuses on judgment and decision making as causal factors. There’s an intermediate step between intelligence and longevity. Hypothesis B is more direct – the same factor causes both intelligence and longevity. There is no need for an intermediate cause.
The debate is oddly similar to the association between attractiveness and success. Sociologists have long noted that more attractive people also tend to be more successful. Researchers generally assumed that the halo effect caused the association. People judged attractive people to be more capable in other domains and thus provided them more opportunities to succeed. This is similar to our Hypothesis A – the result depends on (other people’s) judgment and there is an intermediate step between cause and effect.
Yet a recent study of Tour de France riders tested the notion that attractiveness and success might have a common cause. Researchers rated the attractiveness of the riders and compared the rankings to race results. They found that more attractive riders finished in higher positions in the race. Clearly, success in the Tour de France does not depend on the halo effect so, perhaps, that which causes the riders to be attractive may also cause them to be better racers.
And what about the relationship between intelligence and longevity? Could the two variables have a single, common cause? Perhaps the best study so far was published in the International Journal Of Epidemiology last year. The researchers looked at various twin registries and compared IQ tests with mortality. The study found a small (but statistically significant) relationship between IQ and longevity. In other words, the smarter twin lived longer. Though the effects are small, the researchers conclude, “The association between intelligence and lifespan is mostly genetic.”
Are they right? I’m not (yet) convinced. Though significant, the statistical relationship is very small with r = 0.12. As noted elsewhere, variance is explained by the square of r. So in this study, IQ explains only 1.44% (0.12 x 0.12 x 100) of the variance in longevity. That seems like weak evidence to conclude that the relationship is “mostly genetic”.
Still, we have some interesting research paths to follow up on. If the theory of system integrity is correct, it could predict a whole host of relationships, not just IQ and longevity. Attractiveness could also be a useful variable to study. Perhaps there’s a social aspect to it as well. Perhaps people who are healthy and intelligent also have a larger social circle (see also Dunbar’s number). Perhaps they’re more altruistic. Perhaps they are more symmetric. Ultimately, we may find that a whole range of variables depend partially – or perhaps mainly – on genetics.
We were in Barcelona last month with our two favorite architects, Julia and Elliot. Of course, we wanted to see the many buildings created by another favorite architect, Antoni Gaudi. A friend also clued us in that, if we wanted to see some really good architecture, we shouldn’t miss the Hospital de Sant Pau.
I enjoy discovering cities but had never thought about visiting hospitals as part of a tourism agenda. Hospitals seem very functional and efficient and somewhat drab. They also look pretty much alike whether you’re in Denver or Paris or Bangkok. They seem to be built for the benefit of the medical staff rather than the patients.
So I was very surprised to find that the Hospital de Sant Pau contained some of the most beautiful buildings I’ve ever seen. The hospital dates to 1401 but the major complex that we visited consisted of about a dozen buildings constructed between 1901 and 1930. The Catalan architect Lluis Doménech I Montaner designed the entire campus, which today claims to be the largest art nouveau site in Europe. The campus is like a fairy tale – every which way you turn reveals something new and stimulating. (My photo above barely does it justice).
(The art nouveau campus was a working hospital until 2009 when it was replaced by a newer hospital – also an architectural gem – just beside it. The art nouveau campus is now a museum and cultural heritage site).
As I wandered about the campus, I thought if I were sick, this is the kind of place I would want to be. It’s beautiful and inspiring. That led me to a different question: Can the architecture of a hospital affect the health of its patients? The answer seems to be: Yes, it can.
The earliest paper I found on healing and architecture was a 1984 study by Roger Ulrich published in Science magazine. The title summarizes the findings nicely: “View Through a Window May Influence Recovery from Surgery.” Ulrich studied the records of patients who had gall bladder surgery in a Philadelphia hospital between 1972 and 1981.
Ulrich matched patients based on whether they had a view of trees out the window or a view of a brick wall. He studied only those patients who had had surgery between May and October “…because the tress have foliage during those months.” He also matched the pairs based on variables such as age, gender, smoking status, etc. As much as possible, everything was equal except the view.
And the results? Patients “…with the tree view had shorter postoperative hospital stays, had fewer negative evaluative comments from nurses, took fewer moderate and strong analgesic doses, and had slightly lower scores for minor postsurgical complications.”
Ulrich’s study (and others like it) has led to a school of thought called evidence-based design. Amber Bauer, writing in Cancer.Net, notes, “Like its cousin, evidence-based medicine, evidence-based design relies on research and data to create physical spaces that will help achieve the best possible outcome.”
Bauer cites Dr. Ellen Fisher, the Dean of the New York School of Interior Design, “An environment designed using the principles of evidence-based design can improve the patient experience and enable patients to heal faster, and better.” Among other things, Dr. Fisher suggests, “A view to the outdoors and nature is very important to healing.” It’s Ulrich redux.
I’ll write more about evidence-based design and the impact of architecture on healing in the coming weeks. In the meantime, put a vase full of fresh flowers beside your bed. You’ll feel better in the morning.
The presidential campaign is about to lurch into high gear and the lying is flying. Or is it? Are the candidates lying or are they bullshitting us? The two concepts are related but not the same.
Let’s take an example from Donald Trump. Trump says that he will build a wall along our southern border and make Mexico pay for it. Many neutral observers claim that it would be prohibitively expensive to build a useful (that is, impenetrable) wall along the entire border. They also suggest that it’s ludicrous to believe that Mexico would pay for it. So is Trump lying or is he bullshitting?
To answer the question, I dug out an essay by the Princeton philosopher, Harry Frankfurt. Originally published in 1986, the essay is aptly tilted, On Bullshit. * Frankfurt lays out the essential differences between lying and bullshit (with a side trip through humbug).
Frankfurt argues that both bullshit and lying are deceptive – but they’re deceptive in different ways. The liar aims to deceive us about reality and “the way things are.” A liar might say that he has a million dollars when he’s actually flat broke. A bullshitter, on the other hand, aims to deceive us about his purpose. Frankfurt writes, “His eye is not on the facts at all…. He does not care whether the things he says describe reality correctly. He just picks them out, or makes them up, to suit his purpose.”
Further, a liar knows the truth and seeks to conceal it. He opposes the truth. By contrast, a bullshitter may or may not know what the truth is – and certainly doesn’t care. Indeed, he may even be telling the truth. Making a true statement or a false statement is beside the point. As Frankfurt notes, “…the truth … of his statements is of no central interest to him.”
A liar is under numerous constraints. He knows the truth and, “…to invent an effective lie, he must design his falsehood under the guidance of that truth.” A bullshitter has no such constraints. He can make everything up, including the context and the backstory. Instead of making a statement about reality, he invents his own reality.
Indeed, the bullshitter avoids the “authority of the truth” altogether. Frankfurt writes that, “He pays no attention to [the truth] at all. By virtue of this, bullshit is a greater enemy of the truth than lies are.”
So is Trump lying or bullshitting about the wall? I’m guessing that he’s bullshitting. He doesn’t seem to care whether his statement is true or false. That’s beside the point. He just makes stuff up to suit his purpose.
So, if making a true statement (or a false one, for that matter), is beside the point, what is his hidden agenda? I think there are two:
So how can Trump’s opponents – Johnson and Clinton – best deal with his bullshitting? To the maximum extent possible, they should ignore him. Don’t get caught up in the trap of making him the center of attention. When a journalist asks about an outrageous Trump statement, don’t take the bait. Just say something along the lines of, “Well, we all know that he’s a world-class bullshitter. Let’s talk about something more useful.”
* Frankfurts’ essay was originally published in The Raritan Quarterly Review in 1986. It was then republished in 2005 as a small book. I’ve depended on the version that’s found here.
When we think of innovation, we often think of bright young people working in creatively organized offices while pushing the envelope and thinking outside the box. It’s fun, exciting, challenging, and maybe even a little bit sexy. It’s the kind of job we all want.
But what about the rest of the world?
Much of the innovation that I have observed takes place in rather mundane places and involves rather ordinary business or social processes. It’s the act of taking some thing (or some process), observing how it’s used, and designing a better way to do it. If we think about innovation only as the process of creating something entirely new, we’ll miss many, many opportunities to change the world for the better.
Take our refrigerator, for instance.
Suellen and I were recently on vacation and asked a very responsible young woman named Alyssa to house sit for us. As soon as we left, our refrigerator stopped working. Alyssa organized a service call, coordinated with the repairman, and had the refrigerator repaired in a jiffy. From our perspective, it was virtually painless (except for the bill, of course).
When we arrived back home, we also got a pleasant surprise. Alyssa had completely reorganized the interior space of the refrigerator. She had examined the food items we keep and adjusted shelves and drawers to fit our lifestyle. She used the space much more efficiently and made frequently used items more readily available. It’s now simpler and easier to store and retrieve our food.
Why hadn’t we organized our fridge more effectively? We never thought about it. It’s one of those ordinary, mundane appliances that doesn’t attract our attention. It’s not leading edge, or state of the art, or sexy. Though we use it every day, we never considered how we might improve it. When the refrigerator arrived in our house, we simply put our food in it. We didn’t think about rearranging shelves or drawers to improve utility and efficiency. It took Alyssa to apply design thinking to an ordinary, everyday item.
We describe some things as “wallpaper” because they recede into the background. We don’t need to pay much attention to them. We don’t consider them as opportunities to create and innovate. But we interact with our wallpaper everyday. That makes even small innovations meaningful and impactful. If you want to be an innovator, spend more time on wallpaper and less time thinking outside the box.
Do men and women think differently? If they do, who should develop artificial intelligence? As we develop AI, should we target “feminine” intelligence or “masculine” intelligence? Do we have enough imagination to create a non-gendered intelligence? What would that look like?
First of all, do the genders think differently? According to Scientific American, our brains are wired differently. As you know, our brains have two hemispheres. Male brains have more connections within each hemisphere as compared to female brains. By contrast, female brains have more connections between hemispheres.
Men, on average, are better at connecting the front of the brain with the back of the brain while women are better at connecting left and right hemispheres. How do these differences influence our behavior? According to the article, “…male brains may be optimized for motor skills, and female brains may be optimized for combining analytical and intuitive thinking.”
Women and men also have different proportions of white and gray matter in their brains. (Click here). Gray matter is “…primarily associated with processing and cognition…” while white matter handles connectivity. The two genders are the same (on average) in general intelligence, so the differences in the gray/white mix suggest that there are two different ways to get to the same result. (Click here). Women seem to do better at integrating information and with language skills in general. Men seem to do better with “local processing” tasks like mathematics.
Do differences in function drive the difference in structure or vice-versa? Hard to tell. Men have a higher percentage of white matter and also have somewhat larger brains compared to women. Perhaps men need more white matter to make connections over longer distances in their larger brains. Women have smaller heads and may need less white matter to make the necessary connections — just like a smaller house would need less electrical wire to connect everything. Thus, a larger proportion of the female brain can be given over to gray matter.
So men and women think differently. That’s not such a surprise. As we look ahead to artificial intelligence, which model should we choose? Should we emphasize language skills, similar to the female brain? Or local processing skills, similar to the male brain? Should we emphasize processing power or information integration?
Perhaps we could do both, but I wonder how realistic that is. I try to imagine what it would be like to think as a woman but I find it difficult to wrap my head around the concept. As a feminist might say, I just don’t get it. I have to imagine that a woman trying to think like a man would encounter similar difficulties.
Perhaps the best way to develop AI would involve mixed teams of men and women. Each gender could contribute what it does best. But that’s not what’s happening today. As Jack Clark points out, “Artificial Intelligence Has A “Sea of Dudes’ Problem”. Clark is mainly writing about data sets, which developers use to teach machines about the world. If men choose all the data sets, the resulting artificial intelligence will be biased in the same ways that men are. Yet male developers of AI outnumber females by a margin of about eight-to-one. Without more women, we run the risk of creating male chauvinist machines. I can just hear my women friends saying, “Oh my God, no!”