Leave it to Jon Stewart and Stephen Colbert (in an Entertainment Weekly interview) to discuss the human factors of this information overload (emphasis mine):

ENTERTAINMENT WEEKLY: You guys regularly make a mockery of the 24-hour news networks. Do you see anything good about the format?

[snip]


STEPHEN COLBERT: There’s not more news now than there was when we were kids. There’s the same amount from when it was just Cronkite. And the easiest way to fill it is to have someone’s opinion on it. Then you have an opposite opinion, and then you have a mishmash of fact and opinion, and you leave it the least informed you can possibly be.

STEWART: We’ve got three financial networks on all day. The bottom falls out of the credit market, and they were all running around. On CNBC I saw a guy talking to eight people in [eight different onscreen] boxes, and they were all like, ”I don’t know!” It’d be like if Hurricane Ike hit, and you put on the Weather Channel, and they were yelling, ”I don’t know what the f— is going on! I’m getting wet and it’s windy and I don’t know why and it’s making me sad! Maybe the president could come down and put up some sort of windscreen?” By being on 24 hours a day, you begin to not be able to tell what’s salient anymore.

Not being able to tell what’s salient anymore. Amongst all the e-mail and blogs and 24-hour cable news chatter, we can’t tell what’s salient anymore. Googling the term “information overload” gets around 2 million hits, and it’s the new buzzword used to describe the phenomenon of people who can’t manage their e-mail, websites, or other information sources. This is new - within the past decade for most people - and they just can’t cope with it.

The computer scientists’ answer is, of course, technology based. Build better software that can help you condense the information. Better spam filters, RSS feeds to bring information to you, and the list goes on. Yes, the problem of information overload was created by software, so software should adapt. But what about the human? Information isn’t going away; people need to adapt to and learn how to manage this information.

Clay Shirky, a web 2.0 guru, recently gave a wonderful talk on information filtering called “It’s Not Information Overload. It’s Filter Failure.” Think about that: it’s not information overload, but a failure of information filtering. People need to learn to better filter the information coming into their brains and decide how best to act on the most relevant stuff.

This gets into the heart of psychology: how do brains pay attention? How can we teach adults to use that knowledge in the real world, and how do we give children the skills to cope with it later? In fact, are the youth of today better equipped to handle all this information? What makes them so? Coping mechanisms? A different brain organization? This all falls into a research area that needs more effort: the psychology of information management. It’ll be huge.

Neuroscience, however, has not progressed far enough to accurately read someone’s mind as to whether they are lying or telling the truth. However, one Indian researcher has used his neuroscience methodology in a murder case in India, and evidence gained from his brain scans were one of the cornerstones of the guilty verdict and life sentence of the defendant.

From the article:

For years, scientists have peered into the brain and sought to identify deception. They have shot infrared beams through liars’ heads, placed them in giant magnetic resonance imaging machines and used scanners to track their eyeballs. Since the Sept. 11 attacks, the United States has plowed money into brain-based lie detection in the hope of producing more fruitful counterterrorism investigations.

The technologies, generally regarded as promising but unproved, have yet to be widely accepted as evidence — except in India, where in recent years judges have begun to admit brain scans. But it was only in June, in a murder case in Pune, in Maharashtra State, that a judge explicitly cited a scan as proof that the suspect’s brain held “experiential knowledge” about the crime that only the killer could possess, sentencing her to life in prison.

This leads to huge ethical implications about the use of this technology. Worse yet, this methodology hasn’t even been reviewed by his peers in neuroscience, so no questions have been raised about how valid this technique is at all, let alone whether it should be used as a primary determination of guilt. Questions such as these have prompted the formation of the Neuroethics Society, a group of concerned neuroscientists who hope to set policy and explore issues with reading someone’s mind.

Hopefully this would never hold up in a U.S. Court, but I’m waiting for it to show up in an episode of Law & Order.

This process has slight variations across consoles, but one feature I found interesting was how the different wireless controllers indicated which Player they were. Back in the days of wired controllers, if a controller was plugged into Port 1, that controller would be Player 1. Today, it’s assigned based on the order each controller is turned on. The interesting differences between video game consoles (Wii, XBox 360, and the PlayStation 3) come in how the controller displays this information.

On the Wii controller, it’s shocking simple. There are four lights, arranged left to right. The light that is on indicates what Player number you are, and the leftmost light is Player 1.

On the XBox 360 controller, it’s not quite as easy. There are still four lights, but they’re arranged in a circle. Upper left indicates Player 1, and the order goes clockwise around the circle. Still intuitive, but not as immediately so as with the Wii.

The one neat feature is that this mapping is shown on the console itself, so anyone just looking at the console knows how many controllers are connected. This is not so on the Wii or the PlayStation 3.

Finally, the PlayStation 3. At first glance, you don’t see anything.

Then you tilt it up, and you see, similar to the Wii, a row of 4 lights.

Except that, from this angle, Player 1 is the rightmost light and Player 4 is the leftmost. This arrangement only makes sense when you’re looking at the controller from a different perspective.

And who in the world looks at their controller from this angle? Not cool, Sony.

Winner? WII! With the XBox 360 close behind.

The article illustrates how tough it is to teach evolution. Even teachers who strongly believe in evolution can’t just teach their students that “Evolution is science and the Bible is not.” All teachers must do what they can to have their students understand the material. This is harder than it sounds, as those students who are very religious may not only choose not to believe in evolution but also choose not to learn anything about it.

The teacher who is profiled in the article (David Campbell of Orange Park, FL) believes in evolution and truly cares that his students at least bring an open mind to the subject. As someone who has taught several classes, his story is inspiring. The content of my classes (cognitive psychology and introductory psychology) is certainly not as controversial as biology class is, but both classes do touch on evolution. I always wonder if anyone is rolling their eyes at me when I talk about it.

But Mr. Campbell truly epitomizes what teaching should be all about: even if students don’t believe in something, the goal is to get them to open their minds and try to understand it. Students should critically think about the material and integrate it into how they see the world.

That kind of thinking about teaching is music to my ears.

“Faith is not based on science,” Mr. Campbell said. “And science is not based on faith. I don’t expect you to ‘believe’ the scientific explanation of evolution that we’re going to talk about over the next few weeks.”
“But I do,” he added, “expect you to understand it.”

Nonetheless, I did get a nice surprise today: I found out that the journal Cognition posted a preprint of the article I have in press with them. I’ve already blogged about this research in a previous post, but now the article is available in its final form for everyone to see.

You can download a copy here.

There are several different reasons for why this is a bad marketing campaign. For example, fooling your customers and making them appear stupid (”You idiot, this is Vista!”) is not a good way to sell a product. Another reason includes the fact that Vista is already set up on this computer with reasonable specs, so any system incompatibilities or installation difficulties have been ironed out. Finally, customers get a 10 minute “demo” of Vista - that’s hardly enough time to make a judgment about an operating system. Wil Shipley put it best in his blog,

Vista is known for people initially liking it, then after a while discovering it’s not working for them, and “downgrading” to XP. This study has told us exactly what we already knew: that, initially, people like Vista.

There is one major psychological error in this ad that I have not seen discussed, though. People are being told that they are seeing a next-generation operating system, and their expectations are instantly set to be more prone to liking the product. This is similar to the New Yorkers going to a fancy restaurant and raving over the Pizza Hut pasta dishes. These people are being set up to like something because it’s fancy or next-generation. Therefore, they are more likely to be impressed.

I’ve actually blogged about research that has shown this effect in people by having them drink the same wines but telling them one is priced higher than another. Not only do people rate the pricier wine as better tasting, but the emotional and pleasure center of their brains are more active when they drink the pricier wine! It’s a deep-rooted effect, and Microsoft is taking full advantage of that here.

“As more journal issues came online, the articles referenced tended to be more recent, fewer journals and articles were cited, and more of the citations were to fewer journals and articles,” writes Evans, who analyzed the citation patterns of 34 million journal articles that went online between 1998 and 2005.

It’s an interesting hypothesis, and it makes some sense. The method I use for keeping up with research is to get e-mail alerts from the journals I read updating me with their new issues and sending me the Table of Contents. It is automatically sent, then I can scan the titles to find something interesting.

This has the benefit of keeping me up to speed on the most recent research, but does not let me find old research on a topic that may interest me. This the main points of the article, and that may be a shame. Literature reviews may just not be as thorough as they used to. Also, though, some sciences (such as cognitive psychology) have really exploded recently, and only the more current articles are the relevant ones. I tend to cite a few tried-and-true articles, but most of my literature review focuses on the recent stuff. I’m curious to see how it breaks down by the age of the field.

Still, food for thought.

I’m a big fan of Alton Brown. When it comes to cooking shows, I think his scientific approach is better than pretty much everything else on the Food Network. So, when I heard that he had helped General Electric design an oven, I had to check it out.

Brown consulted with the engineers who designed GE’s line of Trivection ovens. The company asked Brown to teach their engineers to cook, so that they would better understand the way their appliances are used. The ideas GE’s engineers learned in Brown’s classes lead to the combination of thermal, convection, and microwave energies to cook food faster.

So the engineers at GE were designing ovens when they didn’t really know how to cook? Are you kidding me? GE has been making ovens for how many decades, yet they only think now to bring in an amazing Food Scientist to teach the engineers to cook?

Lesson #1 of consumer product design: KNOW YOUR USER

Author Note: Even though I don’t own my own house, I love to cook and desperately want this oven.

1. We have a ton of data and because of how much information we can store (what Wired calls “The Petabyte Age”), we can always have it on hand.
2. The incredible amount of computing power we have allows us to sift through data and run every possible statistical test on it until something comes up significant.

From the article:

There is now a better way. Petabytes allow us to say: “Correlation is enough.” We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.

The author of the article, Chris Anderson, is not a scientist, and it shows. Researchers already get enough false correlations without running thousands of statistical tests - five or ten is often enough to find some significant correlation, let alone thousands.

What Mr. Anderson is proposing is a reversal of the scientific method. First, collect a bunch of data. Then, run thousands of statistical tests to see what correlated. Then, invent a theory to explain that correlation. It’s so painfully simplistic and shows such an utter lack of understanding about the way science is done that it’s laughable. In psychology, how do we know what data to collect? If we go about research atheoretically, then we would need to collect every possible piece of data about every person so that we can throw it at the computer to see what pans out. Without theory, there is no place to begin.

Sadly, even the editor-in-chief of Wired does not understand science well enough to write an informed article.

The DoD has put out a call for proposals for the development of an object recognition system for computers that obeys psychological principles. Object recognition is obviously important for humans, and as more robots are being used in place of humans, they should also be able to identify objects to aid in mission success. The project description sounds like a short review of the object recognition literature, in fact (emphasis added by me):

Recognizing and identifying an object from a video input turns out to be a very difficult problem. The problem stems from the fact that a single object can be viewed from an infinite number of ways. By rotating, obscuring, or scaling a single object, one can create multiple representations of an object - which makes the problem of matching the object to a database of objects very difficult. The problem expands exponentially when objects that need to be identified have never been viewed before. Combine these limitations with the wide variety of objects which might be identified, and the problem becomes intractable. One solution is to study and understand how human beings recognize objects in the real world and duplicate that functionality in a series of algorithms. Recent research (Tarr and Bulthoff, 1995) has indicated that humans use not one algorithm, but multiple algorithms for the task of object recognition - depending on the object being recognized and the situation at hand. Specifically, research has shown that people use template based algorithms (i.e. similar to the database matching algorithms described earlier) in addition to Geon based (Beiderman, 1995) algorithms and feature based algorithms.

First of all, 1995 counts as recent research? Sounds like some DoD scientists need to attend the Vision Sciences conference. Secondly, it is satisfying to see that the DoD believes that understanding how the human mind works is a big step in implementing human-like cognition in artificial systems.

This is similar to the field of biorobotics, where the understanding of how natural organisms work (say, a dolphin) can be applied to machines (say, a submarine). This makes a lot of sense, actually. Biological organisms are highly evolved - nature has done the work of choosing what works best. By studying what works best, we can use those principles in designing our own machines. It seems like a new principle in engineering, but it makes a lot of sense.