Until a few months ago, Nate Silver was a nerd hero. If you’ve never heard of him, perhaps you’ve heard of sabermetrics (or you’ve seen Moneyball, a movie about sabermetrics). Well, Silver is best known for applying sabermetric models to the study of politics, especially presidential races. The accuracy of Silver’s predictions for the 2008 and 2012 elections earned him accolades and fame.

Silver runs FiveThirtyEight.com, a blog about number crunching and prediction covering most aspects of life including sports and politics. The folks at FiveThirtyEight are basically odds makers and people tend to misunderstand what their products really mean. That’s what this post is about.

Before Tuesday’s election, Silver took quite a bit of criticism for his low certainty in a Clinton win relative to other prediction models. Focusing on one piece in particular that kicked up a lot of dust, HuffPo’s Ryan Grim actually accused Silver of “…Unskewing Polls — All Of Them — In Trump’s Direction”, injecting too much subjective bias into his model. Silver fought back, noting that the way his model weights polls is based on empirical data, but lots of people didn’t buy it.

Silver’s final model gave Clinton a 71.4% chance of winning, but when Grim published his criticism, the number was closer to 65%. This was in stark contrast to others, many of whom gave her odds in the 90s. The final prediction of the New York Times was 85% and the HuffPo model that Grim was so confident in put her at 98%. You might be thinking that Grim is feeling pretty low right now, but I’m not so sure since he hedged his criticisms with:

If [Silver is] right, though, it was just a good guess…

Well, one could argue that nobody was right (except Allan Lichtman, who correctly predicted Trump using only 13 ‘key’ factors, some of which are highly subjective). But that doesn’t mean that everybody was wrong, either, despite the prediction-bashing that I’ve been seeing in my Facebook feed since the election. In Grim’s criticism, he said some things that made me question if he understood the very thing he was writing about and those comments also provide some insight into why people are so upset with Silver post-election.

First, let’s talk very briefly about what these prediction models do. Now, keep in mind that I’m going to oversimplify the process a lot for several reasons, but the details are not particularly relevant to my points.

Most of these models use an aggregate of polls to come up with a prediction. Some, like Silver’s model, include other information (e.g., economic factors) and/or they weight each poll based on its past performance. Silver’s model is highly complex, including a measure of inter-dependency between states. It is in the weighting of polls that Grim’s problem with Silver’s model lies; he felt that Silver’s weights were too subjective and biased toward a Trump win. One Facebook comment I saw even suggested that 538 purposefully made the election look close in order to create anxiety that would keep people clicking on their site.

But here’s what people seem to misunderstand the most about this process. A 55% chance of winning doesn’t necessarily mean “a close race” in terms of votes. Yes, those things go hand-in-hand, but you need to separate them for a deeper understanding. Most people see that 65% probability and their brains translate that number into frequencies — they imagine 65% of people voting for Clinton, which is of course not what the numbers mean. But even if your brain corrects that part of it, you may not be able to shake the concept completely. More on that in a bit.

Most of the modern prediction models do not spit out a victor. The Huffington Post, for example, did not say “Clinton will win”. Well, okay, Grim did:

If you want to put your faith in the numbers, you can relax. She’s got this.

but the model’s output was “Clinton has a 98% chance of winning”. It’s not actually a prediction, but an estimate of the probability that an event will occur. Now, if you have ever read any of my notes on The Odds Must Be Crazy or listened to a segment of it on Skepticality, you know that low-odds events happen all the time. And, quite frankly, the nearly 30% that Silver gave Trump is not even low.

But my point about this is that it is not accurate to say that a prediction like this was “wrong”. I might use that word in the case of HuffPo, whose 98% confidence in Clinton was misplaced, but even then, they gave Trump a 2% chance. That Trump won doesn’t make their prediction “wrong”. They predicted a 2% chance of a Trump win and that’s what happened. That’s how odds work. And in our evaluation of those processes, we have to fight our human brains that want to put things into boxes in irrational ways. [EDIT: If you roll a die, you have only a one-in-six chance of rolling a 6. So if you roll it and a six comes up, will you now say that prediction was wrong? That wouldn’t make sense, right?]

Grim should have known better, but he repeatedly suggested that he didn’t understand the difference between providing odds and picking a winner. He also seemed to think that the election outcome would tell us whose models were “right” — he said so three times in his piece.

Here’s the thing: the outcome of the election doesn’t even tell us for sure which model(s) was better. There just isn’t enough data, which is ironically one of the reasons the models appear to have failed (again, they didn’t ‘fail’).

Yet people are cursing the models and there’s a well-known psychological phenomenon to explain why. Human beings are notoriously bad at understanding and applying information about probability and concepts of uncertainty.

In general, when people hear there is a 10% chance of rain they expect drizzle and when they hear there is a 85% chance of rain, they expect a downpour. But that’s not what the prediction means. An 85% chance of rain means it might not rain, but if I were you, I’d take an umbrella.

Silver’s model also changed as often as new information came in, usually many times during a single day, which does not help people to understand it. At this point, political prediction is more complex than weather prediction, and humans have a difficult time fully understanding that. For example, when asked:

If there is a 55% chance of rain on Saturday and a 75% chance of rain on Sunday, what is the chance that it will rain at some point during the weekend?

you might be tempted to average the two and say 65%. However, the probability of rain over the weekend cannot be less than the probability of rain on a given day, so it must be at least 75%. Or you might be tempted to add them together; there is a famous story of the weatherman who said, “There’s a 50% chance of rain on Saturday and a 50% chance on Sunday, so there’s a 100% chance it will rain this weekend. For those curious, the answer is actually ~88%.

The bottom line is that Nate Silver’s model spit out a 71% chance of a Clinton win. The fact that she did not win is not a failure of the model. It’s just what happened. He also said there was a 10.5% chance that she would win the popular vote but lose in the electoral college. That’s not an insignificant probability, so it’s not a ‘fluke’ that it happened.

I have also seen many people, both before and after the election, suggest that these models are not scientific. I disagree. What makes something a science — hell, what makes it good or bad science — is not its ability to uncover truths or predict outcomes. What makes it a science (and the difference between good and bad science) is the method used.

Now all of this said, there are good reasons that we should not bet on these models for presidential races. The biggest reason is that we simply do not have enough information.

Models are built using information about what has happened in the past. That is true for everything from baseball to weather. And we simply do not have enough real world data about presidential races because:

• The outcomes for presidential races are nearly dichotomous, at least the one measure that most people are interested in: who will win.
• We only have one trial/case every four years.
• The farther back in time we go, the less input info (e.g., polls and economic indicators). While some of this information can be filled in using various techniques such as bootstrapping, the less raw data we have, the less reliable the model will be.

These models will get better as time goes on, but with a race only every four years, it will be a very, very slow process of perfecting. And even then there will always be times in which the predicted underdog wins. Always. Because even a 1% chance is a chance.

But the absolute most important reason these models didn’t tell us that Trump would win? The polls were wrong. You’ve heard “Garbage In, Garbage Out”? That’s what happened here. Most of the polls were just plain wrong (and that’s a whole other topic of discussion I won’t get into here). If the numbers you put into a good model are not accurate, the output is going to be inaccurate. Silver accounted for some of the reliability of the polls, but only in relation to each other, and very few appear to have been accurate.

Finally, even the best models will always have a hard time accounting for the complexity of human behavior. I often felt the futility of it all as a researcher; as soon as we’ve figured out something, it changes. We do keep trying and we do make progress, but I think there will always be surprises. Humans will always be at least a little unpredictable.

This election was unprecedented in a myriad of ways. Very little about it was “normal”. It shouldn’t be surprising that the outcome wasn’t within the expected range.

I said it before the election and I will say it again now: I have more faith in Nate Silver’s model than in any other. The approach, the math has proven itself (no pun intended) in other applications in which there is a lot more data (e.g., baseball). But no model can overcome the problem of too little data.

One more thing before I go. You might notice that I have made no statement about the value of these predictions. I’ve heard and read a lot of comments, both before and after the election, suggesting that sites like 538 provide only useless information. On the one hand, I agree. I think that we love these sites because human beings just love information. It makes us feel more in control if we can predict outcomes, even if we are helpless to change them. On the other hand, they seem to be useful in sports and other applications, so I have to believe that they are useful in politics somehow. I don’t know, though; I’m not a politician. And thank goodness for that.

I really, really hate infographics.

Really.

They’re worse than memes. Well, I guess technically they are memes. They are notoriously inaccurate. They are usually agenda-driven and often spin facts to the point of wrongness. But mostly I just see them as click bait.

I have less disdain for listicles, but they sometimes bug me, too.

Yes, babies sleep a lot. Bet you didn’t know that!
/sarcasm

The only source is a link. The link goes to–surprise, surprise–an infographic.

Ugh.

Actually, it goes to an infographic that was re-posted from another site where I assume it originated (embedded below).

The graphic itself cites sources at the bottom, so I dug in. But before I talk about the source material, let’s take a look at the list.

1. We can only dream about faces we have already seen, whether we actively remember them or not.

Um, what? As opposed to faces that we haven’t seen?

No, we can’t “see” the faces of real people we’ve never seen, but we are perfectly capable of making up faces in our dreams. People we make up are certainly people we’ve never seen.

2. When dolphins sleep, only half their brain shuts down. The other half stays awake to help with breathing cycles.

True. Dolphins and whales sleep one hemisphere at a time.

3. Men have dreams about other men 70% of the time. But women dream about women and men equally.

I haven’t seen this in any of my textbooks, nor have I read any studies that confirm this. I’m skeptical, but it’s one of those factoids that, if true, I’d think “so what?”

4. While you are sleeping your body recharges, your cells repair themselves, and your body releases important hormones.

True.

5. Parasomnia is a type of sleep disorder that makes you do unnatural movements despite being asleep. Crimes committed on parasomnia include: sleep driving, writing bad cheques, murder, child molesting and sexual assault.

True (although they’re talking about a specific type of parasomnia) and FASCINATING. When I taught introductory psychology, we spent the most class time on parasomnias because it’s so fascinating. Share your sleepwalking stories in the comments because I never tire of them.

6. 12% of people dream only in black and white. This number used to be higher but since the advent of color television, more people dream in color than before.

Another bit I’ve never heard. I wouldn’t be surprised, but I also don’t know why it matters.

7. Dreaming is normal. People who do not dream generally have personality disorders.

This is bullshit. First, dreaming isn’t just normal, but it’s something that everyone does. People who say that they don’t dream simply don’t remember their dreams.

And no, failing to remember your dreams absolutely does not mean that you have a personality disorder.

No. Nuh uh. Not remotely.

8. Sleep positions may determine your personality.

Um, no. No “may” about it. This is about as true as saying your favorite color determines your personality.

9. 1 in 4 married couples sleep in separate beds.

Again, I don’t recall ever hearing about or reading a statistic on this, but 1 in 4 seems awfully high to me. I wouldn’t be terribly surprised. There are lots of reasons for it. But 1 in 4? I’m skeptical.

10. British soldiers were the first to develop a method in staying up 36 hours without sleep. When fatigued, they put on special visors that emulated the brightness of a sunrise and it woke them up.

I can’t confirm this, but it’s plausible.

11. Longest sleeping mammals are koalas (22 hours) and the shortest sleeping are giraffes (1.9 hours taken in 5-10 minute sessions).

May be true. But seriously, who cares?

12. You need different amounts of sleep depending on your age. Babies need the most (16 hours) and people over 65 need the least (6 hours).

Although it is true that age matters when it comes to sleep requirements, there is a lot of variability among individuals and the recommendations have changed in recent years. In general, the older you are, the less sleep you probably need, but most Americans are at least a little sleep deprived.

13. You’ll die from sleep deprivation before food deprivation. It takes 2 weeks to starve, but 10 days without sleep can kill you.

I have to wonder where this one came from.

First, the term “sleep deprivation” includes too little sleep, not just no sleep.

Sleep deprivation can have very serious health effects. However, one does not usually die from lack of sleep. It’s sort of like dying from holding your breath. You can’t. You’ll eventually pass out and your body will resume breathing without your will to do so.

One can certainly die from the health problems that sleep deprivation contributes to or may even cause, but in 10 days? Not likely. There aren’t a whole lot of documented cases of total deprivation, so I can’t even guess where this number came from.

At most I think that we can say that sleep is necessary for good health. Might even say that you don’t want to go without it, but if you do, you just mind find yourself in a situation in which you have no longer have a choice.

14. Blind people can still see images in dreams. Those born blind experience dreams involving emotion, sound, smell, and touch instead of sight.

Well, of course. Our brain activity when dreaming is very similar to waking states. The biggest difference is that the information isn’t coming in through our senses. It makes sense that the experience would mimic the life our brain has developed to experience.

15. Within 5 minutes of waking up, 50% of your dream is forgotten. Within 10 minutes, 90% is gone.

This is just made up.

16. 1 out of 50 teenagers still wet their beds.

I looked at about a dozen sources and all put the number at 1-2 in 100, so I think 1 in 50 is the highest in the range of estimates. But the statement is a bit misleading in that it suggests that it’s a chronic problem for that many teens. The estimate includes those who experience a bed wetting incident once in their teen years, which is probably the majority of cases.

So that’s it. A few fun facts, some boring and unverified factoids, and some outright bits of bullshit. That’s what happens when you regurgitate something that was regurgitated by someone else using something that was copied from something else that was created by someone who basically made stuff up.

Now let’s take a look at the ‘citations’.

The source list for the infographic is printed on the bottom of the graphic itself, so I dug in. There are 16 citations and 16 list items, but they don’t appear to be related to one another in a one-on-one fashion at least.

The first source is a site called “MEDPAGE TODAY”. It’s not a bad piece, but I can’t find an item on the infographic that corresponds to what’s discussed on the page.

The next three sources resulted in error pages. The second of these defunct links is to–another surprise–a LISTICLE. Someone was kind enough to post this one in a forum, so we can see the original content. Unfortunately, no citations were included.

The next item, sleepapnea.org, documented only the main page of the website. I cannot tell which “facts” were gleaned from this source.

Item number 6 is a Slate piece about sleeping with your dog. There is nothing in the infographic or the listicle about sleeping with your dog.

The next three are news articles about parasomnia. Two are dead-ends. So three links to support one item on the list and two are outdated (giving the author the benefit of the doubt).

The next link is incomplete, so there’s no way to access it, and the one that follows that one is the same as link number 2.

The next link might be the jackpot. It’s a site cataloging “interesting facts about dreams”. It lists 99 items from seven sources. One of those sources is specific and the rest are for-the-masses books like “The Big Book of Dreams”.

Then there are a few more dead ends and a final page that doesn’t appear to correspond to anything on the list.

Okay, so now we have some idea of where this stuff came from (don’t say it), but not much.

From Visually.

A skeptical friend sent me an interesting link this week. The headline makes the bold claim that a study suggests that people who like black coffee are more likely to be psychopaths. I’m sure you can guess my initial reaction: skepticism.

So let’s look at the research.

First, the choice of singling out black coffee is journalistic bullshit. The research is not so specific. Instead, the researchers categorized foods by taste and included coffee as a member of the “bitter” group.

Now, I think that’s a questionable categorization. Some coffee, especially strong coffee, can be bitter. However, when I hear or read the word “coffee”, I don’t think “bitter”. And that is directly related to the biggest problem with the study itself: the method was survey, not taste test. In other words, we don’t know if people truly preferred the tastes themselves. Self-reports of such things are problematic, especially when the food categorizations themselves are arguable.

What the researchers did: an online survey asked participants to rate their preferences for a list of food items, then to complete a number of scales such as personality inventories and measures of malevolent traits. What they found: a strong correlation of preference for sweet foods with agreeableness. Slightly weaker, but robust correlations of preference for bitter foods with psychopathy and “everyday sadism”.

So, in general, what they found is that agreeable people tend to prefer sweet foods more and bitter foods less than disagreeable people. And those who score higher on measures of psychopathy and sadism tend to prefer bitter foods more than those who score low on those measures.

The study itself isn’t bad and the findings are interesting, but it’s very, very limited due to the method.

There are a number of possible explanations for these findings. Taste preferences come from both genetics (our taste buds vary) and habits (what we eat shapes what we like to eat). Likewise, personality traits are like most human traits in that they are partly determined by genetics. It is possible that the small correlation seen here is at least partly a clustering of genetic traits.

It’s also possible that years of munching on radishes makes people cranky and disagreeable.

It’s also possible that rating foods primed people to associate those foods with personality traits (e.g., the authors note the stereotype of bitter foods being associated with bitter people), thereby affecting the outcomes of some personality measures–something the study authors fully acknowledge.

The authors also admit to another limitation of the self-report measure:

…in preferring bitter tasting foods more than less sadistic people, everyday sadists may perceive them as positive due to their potential to cause distaste [as opposed to their own preference], that is, to cause a negative experience in other people.

However, the findings are consistent with other research. For example, one study linked PROP sensitivity (Supertasters) with unpleasant emotional reactions to film clips depicting aggression. PROP Supertasters have a genetic predisposition to experience phenylthiocarbamide (PTC) as bitter, whereas most people find it tasteless. It is a bit of a stretch to conclude from this finding that aversion to bitterness is associated with stronger empathy, but it’s an interesting finding nonetheless.

Still, I have to wonder–and pardon my language here, but–who the fuck cares?

It’s not as if this research suggests that you should avoid sharing a table with someone at Starbucks simply because they order the Sumatra blend instead of a pumpkin spice latte or a mocha cappuccino. It just doesn’t.

Sagioglou C, & Greitemeyer T (2015). Individual differences in bitter taste preferences are associated with antisocial personality traits. Appetite, 96, 299-308 PMID: 26431683

Note: This post also appears on Insight, the official blog of the Skeptic Society.

A few months ago I wrote about the psychology of vaccine denial. In the post I discussed two publications, one of which (Nyhan, et al.) found:

Corrective information reduced misperceptions about the vaccine/autism link but nonetheless decreased intent to vaccinate among parents who had the least favorable attitudes toward vaccines. Moreover, images of children who have MMR and a narrative about a child who had measles actually increased beliefs in serious vaccine side effects.

None of the interventions increased parents’ intent to vaccinate.

Then, a couple of weeks ago, a friend sent me a link to this piece describing research which seems to contradict that finding. The authors (Horne, et al.) concluded that

…highlighting factual information about the dangers of communicable diseases can positively impact people’s attitudes to vaccination.

These two conclusions seem to contract each other. Which should we believe?

Many times this question comes down to the quality of the research. In this case, I believe these are both fairly well-designed studies. One, however, is more precise than the other in several ways. I believe that precision highlights the complexity of the issue as well as giving us a better idea of the direction that vaccine promotion should take.

Let’s look at the differences in sampling and method between the two studies.

The Horne study sampled 315 men and women. In the Nyhan study, the final sample was 1759 parents with children under the age of 18. In most research, 315 subjects is more than sufficient and more is not always better. The danger in larger samples is to find effects that are statistically significant, but not practically significant. However, when comparing conflicting findings, it is best to bet on the side of the larger sample.

Then there’s the question of limiting the study to parents. Although Horne compared parents to non-parents and found no significant differences in attitudes or effects, noise is noise. These two groups of people vary, and the attitudes of non-parents are not particularly relevant. Limiting the study to parents would give me more confidence in the robustness of the findings and their application in real-world activism.

Still, if both are reasonably well-designed studies by competent researchers, the end results should not contradict each other. So there must be more going on. And there is.

For one thing, this is a great example of how complex social sciences are. We should never make policy decisions based on a single study and this demonstrates why. Replication, especially with variants of measures and materials, is essential to learning the best methods of persuasion.

For another, these studies differ in more than just sampling techniques. The Horne study is much simpler and, in fact, oversimplifies. Nyhan, et al. included three outcome measures, each addressing a specific attitude:

1. The belief that vaccines cause autism.
2. Perceived risk of side effects from vaccines.
3. Intent to vaccinate one’s child/children.

By contrast, the Horne study involved a single measure which combined answers to five specific questions (such as “I intend to vaccinate my child.” and “Doctors would not recommend vaccines if they were unsafe.” to come up with a more vague “vaccine attitudes” scale. Even if the answers to these questions are highly correlated, how interventions affect those answers may be very different. They certainly were in the Nyhan study. And if “effective” is defined as increasing intent to vaccinate, then the Horne study does not answer the question it purports to answer. Personally, I am more interested in intent to vaccinate than I am in any other aspect of “vaccine attitudes”, so the Nyhan study’s findings are much more meaningful to me.

In general, it is best to measure outcomes of interest as specifically as possible, but of course the more outcomes a researcher studies, the larger the sample must be.

Finally, and perhaps the most important difference between these two studies, is the timing of the experimental portion. When measuring the effect of treatments or interventions on attitudes, an experiment should be spaced over time. A researcher will measure the attitude, then wait before applying a treatment and measuring the attitude again. When polled about attitudes, those attitudes are brought to mind. This affects our receptiveness to relevant information in complex ways, ways that vary based on a number of other factors such as the strengths of our attitudes and the way the questions are worded. However, allowing subjects to forget about the initial survey provides a more accurate picture of how people confronted with information in the real world may respond to it.

The Horne experiment was conducted a day after the initial screening while the Nyhan experiment occurred about two weeks after initial screening.

My conclusion? I think the issue is complex, but while Horne’s findings appear easier to understand, Nyhan’s findings are more specific, answer more interesting questions, and can be more easily viewed within the framework of well-established knowledge about human decision-making (e.g., cognitive dissonance).

That, and we need more research if we are to develop effective ways of increasing vaccination rates.

Horne Z, Powell D, Hummel JE, & Holyoak KJ (2015). Countering antivaccination attitudes. Proceedings of the National Academy of Sciences of the United States of America, 112 (33), 10321-4 PMID: 26240325

Nyhan B, Reifler J, Richey S, & Freed GL (2014). Effective messages in vaccine promotion: a randomized trial. Pediatrics, 133 (4) PMID: 24590751

Today the Huff Post Weird News section reports that a man in Glasgow, Scotland has seen the face of God (the savior, to be precise) in a bathroom door. Of an Ikea.

My last report on sightings of Our Lord and Savior was about 7 months ago, so I thought it was time for an update. Pareidolia is one of my favorite topics, as its readers may know from my my many previous posts on the subject. If you don’t know what pareidolia is, that last link (this one) covers the definition. I have also written a classroom ‘module’ for the JREF on the topic. It can be downloaded for free here (the pdf is quite large; the site is here: http://archive.randi.org/site/index.php/jref-news/2208-new-jref-in-the-classroom-lessons.html).

I have a fairly extensive collection of images (under “Fun For Everyone” on the right) going back a few years, but new sightings shouldn’t be ignored and here are a few that I have missed and a few more that have appeared since my last report…

Jesus Shops at Walmart

In 2001, a couple in South Carolina found Jesus. On their Walmart receipt. One of them said, “…who else has the power to put their face on a check-out receipt but Jesus?”

It doesn’t look like Jesus to me. To me he looks like a sad Luke Danes on Gilmore girls.

Crabby Jesus

John Canfield found Mr. Crabs while on a trip with his family in Everett, Washington in 2012.

Gawker has suggested that the image looks more like Osama Bin Laden than Jesus. I have to agree, although I have never pictured Bin Laden sad, just angry. This guy looks sad. Like Jesus would be, if we are to believe the Bible.

Stingray Jesus

Also in 2012, Jesus appeared on the back of a cownose stingray. Guess it was an ocean phase.

Erika Sheldt, who photographed the creature, is catholic, but mildly skeptical. She didn’t think it was a message from God, but she noted the coincidence that Easter was around the corner.

“I just kind of thought it looked like a bearded homeless man,” Scheldt told IslandPacket.com “But when I posted pictures on Instagram, one of my friends was like, ‘That’s Jesus.’ And I was like, ‘Oh, my God. You’re right.'”

Jesus Poop

In 2013 Jesus came out of a bird and landed on the windshield of an Ohio man’s car.

Apparently, MSN thought it looked more like a dog wearing a wig. I’m not sure what to think.
 

God’s Signature

More recently, in 2014, a woman recovering from chemotherapy thinks that God was reassuring her when she found his name in the hair regrowing at the top of her head.

Cliff Jesus

And last month a tourist visiting Ireland snapped a picture of Jesus in the side of the Cliffs of Moher. Odd that nobody noticed him there before.
 

Sometimes I wish that I didn’t have a nagging conscience so that I could make millions selling crap at a 6000% profit just by claiming that it does something it doesn’t. Unfortunately, I’d be embarrassed by the first skeptic to challenge me. Oh, and then there’s that pesky fact that I’d be scamming people and promoting pseudoscience.

Anyway, there seems to be no end to the things you can convince people that some token item embedded in $.08 worth of rubber can do.

Last week I stumbled over Sharkbanz.

Screenshot of the Sharkbanz website. The band can be worn on the wrist or ankle.

Sharkbanz are rubber jewelry similar to a Fitbit Flex. Instead of a motion sensor, however, Sharkbanz contain magnets. The company’s founders claim that these magnets repel sharks.

Yes, you read that right. Magnets in a rubber bracelet repel sharks.

How does it work? Well, let’s look at what they claim.

Screenshot of the Sharkbanz website, explaining the technology.

Summary:

• Uses magnets
• No batteries, no electricity, no moving parts
• Rated for 200 meters. What happens when you dive below that? Does the magnet implode or the rubber erode?
• For ages 5 and up. So if you’re 4, you’re some Shark’s dinner I guess, because for some reason it is just not safe for those under 5. By the way, choking hazard warnings are usually for children under 3, so this arbitrary value makes little sense.

The idea is that sharks are annoyed or frightened by the electromagnetic field emitted by the magnet because of their keen electroreception capabilities.

Okay, so I’m not a shark expert, nor am I a physicist or an engineer. For this reason, I’m going to tread a little lightly on the examination of whether the idea is plausible and focus on whether they have demonstrated that the things work. But I will admit to a bit of skepticism given the knowledge I do have. Some of my thoughts:

• I don’t know that the differences between magnetic fields, electrical impulses, and electromagnetic fields matter, but the owners of Sharkbanz imply that any electromagnetic energy is disturbing to sharks. If that were true, then light would bother them. Clearly, just as the human eye only senses electromagnetic energy within a range of wavelengths, sharks’ electroreceptors are limited in range. Yet the website says very little about what research and testing they have done to determine whether sharks even sense their magnets. The most that I can find is a link to a list of tested species on the website of a group called SharkDefense. There is zero detail provided in this list and no citations to peer-reviewed literature about these tests. The site does cite some literature in a section which explains the theory (which, again, I am unqualified to adequately challenge, but it looks mostly correct), but provides no reason to believe that the idea because sharks have electroreception, they will be repelled by this specific small magnet wrapped in a rubber bracelet. In fact, take a look at the size of the magnet the claim to have tested (again, no citation for this): Click here
• Sharkbanz presents no reason that a man-eating shark would have for avoiding the electromagnetic field emitted by their magnets. Just because sharks have electroreceptors doesn’t mean that some random magnet is going to affect their behavior. Perhaps if they made an effort to produce some magnet that emitted a field that mimicked the energy put out by a predator it might make sense, but do bull sharks even have predators? I don’t know, but I’m skeptical.
• Then there’s the fact that the magnet is encased in rubber.

So if you’re an expert on sharks or the physics that apply here, please feel free to comment with your 2 cents, but I’m going to focus on their “scientific testing”.

Sharkbanz are a fun, easy way to add peace of mind to the everyday ocean swim, surf, or snorkel, but make no mistake: the science is real.

Bull*cough*.

This technology has been tested extensively on over ten of the most common predatory shark species…

On the website, there are several references to videos that supposedly show this “extensive testing”. However, most of the videos I’ve found when I click those links are media interviews in which the owners say very little. There are certainly no published articles from peer-reviewed journals, not even some about electroreceptors in sharks that don’t really support their claims. They don’t even try to fake it. What I did find are a few unconvincing videos which show a couple of guys dropping a buoy into the water and watching a fish or two swim away from it.

In this video, the only one that claims to show testing, the voiceover claims that they tied a bracelet to a buoy “in order to be scientific” as well as safe before throwing it into the water with reef sharks. Then, he put two shark bands on his ankles and got into the water which, he claims, induced “obvious repellent reactions when the sharks approached the bands on my feet”. Finally, they “decided to get more of the controlled type of testing” by tying the bracelets around lead weights, which he claims produced “really astonishing repellent behavior”.

Well, I’m sorry guys, but scientists everywhere are laughing at you. They are giving you the virtual equivalent of “there, there” pats on the head and “aren’t you cute? Do you want to be a scientist when you grow up?” Except that given the voice on this video belongs to Dr. Patrick Rice, Senior Marine Biologist at SharkDefense, you’ll have a hard time convincing me that you don’t know quite well that you’re not scientifically testing anything. This is a marketing video and nothing more.

A very short, far-from-exhaustive list of plausible alternative explanations for what the video shows:

• fish in the shots are not darting away from the bracelet, but rather toward food that was just dropped in the water
• cherry-picking shots in which fish are swimming away
• fish examined the item (or the person) and immediately recognized that it wasn’t food (or preferred food)
• fish avoid things hanging from buoys or anything that looks like the item (rather than being repelled by the magnet)

Can you guess what a good, scientific test of this product might entail? A double-blind, placebo controlled study. In other words, you’d want to simulate the movement of a human being as much as possible. You’d want to stop chumming the water after you’ve introduced the treatment (the bracelet). Most of all, you would need to compare the fishes’ behavior toward a Sharkbanz bracelet to their behavior toward a placebo–a bracelet without the magnet. Also, you would need the people recording and judging the behavior to be blind to the condition (they cannot know whether the fish are reacting to an “active” bracelet or a placebo). Without that comparison all of these tests are worthless.

In sum, these guys are charging $60 for heavy rubber bracelet that people will buy because it claims to protect from shark attacks–an extremely rare event with a high fear factor.

In the U.S., it takes a lot of time and money to get a group like this to stop making ridiculous claims, but I have to wonder how this company is allowed to market and sell in Australia, given what happened with Power Balance.

When I saw the Washington Post headline “Internet searches are convincing us we’re smarter than we really are” in my Facebook feed yesterday, I was only a little bit skeptical. Most readers are probably aware that I have been studying self-esteem and narcissism for some time, particularly the aspect of overconfidence. Over confidence prevents learning and interferes with rationality, so it is important to understand its sources.

It seems to be a rare moment these days when I can point to a mainstream media piece reporting a finding from the field of psychology without mistakes ranging from a minor distortion of the implications to facts so incorrect that they’ve reported the opposite of what was found. I’m thankful to say that this time the Washington Post’s piece is quite good, although the headline doesn’t quite fit.

The research is not flawless, but the authors address most of the limitations by running a series of experiments. The overall large sample size and a number of controls and checks compensate for the fact that it was conducted online. It’s not perfect, but few studies in this field are. It is just one series of experiments, so any conclusions drawn should be tentative.

All of that said, the findings are interesting. What they found: people who were asked to use the internet to find or confirm their answers to a series of questions gave, on average, higher ratings of their ability to answer questions in a different domain than those who were asked not to consult the internet. This finding held across experiments and the researchers were able to ferret out some details, including:

• This was an increase in confidence among internet users, not a decrease in confidence among those not allowed to consult the internet.
• The increase was not due to access to information or even the use of the internet to get the information. It was the act of searching for that information that caused the increase in confidence.
• Participants were not considering their access to knowledge in their responses about ability, but their knowledge. They appeared to be conflating shared knowledge (the internet) with personal knowledge (what’s in their heads).

In one experiment, half of the participants were asked to search for specific web pages (e.g., a scientificamerican.com page about dimples on golf balls) while the other half received the information on those pages. This shows that the difference in confidence cannot be attributed to the knowledge itself, but the act of using the internet to search for it. In another, participants did not rate their ability to answer the subsequent questions, but instead predicted their brain activity while doing so. We cannot attribute the difference in confidence levels to assumptions that access to information would be available. People really believe they possess the knowledge.

Overconfidence is one characteristic in a list of those associated with narcissism, so it is useful to look at these findings in relation to narcissism in general, especially considering the historical context. The world wide web’s emergence is relatively recent. In The Narcissism Epidemic, Twenge and Campbell document a sharp increase in narcissism over the past 30-40 years. Although they attribute that increase to changes in culture, tracing it back to a best-selling self-help book called I’m Okay, You’re Okay that was popular in the early 1970s, cultural trends of entitlement can be seen decades earlier in “you deserve it” advertising approaches. Certainly the self-esteem movement of the 80s and 90s moved it along. So far, the internet’s blame has been limited to the vanity aspect of narcissism. There has been quite a bit of research suggesting that social media users are, on average, more narcissistic than others, but such correlations are confounded by factors of age, gender, and others difficult to tease out. It would also be extremely difficult to determine the direction of cause.

The experiments are limited to internet search and the specific characteristic of overconfidence, but they do not suffer from the same problems of confounding as those related to social media use. These findings suggest that searching the internet actually causes an increase in one’s self-assessed knowledge. Perhaps people think of the internet as an extension of the self.

The bottom line, I think, is that overconfidence clearly has many sources. Given this research, it appears that we can count the existence of Google™ among them.

Fisher M, Goddu MK, & Keil FC (2015). Searching for Explanations: How the Internet Inflates Estimates of Internal Knowledge. Journal of experimental psychology. General PMID: 25822461

I don’t know if this could really be called “new”, but it’s a form of anti-intellectualism that usually goes unnoticed. I find it particularly frustrating because I so often see it often among people who claim to respect knowledge, education, and expertise. It is an ironic lack of respect for that same knowledge, education, and expertise.

The Psychology of Vaccine Denial

I’m sure you’re wondering what I’m talking about here, so I will get to the point. Rebecca Watson wrote a short piece, published in Skeptical Inquirer Online, that seems to question the potential effectiveness of a bill currently in the works in California which would eliminate non-medical exemptions for vaccination requirements to attend public school. I say “seems to” because it’s actually unclear.

My main criticism of the piece itself is not that much of what she says is blatantly wrong, but that the piece doesn’t go anywhere and the research cited doesn’t support the weak, barely identifiable thesis at all. It is disjointed and doesn’t flow well. The transition from the topic of education to that of the bill is a huge leap. Her conclusion makes little sense given the rest of the piece. It’s only a few paragraphs (very short for SI), but in those few paragraphs she manages to treat some important research shallowly and selectively, missing the valuable knowledge that a nuanced look at the findings would provide. I won’t make that mistake here.

She cites two articles, the first mention is this:

Researchers Brendan Nyhan and Jason Reifler have spent the past few years conducting studies that seem specifically designed to depress science communicators. Last year, they published a paper in which they showed that correcting myths about the MMR vaccination actually decreased a parent’s intention to vaccinate.

What’s missing is that this was only true among those “with the least favorable vaccine attitudes”.

Even showing participants images of sick children was counterproductive, increasing their belief that vaccines are connected with autism.

Yes, but the “even” part is very misleading. Emotional pleas such as describing disease risks and showing images of or telling stories about children with diseases all increased this belief, but education refuting a link successfully reduced that same belief. 

From the article:

“Autism correction” is most effective in reducing agreement with the autism misperception. Strong agreement declines from a predicted probability of 8.9% to 5.1% (and likewise for other response options). By contrast, the predicted probability of strong agreement increases to 12.6% for “Disease images.” Similarly, the predicted probability of believing serious side effects from MMR are very likely increased from 7.7% among control subjects to 13.8% in the “Disease narrative” condition.

This combination of results tells us a lot about what is happening when people are confronted with different strategies, yet nothing Watson wrote went beyond the few bits she selected from the abstract.

For the second citation, Watson writes:

Last month, they conducted a similar test using the common belief that the flu vaccine causes the flu. The results were the same: correcting the misconception only decreased the subjects’ self-reported intention to get vaccinated.

But this is what the article’s abstract actually says:

Corrective information adapted from the Centers for Disease Control and Prevention (CDC) website significantly reduced belief in the myth that the flu vaccine can give you the flu as well as concerns about its safety. However, the correction also significantly reduced intent to vaccinate among respondents with high levels of concern about vaccine side effects – a response that was not observed among those with low levels of concern.

After reading the article, I can tell you that the education measures worked across the board–in every concern level, educating people about the vaccine significantly reduced belief in the myth. However, those with the most concern about side effects dug in when it came to intent to vaccinate–not everybody, those with the most concern. (BTW, they didn’t conduct the test “last month”.)

These are finer points, but they are far from trivial. The details are what tell us what’s going on. I would not expect someone without an education in psychology to recognize the implications, although Abbie Smith, who reviewed the first study in a blog post last year, managed quite a bit of insight (which she wrote about with care, describing the findings in detail and not speculating beyond the what happened in the study).

And this is where the anti-intellectualism is most apparent in Rebecca’s piece:

At this point, we can only guess as to the reason why this happens.

No, Rebecca, at this point, you can only guess. So, if you don’t know why it happens, then nobody does?

To anyone who has studied decision making, reason, attention, or just about any area of social psychology for a few years, this statement is absurd. The pattern of results found in these two studies is exactly what I would have predicted. We have decades of research telling us why this happens.

Some brief explanations are provided right there in the articles’ discussion sections. The authors mention loss framing, danger priming, and other effects.

For a much more in-depth look, I will ask you to read Mistakes Were Made, But Not By Me by Carol Tavris and Elliot Aronson. The nutshell is that people do all sorts of mental gymnastics to reduce something we call cognitive dissonance–a tension between contradictory attitudes or an attitude and a behavior–in ways that allow us to avoid changing the behavior or strongly-held attitude.

In this case, when those holding strong anti-vaccine attitudes accept that their expressed reasons (e.g., autism) for those attitudes are invalid, they simply find another reason to maintain the attitude (e.g., side effects).

People are invested in the choice not to vaccinate, not the reason for the choice.

This would be especially true for those who have acted on that choice. The alternative is to accept that they have put their children at risk for no reason.

So, although Watson is not incorrect in reporting that some approaches backfired, she failed to see or report the nuances in these findings that tell us why and what we might do about it. And there’s more that I would not expect a layperson to recognize.

These studies only measured attitudes immediately following education–education that worked in dispelling myths about those vaccines. What I would like to see is follow up research examining attitudes months or years afterward. What happens, for example, when people are educated, then given time to change their attitudes without threat to their egos and identities? I predict that a large portion of them will change their minds. Much of the resistance is probably rooted in ego threat. Giving people time and space may allow them to save face while changing the attitude to reduce the cognitive dissonance associated with the conflicting ideas.

Furthermore, in these laboratory studies, parents are asked to report their attitudes prior to the exposure to materials. This is a form of declaration, committing people to a viewpoint that they then feel compelled to defend. That’s not what happens in real world situations.

So her next paragraph…

Do people hold their anti-vaccination beliefs so deeply that correcting a misconception only encourages them to spend time digging around for another reason to hate vaccines? If so, then the answer may be to address the underlying reasons for the belief instead of the scientific facts.

How are these two sentences connected? That people find other reasons to maintain a behavior or attitude is not evidence that there is some hidden reason. And expressed reasons are precisely what what are addressed in the studies she cited. She’s come full-circle with nothing at all to show for it.

Cognitive dissonance and the unconscious strategies people use to reduce it are human nature. We cannot “address” human nature so easily. We can educate people about human nature and how it does not always lead us to the best decisions to meet our goals (and by “we”, I mean people who have studied human nature, such as social scientists with years of training and knowledge), but of course that’s a much broader goal. Increasing vaccination rates is a public safety issue that must be addressed with more urgency and specificity.

Finally, all of this came down to this one guess of hers:

For instance, perhaps the belief is rooted in a fear of government control over individual choices.

Um, seriously? This came out of nowhere as if she just didn’t have an ending to her story, or perhaps couldn’t come up with a good segue to get to the one thing that she meant to talk about: the California bill that may eliminate personal belief exemptions for unvaccinated kids to attend public schools. Rebecca’s logic is that if fear of vaccine harm is actually rooted in fear of government control, then the bill might make matters worse.

This is a huge leap. For one thing, she cites no research showing that fear of government control has anything to do with the average vaccine denier’s choices. Even if it did, the very research she cited shows that removing all government involvement in vaccination would not change intent to vaccinate (those with the most concern would simply find another thing to worry about). But more importantly, she begs the question:

But will the law (which already exists in West Virginia and Mississippi) only encourage the anti-government anti-vaccine activists to band together and renew their efforts to fight for their freedom to harm innocent kids?

Well, now, why not take a few minutes and do a little research to find out how laws affect vaccine rates?

According to Pew,  “states with the strictest immunization laws tend to have the highest immunization rates” (they have a nice graph sorted by vaccination rates and Mississippi is at the top).

Not surprising. People tend to follow the law, and if they want to send their kids to public schools, they must vaccinate. But does this change attitudes? I think a lot of people would say that they don’t care, as long as it changes the behavior, but I think we can all agree that changing the attitude would be best.

And stricter immunization laws will change attitudes and beliefs about vaccines. How do I know this? Simple: cognitive dissonance.

One early finding in studies of cognitive dissonance theory is that it is often easier for people to change an attitude than it is to change a behavior. We have seen numerous examples of this, not only on laboratory studies, but in real-world behaviors such as smoking and exercise habits. Once invested in a behavior, the attitude follows as a matter of reducing the tension because we are invested in the behavior, not the reason for the behavior.

In this case, the biggest thing currently in the way of attitude change is the personal belief exception. Remove that, and behaviors must change. Once behaviors change, attitudes will follow, especially with education, which will pave the way for attitude change by giving parents a way to engage in the behavior (of sending their child to public school) without dissonance. This is especially true when the parent has not declared their attitude prior to education, as they do in a laboratory study.

What the research cited suggests, when included in the context of decades of psychological research about the relationships among attitudes, behaviors, and values, is that a combination of stricter laws and education correcting myths about vaccines is not only highly likely to increase vaccination rates, it will also decrease perceptions of risk of harm from vaccines.  Giving people facts does indeed work. It works to educate people about facts. If you want them to change their attitudes, however, you need to dig a little bit deeper.

To head off what will surely be a the first thing Watson’s supporters will point out: what’s the difference we came to the same conclusion? Her argument is “I think we should try X because nothing else seems to work” and mine is that X is what the science suggests. Only one of these is a valid argument. The ends do not justify the means.

The New Anti-Intellectualism

The implication that just anyone can write about this stuff with authority is the kind of anti-intellectualism I’m referring to in the title.

And before you assume that I am saying that skeptics have nothing to say, think again. Pseudoscience and fraud, the core of skepticism, are not science. Skepticism is a field in and of itself, very distinct from science. It includes scientific thinking and it benefits, as every field does, from the products of science, but it is not science.

This piece is poorly researched, weak, and reads like a book report that someone started, put away, then suddenly realized it was due and wrote the rest while the other kids were watching a film in class. A big part of that is the fact that Watson simply does not know the field, something she has demonstrated repeatedly. Yet, knowing her track record in this area, CFI decided to commission and publish this. The poor quality of the piece is a side effect of overconfidence coupled with a lack of expertise, but it further points to a huge drop in standards by SI Online. Not that SI hasn’t published some misses in the past, but this sad little piece is just one of many lesser-quality articles recently appearing there, including one in which the author describes party/county fair psychics as harmless fun.

So, am I saying journalists and other non-scientists (e.g., skeptics) should never write about science? No, I am not.

It is fine for non-experts to write on topics when they do so with great care. I cannot stress this enough.

A non-expert can do a great job when they do a proper amount of research by talking with experts (rather than spending a few minutes Googling and picking sentences out of abstracts that one believes supports one’s already-formed opinion), when they discuss experiments and studies accurately without omitting important details, when they properly credit the sources of ideas and opinions, when they follow what they find rather than start with a conclusion and attempt to support it, and when they refrain from stating their personal opinions as authoritative. Watson rarely appears to do any of those things when she writes about science. She simply writes and speaks with an air of confidence and that seems to be enough to make some people think that she is clever and knowledgeable.

Good science journalism allows the researchers’ voices to be heard, not the author’s. Think about that.

I have written before about the dangers and hypocrisy of speaking and writing on topics which require expertise one does not have (here, here, and here, for example–two of which are also about Rebecca Watson). It’s actually a topic that has received a lot of coverage, from Massimo Pigliucci’s talk at TAM8 to articles by Daniel Loxton (yes, I’ve linked to them both before and for good reason). I expect to see this kind of thing all over the blogosphere, but to see it on the Skeptical Inquirer’s site is disheartening, especially on the heels of other pieces that fall far below their old standards.

As I stated in this post more than three years ago, we (skeptics in general) criticize Jenny McCarthy and Bill Maher because they don’t have the expertise to make the statements they make. We criticize “the Food Babe” and many, many others for the same reasons. We tell people not to take medical advice from a Playboy Bunny and a talk show host, yet we (skeptics again) give a microphone to a blogger to talk about the psychology of vaccine denial simply because she calls herself “Skepchick”? How is this justified?

Now, I am perfectly aware that many people don’t believe that psychology is a science or that expertise in the field is actually a thing. I deal with that kind of anti-intellectualism every day. But I am still stunned when I see such blatant disregard for it among people and organizations who wave the flag of “listen to the experts” when it suits their purposes. CFI, you should be ashamed.

By now, you’ve either wondered just what color the dress is or you’re living under a rock in the middle of a deserted island with no internet and the first thing you chose to read when you were back online is my blog. Weird, but awesome.

The last few days have seen a flurry of education about our visual system and I won’t duplicate too many efforts here. But I would like to talk a bit about the illusion and the way the internet exploded with pseudoexplanations and other BS as a result. I’m going to spend a little more time on what this illusion does NOT mean.

First, the dress…

http://swiked.tumblr.com/post/ 112073818575/guys-please-help-me-is-this-dress-white-and

When the ugly white and gold dress first appeared in my feed last Thursday, I had the same reaction that I’m sure many of you did: this is a hoax.

I quickly determined that it was indeed real, immediately saw additional pictures of the blue and black dress, both in an online store and on the woman who wore it (BTW, as ugly as that dress is, she manages to pull it off), and started to think about what was happening. I fully accepted that the dress was actually blue and black, but I couldn’t perceive it that way in that photograph to save my life. It was fascinating!

At this point I should note that I have studied color vision and color perception since I was an undergrad. My first real experiment involved asking people to rate the facial expressions of expressionless faces drawn on backgrounds of different colors. The purpose of the study was to test the claims made… well, everywhere… that colors affect people’s emotions. I continued that line of research for more than 10 years and won several awards for it. My master’s thesis was titled “The Physiological Effects of Color on Human Emotion”. A summary of many years’ worth of findings is available here.

I also taught cognitive psychology (a portion of which involves sensation and perception) for several years and supervised a number of student experiments about color, some with very interesting results. What I am trying to say is that I have a good handle on what is causing the illusion. I was still mesmerized.

The illusion itself is not what I find so fascinating. What’s fascinating, and what caused it to blow up the internet, are the individual differences. Most polls only offered two possibilities, with about 70% claiming to see it as white and gold, 30% as blue and black, but I counted about 1 in 5 in my Facebook feed who said that it was sometimes white/gold and sometimes blue/black. I can recreate very similar illusions quickly using a basic drawing program, but illusions tend to be fairly universal. While we see some differences across cultures, mostly due to differing environments, I don’t think that I have ever seen people in the same household, looking at the same picture, perceive an image so differently and in a stable manner. Yet my youngest son saw only blue and black while the rest of the house saw white and gold. When it comes to ambiguous figures, such as the famous figure/ground image below, most people can perceive the image either way and reverse it at will. Of those who said that they sometimes saw the dress as white/gold and sometimes as blue/black, nobody I talked to said that they could switch the perception at will.

Do you see faces or a vase?

On Friday, post after post tumbled through my Facebook feed. The first posts I saw picked apart the image, extracting information about the color of the pixels. Well, that stuff is mostly irrelevant. Perception is much, much more than the simple sensation of the color of light hitting our eyes. The color of the dress in the photograph does not tell us the color of the dress (which we know from other sources) or why some people perceive the dress’s color as it is (blue/black) and some so differently (white/gold). Both, btw, are considered illusions since neither matches the pixels in the image, but nobody should perceive the dress as the pixel colors because they wouldn’t perceive it that way in person. Confused yet?

Next came all of the explanations. Some claimed to show us how we could perceive the dress differently, replete with not-quite-right explanations for why it’s happening. Yet I have met nobody who could force a different perception, at least not for more than a fraction of a second, much less using the methods suggested. Those doctored images just looked like doctored images to me. They did not change my perception that the dress was white with gold lace. Many gave some pretty bad explanations (those who saw blue/black do not have better color constancy). Some suggested that one’s sleep cycle could explain individual differences (it can’t). This guy says:

Your eyes have retinas, the things that let you interpret color. There’s rods, round things, and cones that stick out, which is what gives your eye a textured appearance in the colored part.

And that, my friends, is how a little bit of education can lead to dangerous things like deciding not to vaccinate your children. He has either skimmed Wikipedia’s entry on color theory or was half asleep through a half hour lecture in an intro psych class and now thinks he understands how eyes work.

And as of this writing that bit of BS has been RTed over eight thousand times.

My favorite bogus explanation: Mood. The color you see depends on your mood. That’s the one my kids heard the most during school that day.

And the jokes. Oh, the jokes. Some, like XKCD, were 10 kinds of awesome (make sure you read the alt text, and if you don’t get it, read this post). Others were not so funny.

Then, late Friday evening, after I’d taken a bit of a break from “the dress”, someone sent me this video and all hell broke loose. The video content isn’t relevant; it’s just a fun look at how to correct the photo. What is relevant is that suddenly the dress was BLUE AND BLACK. Not brown, not like an altered photo of a white and gold dress, but blue and black–the same royal blue that is in the other photos. I thought maybe the image in the video had been altered, so I pulled up a blog post with the original picture and it looked the same. I Googled “what color is this dress” and looked at the images. I saw a sea of blue/black dresses with one white/gold one in the corner. It looked to me like someone had replaced most of the pictures on the internet!

Since then the dress color switches for me. I usually see it as white with gold lace, but now and again it’s deep blue with black lace.

And I know why, yet I am helpless to control it.

And over the weekend, I started to see about-the-dress-here’s-some-more-BS-about-color-vision posts. Business Insider, which is becoming more and more like Buzzfeed every day, posted a number of pieces of varying quality. One of them had the unfortunate title, “No one could see the color blue until modern times”. The piece itself isn’t bad. It speculates about the effect that naming colors has on perceiving colors. There is some evidence that cultures which fail to distinguish between blue and green perceive fewer distinct hues in that area of the spectrum, but to extract from that the idea that human beings didn’t “see” blue until they had a name for it? Well, that’s a preposterous leap that’s actually a bit silly. Why would they name something that didn’t exist?

Another which has been picking up steam in the last couple of days is this incredibly bad piece on linkedin which makes the bold claim that 25% of people have a 4th cone that allows them to “see colors as they are”. It’s a very strange thing to claim–to “see colors as they are”, since colors are simply the brain’s interpretation of wavelengths of light. In that sense, colors aren’t. They kind of don’t exist. The article talks about tetrachromacy, which is a real phenomenon, but the author basically made up the rest. I cannot fully explain color vision (or vision in general) in a blog post, but I can tell you this is wrong. Also, tetrachromacy is extremely rare, at least in functional form, and her “test” is totally bogus. The author calls herself “Prof. Diana Derval, expert in neuromarketing”. I know that it’s trendy to slap “neuro” onto everything, but really? Neuromarketing? Ugh. I first saw and responded to the piece on Facebook Sunday night and by Monday afternoon Snopes had covered it (they did a nice job, too, but they usually do), but that didn’t keep it from going viral.

So what is going on with the dress?

Well, several pieces have explained it with relative accuracy. I said I wouldn’t duplicate those efforts and I won’t. I will instead recommend that you read/watch more than one of those links, take a look at the additional illusions that I created below, and internalize this perfect summation:

“It’s an illusion,” said [David] Whitney. “But everything is an illusion.”

And that’s the long and short of it. What we “see” is never, ever exactly what’s out there in the world. It’s our brain’s best interpretation of what’s out there. We are amazingly good at it, but it’s not perfect and perfection is not possible.

The grey bar in the middle is a solid color. We only perceive it as darker on one side than the other because of contrast with the surrounding color.

Although one bird appears to be more orange than the other, they are identical.

In 1987 I worked as a receptionist in the real estate lending office of a savings and loan. A savings and loan, for those too young to remember, is a bit like a bank which invests most of it’s money in mortgages (think Bailey Building and Loan). Shortly after I was hired the whole savings and loan industry collapsed, mostly due to questionable commercial lending practices and other bad investments. My office was one of the last to close, so for months we had plenty of time for office chatter.

In our office of about 20 people, and me, about half visited a psychic on a regular basis. They saw the same woman. I often heard my co-workers going on and on about what Sally (I don’t remember her name) told them and when they would go to see her next. I tried a few times to talk to them about psychics. I told them about all of my failed experiments with Zenar cards as a kid. I told them about my experience in high school, when a man came to my psychology class, did a few tricks, then told us he wasn’t psychic, but a magician. I told them about the challenge the Bay Area Skeptics and James Randi (and probably others) offered to anyone who could demonstrate psychic ability.

The looks I got gave me chills. These people were not simply unconvinced. They hated me for what I was saying.

And what they said in response was hurtful. I was just a kid (I was almost, but not quite, 21) with no experience in the world. What did I know? I’d learn.

Fast forward a few years to around 1992. At that time I was working at a software company and was fairly well-respected in my position as an administrator. I called most of my coworkers friends and the company had low turnover, so we had known each other for some time. But I had no idea I was among so many believers.

A picture of me (blown out by the flash), at the Monte Carlo party, before I saw the psychic.

The company threw a daytime party that year in an empty space next door. The theme was “Monte Carlo” and we all got dressed up, imbibed, ate, and played blackjack for a few hours. And visited the psychic.

I never understood why the person who planned the party included a psychic. I didn’t realize that psychics were part of the Monte Carlo culture. But there she was. A psychic. At our Monte Carlo office party. And several friends could not stop talking about it.

“Don’t you want to hear what she has to say?” several people asked.

I said “no” every time. I told them about all of my failed experiments with Zenar cards as a kid. I talked about my experience in high school. I told them about the challenge. I talked about the lack of evidence for psychic abilities.

Nobody got angry or hurtful this time. Instead, they wanted to prove to me that it was real. They begged me to take a turn. So I did.

I sat down at her table and vowed to myself that I would not scoff or laugh. I would just answer her questions truthfully and try not to give her any clues. I have a pretty good poker face.

Sylvia (I don’t remember her name, either) really only asked me one question of interest and it was her downfall.

She asked, “Is your mother more like Betty Crocker or Susan B. Anthony?”

That was easy. “Betty Crocker,” I said.

Sylvia then went on for about 20 minutes while I sat, amused and expressionless, listening. My friends/coworkers listened, too. Sylvia lectured me about my inability to break out of the character that my mother had modeled for me–the meek and timid woman who never felt strong enough to stand up for herself or speak up for others. She told me to find my own voice, that I needed to be more assertive. And so on…

I thanked her, then got up and headed back to the office to get some work done.

I thought that this reading would convince my friends that psychics were frauds. You see, I had built a reputation at that company. I was certainly not timid. I was not quiet. I was not meek. I was in fact… kind of a bitch. But I got the job done precisely because I was assertive. My personality has not changed much.

And my mother? Well, the mistake Sylvia made was asking such a simplistic question. I answered “Betty Crocker” because my mother took cake decorating classes (and made the most amazing doll cakes for me every year; she made my wedding cake, too) and is a very talented seamstress. Yes, she cooked and baked and sewed and got involved with the Navy Wives Club and volunteered as a nurse at my elementary school. She was also nothing like Susan B. Anthony. She didn’t burn her bra or march for women’s liberation. BUT, she was tough. Still is. She took cake decorating, but she also took auto repair classes and she taught me how to install car radios. My mother is not meek, not timid, and certainly has no trouble asserting herself. Nor do I.

And I thought it was blatantly obvious that the psychic had totally blown it.

But my friends still gathered around me, giggling excitedly about how great Sylvia was. When I said, “But she got everything wrong,” they dismissed it. They said, “She’s just telling you that you’re on the right track!”

When I objected with, “But my mother is nothing like that,” they said, “Well nobody gets everything 100% perfect.”

They talked about all of the vague things that she’d said in their readings and what they thought all of those things meant. They were drenched in the excitement of belief.

I shook my head and trudged back to my office alone. If that demonstration didn’t convince them, I didn’t know what would. I was sad about that for a long time.

It would be years before I went back to school to study psychology, teach, and look for better ways to promote skepticism.

People who believe in psychics don’t care whether they saw the psychic at their place of business, at a party, or at a county fair. They don’t think that matters because a psychic is a psychic. They don’t think that “party psychics” are just there to give bogus readings for fun. What fun would that be, anyway, if you don’t believe they are real?

“Party psychics” may not bilk a mark out of thousands of dollars, but they take money in exchange for pretending to know things they cannot know. They are no less fraudulent in their actions and just as guilty of promoting harmful superstition. This is not harmless.