Category: Science

When Technology Takes Revenge

While runaway cars and vengeful stitched-together humans may be the stuff of science fiction, technology really can take revenge on us. Seeing technology as part of a complex system can help us avoid costly unintended consequences. Here’s what you need to know about revenge effects.

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By many metrics, technology keeps making our lives better. We live longer, healthier, richer lives with more options than ever before for things like education, travel, and entertainment. Yet there is often a sense that we have lost control of our technology in many ways, and thus we end up victims of its unanticipated impacts.

Edward Tenner argues in Why Things Bite Back: Technology and the Revenge of Unintended Consequences that we often have to deal with “revenge effects.” Tenner coined this term to describe the ways in which technologies can solve one problem while creating additional worse problems, new types of problems, or shifting the harm elsewhere. In short, they bite back.

Although Why Things Bite Back was written in the late 1990s and many of its specific examples and details are now dated, it remains an interesting lens for considering issues we face today. The revenge effects Tenner describes haunt us still. As the world becomes more complex and interconnected, it’s easy to see that the potential for unintended consequences will increase.

Thus, when we introduce a new piece of technology, it would be wise to consider whether we are interfering with a wider system. If that’s the case, we should consider what might happen further down the line. However, as Tenner makes clear, once the factors involved get complex enough, we cannot anticipate them with any accuracy.

Neither Luddite nor alarmist in nature, the notion of revenge effects can help us better understand the impact of intervening with complex systems But we need to be careful. Although second-order thinking is invaluable, it cannot predict the future with total accuracy. Understanding revenge effects is primarily a reminder of the value of caution and not of specific risks.

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Types of revenge effects

There are four different types of revenge effects, described here as follows:

  1. Repeating effects: occur when more efficient processes end up forcing us to do the same things more often, meaning they don’t free up more of our time. Better household appliances have led to higher standards of cleanliness, meaning people end up spending the same amount of time—or more—on housework.
  2. Recomplicating effects: occur when processes become more and more complex as the technology behind them improves. Tenner gives the now-dated example of phone numbers becoming longer with the move away from rotary phones. A modern example might be lighting systems that need to be operated through an app, meaning a visitor cannot simply flip a switch.
  3. Regenerating effects: occur when attempts to solve a problem end up creating additional risks. Targeting pests with pesticides can make them increasingly resistant to harm or kill off their natural predators. Widespread use of antibiotics to control certain conditions has led to be resistant strains of bacteria that are harder to treat.
  4. Rearranging effects: occur when costs are transferred elsewhere so risks shift and worsen. Air conditioning units on subways cool down the trains—while releasing extra heat and making the platforms warmer. Vacuum cleaners can throw dust mite pellets into the air, where they remain suspended and are more easily breathed in. Shielding beaches from waves transfers the water’s force elsewhere.

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Recognizing unintended consequences

The more we try to control our tools, the more they can retaliate.

Revenge effects occur when the technology for solving a problem ends up making it worse due to unintended consequences that are almost impossible to predict in advance. A smartphone might make it easier to work from home, but always being accessible means many people end up working more.

Things go wrong because technology does not exist in isolation. It interacts with complex systems, meaning any problems spread far from where they begin. We can never merely do one thing.

Tenner writes: “Revenge effects happen because new structures, devices, and organisms react with real people in real situations in ways we could not foresee.” He goes on to add that “complexity makes it impossible for anyone to understand how the system might act: tight coupling spreads problems once they begin.”

Prior to the Industrial Revolution, technology typically consisted of tools that served as an extension of the user. They were not, Tenner argues, prone to revenge effects because they did not function as parts in an overall system like modern technology. He writes that “a machine can’t appear to have a will of its own unless it is a system, not just a device. It needs parts that interact in unexpected and sometimes unstable and unwanted ways.”

Revenge effects often involve the transformation of defined, localized risks into nebulous, gradual ones involving the slow accumulation of harm. Compared to visible disasters, these are much harder to diagnose and deal with.

Large localized accidents, like a plane crash, tend to prompt the creation of greater safety standards, making us safer in the long run. Small cumulative ones don’t.

Cumulative problems, compared to localized ones, aren’t easy to measure or even necessarily be concerned about. Tenner points to the difference between reactions in the 1990s to the risk of nuclear disasters compared to global warming. While both are revenge effects, “the risk from thermonuclear weapons had an almost built-in maintenance compulsion. The deferred consequences of climate change did not.”

Many revenge effects are the result of efforts to improve safety. “Our control of the acute has indirectly promoted chronic problems”, Tenner writes. Both X-rays and smoke alarms cause a small number of cancers each year. Although they save many more lives and avoiding them is far riskier, we don’t get the benefits without a cost. The widespread removal of asbestos has reduced fire safety, and disrupting the material is often more harmful than leaving it in place.

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Not all effects exact revenge

A revenge effect is not a side effect—defined as a cost that goes along with a benefit. The value of being able to sanitize a public water supply has significant positive health outcomes. It also has a side effect of necessitating an organizational structure that can manage and monitor that supply.

Rather, a revenge effect must actually reverse the benefit for at least a small subset of users. For example, the greater ease of typing on a laptop compared to a typewriter has led to an increase in carpal tunnel syndrome and similar health consequences. It turns out that the physical effort required to press typewriter keys and move the carriage protected workers from some of the harmful effects of long periods of time spent typing.

Likewise, a revenge effect is not just a tradeoff—a benefit we forgo in exchange for some other benefit. As Tenner writes:

If legally required safety features raise airline fares, that is a tradeoff. But suppose, say, requiring separate seats (with child restraints) for infants, and charging a child’s fare for them, would lead many families to drive rather than fly. More children could in principle die from transportation accidents than if the airlines had continued to permit parents to hold babies on their laps. This outcome would be a revenge effect.

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In support of caution

In the conclusion of Why Things Bite Back, Tenner writes:

We seem to worry more than our ancestors, surrounded though they were by exploding steamboat boilers, raging epidemics, crashing trains, panicked crowds, and flaming theaters. Perhaps this is because the safer life imposes an ever increasing burden of attention. Not just in the dilemmas of medicine but in the management of natural hazards, in the control of organisms, in the running of offices, and even in the playing of games there are, not necessarily more severe, but more subtle and intractable problems to deal with.

While Tenner does not proffer explicit guidance for dealing with the phenomenon he describes, one main lesson we can draw from his analysis is that revenge effects are to be expected, even if they cannot be predicted. This is because “the real benefits usually are not the ones that we expected, and the real perils are not those we feared.”

Chains of cause and effect within complex systems are stranger than we can often imagine. We should expect the unexpected, rather than expecting particular effects.

While we cannot anticipate all consequences, we can prepare for their existence and factor it into our estimation of the benefits of new technology. Indeed, we should avoid becoming overconfident about our ability to see the future, even when we use second-order thinking. As much as we might prepare for a variety of impacts, revenge effects may be dependent on knowledge we don’t yet possess. We should expect larger revenge effects the more we intensify something (e.g., making cars faster means worse crashes).

Before we intervene in a system, assuming it can only improve things, we should be aware that our actions can do the opposite or do nothing at all. Our estimations of benefits are likely to be more realistic if we are skeptical at first.

If we bring more caution to our attempts to change the world, we are better able to avoid being bitten.

 

The Observer Effect: Seeing Is Changing

The act of looking at something changes it – an effect that holds true for people, animals, even atoms. Here’s how the observer effect distorts our world and how we can get a more accurate picture.

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We often forget to factor in the distortion of observation when we evaluate someone’s behavior. We see what they are doing as representative of their whole life. But the truth is, we all change how we act when we expect to be seen. Are you ever on your best behavior when you’re alone in your house? To get better at understanding other people, we need to consider the observer effect: observing things changes them, and some phenomena only exist when observed.

The observer effect is not universal. The moon continues to orbit whether we have a telescope pointed at it or not. But both things and people can change under observation. So, before you judge someone’s behavior, it’s worth asking if they are changing because you are looking at them, or if their behavior is natural. People are invariably affected by observation. Being watched makes us act differently.

“I believe in evidence. I believe in observation, measurement, and reasoning, confirmed by independent observers.”

— Isaac Asimov

The observer effect in science

The observer effect pops up in many scientific fields.

In physics, Erwin Schrödinger’s famous cat highlights the power of observation. In his best-known thought experiment, Schrödinger asked us to imagine a cat placed in a box with a radioactive atom that might or might not kill it in an hour. Until the box opens, the cat exists in a state of superposition (when half of two states each occur at the same time)—that is, the cat is both alive and dead. Only by observing it does the cat shift permanently to one of the two states. The observation removes the cat from a state of superposition and commits it to just one.

(Although Schrodinger meant this as a counter-argument to Einstein’s proposition of superposition of quantum states – he wanted to demonstrate the absurdity of the proposition – it has caught on in popular culture as a thought experiment of the observer effect.)

In biology, when researchers want to observe animals in their natural habitat, it is paramount that they find a way to do so without disturbing those animals. Otherwise, the behavior they see is unlikely to be natural, because most animals (including humans) change their behavior when they are being observed. For instance, Dr. Cristian Damsa and his colleagues concluded in their paper “Heisenberg in the ER” that being observed makes psychiatric patients a third less likely to require sedation. Doctors and nurses wash their hands more when they know their hygiene is being tracked. And other studies have shown that zoo animals only exhibit certain behaviors in the presence of visitors, such as being hypervigilant of their presence and repeatedly looking at them.

In general, we change our behavior when we expect to be seen. Philosopher Jeremy Bentham knew this when he designed the panopticon prison in the eighteenth century, building upon an idea by his brother Samuel. The prison was constructed so that its cells circled a central watchtower so inmates could never tell if they were being watched or not. Bentham expected this would lead to better behavior, without the need for many staff. It never caught on as an actual design for prisons, but the modern prevalence of CCTV is often compared to the Panopticon. We never know when we’re being watched, so we act as if it’s all the time.

The observer effect, however, is twofold. Observing changes what occurs, but observing also changes our perceptions of what occurs. Let’s take a look at that next.

“How much does one imagine, how much observe? One can no more separate those functions than divide light from air, or wetness from water.”

— Elspeth Huxley

Observer bias

The effects of observation get more complex when we consider how each of us filters what we see through our own biases, assumptions, preconceptions, and other distortions. There’s a reason, after all, why double-blinding (ensuring both tester and subject does not receive any information that may influence their behavior) is the gold-standard in research involving living things. Observer bias occurs when we alter what we see, either by only noticing what we expect or by behaving in ways that have influence on what occurs. Without intending to do so, researchers may encourage certain results, leading to changes in ultimate outcomes.

A researcher falling prey to the observer bias is more likely to make erroneous interpretations, leading to inaccurate results. For instance, in a trial for an anti-anxiety drug where researchers know which subjects receive a placebo and which receive actual drugs, they may report that the latter group seems calmer because that’s what they expect.

The truth is, we often see what we expect to see. Our biases lead us to factor in irrelevant information when evaluating the actions of others. We also bring our past into the present and let that color our perceptions as well—so, for example, if someone has really hurt you before, you are less likely to see anything good in what they do.

The actor-observer bias

Another factor in the observer effect, and one we all fall victim to, is our tendency to attribute the behavior of others to innate personality traits. Yet we tend to attribute our own behavior to external circumstances. This is known as the actor-observer bias.

For example, a student who gets a poor grade on a test claims they were tired that day or the wording on the test was unclear. Conversely, when that same student observes a peer who performed badly on a test on which they performed well, the student judges their peer as incompetent or ill-prepared. If someone is late to a meeting with a friend, they rush in apologizing for the bad traffic. But if the friend is late, they label them as inconsiderate. When we see a friend having an awesome time in a social media post, we assume their life is fun all of the time. When we post about ourselves having an awesome time, we see it as an anomaly in an otherwise non-awesome life.

We have different levels of knowledge about ourselves and others. Because observation focuses on what is displayed, not what preceded or motivated it, we see the full context for our own behavior but only the final outcome for other people. We need to take the time to learn the context of other’s lives before we pass judgment on their actions.

Conclusion

We can use the observer effect to our benefit. If we want to change a behavior, finding some way to ensure someone else observes it can be effective. For instance, going to the gym with a friend means they know if we don’t go, making it more likely that we stick with it. Tweeting about our progress on a project can help keep us accountable. Even installing software on our laptop that tracks how often we check social media can reduce our usage.

But if we want to get an accurate view of reality, it is important we consider how observing it may distort the results. The value of knowing about the observer effect in everyday life is that it can help us factor in the difference that observation makes. If we want to gain an accurate picture of the world, it pays to consider how we take that picture. For instance, you cannot assume that an employee’s behavior in a meeting translates to their work, or that the way your kids act at home is the same as in the playground. We all act differently when we know we are being watched.

How To Spot Bad Science

In a digital world that clamors for clicks, news is sensationalized and “facts” change all the time. Here’s how to discern what is trustworthy and what is hogwash.

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Unless you’ve studied it, most of us are never taught how to evaluate science or how to parse the good from the bad. Yet it is something that dictates every area of our lives. It is vital for helping us understand how the world works. It might be too much effort and time to appraise research for yourself, however. Often, it can be enough to consult an expert or read a trustworthy source.

But some decisions require us to understand the underlying science. There is no way around it. Many of us hear about scientific developments from news articles and blog posts. Some sources put the work into presenting useful information. Others manipulate or misinterpret results to get more clicks. So we need the thinking tools necessary to know what to listen to and what to ignore. When it comes to important decisions, like knowing what individual action to take to minimize your contribution to climate change or whether to believe the friend who cautions against vaccinating your kids, being able to assess the evidence is vital.

Much of the growing (and concerning) mistrust of scientific authority is based on a misunderstanding of how it works and a lack of awareness of how to evaluate its quality. Science is not some big immovable mass. It is not infallible. It does not pretend to be able to explain everything or to know everything. Furthermore, there is no such thing as “alternative” science. Science does involve mistakes. But we have yet to find a system of inquiry capable of achieving what it does: move us closer and closer to truths that improve our lives and understanding of the universe.

“Rather than love, than money, than fame, give me truth.”

— Henry David Thoreau

There is a difference between bad science and pseudoscience. Bad science is a flawed version of good science, with the potential for improvement. It follows the scientific method, only with errors or biases. Often, it’s produced with the best of intentions, just by researchers who are responding to skewed incentives.

Pseudoscience has no basis in the scientific method. It does not attempt to follow standard procedures for gathering evidence. The claims involved may be impossible to disprove. Pseudoscience focuses on finding evidence to confirm it, disregarding disconfirmation. Practitioners invent narratives to preemptively ignore any actual science contradicting their views. It may adopt the appearance of actual science to look more persuasive.

While the tools and pointers in this post are geared towards identifying bad science, they will also help with easily spotting pseudoscience.

Good science is science that adheres to the scientific method, a systematic method of inquiry involving making a hypothesis based on existing knowledge, gathering evidence to test if it is correct, then either disproving or building support for the hypothesis. It takes many repetitions of applying this method to build reasonable support for a hypothesis.

In order for a hypothesis to count as such, there must be evidence that, if collected, would disprove it.

In this post, we’ll talk you through two examples of bad science to point out some of the common red flags. Then we’ll look at some of the hallmarks of good science you can use to sort the signal from the noise. We’ll focus on the type of research you’re likely to encounter on a regular basis, including medicine and psychology, rather than areas less likely to be relevant to your everyday life.

[Note: we will use the terms “research” and “science” and “researcher” and “scientist” interchangeably here.]

Power Posing

“The saddest aspect of life right now is that science gathers knowledge faster than society gathers wisdom.” ―Isaac Asimov

First, here’s an example of flawed science from psychology: power posing. A 2010 study by Dana Carney, Andy J. Yap, and Amy Cuddy entitledPower Posing: Brief Nonverbal Displays Effects Neuroendocrine Levels and Risk Tolerance” claimed “open, expansive” poses caused participants to experience elevated testosterone levels, reduced cortisol levels, and greater risk tolerance. These are all excellent things in a high-pressure situation, like a job interview. The abstract concluded that “a person can, via a simple two-minute pose, embody power and instantly become more powerful.” The idea took off. It spawned hundreds of articles, videos, and tweets espousing the benefits of including a two-minute power pose in your day.

Yet at least eleven follow up studies, many led by Joseph Cesario of Michigan State University including “’Power Poses’ Don’t Work, Eleven New Studies Suggest,” failed to replicate the results. None found that power posing has a measurable impact on people’s performance in tasks or on their physiology. While subjects did report a subjective feeling of increased powerfulness, their performance did not differ from subjects who did not strike a power pose.

One of the researchers of the original study, Carney, has since changed her mind about the effect. Carney stated she no longer believe the results of the original study. Unfortunately, this isn’t always how researchers respond when confronted with evidence discrediting their prior work. We all know how uncomfortable changing our minds is.

The notion of power posing is exactly the kind of nugget that spreads fast online. It’s simple, free, promises dramatic benefits with minimal effort, and is intuitive. We all know posture is important. It has a catchy, memorable name. Yet examining the details of the original study reveals a whole parade of red flags. The study had 42 participants. That might be reasonable for preliminary or pilot studies. But is in no way sufficient to “prove” anything. It was not blinded. Feedback from participants was self-reported, which is notorious for being biased and inaccurate.

There is also a clear correlation/causation issue. Powerful, dominant animals tend to use expansive body language that exaggerates their size. Humans often do the same. But that doesn’t mean it’s the pose making them powerful. Being powerful could make them pose that way.

A TED Talk in which Amy Cuddy, the study’s co-author, claimed power posing could “significantly change the way your life unfolds” is one of the most popular to date, with tens of millions of views. The presentation of the science in the talk is also suspect. Cuddy makes strong claims with a single, small study as justification. She portrays power posing as a panacea. Likewise, the original study’s claim that a power pose makes someone “instantly become more powerful” is suspiciously strong.

This is one of the examples of psychological studies related to small tweaks in our behavior that have not stood up to scrutiny. We’re not singling out the power pose study as being unusually flawed or in any way fraudulent. The researchers had clear good intentions and a sincere belief in their work. It’s a strong example of why we should go straight to the source if we want to understand research. Coverage elsewhere is unlikely to even mention methodological details or acknowledge any shortcomings. It would ruin the story. We even covered power posing on Farnam Street in 2016—we’re all susceptible to taking these ‘scientific’ results seriously, without checking on the validity of the underlying science.

It is a good idea to be skeptical of research promising anything too dramatic or extreme with minimal effort, especially without substantial evidence. If it seems too good to be true, it most likely is.

Green Coffee Beans

“An expert is a person who has made all the mistakes that can be made in a very narrow field.” ―Niels Bohr

The world of weight-loss science is one where bad science is rampant. We all know, deep down, that we cannot circumnavigate the need for healthy eating and exercise. Yet the search for a magic bullet, offering results without effort or risks, continues. Let’s take a look at one study that is a masterclass in bad science.

EntitledRandomized, Double-Blind, Placebo-Controlled, Linear Dose, Crossover Study to Evaluate the Efficacy and Safety of a Green Coffee Bean Extract in Overweight Subjects,” it was published in 2012 in the journal Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. On the face of it, and to the untrained eye, the study may appear legitimate, but it is rife with serious problems, as Scott Gavura explained in the article “Dr. Oz and Green Coffee Beans – More Weight Loss Pseudoscience” in the publication Science-Based Medicine. The original paper was later retracted by its authors. The Federal Trade Commission (FTC) ordered the supplement manufacturer who funded the study to pay a $3.5 million fine for using it in their marketing materials, describing it as “botched.”

The Food and Drug Administration (FDA) recommends studies relating to weight-loss consist of at least 3,000 participants receiving the active medication and at least 1,500 receiving a placebo, all for a minimum period of 12 months. This study used a mere 16 subjects, with no clear selection criteria or explanation. None of the researchers involved had medical experience or had published related research. They did not disclose the conflict of interest inherent in the funding source. It didn’t cover efforts to avoid any confounding factors. It is vague about whether subjects changed their diet and exercise, showing inconsistencies. The study was not double-blinded, despite claiming to be. It has not been replicated.

The FTC reported that the study’s lead investigator “repeatedly altered the weights and other key measurements of the subjects, changed the length of the trial, and misstated which subjects were taking the placebo or GCA during the trial.” A meta-analysis by Rachel Buchanan and Robert D. Beckett, “Green Coffee for Pharmacological Weight Loss” published in the Journal of Evidence-Based Complementary & Alternative Medicine, failed to find evidence for green coffee beans being safe or effective; all the available studies had serious methodological flaws, and most did not comply with FDA guidelines.

Signs of Good Science

“That which can be asserted without evidence can be dismissed without evidence.” ―Christopher Hitchens

We’ve inverted the problem and considered some of the signs of bad science. Now let’s look at some of the indicators a study is likely to be trustworthy. Unfortunately, there is no single sign a piece of research is good science. None of the signs mentioned here are, alone, in any way conclusive. There are caveats and exceptions to all. These are simply factors to evaluate.

It’s Published by a Reputable Journal

“The discovery of instances which confirm a theory means very little if we have not tried, and failed, to discover refutations.” —Karl Popper

A journal, any journal, publishing a study says little about its quality. Some will publish any research they receive in return for a fee. A few so-called “vanity publishers” claim to have a peer-review process, yet they typically have a short gap between receiving a paper and publishing it. We’re talking days or weeks, not the expected months or years. Many predatory publishers do not even make any attempt to verify quality.

No journal is perfect. Even the most respected journals make mistakes and publish low-quality work sometimes. However, anything that is not published research or based on published research in a journal is not worth consideration. Not as science. A blog post saying green smoothies cured someone’s eczema is not comparable to a published study. The barrier is too low. If someone cared enough about using a hypothesis or “finding” to improve the world and educate others, they would make the effort to get it published. The system may be imperfect, but reputable researchers will generally make the effort to play within it to get their work noticed and respected.

It’s Peer Reviewed

Peer review is a standard process in academic publishing. It’s intended as an objective means of assessing the quality and accuracy of new research. Uninvolved researchers with relevant experience evaluate papers before publication. They consider factors like how well it builds upon pre-existing research or if the results are statistically significant. Peer review should be double-blinded. This means the researcher doesn’t know who is reviewing their work and the reviewer doesn’t know who the researcher is.

Publishers only perform a cursory “desk check” before moving onto peer review. This is to check for major errors, nothing more. They cannot have the expertise necessary to vet the quality of every paper they handle—hence the need for external experts. The number of reviewers and strictness of the process depends on the journal. Reviewers either declare a paper unpublishable or suggest improvements. It is rare for them to suggest publishing without modifications.

Sometimes several rounds of modifications prove necessary. It can take years for a paper to see the light of day, which is no doubt frustrating for the researcher. But it ensures no or fewer mistakes or weak areas.

Pseudoscientific practitioners will often claim they cannot get their work published because peer reviewers suppress anything contradicting prevailing doctrines. Good researchers know having their work challenged and argued against is positive. It makes them stronger. They don’t shy away from it.

Peer review is not a perfect system. Seeing as it involves humans, there is always room for bias and manipulation. In a small field, it may be easy for a reviewer to get past the double-blinding. However, as it stands, peer review seems to be the best available system. In isolation, it’s not a guarantee that research is perfect, but it’s one factor to consider.

The Researchers Have Relevant Experience and Qualifications

One of the red flags in the green coffee bean study was that the researchers involved had no medical background or experience publishing obesity-related research.

While outsiders can sometimes make important advances, researchers should have relevant qualifications and a history of working in that field. It is too difficult to make scientific advancements without the necessary background knowledge and expertise. If someone cares enough about advancing a given field, they will study it. If it’s important, verify their backgrounds.

It’s Part of a Larger Body of Work

“Science, my lad, is made up of mistakes, but they are mistakes which it is useful to make, because they lead little by little to the truth.” ―Jules Verne

We all like to stand behind the maverick. But we should be cautious of doing so when it comes to evaluating the quality of science. On the whole, science does not progress in great leaps. It moves along millimeter by millimeter, gaining evidence in increments. Even if a piece of research is presented as groundbreaking, it has years of work behind it.

Researchers do not work in isolation. Good science is rarely, if ever, the result of one person or even one organization. It comes from a monumental collective effort. So when evaluating research, it is important to see if other studies point to similar results and if it is an established field of work. For this reason, meta-analyses, which analyze the combined results of many studies on the same topic, are often far more useful to the public than individual studies. Scientists are humans and they all make mistakes. Looking at a collective body of work helps smooth out any problems. Individual studies are valuable in that they further the field as a whole, allowing for the creation of meta-studies.

Science is about evidence, not reputation. Sometimes well-respected researchers, for whatever reason, produce bad science. Sometimes outsiders produce amazing science. What matters is the evidence they have to support it. While an established researcher may have an easier time getting support for their work, the overall community accepts work on merit. When we look to examples of unknowns who made extraordinary discoveries out of the blue, they always had extraordinary evidence for it.

Questioning the existing body of research is not inherently bad science or pseudoscience. Doing so without a remarkable amount of evidence is.

It Doesn’t Promise a Panacea or Miraculous Cure

Studies that promise anything a bit too amazing can be suspect. This is more common in media reporting of science or in research used for advertising.

In medicine, a panacea is something that can supposedly solve all, or many, health problems. These claims are rarely substantiated by anything even resembling evidence. The more outlandish the claim, the less likely it is to be true. Occam’s razor teaches us that the simplest explanation with the fewest inherent assumptions is most likely to be true. This is a useful heuristic for evaluating potential magic bullets.

It Avoids or at Least Discloses Potential Conflicts of Interest

A conflict of interest is anything that incentivizes producing a particular result. It distorts the pursuit of truth. A government study into the health risks of recreational drug use will be biased towards finding evidence of negative risks. A study of the benefits of breakfast cereal funded by a cereal company will be biased towards finding plenty of benefits. Researchers do have to get funding from somewhere, so this does not automatically make a study bad science. But research without conflicts of interest is more likely to be good science.

High-quality journals require researchers to disclose any potential conflicts of interest. But not all journals do. Media coverage of research may not mention this (another reason to go straight to the source). And people do sometimes lie. We don’t always know how unconscious biases influence us.

It Doesn’t Claim to Prove Anything Based on a Single Study

In the vast majority of cases, a single study is a starting point, not proof of anything. The results could be random chance, or the result of bias, or even outright fraud. Only once other researchers replicate the results can we consider a study persuasive. The more replications, the more reliable the results are. If attempts at replication fail, this can be a sign the original research was biased or incorrect.

A note on anecdotes: they’re not science. Anecdotes, especially from people close to us or those who have a lot of letters behind their name, have a disproportionate clout. But hearing something from one person, no matter how persuasive, should not be enough to discredit published research.

Science is about evidence, not proof. And evidence can always be discredited.

It Uses a Reasonable, Representative Sample Size

A representative sample represents the wider population, not one segment of it. If it does not, then the results may only be relevant for people in that demographic, not everyone. Bad science will often also use very small sample sizes.

There is no set target for what makes a large enough sample size; it all depends on the nature of the research. In general, the larger, the better. The exception is in studies that may put subjects at risk, which use the smallest possible sample to achieve usable results.

In areas like nutrition and medicine, it’s also important for a study to last a long time. A study looking at the impact of a supplement on blood pressure over a week is far less useful than one over a decade. Long-term data smooths out fluctuations and offers a more comprehensive picture.

The Results Are Statistically Significant

Statistical significance refers to the likelihood, measured in a percentage, that the results of a study were not due to pure random chance. The threshold for statistical significance varies between fields. Check if the confidence interval is in the accepted range. If it’s not, it’s not worth paying attention to.

It Is Well Presented and Formatted

“When my information changes, I alter my conclusions. What do you do, sir?” ―John Maynard Keynes

As basic as it sounds, we can expect good science to be well presented and carefully formatted, without prominent typos or sloppy graphics.

It’s not that bad presentation makes something bad science. It’s more the case that researchers producing good science have an incentive to make it look good. As Michael J. I. Brown of Monash University explains in How to Quickly Spot Dodgy Science, this is far more than a matter of aesthetics. The way a paper looks can be a useful heuristic for assessing its quality. Researchers who are dedicated to producing good science can spend years on a study, fretting over its results and investing in gaining support from the scientific community. This means they are less likely to present work looking bad. Brown gives an example of looking at an astrophysics paper and seeing blurry graphs and misplaced image captions—then finding more serious methodological issues upon closer examination. In addition to other factors, sloppy formatting can sometimes be a red flag. At the minimum, a thorough peer-review process should eliminate glaring errors.

It Uses Control Groups and Double-Blinding

A control group serves as a point of comparison in a study. The control group should be people as similar as possible to the experimental group, except they’re not subject to whatever is being tested. The control group may also receive a placebo to see how the outcome compares.

Blinding refers to the practice of obscuring which group participants are in. For a single-blind experiment, the participants do not know if they are in the control or the experimental group. In a double-blind experiment, neither the participants nor the researchers know. This is the gold standard and is essential for trustworthy results in many types of research. If people know which group they are in, the results are not trustworthy. If researchers know, they may (unintentionally or not) nudge participants towards the outcomes they want or expect. So a double-blind study with a control group is far more likely to be good science than one without.

It Doesn’t Confuse Correlation and Causation

In the simplest terms, two things are correlated if they happen at the same time. Causation is when one thing causes another thing to happen. For example, one large-scale study entitled “Are Non-Smokers Smarter than Smokers?” found that people who smoke tobacco tend to have lower IQs than those who don’t. Does this mean smoking lowers your IQ? It might, but there is also a strong link between socio-economic status and smoking. People of low income are, on average, likely to have lower IQ than those with higher incomes due to factors like worse nutrition, less access to education, and sleep deprivation. A study by the Centers for Disease Control and Prevention entitled “Cigarette Smoking and Tobacco Use Among People of Low Socioeconomic Status,” people of low socio-economic status are also more likely to smoke and to do so from a young age. There might be a correlation between smoking and IQ, but that doesn’t mean causation.

Disentangling correlation and causation can be difficult, but good science will take this into account and may detail potential confounding factors of efforts made to avoid them.

Conclusion

“The scientist is not a person who gives the right answers, he’s one who asks the right questions.” ―Claude Lévi-Strauss

The points raised in this article are all aimed at the linchpin of the scientific method—we cannot necessarily prove anything; we must consider the most likely outcome given the information we have. Bad science is generated by those who are willfully ignorant or are so focused on trying to “prove” their hypotheses that they fudge results and cherry-pick to shape their data to their biases. The problem with this approach is that it transforms what could be empirical and scientific into something subjective and ideological.

When we look to disprove what we know, we are able to approach the world with a more flexible way of thinking. If we are unable to defend what we know with reproducible evidence, we may need to reconsider our ideas and adjust our worldviews accordingly. Only then can we properly learn and begin to make forward steps. Through this lens, bad science and pseudoscience are simply the intellectual equivalent of treading water, or even sinking.

Article Summary

  • Most of us are never taught how to evaluate science or how to parse the good from the bad. Yet it is something that dictates every area of our lives.
  • Bad science is a flawed version of good science, with the potential for improvement. It follows the scientific method, only with errors or biases.
  • Pseudoscience has no basis in the scientific method. It does not attempt to follow standard procedures for gathering evidence. The claims involved may be impossible to disprove.
  • Good science is science that adheres to the scientific method, a systematic method of inquiry involving making a hypothesis based on existing knowledge, gathering evidence to test if it is correct, then either disproving or building support for the hypothesis.
  • Science is about evidence, not proof. And evidence can always be discredited.
  • In science, if it seems too good to be true, it most likely is.

Signs of good science include:

  • It’s Published by a Reputable Journal
  • It’s Peer Reviewed
  • The Researchers Have Relevant Experience and Qualifications
  • It’s Part of a Larger Body of Work
  • It Doesn’t Promise a Panacea or Miraculous Cure
  • It Avoids or at Least Discloses Potential Conflicts of Interest
  • It Doesn’t Claim to Prove Anything Based on a Single Study
  • It Uses a Reasonable, Representative Sample Size
  • The Results Are Statistically Significant
  • It Is Well Presented and Formatted
  • It Uses Control Groups and Double-Blinding
  • It Doesn’t Confuse Correlation and Causation

The Stormtrooper Problem: Why Thought Diversity Makes Us Better

Diversity of thought makes us stronger, not weaker. Without diversity, we die off as a species. We can no longer adapt to changes in the environment. We need each other to survive.

***

Diversity is how we survive as a species. This is a quantifiable fact easily observed in the biological world. From niches to natural selection, diversity is the common theme of success for both the individual and the group.

Take the central idea of natural selection: The genes, individuals, groups, and species with the most advantageous traits in a given environment survive and reproduce in greater numbers. Eventually, those advantageous traits spread. The overall population becomes more suited to that environment. This occurs at multiple levels, from single genes to entire ecosystems.

That said, natural selection cannot operate without a diverse set of traits to select from! Without variation, selection cannot improve the lot of the higher-level group.

Diversity of Thought

We often seem to struggle with diversity of thought. This type of diversity shouldn’t threaten us. It should energize us. It means we have a wider variety of resources to deal with the inevitable challenges we face as a species.

Imagine that a meteor is on its way to earth. A crash would be the end of everyone. No matter how self-involved we are, no one wants to see humanity wiped out. So what do we do? Wouldn’t you hope that we could call on more than three people to help find a solution?

Ideally there would be thousands of people with different skills and backgrounds tackling this meteor problem, many minds and lots of options for changing the rock’s course and saving life as we know it. The diversity of backgrounds—variations in skills, knowledge, ways of looking at and understanding the problem—might be what saves the day. But why wait for the threat? A smart species would recognize that if diversity of knowledge and skills would be useful for dealing with a meteor, then diversity would be probably useful in a whole set of other situations.

For example, very few businesses can get by with one knowledge set that will take their product from concept to the homes of customers. You would never imagine that a business could be staffed with clones and be successful. It would be the ultimate in social proof. Everyone would literally be saying the same thing.

The Stormtrooper Problem

Intelligence agencies face a unique set of problems that require creative, un-googleable solutions to one-off problems.

You’d naturally think they would value and seek out diversity in order to solve those problems. And you’d be wrong. Increasingly it’s harder and harder to get a security clearance.

Do you have a lot of debt? That might make you susceptible to blackmail. Divorced? You might be an emotional wreck, which could mean you’ll make emotional decisions and not rational ones. Do something as a youth that you don’t want anyone to know? That makes it harder to trust you. Gay but haven’t told anyone? Blackmail risk. Independently wealthy? That means you don’t need our paycheck, which means you might be harder to work with. Do you have a nuanced opinion of politics? What about Edward Snowden? Yikes. The list goes on.

As the process gets harder and harder (trying to reduce risk), there is less and less diversity in the door. The people that make it through the door are Stormtroopers.

And if you’re one of the lucky Stormtrooopers to make it in, you’re given a checklist career development path. If you want a promotion, you know the exact experience and training you need to receive one. It’s simple. It doesn’t require much thought on your part.

The combination of these two things means that employees increasingly look at—and attempt to solve—problems the same way. The workforce is less effective than it used to be. This means you have to hire more people to do the same thing or outsource more work to people that hire misfits. This is the Stormtrooper problem.

Creativity and Innovation

Diversity is necessary in the workplace to generate creativity and innovation. It’s also necessary to get the job done. Teams with members from different backgrounds can attack problems from all angles and identify more possible solutions than teams whose members think alike. Companies also need diverse skills and knowledge to keep a company functioning. Finance superstars may not be the same people who will rock marketing. And the faster things change, the more valuable diversity becomes for allowing us to adapt and seize opportunity.

We all know that any one person doesn’t have it all figured out and cannot possibly do it all. We can all recognize that we rely on thousands of other people every day just to live. We interact with the world through the products we use, the entertainment we consume, the services we provide. So why do differences often unsettle us?

Any difference can raise this reaction: gender, race, ethnic background, sexual orientation. Often, we hang out with others like us because, let’s face it, communicating is easier with people who are having a similar life experience. And most of us like to feel that we belong. But a sense of belonging should not come at the cost of diversity.

Where Birds Got Feathers

Consider this: Birds did not get their feathers for flying. They originally developed them for warmth, or for being more attractive to potential mates. It was only after feathers started appearing that birds eventually began to fly. Feathers are considered an exaptation, something that evolved for one purpose but then became beneficial for other reasons. When the environment changes, which it inevitably does, a species has a significantly increased chance of survival if it has a diversity of traits that it can re-purpose. What can we re-purpose if everyone looks, acts, and thinks the same?

Further, a genetically homogeneous population is easy to wipe out. It baffles me that anyone thinks they are a good idea. Consider the Irish Potato Famine. In the mid-19th century a potato disease made its way around much of the world. Although it devastated potato crops everywhere, only in Ireland did it result in widespread devastation and death. About one quarter of Ireland’s population died or emigrated to avoid starvation over just a few years. Why did this potato disease have such significant consequences there and not anywhere else?

The short answer is a lack of diversity. The potato was the staple crop for Ireland’s poor. Tenant farms were so small that only potatoes could be grown in sufficient quantity to—barely—feed a family. Too many people depended on this one crop to meet their nutritional needs. In addition, the Irish primarily grew one type of potato, so most of the crops were vulnerable to the same disease. Once the blight hit, it easily infected potato fields all over Ireland, because they were all the same.

You can’t adapt if you have nothing to adapt. If we are all the same, if we’ve wiped out every difference because we find it less challenging, then we increase our vulnerability to complete extinction. Are we too much alike to survive unforeseen challenges?

Even the reproductive process is, at its core, about diversity. You get half your genes from your mother and half from your father. These can be combined in so many different ways that 21 siblings are all going to be genetically unique.

Why is this important? Without this diversity we never would have made it this far. It’s this newness, each time life is started, that has given us options in the form of mutations. They’re like unexpected scientific breakthroughs. Some of these drove our species to awesome new capabilities. The ones that resulted in less fitness? These weren’t likely to survive. Success in life, survival on the large scale, has a lot to do with the potential benefits created by the diversity inherent in the reproductive process.

Diversity is what makes us stronger, not weaker. Biologically, without diversity we die off as a species. We can no longer adapt to changes in the environment. This is true of social diversity as well. Without diversity, we have no resources to face the inevitable challenges, no potential for beneficial mutations or breakthroughs that may save us. Yet we continue to have such a hard time with that. We’re still trying to figure out how to live with each other. We’re nowhere near ready for that meteor.

Article Summary

  • Visible diversity is not the same as cognitive diversity.
  • Cognitive diversity comes from thinking about problems differently, not from race, gender, or sexual orientation.
  • Cognitive diversity helps us avoid blind spots and adapt to changing environments.
  • You can’t have selection without variation.
  • The Stormtrooper problem is when everyone working on a problem thinks about it in the same way.

Alexander von Humboldt and the Invention of Nature: Creating a Holistic View of the World Through A Web of Interdisciplinary Knowledge

In his piece in 2014’s Edge collection This Idea Must Die: Scientific Theories That Are Blocking Progress, dinosaur paleontologist Scott Sampson writes that science needs to “subjectify” nature. By “subjectify”, he essentially means to see ourselves connected with nature, and therefore care about it the same way we do the people with whom we are connected.

That’s not the current approach. He argues: “One of the most prevalent ideas in science is that nature consists of objects. Of course, the very practice of science is grounded in objectivity. We objectify nature so that we can measure it, test it, and study it, with the ultimate goal of unraveling its secrets. Doing so typically requires reducing natural phenomena to their component parts.”

But this approach is ultimately failing us.

Why? Because much of our unsustainable behavior can be traced to a broken relationship with nature, a perspective that treats the nonhuman world as a realm of mindless, unfeeling objects. Sustainability will almost certainly depend upon developing mutually enhancing relations between humans and nonhuman nature.

This isn’t a new plea, though. Over 200 years ago, the famous naturalist Alexander Von Humboldt (1769-1859) was facing the same challenges.

In her compelling book The Invention of Nature: Alexander Von Humboldt’s New World, Andrea Wulf explores Humboldt as the first person to publish works promoting a holistic view of nature, arguing that nature could only be understood in relation to the subjectivity of experiencing it.

Fascinated by scientific instruments, measurements and observations, he was driven by a sense of wonder as well. Of course nature had to be measured and analyzed, but he also believed that a great part of our response to the natural world should be based on the senses and emotions.

Humboldt was a rock star scientist who ignored conventional boundaries in his exploration of nature. Humboldt’s desire to know and understand the world led him to investigate discoveries in all scientific disciplines, and to see the interwoven patterns embedded in this knowledge — mental models anyone?

If nature was a web of life, he couldn’t look at it just as a botanist, a geologist or a zoologist. He required information about everything from everywhere.

Humboldt grew up in a world where science was dry, nature mechanical, and man an aloof and separate chronicler of what was before him. Not only did Humboldt have a new vision of what our understanding of nature could be, but he put humans in the middle of it.

Humboldt’s Essay on the Geography of Plants promoted an entirely different understanding of nature. Instead of only looking at an organism, … Humboldt now presented relationships between plants, climate and geography. Plants were grouped into zones and regions rather than taxonomic units. … He gave western science a new lens through which to view the natural world.

Revolutionary for his time, Humboldt rejected the Cartesian ideas of animals as mechanical objects. He also argued passionately against the growing approach in the sciences that put man atop and separate from the rest of the natural world. Promoting a concept of unity in nature, Humboldt saw nature as a “reflection of the whole … an organism in which the parts only worked in relation to each other.”

Furthermore, that “poetry was necessary to comprehend the mysteries of the natural world.”

Wulf paints one of Humboldt’s greatest achievements as his ability and desire to make science available to everyone. No one before him had “combined exact observation with a ‘painterly description of the landscape”.

By contrast, Humboldt took his readers into the crowded streets of Caracas, across the dusty plains of the Llanos and deep into the rainforest along the Orinoco. As he described a continent that few British had ever seen, Humboldt captured their imagination. His words were so evocative, the Edinburgh Review wrote, that ‘you partake in his dangers; you share his fears, his success and his disappointment.’

In a time when travel was precarious, expensive and unavailable to most people, Humboldt brought his experiences to anyone who could read or listen.

On 3 November 1827, … Humboldt began a series of sixty-one lectures at the university. These proved so popular that he added another sixteen at Berlin’s music hall from 6 December. For six months he delivered lectures several days a week. Hundreds of people attended each talk, which Humboldt presented without reading from his notes. It was lively, exhilarating and utterly new. By not charging any entry fee, Humboldt democratized science: his packed audiences ranged from the royal family to coachmen, from students to servants, from scholars to bricklayers – and half of those attending were women. Berlin had never seen anything like it.

The subjectification of nature is about seeing nature, experiencing it. Humboldt was a master of bringing people to worlds they couldn’t visit, allowing them to feel a part of it. In doing so, he wanted to force humanity to see itself in nature. If we were all part of the giant web, then we all had a responsibility to understand it.

When he listed the three ways in which the human species was affecting the climate, he named deforestation, ruthless irrigation and, perhaps most prophetically, the ‘great masses of steam and gas’ produced in the industrial centres. No one but Humboldt had looked at the relationship between humankind and nature like this before.

His final opus, a series of books called Cosmos, was the culmination of everything that Humboldt had learned and discovered.

Cosmos was unlike any previous book about nature. Humboldt took his readers on a journey from outer space to earth, and then from the surface of the planet into its inner core. He discussed comets, the Milky Way and the solar system as well as terrestrial magnetism, volcanoes and the snow line of mountains. He wrote about the migration of the human species, about plants and animals and the microscopic organisms that live in stagnant water or on the weathered surface of rocks. Where others insisted that nature was stripped of its magic as humankind penetrated into its deepest secrets, Humboldt believed exactly the opposite. How could this be, Humboldt asked, in a world in which the coloured rays of an aurora ‘unite in a quivering sea flame’, creating a sight so otherworldly ‘the splendour of which no description can reach’? Knowledge, he said, could never ‘kill the creative force of imagination’ – instead it brought excitement, astonishment and wondrousness.

This is the ultimate subjectivity of nature. Being inspired by its beauty to try and understand how it works. Humboldt had respect for nature, for the wonders it contained, but also as the system in which we ourselves are an inseparable part.

Wulf concludes at the end that Humboldt,

…was one of the last polymaths, and died at a time when scientific disciplines were hardening into tightly fenced and more specialized fields. Consequently his more holistic approach – a scientific method that included art, history, poetry and politics alongside hard data – has fallen out of favour.

Maybe this is where the subjectivity of nature has gone. But we can learn from Humboldt the value of bringing it back.

In a world where we tend to draw a sharp line between the sciences and the arts, between the subjective and the objective, Humboldt’s insight that we can only truly understand nature by using our imagination makes him a visionary.

A little imagination is all it takes.

Warnings From Sleep: Nightmares and Protecting The Self

“All of this is evidence that the mind, although asleep,
is constantly concerned about the safety and integrity of the self.”

***

Rosalind Cartwright — also known as the Queen of Dreams — is a leading sleep researcher. In The Twenty-four Hour Mind: The Role of Sleep and Dreaming in Our Emotional Lives, she explores the role of nightmares and how we use sleep to protect ourselves.

When our time awake is frightening or remains unpressed, the sleeping brain “may process horrible images with enough raw fear attached to awaken a sleeper with a horrendous nightmare.” The more trauma we have in our lives the more likely we are to experience anxiety and nightmares after a horrific event.

The common feature is a threat of harm, accompanied by a lack of ability to control the circumstances of the threat, and the lack of or inability to develop protective behaviors.

The strategies we use for coping effectively with extreme stress and fear are controversial. Should we deny the threatening event and avoid thinking about it better than thinking about it and becoming sensitized to it?

One clear principle that comes out of this work is that the effects of trauma on sleep and dreaming depend on the nature of the threat. If direct action against the threat is irrelevant or impossible (as it would be if the trauma was well in the past), then denial may be helpful in reducing stress so that the person can get on with living as best they can. However, if the threat will be encountered over and over (such as with spousal abuse), and direct action would be helpful in addressing the threat, then denial by avoiding thinking about the danger (which helps in the short-term) will undermine problem-solving efforts and mastery in the long run. In other words, if nothing can be done, emotion-coping efforts to regulate the distress (dreaming) is a good strategy; but if constructive actions can be taken, waking problem-solving action is more adaptive.

What about nightmares?

Nightmares are defined as frightening dreams that wake the sleeper into full consciousness and with a clear memory of the dream imagery. These are not to be confused with sleep terrors. There are three main differences between these two. First, nightmare arousals are more often from late in the night’s sleep, when dreams are longest and the content is most bizarre and affect-laden (emotional); sleep terrors occur early in sleep. Second, nightmares are REM sleep-related, while sleep terrors come out of non-REM (NREM) slow-wave sleep (SWS). Third, sleepers experience vivid recall of nightmares, whereas with sleep terrors the experience is of full or partial amnesia for the episode itself, and only rarely is a single image recalled.

Nightmares abort the REM sleep, a critical component of our always on brain, Cartwright explains:

If we are right that the mind is continuously active throughout sleep—reviewing emotion-evoking new experiences from the day, scanning memory networks for similar experiences (which will defuse immediate emotional impact), revising by updating our organized sense of ourselves, and rehearsing new coping behaviors—nightmares are an exception and fail to perform these functions.

The impact is to temporarily relieve the negative emotion. The example Cartwright gives is “I am not about to be eaten by a monster. I am safe in my own bed.” But because the nightmare has woken me up, the nightmare is of no help in regulating my emotions (a critical role of sleep). As we learn to manage negative emotions while we are awake, that is, as we grow up, nightmares reduce in frequency and we develop skills for resolving fears.

It’s not always fear that wakes us from a nightmare. We can also be woken by anger, disgust, and grief.

Cartwright concludes, with an interesting insight, on the role of sleep in consolidating and protecting “the self.”:

[N]ightmares appear to be more common in those who have intense reactions to stress. The criteria cited for nightmare disorder in the diagnostic manual for psychiatric disorders, the Diagnostic and Statistical Manual IV-TR (DSM IV-TR), include this phrase “frightening dreams usually involving threats to survival, security, or self-esteem.” This theme may sound familiar: Remember that threats to self-esteem seem to precede NREM parasomnia awakenings. All of this is evidence that the mind, although asleep, is constantly concerned about the safety and integrity of the self.

The Twenty-four Hour Mind goes on to explore the history of sleep research through case studies and synthesis.