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CHAPTER 1
The Science of Deception
On the morning of July 19, 2012, I listened with interest as two former CIA agents, Philip Houston and Michael Floyd, were interviewed during an episode of The Diane Rehm Show on National Public Radio about their new book, Spy the Lie. The book was a popular-press attempt to share the secrets of lie detection with the book-buying public. It seemed to me that some of what they were saying was right on target, while some of their other advice was pure bunk. What really caught my ear, however, was their response to one particular caller who asserted that we might not be able to detect lies very well. Some liars, this caller said, were really good at lying. The caller referenced Robert Hanssen, the FBI agent who spied against the United States for Russia and successfully evaded detection for more than twenty years. Didn't Robert Hanssen exemplify our inability to catch some lies and liars?
The authors replied that their approach to detecting lies was not based on scientific research but on anecdotes and personal experience. Experience had taught them that their approach was highly effective.
Wow! I found this response really curious. First, the caller had not referenced academic research. The caller's comments involved anecdote, not science. As we will see in chapter 3, much research shows that people are poor lie detectors. Science clearly contradicts some of these authors' assertions. But why bring scientific research up at that time? Second, I did not expect the authors to volunteer information implying that their view might contradict scientific evidence, and to openly express their hopeful desire that listeners trust their anecdotes over science. Is that really persuasive? Presumably, they were on the radio to promote their book. To my ear, they had just undercut themselves. Third, while they might have had good reasons to believe that the lies they detected were valid, how could they have known how many lies they had missed? They had no way of knowing how often they had been suckered. The best lies are never detected. In the lab, researchers know what is truth and what is lie. In everyday life, we often cannot know what is truth and what is lie with 100 percent certainty. Sometimes we are wrong and never know we are wrong. This was the caller's point, and it was a good one. As we will see in chapter 13, some liars are really good at telling convincing lies.
Here is an observation from my own research that applies to using examples as evidence for what works in lie detection. From 2007 to 2010, I had funding from the National Science Foundation to create a collection of videotaped truths and lies for use in deception detection research. I ended up creating more than three hundred taped interviews during that time. (I have made more since then with funding from the FBI.) I have watched these three hundred interviews many times over the years. For every liar you can point to multiple things that seem to give the lie away. If you watch the tapes carefully, the clues are almost always there to see.
There are, however, a couple important catches. First, what gives away one liar is usually different from the signals that reveal the next liar. The signs seem to be unique to the particular lie, and the science discussed later in the book backs this up. Second, if you go through the tapes carefully, for every liar who seems to be exposed by a telltale sign or collection of clues, there are honest people who act the same way and do the same things. That is, most of the behaviors that seem to give away liars also serve to misclassify honest people.
That honest people can appear deceptive is one of the many insights I have gained from watching so many tapes where the actual truth (called "ground truth" by researchers) is known for certain. If you know some statement is a lie, you can usually point to clues indicating deceit. That is because of hindsight. Pointing out clues with hindsight is one thing. Using those same behaviors to correctly distinguish truthful from deceptive communication is quite another. Different liars do different things, and some honest people do those things too. When I watch tapes of truths and lies without knowing in advance which is which, whether some behavior indicates a lie is not entirely clear. I find that when I don't know who is a liar beforehand, I miss some lies, and I falsely suspect some honest people of deceit. Many times, I am just not sure one way or the other. Cherry-picking examples is easy and makes for persuasive and appealing anecdotes. Cherry-picked examples informed by hindsight do not lead to useful knowledge and understanding that extend beyond the specific example.
This makes me suspicious of knowledge by common sense, anecdote, and personal experience. I want scientifically defensible evidence. If what I think does not mesh with the data, we have to question what I think. This principle, by the way, is not only useful in assessing the quality of advice. It is also a good way to detect lies. There is much more on the use of evidence in lie detection in chapter 14.
What the scientific research says (at least up through 2006; current findings are more nuanced) is that people are typically not very good at accurately distinguishing truths from lies. The research behind this conclusion is extensive and solid, and that will be covered in chapter 3.
Nevertheless, we should not be too quick to dismiss professionals with expertise in interrogation and interviewing who believe there are ways to catch liars and detect lies. Just because their evidence is anecdotal does not mean that it is false or necessarily incorrect. In fact, my research described in this book is, in part, an effort to use science to reconcile research findings with practitioners' experience. That is, rather than trying to debunk practitioners, as so many of my fellow academics try to do, I began designing experiments to explain the differences between successful interrogations and typical deception detection laboratory experiments. Much of the research, I have come to believe, tells us more about lie detection in the lab than in real life.
A more accurate scientific conclusion is that people were not very good at detecting lies in lie-detection experiments published prior to 2006. The research did not prove that lies can't be detected! The research showed that lies cannot be accurately detected in the type of experiments that were used to study lie detection. Conclusions from research are always limited by how the research was done. In the case of research on the accuracy of deception detection, I have come to believe that this is a critical, game-changing point (see chapters 12, 13, and 14, and compare the research reviewed in chapter 14 to that reviewed in chapter 3).
I have come to believe that many approaches to lie detection are ineffectual, especially those that involve what I call "cues." Some approaches do have more promise. Improving accuracy involves understanding what works, what does not work, and why. Because I am a social scientist, anecdotes, yarns, and good stories are not going to cut it as evidence. Scientific evidence is required. Real-world observations are critical in generating the ideas that I research, but such observations are only the starting point. I prove my points with controlled experiments. I insist that my results replicate. I think my readers should expect this. And it is this insistence on scientific evidence that can be replicated that makes my approach better than the alternative approaches and theories out there.
This, however, does not mean I have an aversion to good stories. I began the chapter with a story about listening to the radio one morning. Then there was a second story about my repeated viewing of the NSF deception tapes. Stories are great for explaining ideas, making ideas understandable, and generating research ideas. Stories are essential for making points interesting and engaging. I will tell plenty of stories throughout the book. I will also present hard data that are scientifically defensible and have passed the dual tests of replication and publication in peer-reviewed academic journals. At the end of the day, I am doing science, and this book is about a scientific approach to deception and deception detection.
Speaking of stories, here is another, and while it is a digression, I think it addresses a question many readers may have at the outset. People tend to find deception interesting. People are naturally curious about lies and lie detection. And it's not every day that people meet a deception detection researcher. Actually, there are not many of us around to meet. People who have sustained careers studying the social science of deception probably number less than two or three dozen worldwide. Anyway, when people find out that I study deception, one common question is how and why I got into deception research. This is a question that I have been asked too many times to count, and this is a good time and place to answer it.
The truth is that I stumbled into deception research. I became a deception researcher largely out of serendipity. Remaining a deception researcher was opportunistic. Back in grade school, I was very interested in the physical sciences. Other little kids wanted to be policemen or firemen or astronauts, but I wanted to be a geologist when I grew up. That changed in junior high and high school. I had a strong fascination for why people did things and with social dynamics. One of my nicknames in high school was Freud; but I wasn't interested in psychological disorders. I was curious about normal, everyday social behavior. And I still am. What I call truth-default theory (TDT) is about deception in the lives of normal people in their everyday social interactions.
When I was in high school, it was unclear whether I could go to college. I'm dyslexic. A psychologist told my parents it would be a waste of money to send me to college. I was sure to flunk out. Fortunately for me, my grades were good enough, and I scored well enough on the ACT test, to be admitted to all the colleges to which I applied. My parents agreed to give me a chance, as long as I selected a public, in-state university with low tuition. I chose Northern Arizona University.
When I went off to college, I knew I would be a psychology major. As I learned more, I gravitated toward persuasion as a topic. I grew up the son of a real estate salesperson, and sales and social influence intrigued me. During my third year in college, I learned that persuasion was a topic of research, and when I went on to graduate school, that was the topic that drew me in. I switched from psychology to communication mostly for practical reasons. It was easier to get into top-rated graduate programs with full-ride funding in communication than in the more competitive field of psychology. I did both my MA thesis and my PhD thesis on the topic of persuasion. I teach classes on persuasion to this day. It was early in graduate school that I started picking up interpersonal-communication processes as a second area of focus.
By the time I finished my first semester of graduate school, I pretty much knew my career choice was in academia and that I wanted to be a professor. It turned out that I had some talent in research and that I enjoyed teaching. I managed to get into the highly regarded PhD program at Michigan State University, where two leaders in persuasion (Gerry Miller and Frank Boster) were on the faculty. Miller's health was in decline, and I ended up studying under Boster.
About halfway through my PhD studies, Michigan State hired a new professor by the name of Steve McCornack. Steve and I were nearly the same age, and we had much in common. More than that, I was really impressed by Steve. I thought (and still do) that he was really smart. I like smart people. As an undergraduate student, Steve had done a research project on deception that had won an international award and been published. Writing and publishing an award-winning research paper as an undergraduate — wow! Even more than just the award and publication, his ideas and findings were really cool.
Prior to Steve's, there had been only one other study on lie detection among people who knew each other. The prevailing wisdom at the time was that the better you knew someone, the better you would be at detecting their lies. Knowledge of another person was expected to enhance deception detection accuracy. Steve, however, predicted the exact opposite. The better you know someone, the more you tend to think you can tell when they lie, but also the more you think they wouldn't lie to you. Relationship closeness, according to Steve, makes us truth-biased. This was intriguing. I read Steve's research, I heard him present his research, and I knew this was someone I wanted to collaborate with and learn from.
When Steve joined the faculty at Michigan State, I arranged to be assigned as his research assistant. My advisor, Frank Boster, was graduate director, and getting the assignment to Steve as his assistant was a simple matter. Over the next couple of years, we did a number of studies together. I just got sucked into deception research. Each study led to more questions. The more I learned about deception, the more a set of challenging puzzles became apparent to me. One thing led to another, and now I am writing this book twenty-five years later. It took a quarter century, but I now have answers that hold up and are worth sharing.
What I like most about deception research, and probably the biggest reason I stuck with it, is that in the realm of deception research, most things are not what they seem. Common sense is often wrong, and surprising twists come one after another. Too much social science is content with documenting the obvious. Deception research, in contrast, presents a challenging set of puzzles to solve.
What drew me to deception research is similar to what attracts my wife and me to certain television dramas. We get bored quickly with series that are conventional and predictable. We like complex plotlines and unanticipated developments. This is what I really like about Game of Thrones (both the HBO series and the books) and Lonesome Dove (book and miniseries).
The other thing that has kept me doing deception research is that the need and potential for improvement have been apparent to me since my first involvement as a graduate student. It seemed to me that deception research could do better. The theory needed improvement, the methodology could be made better, and the findings could be stronger and more coherent. In short, there was plenty of opportunity to make a scientific splash. So many areas of social science research evolve into super-specialized endeavors looking at ever-more microscopic issues of little interest to anyone outside the sub-sub-subspecialty. But this was not the case in deception research. So I stuck with deception as a topic and gradually solved one puzzle after another.
PRIOR DECEPTION RESEARCH AND THE NEED FOR A NEW APPROACH TO DECEPTION
This book offers a new approach to understanding deception and deception detection: truth-default theory. The main impetuses behind the theory and this book were my growing dissatisfaction with the prevailing theory and my desire to solve some challenging puzzles stemming from the research findings. What was needed to really understand deception and deception detection was a new theory. It has taken much research, much persistence, some talented and insightful collaborators, and more than a little luck to get to this point.
I have several goals for TDT besides just offering an explanation of deception and deception detection. For one, the theory needs to solve some persistent mysteries. There are a number of odd things in the existing scientific literature that (until TDT) did not seem to make much sense. A coherent way to make sense of the literature is needed. Second, there is a need for a coherent logic that points in new directions and yields new findings. Much deception research seems to be spinning its wheels, so to speak. The research needs to get out of an intellectual rut. Most of all, the theory needs to make predictions that turn out to be right. It seems to me that older theories are better at excuse generation than accurate prediction. Findings really don't support the older theories, but the failures are either ignored or explained away. I want a theory that when put to the test will clearly and unequivocally pass. In short, the aim is to provide a theory of deception that makes past findings coherent, leads to interesting new discoveries, and, most of all, passes scientific muster.
The previous research on deception is diverse. In this and the next two chapters, I will focus on four interrelated questions that have received large amounts of attention. As research has progressed, well-documented answers have emerged. The four questions are as follows:
1. What do people look for in order to distinguish between whether someone else is honest or lying?
(Continues…)
Excerpted from "Duped"
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