psychic staring effect - scopaesthesia - The Skeptic's Dictionary (original) (raw)
"Statistical significance can be totally meaningless and it usually is." -- James Alcock
"Lots of things published in the name of science are nonsense."*
The psychic staring effect (PSE) is the alleged psychic ability to know when you are being stared at. Many people claim that even though they cannot see the person who is staring at them, they can "sense" it. Some claim that they can make a person in front of them turn around simply by staring at the back of the person's neck. Studies have found that about 90% of those asked think they can sense when people they can't see are staring at them (Hood 2009, ch. 9).
The first scientific studies of the PSE were reported in 1898 by British psychologist Edward B. Titchener. All his results were negative. His report in Science does not state how many subjects were involved or how the studies were conducted. Titchener dismissed telepathy as something no "scientifically-minded psychologist" would believe in.* He realized that the experiments would be considered a waste of time by most scientists, but he justified them by noting that they could serve to undermine a deep and widespread superstition. Titchener seems to have been proven wrong. This and many other widespread superstitions have failed to be validated in scientific experiments, yet belief in them continues unabated in the public consciousness.
More to the liking of the general public is the work of Rupert Sheldrake, who has done several informal and formal studies that he thinks show that the PSE is real. Replicating Sheldrake's work has been problematic, however. When a truly random process and other strict controls are used, the results are negative. Critics of Sheldrake's work, such as Marks and Colwell (2000) and Hood (2009), suspect that his positive results occur when he doesn't use a truly random sequence in his tests. What seems to be happening is that many participants are learning to detect nonrandom sequences. Giving participants feedback in trials with nonrandom sequences also seems to improve performance. Brugger and Taylor (2003) have argued that the data in many ESP experiments indicate that some people have an ability to subconsciously recognize hidden patterns (“implicit sequence learning”). Marks and Colwell argue that the non-randomness of the sequences allows pattern recognition to occur among some of the participants, and that this alone could account for the positive statistical results.
Michael Shermer added to the list of faults in Sheldrake's work, claiming Sheldrake was guilty of confirmation bias and experimenter bias.
A major problem with parapsychology's effort to verify widespread superstitions is that the believers put too much emphasis on anecdotes and clinical trials and not enough emphasis on prior plausibility. Parapsychologists are analogous to so-called alternative medicine advocates: they are evidence-based without being science-based. Parapsychologists create all the trappings of science in their clinical trials, but they do not critically evaluate some of the inherent problems with clinical trials that involve people, especially people who have a vested interest in the outcome of the studies. The media routinely report results of such research as offering strong support for the efficacy of such things as distantprayer,alternative medicine, memory in water,dowsing,communicating with the dead, and the like. Faulty randomization procedures is just one of many problems with such studies. As Kimball Atwood says of medical clinical trials:
...clinical trials are necessarily less powered and more prone to numerous other sources of error: biases, whether conscious or not, causing or resulting from non-comparable experimental and control groups, cuing of subjects, post-hoc analyses, multiple testing artifacts, unrecognized confounding of data due to subjects’ own motivations, non-publication of results, inappropriate statistical analyses, conclusions that don’t follow from the data, inappropriate pooling of non-significant data from several, small studies to produce an aggregate that appears statistically significant, fraud, and more*....
As I note in the entry on the psi-assumption:
Here are just a few possible explanations for data indicating significantly greater than chance results in psi experiments: selective reporting, poor experimental design, inadequate number of individuals in the study, inadequate number of trials in the experiment, inadequate number of experiments (e.g., drawing strong conclusions from single studies),file-drawer effect (formeta-studies), deliberate fraud, errors in calibration, inadequate randomization procedures,* software errors, [equipment effects due to changes in temperature, moisture, altitude, etc.] and various kinds of statistical errors. If any of the above occur, it is possible that the data would indicate performance at significantly greater than expected by chance and would make it appear as if there had been a transfer of information when there had not been any such transfer. It is also possible that information is being transferred, but not telepathically, throughsensory leakage. Or, maybe some people have an ability to subconsciously recognize hidden patterns.
Sheldrake responded to the criticism of his randomization procedures by defending the process of using a coin flip to determine whether staring or not staring would be the next test item in the sequence during his staring experiments. I've noted in other entries that intuitive randomization procedures are not always what they seem to be.
There is no reason to believe that the laws of probability, which are purely formal and ideal, should apply directly to any finite set of events. It may be true that the odds of a coin coming up heads or tails is 1 in 2, but that gives us no information as to what will happen in the real world for any given number of tosses. Ideally, in a large number of tosses, heads should come up 50% of the time. In the real world, there is no way to know exactly how many times heads will come up in, say, ten million tosses. We can be pretty sure the number will be very close to five million (assuming a fair coin and a fair toss), but we cannot know a priori exactly how many times heads will come up.
Studies comparing random strings with random strings, to simulate guessing numbers or cards, have found significant departures from what would be expected theoretically by chance (Alcock 1981: 159). For example, Harvie “selected 50,000 digits from various sources of random numbers and used them to represent “target cards” in anESP experiment. Instead of having subjects make guesses, a series of 50,000 random numbers were produced by a computer.” He found a hit rate that was significantly less than what would be predicted by chance (Alcock 1981: 158-159).
In the 1930s, Walter Pitkin of Columbia University printed up 200,000 cards, half red and half blue, with 40,000 of each of the fiveESP card symbols. The cards were mechanically shuffled and read by a machine. The result was two lists of 100,000 randomly selected symbols. One list would represent chance distribution of the symbols and the other would represent chance guessing of the symbols. However, the actual matches and what would be predicted by accepted odds didn’t match up. The total number was 2% under mathematical expectancy. Runs of 5 matching pairs were 25% under and runs of 7 were 59% greater than mathematical expectancy (Christopher 1970: 27-28). The point is not whether these runs are typical in a real world of real randomness or whether they represent some peculiarity of the shuffling machine or some other quirk. The point is that it is not justified to assume that statistical probability based on true randomness and a very large number of instances applies without further consideration to any finite operation in the real world such as [flipping a coin,] guessing symbols in decks of 25 cards shuffled who knows how or how often, or rolling dice, or trying to affect a random number generator with one's mind. As Alcock put it: “If such significant variation can be produced by comparing random strings with random strings, then the assumption that any significant variation from chance is due to psi seems untenable (Alcock 1981: 158-159).”
Just as no person has yet been found who can move a pencil with his thoughts or correctly identify a hidden drawing by mental perception (though many can appear to do so through trickery), there has yet to be found a single person who can tell by psychic means when people are staring at him.
And, despite what evidence Rupert Sheldrake's studies might produce, there really are no psychic parrots.
See also topical index: paranormal andA Short History of Psi Research by Robert Todd Carroll.
further reading
books and articles
Alcock, James E. (1981). Parapsychology: Science or Magic? Pergamon Press.
Hood, Bruce. 2009. SuperSense: Why We Believe in the Unbelievable. HarperCollins. See my review of this book here.
Neher, Andrew The Psychology of Transcendence (1980). This Prentice-Hall book is out of print. Used copies may be available from Amazon.com. It was reissued in 1990 by Dover Books as Paranormal and Transcendental Experience.
Shermer, Michael. 2005. Rupert's Resonance. Scientific American, October.
Titchener, E. B. "The 'feeling of being stared at.'" Science, 1898.
Vyse, Stuart A. Believing in Magic: The Psychology of Superstition (Oxford University Press 2000).
websites
Sheldrake's response to Marks and Colwell
Robert Baker's response to Sheldrake
Rupert Sheldrake: The delightful crackpot by David Bowman
The amazing ideas of Rupert Sheldrake by John Blanton
Last updated 14-Aug-2011