Melinda Wenner Moyer’s article on “Why We Believe Conspiracy Theories” took me back about a decade to when I was a member of a team of HIV/AIDS researchers and activists battling the denialists who variously argued that HIV did not exist, was not the cause of AIDS or was created in government laboratories for evil purposes. At that time, AIDS denialists influenced national policies on HIV/AIDS in South Africa, costing an estimate of more than 300,000 lives, and manipulated vulnerable individuals worldwide to make health-threatening choices.

Much of what Moyer describes resonates with my experiences (such as threats and smears regularly sent to my university’s administration or me) and the collective strategies employed by my colleagues and me. We, too, found that most of the more prominent HIV/AID denialists were also members of other conspiracy groups, whether health-related or more generally.

This link was a weakness we could exploit, particularly for those with academic connections: our pointing out to universities that a faculty member published on, say, the existence of the Loch Ness Monster or how the U.S. faked the moon landing helped to erode that person’s intramural credibility while having a positive effect on individuals who believed they were receiving expert advice. And we could reason with and better educate such at-risk people, something that was utterly unproductive with the hard-core naysayers.

The AIDS denialists are still around. Their damaging effects have diminished in recent years, but many of them are now active in the “anti-vaxxer” movement, peddling the lies that compromise vaccine uptake by a significant number of people, with adverse public health outcomes that are all too apparent. Publicly naming and shaming these conspiracy theorists for who and what they really are—and what they also believe—can be an effective tactic. The gloves should come well and truly off.

JOHN P. MOORE Weill Cornell Medicine and
SCIENTIFIC AMERICAN’s board of advisers

No writer on the topic of conspiracy theories can afford to overlook the remarkable 1964 essay “The Paranoid Style in American Politics,” by Richard Hofstadter, one of the great scholars of American history, who was active during the 1940s to 1960s. It has been reprinted many times and is currently available on the Internet. Hofstadter traces the recurrent waves of political paranoia in American society going back to the 18th century, listing the targets of those waves, the similarities in how certain groups have responded to those perceived threats, and the important differences between normal fears and concerns and what he terms the “paranoid style.” His analysis clearly parallels that proposed in Moyer’s article. The targets have changed over the years, but the story and the style of its telling have not.

Port Hadlock, Wash.

Moyer notes that the perceived powerlessness in the face of real and imagined social forces creates susceptibility to conspiracy theories. Many believers in such theories were driven into economic insecurity, despite years of hard work in often highly skilled occupations that did not require college degrees. People who are financially secure and who have an education conducive to seeking out and evaluating evidence are less vulnerable to such notions.



In “The Orca’s Sorrow,” Barbara J. King presents accumulated observations that suggest that animals grieve. Everyday observations strongly support that animals experience emotions similarly to humans. The reverse would be quite surprising because it would somehow call for the evolution of emotions strictly or separately in our species. Emotions are a key driver of behavior and clearly have deep and adaptive evolutionary roots. Occam’s razor and sound science place the burden of proof on those who deny animals have them. A corollary is that cruelty to animals is as intolerable as cruelty to our fellow humans.

Swampscott, Mass.

KING REPLIES: Emotions have indeed evolved widely in the animal kingdom to guide behavior. Yet denial of this cross-species similarity still happens routinely: In my article, I describe how the orca Tahlequah carried her dead calf for 17 days. In the Guardian, zoological writer and consultant Jules Howard writes that classifying her behavior as grief means “making a case that rests on faith not on scientific endeavour.” Howard has it precisely backward, though; it’s good science to recognize visible evidence of animal emotion and of evolutionary continuity. We owe it to animals to see them for who they are.


In “The Undiscovered Illness,” Simon Makin states that unipolar mania—mania that does not occur alongside depressive episodes—is not listed as a “distinct and unalloyed condition” in diagnostic systems. But that does not mean it is neglected everywhere. The diagnosis features in clinical practice, perhaps most commonly in countries where formal classification systems, such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), are used as intended—as general guides rather than checkbox tools.

As a psychiatrist familiar with the DSM but not compelled to use it, I used to be annoyed whenever I saw it described as “the psychiatrist’s bible.” On reflection, though, that is quite a good description because in practice, some psychiatrists (chiefly in the U.S.) consult the DSM commonly, others ignore it completely and a great majority draw on it selectively, focusing on the parts that make sense to them and completely ignoring large sections that do not.

Trinity College Dublin


Based on personal experience of the threat of Hurricanes Florence and Michael, Zeynep Tufekci argues in “Big Data and Small Decisions” [The Intersection] that when one is presented with a deluge of data, even a simple binary choice (stay or go, in her case) can be difficult. Unable to make a data-driven decision, she notes that she followed the advice of her neighbors.

Another way to frame this dilemma would be through the decision-making framework proposed by David Snowden, formerly at IBM and now at Cognitive Edge. Rather than ponder “What to do?” he essentially suggested we ask, “What kind of problem is this?”

Some well-structured problems are complicated, with cause and effect reasonably clear, so decision-making may call for experts who can sort through enormous data sets (the domain of “good practice“). But problems where cause and effect are nonlinear and nonproportional and where elements are volatile, uncertain, complex and ambiguous (VUCA) are in the domain of “emergence.” An example is a hurricane scenario akin to Tufekci’s, for which crowdsourcing via neighbors who, it is hoped, have more knowledge and practical wisdom of the area may be a reasonable way to make the choice of staying or leaving.

LARRY M. STARR Director, Doctor of Management in Strategic Leadership program and Doctor of Philosophy in Complex Systems Leadership program,
Thomas Jefferson University