Scientific American - 09.2019

Illustration by Bud Cook September 2019, ScientificAmerican.com 91

paign and leaked certain details to the public to dam-
age reputations.
Having monitored misinformation in eight elections
around the world since 2016, I have observed a shift in
tactics and techniques. The most effective disinforma-
tion has always been that which has a kernel of truth to
it, and indeed most of the content being disseminated
now is not fake—it is misleading. Instead of wholly fab-
ricated stories, influence agents are reframing genuine
content and using hyperbolic headlines. The strategy
involves connecting genuine content with polarizing
topics or people. Because bad actors are always one step
(or many steps) ahead of platform moderation, they are
relabeling emotive disinformation as satire so that it
will not get picked up by fact-checking processes. In
these efforts, context, rather than content, is being
weap onized. The result is intentional chaos.
Take, for example, the edited video of House Speak-

er Nancy Pelosi that circulated this past May. It was a

genuine video, but an agent of disinformation slowed

down the video and then posted that clip to make it

seem that Pelosi was slurring her words. Just as in-

tended, some viewers immediately began speculating

that Pelosi was drunk, and the video spread on social

media. Then the mainstream media picked it up,

which undoubtedly made many more people aware of

the video than would have originally encountered it.

Research has found that traditionally reporting on

misleading content can potentially cause more harm.

Our brains are wired to rely on heuristics, or mental

shortcuts, to help us judge credibility. As a result, rep-

etition and familiarity are two of the most effective

mechanisms for ingraining misleading narratives,

even when viewers have received contextual informa-

tion explaining why they should know a narrative

is not true.

Physics is the most mature science,

and physicists are obsessive on the

subject of truth. There is an actual universe out

there. The central miracle is that there are simple underlying

laws, expressed in the precise language of mathematics, which

`D³lxä`ߞUxžîÍ5šDîäDžljǚāäž`žäîäl ̧³ÜîîßD‡`ž³`xßîDž³îžxä

Uøîž³lxßxxä ̧…` ̧³‰lx³`xÍ=xÜþx§xDß³xl ̧øߧxää ̧³iîšß ̧øš-

out history, we have again and again found out that some princi-

ple we thought was central to the ultimate description of reality

isn’t quite right.

5 ̧‰øßx ̧øîš ̧ÿîšxÿ ̧ߧlÿ ̧ߦäjÿxšDþxîšx ̧ߞxäD³lUøž§l

xĀÇxߞ­x³îäî ̧îxäîîšx­Ížäî ̧ߞ`D§§ājä­xîš ̧lÿ ̧ߦäÍ ̧ß

example, physicists predicted the existence of the Higgs boson par-

ticle in 1964, built the Large Hadron Collider (LHC) at CERN in the

late 1990s and early 2000s, and found physical evidence of the

Higgs in 2012. Other times we can’t build the experiment—it is too

massive or expensive or would be impossible with available tech-

nology. So we try thought experiments that pull from the existing

infrastructure of existing mathematical laws and experimental data.

xßxÜä ̧³xi5šx` ̧³`xÇî ̧…äÇD`xxšDäUxx³D``xÇîxl

䞳`xîšxxDߧā¿ ́ććäÍ

øîî ̧§ ̧ ̧¦Dîä­D§§xßäÇD`xäjā ̧øšDþxî ̧

use more powerful resolution. That’s why the LHC is 17 miles

around—to produce the huge energies needed to probe tiny dis-

tances between particles. But at some point, something bad hap-

Çx³äÍ? ̧øܧ§Çøî ̧øîäø`šD³x³ ̧ß­ ̧øäD­ ̧ø³î ̧…x³xߐāî ̧§ ̧ ̧¦

Dîäø`šDä­D§§Užî ̧…äÇD`xîšDîā ̧øܧ§D`îøD§§ā`ßxDîxDU§D`¦š ̧§x

ž³äîxDlÍ? ̧øßDîîx­Çîî ̧äxxÿšDîžäž³äžlx­D¦xäžîž­Ç ̧ääžU§xî ̧

l ̧ä ̧jD³lîšx³ ̧îž ̧³ ̧…äÇD`xxUßxD¦äl ̧ÿ³Í

At any moment in history, we can understand some aspects

of the world but not everything. When a revolutionary change

Uߞ³äž³­ ̧ßx ̧…îšx§DߐxßǞ`îøßxjÿxšDþxî ̧ßx` ̧³‰øßxÿšDî

ÿx¦³xÿÍ5šx ̧§l³äDßxä§ÇDßî ̧…îšxîßøîšUøîšDþxî ̧

UxäÇø³Dß ̧ø³lD³lÇøîUD`¦ž³î ̧îšx§DߐxßǞ`îøßxž³D³xÿÿDāÍ

Nima Arkani-Hamed, a professor in the School of Natural Sciences

at the Institute for Advanced Study in Princeton, N.J., as told to

Brooke Borel

H O W A T H E O R E T I C A L P H Y S I C I S T

SEARCHES FOR ANSWERS