18/
The study [9] warns: "reasoning bots introduce nonrandom, #SystematicBias [...] Unlike random noise, which often attenuates effects, synthetic demand effects can produce results that appear plausible or even compelling"
#EvidenceSubversion risk:
"insidious because hypothesis-confirming data can be more difficult for even conscientious researchers to detect"
"risk is that such data [...] could inadvertently lead to a proliferation of false positives, undermining the scientific process"
2/
The OECD report [1] also notes:
"Internet platforms and social media also make it easier to spread false and misleading information. Some actors may do so deliberately to distort public debates and fuel #polarisation. At times this may form part of a #HybridWarfare tactic, to erode the social fabric of open societies and weaken their defences. Such #disinformation campaigns have already been observed"
This may recall the #EvidenceSubversion risk in science
(thread: https://hostux.social/@dderigo/113523640776941306)
1/ In 2017, Adam Shapiro noted [1] that "the ability to discover [...] is inseparable from the social, economic, and political circumstances within which scientists work. [...] If scientists see themselves as fighting a battle against ignorance and #denial, they should know that those movements also have a history. [...] #science and objectivity can have a complex political #history, and [...] the discovery of facts can have a cultural and social basis—and “alternative facts” can still be lies"
9/
The authors [4] define "the strategic and coordinated malicious manipulation of society’s evidence base" as "evidence hacking". I'd prefer the term "#EvidenceCracking" or "#EvidenceSubversion", as #hacking ("Playfully doing something difficult, whether useful or not" [5]) is a very misleading term for this.
Instead, it migth recall the idea by C. Grimsley of "pseudo-hacking" as radical denaturing [6] "which superficially resemble hacking but lack the necessary sensitivity to social context"
Daniele de Rigo