Post #1276204

2022-12-10 05:15 UTC

More subtly, could bad-faith actors compromise our systems by generating fake but plausible data to conceal actual patterns? AI chat tools seem perfect for such attacks. A corporation might try to prolong current operations and maintain profits by generating fake survey datasets or large volumes of bogus citizen science records that conceal habitat quality, minimise evidence of harm or fake the size of species populations. How would we detect and respond to such deception? (6/6)

Replies (2)

@KorimakoEcology@ecoevo.social 2022-12-11 03:37

@dhobern That's an interesting thought. A few months ago I tweeted about how iNaturalist observations were being used by ecologists in lots of development consent applications now, which led to this story (they asked to interview me but I declined). I'm not sure though how fake data would be helpful for bad actors in these examples though. https://www.rnz.co.nz/national/programmes/afternoons/audio/2018857793/using-inaturalist-community-to-keep-an-eye-on-urban-sprawl

Open ##1276205
@joncounts@mastodon.nz 2022-12-11 07:48

@dhobern @KorimakoEcology Interesting thread. If bad actors ever figured out how to flood #iNaturalist with fake accounts and fake observations, that would be a huge headache. I'd like to think that a bot generating lots of implausible observations would quickly get flagged. Citizen science data projects need to be vigilant that people really are people. Also important is basing land management decisions on the consensus of more than one source of data (many observers, many datasets).

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