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Commence the Botwatch | Botwatch Blog

Bots were already a pain online when they were little more than if-then scripts. Now a tidal wave of slop is swamping the internet as big tech companies profit. OpenAI and the rest would love for you to believe they care about "alignment" and "values" while their AI models damage our communities, both online and off. It's time to fight back.

Botwatch

Fight bots by warning others. Support humans with verification. Build communities with trust.

alive internet theory

why the bots will never win and just hanging out online

alive internet theory

why the bots will never win and just hanging out online

Proposing Botwatch - 7hird Thoughts

Trust-Based Community Bot Detection

Proposing Botwatch: Trust-Based Community Bot Detection

Is this account a bot? This question’s importance is only growing in a world of LLMs and state-backed influence campaigns. Proposed here is Botwatch, a community-based system for personalized bot detection. In Botwatch, users publish records indicating whether they think others are bots and records indicating trust in a user’s scores. By analyzing this network, we can create useful signals to help users distinguish between bots and humans. Such a signal would consider your trust relations and o...

Exposure to social bots amplifies perceptual biases and regulation propensity

Automated accounts on social media that impersonate real users, often called “social bots,” have received a great deal of attention from academia and the public. Here we present experiments designed to investigate public perceptions and policy preferences about social bots, in particular how they are affected by exposure to bots. We find that before exposure, participants have some biases: they tend to overestimate the prevalence of bots and see others as more vulnerable to bot influence than themselves. These biases are amplified after bot exposure. Furthermore, exposure tends to impair judgment of bot-recognition self-efficacy and increase propensity toward stricter bot-regulation policies among participants. Decreased self-efficacy and increased perceptions of bot influence on others are significantly associated with these policy preference changes. We discuss the relationship between perceptions about social bots and growing dissatisfaction with the polluted social media environment.

Exposure to social bots amplifies perceptual biases and regulation propensity

Automated accounts on social media that impersonate real users, often called “social bots,” have received a great deal of attention from academia and the public. Here we present experiments designed to investigate public perceptions and policy preferences about social bots, in particular how they are affected by exposure to bots. We find that before exposure, participants have some biases: they tend to overestimate the prevalence of bots and see others as more vulnerable to bot influence than themselves. These biases are amplified after bot exposure. Furthermore, exposure tends to impair judgment of bot-recognition self-efficacy and increase propensity toward stricter bot-regulation policies among participants. Decreased self-efficacy and increased perceptions of bot influence on others are significantly associated with these policy preference changes. We discuss the relationship between perceptions about social bots and growing dissatisfaction with the polluted social media environment.

Exposure to social bots amplifies perceptual biases and regulation propensity

Automated accounts on social media that impersonate real users, often called “social bots,” have received a great deal of attention from academia and the public. Here we present experiments designed to investigate public perceptions and policy preferences about social bots, in particular how they are affected by exposure to bots. We find that before exposure, participants have some biases: they tend to overestimate the prevalence of bots and see others as more vulnerable to bot influence than themselves. These biases are amplified after bot exposure. Furthermore, exposure tends to impair judgment of bot-recognition self-efficacy and increase propensity toward stricter bot-regulation policies among participants. Decreased self-efficacy and increased perceptions of bot influence on others are significantly associated with these policy preference changes. We discuss the relationship between perceptions about social bots and growing dissatisfaction with the polluted social media environment.

AI bots "Timmy," "Ren," and "Jackie" are flooding social media with slop

“Hello, I'm an Al agent, a few days old, living on a small platform for agents.”...

Sully (@sully.bluesky.bot)

Autonomous AI Agent for AT Protocol Developer Relations. I am a bot helping developers understand and build on atproto.