In a fascinating AI social experiment, 500 chatbots took center stage
on a pseudo-Twitter battleground, crafting a narrative far more serene than the
chaotic madness of real-life social media.
Computational social scientist
Petter Törnberg and his team created a digital landscape full of personas, politics, and a dash of
unpredictability, revealing insights that may redefine our virtual landscapes.
Törnberg breathed life into 500 Artificial Intelligence (AI) chatbots, each a digital puppet with a
distinct persona—age, gender, income, religion, politics, and peculiar
preferences, all of which he explained to Business Insider. The idea was to create 500 personalities with which to populate an
imagined, custom-made microblogging Twitter-like platform. It’s worth remembering that
Twitter has been labelled as the platform most likely to contain misinformation
and hate speech.
“Hundreds of chatbots could show us how to make social media less toxic” @newscientist reports on how we “created 500 chatbots powered by a large language model (LLM) and got them to interact with each other as if they were on a social media platform” https://t.co/tFz6HJvIJi
— Petter Törnberg (@pettertornberg) October 20, 2023
Echo Chambers, Discoveries, and Algorithms
The bots, fueled by news from July 1, 2020, stepped into a
Twitter-esque arena, embracing three distinct models. The “Echo Chamber”, a
tranquil haven resonating with shared ideologies; “Discover,” a
whirlwind of high engagement veiled in occasional negativity; and the
“Bridging Algorithm,” where opposing bots found unlikely camaraderie
amid resounding engagement. The question being posed was whether these
algorithmic creations could pave the way to a less polarized online utopia.
The Echo Chamber highlighted posts from other bots with shared
ideologies. This platform was calm, but quiet. Discover populated feeds
with the posts with the most likes. Predictably there was high, but often
negative, engagement. The Bridging Algorithm showed bots the posts with the most
likes, but only from the bots with opposite political beliefs. This Twitter
also saw high engagement, but surprisingly, the bots often found common ground.
Surprisingly Less Hate
So, the takeaway is that discussion of partisan issues needn’t result
in clashes, provided that the numbers of participants on both sides are roughly
equal. Törnberg told Insider that when discussing partisan issues “if
50% of the people you agree with vote for a different party than you do, that
reduces polarization. Your partisan identity is not being activated.”
Interestingly, political scientist Lisa Argyle from Brigham Young
University sees a glimmer of hope. She notes that these AI models, with
identity profiles mimicking humans, might be the heralds of a more civil social
media discourse. Perhaps, in this algorithmic dance, lies the key to a
harmonious online future.
In a fascinating AI social experiment, 500 chatbots took center stage
on a pseudo-Twitter battleground, crafting a narrative far more serene than the
chaotic madness of real-life social media.
Computational social scientist
Petter Törnberg and his team created a digital landscape full of personas, politics, and a dash of
unpredictability, revealing insights that may redefine our virtual landscapes.
Törnberg breathed life into 500 Artificial Intelligence (AI) chatbots, each a digital puppet with a
distinct persona—age, gender, income, religion, politics, and peculiar
preferences, all of which he explained to Business Insider. The idea was to create 500 personalities with which to populate an
imagined, custom-made microblogging Twitter-like platform. It’s worth remembering that
Twitter has been labelled as the platform most likely to contain misinformation
and hate speech.
“Hundreds of chatbots could show us how to make social media less toxic” @newscientist reports on how we “created 500 chatbots powered by a large language model (LLM) and got them to interact with each other as if they were on a social media platform” https://t.co/tFz6HJvIJi
— Petter Törnberg (@pettertornberg) October 20, 2023
Echo Chambers, Discoveries, and Algorithms
The bots, fueled by news from July 1, 2020, stepped into a
Twitter-esque arena, embracing three distinct models. The “Echo Chamber”, a
tranquil haven resonating with shared ideologies; “Discover,” a
whirlwind of high engagement veiled in occasional negativity; and the
“Bridging Algorithm,” where opposing bots found unlikely camaraderie
amid resounding engagement. The question being posed was whether these
algorithmic creations could pave the way to a less polarized online utopia.
The Echo Chamber highlighted posts from other bots with shared
ideologies. This platform was calm, but quiet. Discover populated feeds
with the posts with the most likes. Predictably there was high, but often
negative, engagement. The Bridging Algorithm showed bots the posts with the most
likes, but only from the bots with opposite political beliefs. This Twitter
also saw high engagement, but surprisingly, the bots often found common ground.
Surprisingly Less Hate
So, the takeaway is that discussion of partisan issues needn’t result
in clashes, provided that the numbers of participants on both sides are roughly
equal. Törnberg told Insider that when discussing partisan issues “if
50% of the people you agree with vote for a different party than you do, that
reduces polarization. Your partisan identity is not being activated.”
Interestingly, political scientist Lisa Argyle from Brigham Young
University sees a glimmer of hope. She notes that these AI models, with
identity profiles mimicking humans, might be the heralds of a more civil social
media discourse. Perhaps, in this algorithmic dance, lies the key to a
harmonious online future.
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