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Abstract
Artificial intelligence (AI) technologies are rapidly advancing, enhancing human capabilities across various fields spanning from finance to medicine. Despite their numerous advantages, AI systems can exhibit biased judgements in domains ranging from perception to emotion. Here, in a series of experiments (n = 1,401 participants), we reveal a feedback loop where human–AI interactions alter processes underlying human perceptual, emotional and social judgements, subsequently amplifying biases in humans. This amplification is significantly greater than that observed in interactions between humans, due to both the tendency of AI systems to amplify biases and the way humans perceive AI systems. Participants are often unaware of the extent of the AI’s influence, rendering them more susceptible to it. These findings uncover a mechanism wherein AI systems amplify biases, which are further internalized by humans, triggering a snowball effect where small errors in judgement escalate into much larger ones.
Academic Publication How human–AI feedback loops alter human perceptual, emotional and social judgements
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How human–AI feedback loops alter human perceptual, emotional and social judgements
Abstract Artificial intelligence (AI) technologies are rapidly advancing, enhancing human capabilities across various fields spanning from finance to medicine. Despite their numerous adva...
Empromptu AI
the feedback loop approach is smart. the part that usually trips teams up isnt the training pipeline though, its the quality of the corrections feeding it. if the humans correcting the AI output do...
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Human-computer Interaction
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What is the core focus of the research titled 'How human–AI feedback loops alter human perceptual, emotional and social judgements'?
This literature focuses on: Abstract Artificial intelligence (AI) technologies are rapidly advancing, enhancing human capabilities across various fields spanning from finance to medicine. Despite their numerous advantages, AI systems can exhibit biased judgements i...
Are there open-source GitHub repositories related to How human–AI feedback loops alter human perceptual, emotional and social judgements?
Yes, open-source projects like slowmist/openclaw-security-practice-guide (This guide is designed for OpenClaw itself (Agent-facing), not as a traditional human-only hardening checklist.) are actively building upon these concepts.
Which startups are commercializing the technology behind How human–AI feedback loops alter human perceptual, emotional and social judgements?
Products like Offsite are bringing this to market. Their focus is: Build teams of humans and agents, watch them work..
What other academic literature is closely related to 'How human–AI feedback loops alter human perceptual, emotional and social judgements'?
Yes, highly correlated activity was mapped. An entry titled 'How human–AI feedback loops alter human perceptual, emotional and social judgements' discusses this: Abstract Artificial intelligence (AI) technologies are rapidly advancing, enhancing human capabilities across various fields spanning fro...
Are there commercial applications of 'How human–AI feedback loops alter human perceptual, emotional and social judgements' in market news publications?
Yes, highly correlated activity was mapped. An entry titled 'Human-computer Interaction' discusses this: Human-computer interaction is evolving rapidly with AI-driven 'agent phones' and flexible electronics. The psychological impact of AI, such as chat...
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GitHubslowmist/openclaw-security-practice-guide
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GitHubpaperclipai/paperclip
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