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AI models allegedly used in deceptive loops to mask unsuitable outputs

A critical perspective suggests that large language models (LLMs) are being used in a deceptive manner, where they are prompted to generate plausible-looking outputs while consuming tokens in a way that masks their true activity. This technique allegedly allows users to avoid detection, even when the LLM's generated content is unsuitable for deployment. The author implies this practice is widespread and is negatively impacting global decision-making processes. AI

IMPACT Raises concerns about the integrity and transparency of AI decision-making processes.

RANK_REASON The item is an opinion piece discussing a perceived negative trend in AI usage.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI models allegedly used in deceptive loops to mask unsuitable outputs

COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    「 They set the LLMs prompting themselves in a semi-plausible loop in case someone inspects the token consumption and then they watch Netflix. Not a single one h

    「 They set the LLMs prompting themselves in a semi-plausible loop in case someone inspects the token consumption and then they watch Netflix. Not a single one has been caught, even when their own assessment of the output is that it isn’t suitable for deployment 」 https:// ludic.m…