1 citations · 2 across the 8 of their papers we have counts for
8 papers
The Normalization of Deviance in AI Development
Emilio Barkett, Alexander Kimpton, Daniel Graham +1
Work on the risks of artificial intelligence has focused predominantly on capability risk: the danger that systems become too powerful, too autonomous, or too misaligned with human…
Whose Alignment? Comparing LLM Process Alignment Across Diverse Organizational Decision Contexts
Niklas Weller, Emilio Barkett
Steerable pluralism requires a model to faithfully represent one specified perspective. Organizations are a natural setting for this demand, since they deploy LLMs to make decision…
Representation Without Control: Testing the Realization Effect in Language Models
Ciarán Walsh, Emilio Barkett
Large language models are increasingly used as behavioral simulators, but it remains unclear when their outputs reflect human-like cognitive mechanisms rather than prompt-sensitive…
The Compulsory Imaginary: AGI and Corporate Authority
Emilio Barkett
This paper argues that the two leading AGI firms -- OpenAI and Anthropic -- construct sociotechnical imaginaries through a structurally consistent rhetorical strategy, despite mean…
Status Hierarchies in Language Models
Emilio Barkett
From school playgrounds to corporate boardrooms, status hierarchies -- rank orderings based on respect and perceived competence -- are universal features of human social organizati…
Don't Change My View: Ideological Bias Auditing in Large Language Models
Paul Kröger, Emilio Barkett
As large language models (LLMs) become increasingly embedded in products used by millions, their outputs may influence individual beliefs and, cumulatively, shape public opinion. I…
Getting out of the Big-Muddy: Escalation of Commitment in LLMs
Emilio Barkett, Olivia Long, Paul Kröger
Large Language Models (LLMs) are increasingly deployed in autonomous decision-making roles across high-stakes domains. However, since models are trained on human-generated data, th…
Reasoning Isn't Enough: Examining Truth-Bias and Sycophancy in LLMs
Emilio Barkett, Olivia Long, Madhavendra Thakur
Despite their widespread use in fact-checking, moderation, and high-stakes decision-making, large language models (LLMs) remain poorly understood as judges of truth. This study pre…