Dan Jurafsky

Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study

2023 · 426 Zit. · The Lancet Digital Health

Dialect prejudice predicts AI decisions about people's character, employability, and criminality

2024 · 32 Zit. · arXiv (Cornell University)

Coding Inequity: Assessing GPT-4’s Potential for Perpetuating Racial and Gender Biases in Healthcare

2023 · 30 Zit. · medRxiv

Using Large Language Models to Promote Health Equity

2025 · 15 Zit. · NEJM AI

Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models

2023 · 12 Zit.

Advancing science- and evidence-based AI policy

2025 · 8 Zit. · Science

Language models cannot reliably distinguish belief from knowledge and fact

2025 · 8 Zit. · Nature Machine Intelligence

Labeling messages as AI-generated does not reduce their persuasive effects

2026 · 7 Zit. · PNAS Nexus

Beyond Tokens: Concept-Level Training Objectives for LLMs

2026 · 0 Zit. · arXiv (Cornell University)

Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models

2022 · 0 Zit. · arXiv (Cornell University)

Accommodation and Epistemic Vigilance: A Pragmatic Account of Why LLMs Fail to Challenge Harmful Beliefs

2026 · 0 Zit. · ArXiv.org

Concept Training for Human-Aligned Language Models

2026 · 0 Zit. · arXiv (Cornell University)

Accommodation and Epistemic Vigilance: A Pragmatic Account of Why LLMs Fail to Challenge Harmful Beliefs

2026 · 0 Zit. · arXiv (Cornell University)

Beyond Tokens: Concept-Level Training Objectives for LLMs

2026 · 0 Zit. · ArXiv.org

The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices?

2026 · 0 Zit. · Open MIND