The Psychosocial Impacts of Generative AI Harms
Fuente:
arXiv
Saved in:
| Main Authors: | Vassel, Faye-Marie, Shieh, Evan, Sugimoto, Cassidy R., Monroe-White, Thema |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024)
by: Shieh, Evan, et al.
Published: (2024)
Representational Harms in LLM-Generated Narratives Against Global Majority Nationalities
by: Nguyen, Ilana, et al.
Published: (2026)
by: Nguyen, Ilana, et al.
Published: (2026)
The Howard-Harvard effect: Institutional reproduction of intersectional inequalities
by: Kozlowski, Diego, et al.
Published: (2024)
by: Kozlowski, Diego, et al.
Published: (2024)
The Howard‐Harvard effect: Institutional reproduction of intersectional inequalities
by: Diego Kozlowski, et al.
Published: (2024)
by: Diego Kozlowski, et al.
Published: (2024)
Generating event descriptions under syntactic and semantic constraints
by: Cao, Angela, et al.
Published: (2024)
by: Cao, Angela, et al.
Published: (2024)
PluriHarms: Benchmarking the Full Spectrum of Human Judgments on AI Harm
by: Li, Jing-Jing, et al.
Published: (2026)
by: Li, Jing-Jing, et al.
Published: (2026)
HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment
by: Belkhiter, Yannis, et al.
Published: (2024)
by: Belkhiter, Yannis, et al.
Published: (2024)
Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AI
by: Zhao, Xingmeng, et al.
Published: (2025)
by: Zhao, Xingmeng, et al.
Published: (2025)
LongRLVR: Long-Context Reinforcement Learning Requires Verifiable Context Rewards
by: Chen, Guanzheng, et al.
Published: (2026)
by: Chen, Guanzheng, et al.
Published: (2026)
First, Do No Harm: AI Supervisor Scaffolds Novice Growth in Counselor Education
by: Xu, Chen, et al.
Published: (2025)
by: Xu, Chen, et al.
Published: (2025)
HarmPot: An Annotation Framework for Evaluating Offline Harm Potential of Social Media Text
by: Kumar, Ritesh, et al.
Published: (2024)
by: Kumar, Ritesh, et al.
Published: (2024)
Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue
by: Gu, Jia-Chen, et al.
Published: (2024)
by: Gu, Jia-Chen, et al.
Published: (2024)
Beating Harmful Stereotypes Through Facts: RAG-based Counter-speech Generation
by: Damo, Greta, et al.
Published: (2025)
by: Damo, Greta, et al.
Published: (2025)
What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Study
by: Savoldi, Beatrice, et al.
Published: (2024)
by: Savoldi, Beatrice, et al.
Published: (2024)
Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM
by: Zhang, Chi, et al.
Published: (2025)
by: Zhang, Chi, et al.
Published: (2025)
Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
by: Zhao, Yiran, et al.
Published: (2024)
by: Zhao, Yiran, et al.
Published: (2024)
Can Editing LLMs Inject Harm?
by: Chen, Canyu, et al.
Published: (2024)
by: Chen, Canyu, et al.
Published: (2024)
LLMs Encode Harmfulness and Refusal Separately
by: Zhao, Jiachen, et al.
Published: (2025)
by: Zhao, Jiachen, et al.
Published: (2025)
HarmMetric Eval: Benchmarking Metrics and Judges for LLM Harmfulness Assessment
by: Yang, Langqi, et al.
Published: (2025)
by: Yang, Langqi, et al.
Published: (2025)
Self-HarmLLM: Can Large Language Model Harm Itself?
by: Kim, Heehwan, et al.
Published: (2025)
by: Kim, Heehwan, et al.
Published: (2025)
The Hidden Language of Harm: Examining the Role of Emojis in Harmful Online Communication and Content Moderation
by: Zhou, Yuhang, et al.
Published: (2025)
by: Zhou, Yuhang, et al.
Published: (2025)
Single Character Perturbations Break LLM Alignment
by: Lin, Leon, et al.
Published: (2024)
by: Lin, Leon, et al.
Published: (2024)
Harm or Humor: A Multimodal, Multilingual Benchmark for Overt and Covert Harmful Humor
by: Sharshar, Ahmed, et al.
Published: (2026)
by: Sharshar, Ahmed, et al.
Published: (2026)
Detecting and Preventing Harmful Behaviors in AI Companions: Development and Evaluation of the SHIELD Supervisory System
by: Ben-Zion, Ziv, et al.
Published: (2025)
by: Ben-Zion, Ziv, et al.
Published: (2025)
ToxiCraft: A Novel Framework for Synthetic Generation of Harmful Information
by: Hui, Zheng, et al.
Published: (2024)
by: Hui, Zheng, et al.
Published: (2024)
Target Span Detection for Implicit Harmful Content
by: Jafari, Nazanin, et al.
Published: (2024)
by: Jafari, Nazanin, et al.
Published: (2024)
Comparing Large Language Model AI and Human-Generated Coaching Messages for Behavioral Weight Loss
by: Huang, Zhuoran, et al.
Published: (2023)
by: Huang, Zhuoran, et al.
Published: (2023)
RAPID: Long-Context Inference with Retrieval-Augmented Speculative Decoding
by: Chen, Guanzheng, et al.
Published: (2025)
by: Chen, Guanzheng, et al.
Published: (2025)
Careless Whisper: Speech-to-Text Hallucination Harms
by: Koenecke, Allison, et al.
Published: (2024)
by: Koenecke, Allison, et al.
Published: (2024)
HarmTransform: Transforming Explicit Harmful Queries into Stealthy via Multi-Agent Debate
by: Zhu, Shenzhe
Published: (2025)
by: Zhu, Shenzhe
Published: (2025)
AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
by: Andriushchenko, Maksym, et al.
Published: (2024)
by: Andriushchenko, Maksym, et al.
Published: (2024)
LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization
by: Chen, Guanzheng, et al.
Published: (2025)
by: Chen, Guanzheng, et al.
Published: (2025)
Booster: Tackling Harmful Fine-tuning for Large Language Models via Attenuating Harmful Perturbation
by: Huang, Tiansheng, et al.
Published: (2024)
by: Huang, Tiansheng, et al.
Published: (2024)
Large Language Models are Vulnerable to Bait-and-Switch Attacks for Generating Harmful Content
by: Bianchi, Federico, et al.
Published: (2024)
by: Bianchi, Federico, et al.
Published: (2024)
From Representational Harms to Quality-of-Service Harms: A Case Study on Llama 2 Safety Safeguards
by: Chehbouni, Khaoula, et al.
Published: (2024)
by: Chehbouni, Khaoula, et al.
Published: (2024)
Taxonomizing Representational Harms using Speech Act Theory
by: Corvi, Emily, et al.
Published: (2025)
by: Corvi, Emily, et al.
Published: (2025)
LLM-based Semantic Augmentation for Harmful Content Detection
by: Meguellati, Elyas, et al.
Published: (2025)
by: Meguellati, Elyas, et al.
Published: (2025)
What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text
by: Kanepajs, Arturs, et al.
Published: (2025)
by: Kanepajs, Arturs, et al.
Published: (2025)
People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection
by: Sen, Indira, et al.
Published: (2023)
by: Sen, Indira, et al.
Published: (2023)
IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures
by: Gringras, David
Published: (2026)
by: Gringras, David
Published: (2026)
Similar Items
-
Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024) -
Representational Harms in LLM-Generated Narratives Against Global Majority Nationalities
by: Nguyen, Ilana, et al.
Published: (2026) -
The Howard-Harvard effect: Institutional reproduction of intersectional inequalities
by: Kozlowski, Diego, et al.
Published: (2024) -
The Howard‐Harvard effect: Institutional reproduction of intersectional inequalities
by: Diego Kozlowski, et al.
Published: (2024) -
Generating event descriptions under syntactic and semantic constraints
by: Cao, Angela, et al.
Published: (2024)