Tag: AI Ethics

All the articles with the tag "AI Ethics".

• AI in Money Matters

  Published: 15 May, 2025 |  at  11:03 AM

  

  99.13 🤔

  This paper investigates the cautious adoption of Large Language Models like ChatGPT in the Fintech industry through qualitative interviews, highlighting professionals' optimism for routine task automation, concerns over regulatory inadequacies, and interest in bespoke models to ensure compliance and data control.

• A Statistical Case Against Empirical Human-AI Alignment

  Published: 15 May, 2025 |  at  11:06 AM

  

  98.37 🤔

  This position paper argues against forward empirical human-AI alignment due to statistical biases and anthropocentric limitations, advocating for prescriptive and backward alignment approaches to ensure transparency and minimize bias, supported by a case study on language model decoding strategies.

• Adversarial Attacks in Multimodal Systems: A Practitioner's Survey

  Published: 8 May, 2025 |  at  11:09 AM

  

  96.71 🤔

  This survey paper provides a comprehensive overview of adversarial attacks on multimodal AI systems across text, image, video, and audio modalities, categorizing threats by attacker knowledge, intention, and execution to equip practitioners with knowledge of vulnerabilities and cross-modal risks.

• A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem

  Published: 16 May, 2025 |  at  11:13 AM

  

  94.41 🤔

  This paper conducts a large-scale empirical analysis of 14,904 custom GPTs in the OpenAI store, revealing over 95% lack adequate security against attacks like roleplay (96.51%) and phishing (91.22%), introduces a multi-metric popularity ranking system, and highlights the need for enhanced security in both custom and base models.

• A Comprehensive Analysis of Adversarial Attacks against Spam Filters

  Published: 15 May, 2025 |  at  11:07 AM

  

  93.91 🤔

  This paper conducts a comprehensive analysis of adversarial attacks on deep learning-based spam filters, revealing significant vulnerabilities across character, word, sentence, and AI-generated paragraph levels using novel scoring functions like spam weights, with distilBERT showing relative resilience at paragraph-level attacks.