Ethical Generative AI in Law: Accountability & Transparency
Integration of generative AI into the legal sector necessitates ethical considerations as well as maintaining accountability and transparency
Safeguarding the justice system against the Deepfakes threat
A comprehensive recommendation for safeguarding the justice system against the threats posed by deep fakes.
Navigating Change: Lena O’Brien on Modernizing Legal Operations
Lena O’Brien discusses modernizing legal operations through AI and technology, focusing on change management, efficiency, and overcoming resistance in the legal sector.
The Rise of AI-Generated Deepfakes and Legal Challenges
The rise of AI-generated deepfakes threatens legal integrity. This article explores challenges, legal frameworks, and detection technologies.
Key measures of accurate AI output: Building Trust in AI
Understand key measures of accurate AI output, including reliability, transparency, and citation validation, to build trustworthy AI systems.
Generative AI Success Relies on A Strong Data Strategy
Achieving success in generative AI requires a strong data strategy with well-defined pipelines and enriched datasets.
Building Trust in AI: The EU AI Act’s Risk-Based Approach
Discover EU AI Act’s risk-based approach, its impact on AI governance, trustworthiness, and the key challenges businesses face in implementing the regulations
Mitigating LLM Hallucinations in Legal Back Office Systems
Explore strategies to reduce hallucinations in legal AI, including robust training data, RAFT, human oversight, and specific prompts to enhance accuracy.
The introduction of Microsoft Copilot to the Legal Industry
Learn how Microsoft Copilot revolutionizes the legal industry with AI-driven productivity and workflow enhancements.
Adapting to Change: ALSPs and Tech in the Legal Industry
Legal industry adapts to digitalization with effective change management, enhancing operations and client satisfaction through innovative tech solutions
