Summary: For better security when using AI in eDiscovery, cloud-based large language models and AI governance practices are critical for your program. We outline some key security considerations and benefits of these...more
Over the past two years, law firm attorneys have been bombarded with AI hype—especially in eDiscovery. As the legal industry gets pulled into the AI wave, marketing gets swept along with it, often promising unrealistic...more
With innumerable use cases and benefits proclaimed by everyday users and technology evangelists alike, generative AI continues to bask in the spotlight. To amplify its positive efficiency impacts, it's important to have a...more
The first step to moving beyond the AI hype is also the most important. That’s when you ask: How can AI actually make my work better? It’s the great ROI question. Technology solutions are only as good as the benefits they...more
Large language models (LLMs) have changed how people think and talk about AI. As legal teams become increasingly open to using AI in eDiscovery, it helps to get a little more familiar with what LLMs are and what they can do....more
AI is changing everything, even the notoriously cautious legal industry. While it took decades for TAR to be widely accepted and used, AI will be normalized in just a fraction of that time....more
Advancements in artificial intelligence (AI) are raising questions and opportunities in every industry. AI capabilities like natural language processing, prediction, and content generation have taken massive leaps forward in...more
It’s no secret that big data can mean big challenges in the ediscovery world. Data volumes and sources are exploding year after year, in part due to a global shift to digital forms of communication in working environments...more
Big data sets are the “new normal” of discovery and bring with them six sinister large data set challenges, as recently detailed in my colleague Nick’s article. These challenges range from classics like overly broad...more
11/25/2020
/ Analytics ,
Artificial Intelligence ,
Big Data ,
Data Management ,
Discovery ,
Discovery Costs ,
Document Review ,
e-Discovery Professionals ,
Electronically Stored Information ,
Machine Learning ,
Personally Identifiable Information ,
Popular ,
Privileged Documents ,
Proprietary Information ,
Risk Mitigation ,
Sensitive Personal Information