How Artificial Intelligence and Machine Learning Are Impacting the Litigation Landscape

Mike DeCesaris | Cornerstone Research

Mike DeCesaris has twenty years of consulting and litigation experience. He leads the firm’s Data Science Center. Mr. DeCesaris specializes in directing complex, data-intensive projects requiring data management, production, and integration, along with advanced empirical analysis. He has worked with both outside and inside counsel to efficiently manage the discovery of large, proprietary databases in complex litigation, investigations, and merger reviews.

His extensive experience spans matters related to healthcare, the False Claims Act, antitrust and competition, consumer fraud and product misrepresentation, internal investigations, intellectual property, and breaches of contracts. Mr. DeCesaris is experienced leading teams assisting clients seeking to conduct complex internal investigations, address class certification, establish the impact of conduct, estimate damages, assess exposure, or calculate settlement payments. The matters he has worked have involved a range of industries, including healthcare and life sciences, financial services, energy and commodities, telecommunications and media, high technology, consumer products, tobacco, and airlines.

Mr. DeCesaris is the author of the article “Using Big Data in Gathering Expert Testimony,” published in Law360. He also coauthored “Mobile Advertising: An Economic Perspective,” published in Distribution, the newsletter of the American Bar Association’s Antitrust Section; and “Energy Trading Strategies in California: Market Manipulation?” published in Obtaining the Best from Regulation and Competition. Metropolitan Corporate Counsel published an interview with Mr. DeCesaris on “Digging for Deep Expertise: Big data and discovery deadlines drive surging need for well-prepared experts.”

Ernest Kim Song | Cornerstone Research

Ernest Kim Song has over ten years of experience consulting on all phases of commercial litigation, internal investigations, and regulatory matters. As director of Cornerstone Research’s Data Science Center, Mr. Song leads interdisciplinary data scientists in applying artificial intelligence (AI), social media analysis, geospatial analysis, big data analytics, and machine learning (ML) techniques to support expert testimony.

Mr. Song consults on issues at the intersection of law, technology, big data, and data science. These include analyzing algorithmic trading platform code, interfacing with cryptocurrency network infrastructure, and assessing how information is disseminated through social media and chatting platforms. His expertise includes advanced analytics and evaluating complex data workflow issues in matters involving cryptocurrency, antitrust, merger review, securities class actions, and mortgage-backed securities. He has also provided data science support in matters alleging defamation and market manipulation.

I. Potential new business opportunities created by clients’ use of AI and LLMs | 2:00pm – 2:20pm

• Privacy and data security | 2:00pm – 2:02pm
• Intellectual property | 2:02pm – 2:04pm
• Product liability | 2:04pm – 2:08pm
• Labor and employment | 2:08pm – 2:12pm
• Antitrust and competition | 2:12pm – 2:16pm
• Healthcare and life sciences | 2:16pm – 2:20pm

II. Potential impact of LLMs and generative AI on litigation practice | 2:20pm – 2:40pm

• Assess the current state of the technology | 2:20pm – 2:30pm
• What use cases law firms are exploring and where things may be in a few years | 2:30pm – 2:40pm

III. The use of AI and ML in expert testimony by both plaintiff and defense side experts over the last several years | 2:40pm – 3:00pm

• One area where these techniques can be particularly helpful is in analyzing large volumes of user-generated content such as social media posts and consumer reviews | 2:40pm – 2:50pm
• Explore use cases for AI and ML in expert testimony, including | 2:50pm – 3:00pm
  • Domain-specific sentiment analysis
  • Assessing marketing influence on social media
  • Image object detection
  • Public press topic modeling
  • Multimedia characterization
  • Assessing the nature of allegedly defamatory statements, product liability, and class certification