Artificial Intelligence, Business, and the Law Cory Fisher cwfisher@shb.com
ar ti fi cial in tel li gence /ˌärdəˈfiSHəl inˈteləjəns/ Noun the capability of a machine to imitate intelligent human behavior AKA: Machine Learning, Machine Decision Making, Deep Learning, Automation, IoT
Application of AI
The Tipping Point MACHINE LEARNING Artificial Intelligence CONNECTED WORLD COST OF COMPUTING DATA
The Risks
AI - Two Sides of a Coin AI Used By Lawyers AKA: Legal Tools AI Used by Clients AKA: Legal Issues
Lawyer Implementation of AI AI Used By Lawyers AKA: Legal Tools AI Used by Clients AKA: Legal Issues
Business Implementation of AI AI Used By Lawyers AKA: Legal Tools AI Used by Clients AKA: Legal Issues
Universal challenges with AI implementation Compliance Public Policy Data Security and Privacy Intellectual Property Business Litigation Tort and Products Liability Class Action and Complex Litigation
Compliance Challenges - Navigating uneven regulatory frameworks not designed for AI solutions. - Example: GDPR language suggests that, as of next year, companies operating in the EU will be required to provide consumers with explanations for decisions made about them by AI. - Ensuring AI applications do not violate workplace or other laws governing discrimination and equal access to services.
Public Policy Challenges - Identifying opportunities to influence technology-cognizant legislation. - Example: U.S. Senator Maria Cantwell is working on legislation that would require the federal government to study AI s impact on employment via a new Department of Commerce committee. - Preventing overzealous plaintiff s bar from extending liability under laws not intended to accommodate AI. - Demonstrating to the public and government that the benefits and protections provided by applied AI outweigh potential liabilities and risks.
Data Security and Privacy Challenges - Complying with the patchwork of privacy laws when handling the large amounts of employee, patient or personal data needed to AI. - Building AI systems designed to monitor and prevent cyberattacks to comply with all legal reporting requirements. - Responding to breaches or the unauthorized transfer of data that may occur with the sharing of information across AI platforms.
Intellectual Property Challenges - Prosecuting patents and developing portfolios related to AI applications. - Defending against or filing claims related to infringement of AI applications. - Determining or asserting ownership of AI-generated content or AIgenerated inventions.
Business Litigation Challenges - Navigating insurance coverage disputes stemming from AI applications. - Avoiding employment disputes arising from discriminatory AI applications or labor disputes arising from displaced workers. - Resolving contractual and business disputes related to the sale, transfer and licensing of AI systems or data pools.
Tort and Product Liability Challenges - Defeating product liability, malpractice and professional liability claims arising from AI applications and AI decision making. - Preparing for personal injury or premises liability claims related to use of AI in the workplace, operating room, clinical trials or public spaces. - Adapting legal arguments to address negligence when manufacturers or operators cannot foresee the consequences of AI.
Class Action and Complex Litigation Challenges - Avoiding fraud claims stemming from the use of AI to simulate human interactions. - Providing transparency to consumers and users of proprietary AI, while preserving trade secrets. - Handling AI-related commercial and consumer class actions parallel to regulatory enforcement.
It's not what you look at that matters, it's what you see. - Henry David Thoreau
Artificial Intelligence, Business, and the Law Cory Fisher cwfisher@shb.com