Practice Guide: Ethical Use of Artificial Intelligence in Legal Practice: Five Key Guidelines
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Summary
Artificial intelligence is now embedded in many aspects of legal practice, from eDiscovery and document review to legal research and document drafting. While AI tools can provide valuable assistance and deliver meaningful efficiency gains, lawyers must understand that their ethical obligations apply fully to the use of these tools. AI does not change a lawyer’s professional duties—it changes how those duties must be exercised. Across jurisdictions, ethical guidance from bar associations and courts has converged around five key principles that lawyers should keep in mind when using AI in their practice. These principles derive from the core ethical duties common to lawyers in all states. To help illustrate how these familiar rules apply in new technological contexts, we’ve included some plausible hypotheticals, an analysis of the applicable ethical responsibilities, and some helpful practice takeaways.
In this Practice Guide
- The five key principles of ethical AI use
- Hypothetical examples with ethical analysis
- National and state guidance resources
Key Insights
- The rules haven’t changed, but the context has
- Understanding the limits of reliability is critical
- Ongoing education is essential to successful use
Summary
Artificial intelligence is now embedded in many aspects of legal practice, from eDiscovery and document review to legal research and document drafting. While AI tools can provide valuable assistance and deliver meaningful efficiency gains, lawyers must understand that their ethical obligations apply fully to the use of these tools. AI does not change a lawyer’s professional duties—it changes how those duties must be exercised. Across jurisdictions, ethical guidance from bar associations and courts has converged around five key principles that lawyers should keep in mind when using AI in their practice. These principles derive from the core ethical duties common to lawyers in all states. To help illustrate how these familiar rules apply in new technological contexts, we’ve included some plausible hypotheticals, an analysis of the applicable ethical responsibilities, and some helpful practice takeaways.
In this Practice Guide
- The five key principles of ethical AI use
- Hypothetical examples with ethical analysis
- National and state guidance resources
Key Insights
- The rules haven’t changed, but the context has
- Understanding the limits of reliability is critical
- Ongoing education is essential to successful use
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