This chapter provides a foundational introduction to generative AI and large language models, addressing their capabilities and limitations. These models can perform competitively with humans on standardized exams and legal reasoning tasks and can be applied flexibly to legal challenges through natural language prompts.

However, significant limitations constrain their deployment in legal contexts. Models produce hallucinations, generating confident but incorrect information that can mislead users making critical legal decisions. The ELIZA effect compounds this risk as users tend to anthropomorphize AI and overestimate its capabilities. Additional challenges include potential biases introduced by the training data, privacy concerns associated with hosted models, and substantial computational costs. Understanding both the opportunities and limitations is crucial for safely deploying generative AI to address access-to-justice challenges.