The legal system, despite its structure, is fundamentally non-deterministic and influenced by human factors. Applying new, equally non-deterministic AI systems to this already unpredictable human process poses a deep philosophical challenge to the notion of law as a computable, deterministic process.

Related Insights

The need for explicit user transparency is most critical for nondeterministic systems like LLMs, where even creators don't always know why an output was generated. Unlike a simple rules engine with predictable outcomes, AI's "black box" nature requires giving users more context to build trust.

A core debate in AI is whether LLMs, which are text prediction engines, can achieve true intelligence. Critics argue they cannot because they lack a model of the real world. This prevents them from making meaningful, context-aware predictions about future events—a limitation that more data alone may not solve.

AI is engineered to eliminate errors, which is precisely its limitation. True human creativity stems from our "bugs"—our quirks, emotions, misinterpretations, and mistakes. This ability to be imperfect is what will continue to separate human ingenuity from artificial intelligence.

As AI models are used for critical decisions in finance and law, black-box empirical testing will become insufficient. Mechanistic interpretability, which analyzes model weights to understand reasoning, is a bet that society and regulators will require explainable AI, making it a crucial future technology.

Current AI tools are empowering laypeople to generate a flood of low-quality legal filings. This 'sludge' overwhelms the courts and creates more work for skilled attorneys who must respond to the influx of meritless litigation, ironically boosting demand for the very profession AI is meant to disrupt.

A top-tier lawyer’s value mirrors that of a distinguished engineer: it's not just their network, but their ability to architect complex transactions. They can foresee subtle failure modes and understand the entire system's structure, a skill derived from experience with non-public processes and data—the valuable 'reasoning traces' AI models lack.

While AI "hallucinations" grab headlines, the more systemic risk is lawyers becoming overly reliant on AI and failing to perform due diligence. The LexisNexis CEO predicts an attorney will eventually lose their license not because the AI failed, but because the human failed to properly review the work.

Law, code, biology, and religion are all forms of language—the operating system of human civilization. Transformer-based AIs are designed to master and manipulate language in all its forms, giving them the unprecedented ability to hack the foundational structures of society.

Technological advancement, particularly in AI, moves faster than legal and social frameworks can adapt. This creates 'lawless spaces,' akin to the Wild West, where powerful new capabilities exist without clear rules or recourse for those negatively affected. This leaves individuals vulnerable to algorithmic decisions about jobs, loans, and more.

Instead of forcing AI to be as deterministic as traditional code, we should embrace its "squishy" nature. Humans have deep-seated biological and social models for dealing with unpredictable, human-like agents, making these systems more intuitive to interact with than rigid software.