5 minutes

Navigating the Risks of Hallucination in Legal AI

Artificial intelligence (AI) is transforming the legal profession in exhilarating new ways. But these rapid advancement bring unique challenges.
Written by
Jamie Fonarev
Published on
Jan 24, 2024

Artificial intelligence (AI) is transforming the legal profession in exhilarating new ways. The potential to automate rote tasks allows professionals to focus on higher-level strategic thinking. Meanwhile, trained AI can analyze huge volumes of case law and case facts, identifying patterns and insights faster than any human team.

But these rapid advancement bring unique challenges. Although the legal profession has ardently and effectively combated human error, today, it is faced with a new class of mistakes: the challenge of 'hallucination' - AI-generated misinformation. 

These new risks demand attention, education, and solutions. One might feel overwhelmed or skeptical about integrating AI. These concerns are valid. 

That is why we embrace this technology with cautious optimism, implementing safeguards while celebrating achievements. With the right balance of human oversight and AI augmentation, the legal profession can enter an era of increased productivity and innovation.

In this article we will focus on the risks associated with AI hallucination. We will dive into the types of problems that can arise and lay out some best practices and advice on mitigating these risks, empowering you to expand the value legal professionals can garner from legal AI.

Understanding AI Hallucination: The New Frontier of Legal Risks

As AI capabilities grow, so do risks like AI “hallucination.” Hallucination refers to when AI generates fictional information or draws false inferences. This is extremely dangerous in the legal field where accuracy is paramount. The now infamous case from New York of Mr. Schwartz, who, relying on AI for legal research, inadvertently cited nonexistent cases in his brief illustrates the gravity of these risks. 

To help contextualize the impact of mistakes in the legal profession, we can think about the duality of mistakes: what mistakes can AI prevent, and what types of mistakes can AI make (that a human wouldn’t).

What Mistakes Does AI Solve? 

  • Forgetting details of a relevant case. With perfect memory, AI can call up any case details while performing further case work. These abilities can super-power how legal professionals work through their case strategy, helping prevent a key detail from falling through the cracks. 
  • Making grammar, punctuation, or formatting errors in legal writing. Diligently programmed to follow key style specifications, AI will not make trivial mistakes when generating content. This allows legal teams to deliver impeccable quality of work, saving valuable time on proofreading.
  • Displaying bias or prejudice that negatively influences legal judgment. Without a human bias, AI provides fact-based results and conclusions. This can help ground teams and drive objectivity. 

What Mistakes Does AI Make?

  • Citing fake or fictional case law. This could occur if the AI hallucinates legal precedents or laws during legal research or legal analysis.  Let’s go a bit deeper: If an AI is exposed to too few real legal cases during training, it may try to fabricate new cases to fill gaps in its knowledge. Since AI lacks a human legal researcher's real world knowledge, it might fail to filter out unrealistic, fabricated cases. Additionally, deficiencies in the AI's natural language generation capabilities can lead to creating fictional case details that seem logically coherent but do not actually exist.
  • Drawing incorrect or illogical inferences. The AI may lack the legal reasoning skills to apply precedents properly, connecting key takeaways as strategically as a human mind. Let’s go a bit deeper: While AIs can analyze large volumes of case law data and identify patterns, they lack the legal reasoning skills that attorneys develop through education and experience. Human legal thinking involves complex logic, strategically connecting precedents based on legal principles versus surface patterns. An AI may detect superficial connections between cases, but miss the deeper strategic legal arguments that case law implies. Without understanding legal reasoning, the inferences made by AI can be incorrect or illogical despite seeing statistical patterns in data.
  • Taking quotes out of context. The AI may stitch together fragments in a misleading way if not connected to broader takeaways. Let’s go a bit deeper: When an AI extracts quotes and text segments from case law, it can struggle with reproducing the original context and meaning. Stitching together fragments can distort the original intent, even if the individual quotes are verbatim. This occurs because the AI does not comprehend the broader legal concepts and arguments that provide full context. Humans intuitively maintain context from the overall case when quoting, but AI can lose the original contextual meaning in translation. Without the full picture, isolated quotes can be misleading if an AI cannot reconnect them to the original overarching takeaways.
Strategies for Mitigation: Guardrails in AI and Legal Diligence

As we navigate the complexities of AI hallucination, it's important to adopt a dual approach, much like a mentor guiding a student. First, we ensure our AI technologies are fortified with strong guardrails. Providers should think of this as laying down the foundational knowledge, setting out the lesson plan, and creating a safe environment to explore and expand skills. This includes adding guardrails, limiting the ability to surface unverified content, and other tactics we will discuss below. 

Then, it's up to legal professionals to act as diligent students, constantly learning. We should enhance our practices by weaving in consistent checks and safeguards. Think of it as a continuous learning process where vigilance and adaptation are key. Together, through careful guidance and dedicated practice, we can effectively manage these risks while growing as legal professionals. 

This extra diligence is undeniably demanding for professionals already strapped for time. But pioneering change is never easy. It requires vision to see opportunities beyond short-term growing pains. This journey represents the next frontier for legal professionals to shape. Collaborating across law and tech can enhance AI safety and illuminate new possibilities.

Safeguards Against Hallucination Risks in Legal AI Systems

Legal AI providers have a responsibility to build guardrails into their systems that curb hallucination. Some best practices include:

  • Citing Sources and Providing Audit Trails: AI-generated responses should reference its sources or provide a traceable path for verification. Where possible, this should be the default approach, not something that users need to ask for proactively. 
  • Enabling User Verification: AI systems ought to enable lawyers to verify sourcing details and prompt further investigation into sources for robust cross-checking.
  • Legal Research Isolation: For the particularly risky tasks related to Legal Research AI, limiting tools to query a verified case law database precludes the citation of non-existent cases. For instance, Eve’s Legal Research tool operates within a confined database of verified cases, mitigating the risk of hallucinatory output.

Additionally, safeguards are improved through ongoing collaboration between legal professionals and tech teams. With user feedback and real-world testing, systems continuously enhance protections against errors. The world of legal AI is growing rapidly and becoming better at an unprecedented speed. 

The Legal Professional's Role: Vigilance in the Age of AI

While AI brings new capabilities, legal professionals remain irreplaceable. Human judgment and complex reasoning are indispensable - AI is an aid. With care and vision, professionals can utilize AI to enhance their expertise and judgment. Legal professionals working with AI tools must vigilantly verify outputs, thoroughly checking facts and sources akin to peer-reviewing a colleague's work.

  • Trust But Verify: It is imperative to scrutinize AI-generated outputs, seeking confirmations for any critical information provided: verify key facts, citations, and quotes before relying on them.
  • Request Traceability: If a piece of AI output lacks direct quotations or citations, users should demand comprehensive explanations and references from their tools. 
  • Maintain Oversight: Maintain close oversight over AI-generated work just as you would with a human colleague - ask for explanations, details, and find out the “why” where possible.
The Future of Legal AI - A Super Powered Legal Field

If guided properly, AI can transform the legal field for the better. No tool can perfectly replace human thinking, but AI can extend professionals’ capabilities. To realize AI’s promise, we implement diligent oversight and verification practices. This will allow professionals to take advantage of AI productivity gains while safeguarding accuracy.

With the right balance of technological guardrails and updated legal workflows, the legal field can benefit immensely from AI productivity gains while protecting against the risks of hallucination. With a spirit of adaptation and prudent optimism, the legal profession can step boldly into an exciting new frontier.

For now, AI still requires oversight - with legal professionals verifying all final outputs. While challenges persist, the legal AI’s best days are still to come. We must meet them with equal parts vigilance, collaboration and hope.

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