Using AI to Predict Legal Outcomes: A Powerful New Tool for Lawyers
AI can not only help draft and review your documents but also predict case outcomes -- Including a list of some legal-focused prediction tools. 🔮
image by Dall.e
Knowing at the outset how your case is likely to end would be a fabulous advantage — allowing you to make strategic decisions from the beginning. According to the BBC, a study at the London College of Law back in 2016 showed that AI was able to predict the outcome of 584 cases with 79% accuracy. A significantly larger study in Brazil in 2022 showed that AI could out-predict human experts in small claims matters by 3 to 1, or about 194% better. And AI has improved substantially even in the last 2 years. AI’s ability to predict legal outcomes is groundbreaking. This technology offers lawyers new tools to enhance decision-making processes, assess risks, and provide clients with more accurate advice. But how exactly does this work, and how can legal professionals leverage it to their advantage?
Understanding AI in Legal Predictions
At its core, the use of AI to predict legal outcomes involves machine learning, a branch of AI that learns from data to make predictions. Large Language Models (LLM’s), the driving force behind AI tools, are trained using vast amounts of data, including legal cases and opinions. Legal-specific AI tools and systems are heavily trained on vast amounts of case law, legal precedents, and court outcomes to identify patterns that might escape the human eye. These systems can evaluate the strengths and weaknesses of a case more quickly and with a transformative level of detail.
AI predictions collect data from multiple sources—past court decisions, judge rulings, and legal filings—and then use sophisticated algorithms to detect patterns. Factors such as the nature of the case, applicable laws, and past rulings by the presiding judge are all fed into the LLM, allowing AI tools to give lawyers valuable insights into how a case might unfold. The more vast the collection of relevant data is, the more accurate and specific an AI tool’s output.
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The Benefits of AI Predictions in Law
Knowing your judge’s tendencies can be invaluable in litigation. AI tools can analyze a judge's past rulings, written opinions, and sentencing patterns to predict their likely decisions in future cases. This analysis can highlight whether a judge typically rules in favor of plaintiffs or defendants, how they interpret specific statutes, and the likelihood of them granting certain motions. While it’s impossible to guarantee outcomes, this data-driven insight helps lawyers make more informed decisions about how to present their case or whether settlement might be the best option AI predictions could have a number of benefits for legal cases. Here are a few.
Strategic Decision-Making:
AI’s predictive capabilities allow lawyers to make data-driven decisions. By understanding the likelihood of different outcomes, legal professionals can better plan their approach—whether to settle or go to trial—and prepare their clients for realistic scenarios. This data-backed strategy not only saves attorneys time and, therefore, client expenses but is likely also to enhance client satisfaction.
Risk Assessment:
Every legal case involves a degree of uncertainty. Heading into litigation might, at times, feel only slightly better than a crap shoot in Vegas. The outcome of a given hearing or case might be affected by something as minor as how well the judge or jury slept the previous night. AI tools can reduce this uncertainty by providing probabilistic assessments of case results based on historical data. AI can highlight key risk factors and offer insights into possible outcomes in even the most complex cases, thereby empowering lawyers to make better-informed decisions and better educate their clients.
Enhanced Client Consultations:
Using AI to provide predictive insights, lawyers can offer clients or potential clients AI-enhancedconsultations. My one caution here is to be mindful of client expectations. Use caution, personal expertise, and sound judgment when using predictive AI in client-facing applications. Even if you caution clients that the data is based on probability, it might give them an expectation of how their case will turn out. Imagine that an AI tool predicts an 85% chance of winning a complex intellectual property case. Excited by these odds, the client pushes for an aggressive litigation strategy and rejects settlement offers. However, during the trial, a key piece of evidence is unexpectedly ruled inadmissible, dramatically altering the case's trajectory. Despite the lawyer's best efforts, the case is lost. The client, having based their expectations on the AI's prediction, feels misled and may be more likely to file a malpractice claim or leave negative reviews, even if the lawyer provided appropriate caveats about the AI's limitations. The outcome could lead to greater wrath by the client if the client has unreasonable expectations.
When using these tools, especially at the consultation stage, we must educate the clients to help them understand this is merely a prediction. For example if clients are told of an 85% chance of winning all or most of their claims and then they lose on all their claims, they might feel even worse than if they did not have AI predictions. To avoid this advantage from turning into a double-edged sword, be certain to manage client expectations.
Conversely, the data insights and analytics that AI can provide might help manage over-inflated client expectations. If a client comes to a consultation with an unrealistic idea of the strength of their case or the dollar value of a case, AI analytics could provide data to help ground their expectations in data rather than speculation. This analysis could bolster the lawyer’s expert assessment.
Practical Applications Across Legal Areas
Criminal Law: In criminal law, AI can predict outcomes based on case specifics like the crime, evidence, and precedent. This can help defense attorneys decide whether to pursue a plea deal or go to trial. Lawyers could dial in the data to determine how a certain judge has ruled on similar facts and charges and thereby help clients decide whether to take a plea deal or go to trial.
Civil Law: Jury awards for contract cases and torts are already heavily analyzed. AI can assist in the analysis of civil cases—such as contract disputes or personal injury cases—by assessing the likelihood of success based on past rulings, helping lawyers better advise their clients on litigation strategies.
Family Law: For emotionally charged cases like divorce or custody disputes, predictive AI can provide insights into likely outcomes, helping lawyers give more accurate advice during negotiations or litigation.
Intellectual Property Law: AI can predict the likelihood of patent approval by analyzing similar past applications, assessing the strength of trademark infringement claims based on precedent, and estimating potential damages in copyright cases by comparing them to historical awards.
Employment Law: In this field, AI tools can predict outcomes of wrongful termination suits based on case specifics, assess the likelihood of success in discrimination claims by analyzing similar cases, and estimate potential settlements in workplace injury cases using historical data.
Corporate Law: AI predictions can be particularly useful in estimating the success rate of merger and acquisition approvals, assessing the likelihood of shareholder litigation arising from corporate decisions, and predicting the probability of regulatory approval for new business ventures.
Environmental Law: AI tools can access scientific data, and therefore can predict outcomes of environmental compliance disputes, assess the chances of successfully challenging or defending against environmental regulations, and estimate potential fines or penalties in environmental violation cases based on historical enforcement actions and the latest scientific data.
Immigration Law: In this complex area, AI can predict the success rate of visa applications based on applicant profiles and current policies, assess the likelihood of deportation appeals being granted, and estimate processing times for various immigration procedures.
Tax Law: AI tools can predict the outcome of tax dispute resolutions, assess the risk of audits based on filing patterns, and estimate potential penalties in tax evasion cases by analyzing past IRS actions and court decisions.
Real Estate Law: AI tools can access demographic, area real estate sales, and zoning data. In real estate matters, AI can predict outcomes of zoning disputes, assess the likelihood of success in property contract breach cases, and estimate potential damages in construction defect lawsuits based on similar past cases.
Healthcare Law: AI predictions in healthcare law can help estimate the outcome of medical malpractice suits, assess the likelihood of success in insurance claim disputes, and predict potential penalties in HIPAA violation cases by analyzing past regulatory actions and court decisions.
How General AI Tools Like ChatGPT, Gemini, LLaMA, and Claude Can Help
GenAI is extremely helpful at reviewing contracts and drafting clauses for agreements. But its capabilities exceed those tasks. There are essentially three (3) tiers of proficiency or accuracy of AI prediction tools. The top tier is highly specialized and highly data-rich. This includes tools such as Lex Machina and Epiq. These are tailored specifically for high-level legal analytics. The mid-tier provides more in-depth information but is less data-rich than the top-tier. The third tier is comprised of the more general AI platforms such as ChatGPT, Gemini, Claude, or LLaMA. While not designed specifically for legal analytics, these more commonly available AI models can also provide valuable legal insights:
Case Law Analysis and Summarization: ChatGPT, Gemini, and Claude can quickly summarize legal documents, case law, or statutes. They can surface trends and relevant information, providing lawyers with preliminary insights into case strengths and weaknesses.
Document Drafting and Review: These tools can assist in drafting legal documents such as contracts or pleadings and identify potential issues in the language, helping streamline the preparation process.
Outcome Predictions and Risk Assessment: While general-purpose AI tools don’t have access to proprietary legal databases, they can still help analyze the facts of a case and predict outcomes based on patterns in the input data. Fine-tuning models like LLaMA with legal datasets can improve their accuracy and relevance.
Though not as specialized, these general AI models are far more accessible, affordable, and flexible, making them a valuable option for small law firms or solo practitioners.
Challenges and Ethical Considerations
Despite its benefits, AI-driven legal predictions come with challenges. The accuracy of these predictions depends heavily on the quality and breadth of data used to train the AI. Biases in historical data can result in skewed predictions, inadvertently perpetuating past injustices. This highlights the importance of understanding the limitations of AI systems and ensuring that human judgment remains central to legal decision-making.
In every application, AI should only be used as a tool to augment human decision-making, not replace it. Lawyers must carefully balance data-driven insights with the personal and emotional factors that are often at the forefront in legal cases.
Looking Ahead: AI's Role in the Future of Law
AI’s potential to predict legal outcomes is vast and continues to evolve. As AI technology becomes more refined, its integration into everyday legal practice will become more widespread. For lawyers, embracing AI means stepping into a new era of informed decision-making that could significantly change not only how cases are approached but also the overall dynamics of the lawyer-client relationship. As AI tools improve, they will offer even greater precision in predicting outcomes, empowering lawyers to provide more nuanced, strategic advice and making the legal process more transparent and efficient for clients.
AI Apps That Specialize in Data Analytics and Outcome Prediction 🔮
Several law-focused apps and platforms are designed to help predict legal outcomes by leveraging AI and data analytics. These tools can provide lawyers with valuable insights, risk assessments, and strategic guidance by analyzing patterns in past cases, judicial behavior, and other key factors. Here is a list of some notable tools:
Focus: Litigation analytics and case outcome prediction.
How It Helps: Lex Machina, a part of LexisNexis, offers deep litigation analytics by using AI to track and analyze data from millions of court cases. The platform provides insights into case outcomes, judge behavior, attorney performance, and the likely duration of litigation. It covers a wide range of legal domains, including intellectual property, commercial litigation, and employment law. It not only downloads documents directly from court dockets but also has lawyers review, verify and clean up the data.
Predictive Power: Lex Machina provides a detailed overview of how similar cases have fared, offering key insights into potential litigation strategies. It can even drill down into how a specific attorney or firm has fared in certain cases. It analyzes case outcomes based on factors like case type, court, and judge, allowing lawyers to predict case results, anticipate opposing counsel's strategies, and assess the success rates of particular legal arguments.
Focus: Predictive analytics and attorney performance data, with an emphasis on insurance defense cases.
How It Helps: Premonition touts its ability to predict litigation outcomes by analyzing court data, including the performance of individual lawyers and law firms. It claims to have the largest litigation database in the world and uses AI to rank lawyers and predict case outcomes based on factors like attorney win rates and judge-specific tendencies.
Predictive Power: Premonition's key feature is its ability to provide data on how well particular lawyers perform before certain judges. This insight allows firms to select the best counsel for a case or anticipate how an opposing attorney may perform and their strategies. It helps predict case outcomes by analyzing the effectiveness of legal representation and judicial history, offering valuable strategic insights.
Focus: Litigation analytics and judge evaluation.
How It Helps: Westlaw Edge allows lawyers to search how a judge typically rules on a certain type of case, the facts of the case, and what authority the judge has cited on a given case.
Predictive Power: Westlaw Edge uses AI to analyze cases and judicial rulings for state and federal cases. It can match judicial opinions to the subject matter and the length of time it takes for a judge to issue their opinion. It also allows users to see example motions a judge has granted for a case type and related facts in the motion.
Focus: Legal research and judicial analytics.
How It Helps: LexisNexis offers deep analytics on judges, including their ruling tendencies, reasoning patterns, and citation preferences. By analyzing a judge’s past rulings, it can help lawyers tailor arguments to better align with judicial preferences.
Predictive Power: The Judge Analytics tool helps lawyers predict how a judge might rule on certain legal issues or motions, making it easier to strategize and advise clients. It also provides its data analytics to governmental agencies.
Focus: Law firm infrastructure, class action and mass tort analysis, and regulatory risk analysis, among other services.
How It Helps: Epiq Analytics uses AI and machine learning to analyze data from legal proceedings and administrative proceedings, offering early case assessment and settlement guidance, second-level review, and regulatory risk analysis.
Predictive Power: Epiq helps with data collection and forensics, predicts case outcomes, discovers patterns in legal and regulatory rulings, and assesses potential case costs, making it applicable to litigation planning and strategy, especially for torts.
📌 Judicata – Available currently only for California cases.
Focus: Legal analysis and case outcome prediction.
How It Helps: Judicata focuses on breaking down legal arguments and case law to assess their strength. It analyzes how courts are likely to rule based on the structure of arguments and legal precedent.
Predictive Power: By examining past rulings, the tool helps predict how specific arguments might be received by courts, enabling lawyers to fine-tune their strategies.
Conclusion
The landscape of AI-powered legal prediction tools offers a spectrum of options for legal professionals. From highly specialized platforms that provide deep, data-driven insights into specific areas of law to more versatile, general-purpose AI assistants, these technologies are revolutionizing legal strategy. As always, remember that AI should only ever be used to augment your own expertise as a lawyer, and never add confidential information to an AI tool unless you have thoroughly vetted the AI, including by reading the EULA and ToS.