In the sprawling landscape of technology and innovation, where artificial intelligence (AI) has now carved its niche in virtually every sector, there exists a quiet revolution that is reshaping the legal world.
While the legal industry was initially quite hesitant to adopt AI tools, we saw the adoption rate of legal tech tools jump from 19% in 2023 to 79% in 2024. That’s huge.
According to Haley Sylvester, Associate at Pryor Cashman: “The legal profession, often characterized by a reverence for tradition and resistance to change, is at the cusp of a technological revolution that promises the potential to reshape the profession.”
So, if you’re wondering what all the hype around AI is about, we’re here to explain. AI for lawyers, especially plaintiffs’ attorneys, can dramatically streamline many aspects of day-to-day workflows, including case development, legal research, contract writing, and a whole lot more.
What is AI for lawyers?
Let’s start with the basics.
The term ‘AI’ gets thrown around a lot, especially now that almost every industry is using it in some form.
In a podcast last year, Darrow co-founder and CTO, Gila Hayat, defined AI in the following terms:
“Artificial Intelligence, in a nutshell, is a system that has ingested huge amounts of human intelligence that has been curated for a long period of time. It might look like magic, or even dark magic for some people.
But at the core of things, AI is a machine that has been exposed to a huge amount of data, that due to the sheer volume, couldn't be comprehended by a single human being. Thanks to the exposure, the machine then has the ability to derive or predict the answer to any kind of question. So the more data you put into it, the better results you will get.”
Essentially, AI involves creating machines and algorithms that are capable of performing tasks that typically require human intelligence.
AI and legal tech are particularly valuable for plaintiffs' attorneys because they operate outside the traditional billable hours model. This means they have the luxury of enjoying all that AI has to offer in terms of speed, efficiency, and cost-saving capabilities, without needing to worry about minimizing their bottom lines.
Types of AI used in the legal industry
AI comes in many forms, but the legal industry primarily leverages two types: natural language processing (NLP) and large language models (LLMs), both powered by machine learning.'÷≥
NLP
NLP is a branch of AI that allows computers to understand, analyze, and interact with human language, whether it’s text or speech. It’s the technology behind tools like chatbots, translation apps, and voice assistants, but in the legal world, its applications are even more powerful.
NLP breaks language down into smaller components, determines their meaning, and then executes tasks like analyzing, translating, or responding. In the legal field, this capability translates into document classification, regulatory monitoring, anomaly detection, and language translation.
LLMs
LLMs are a type of advanced NLP model trained on massive amounts of data to understand and process human language. ChatGPT is a prime example.
These models are trained by processing massive amounts of text data, like books, websites, and articles, to learn patterns, context, and relationships in language. During training, the model predicts the next word in a sentence repeatedly, adjusting its internal settings to improve accuracy over time. Attorneys may use LLM technology for legal drafting, legal research, and case summarization.
What is generative AI?
Generative AI is a broader term that includes not just text generation via LLMs, but also the creation of other content, like images or videos—it specifically focuses on the "creation" aspect of what LLMs can do.
When LLMs are applied to tasks like drafting text or creating arguments, they are performing a generative AI function. In other words, generative AI uses LLMs as a tool to achieve its goal of creating new content.
Darrow CEO, Evya Ben Artzi, says that generative AI expands the reach of the law, creating new normative and narrative universes, a concept rooted in the work of legal scholar Robert M. Cover. Cover claimed that law is not just a system of rules, but a rich tapestry of narratives that give those rules meaning.
Evya explains that:
"Generative AI, with its capability to analyze vast datasets and generate human-like text, can craft sophisticated legal arguments, hypothetical scenarios, and predictive models, thereby expanding the normative universe. This means that AI can propose new interpretations and applications of existing laws, create novel legal concepts, and simulate potential legal outcomes."
The three waves of legal tech
Let’s talk about the evolution of legal tech over the past 25 years.
NFX, the venture capital firm famously known for investing in disruptors (and one of Darrow’s early investors), explains in a 2023 blog post that the introduction of AI in the legal profession actually represents the third wave of the ongoing legal tech revolution.
This illustrates the profound impact of artificial intelligence on the legal industry, marking a significant evolution in the way technology is transforming legal practices.
First wave: 2000-2011
The landscape of the first wave was predominantly dominated by traditional Software-as-a-Service (SaaS) companies, such as DocuSign and LegalZoom. While these companies have achieved considerable success in providing valuable products to attorneys (i.e. by automating or digitizing processes and enabling remote work), they primarily operated without significant integration of artificial intelligence (AI).
During the first wave, a notable shift towards AI in the Legal Tech sector was observed with the emergence of e-discovery solutions. AI technologies, like machine learning, began to be applied for tasks like data search, ranking, and categorization, ultimately reducing the manual effort required for document analysis. According to NFX this was a relatively slow period for Legal Tech, with fewer than ten startups founded annually between 2000 and 2010.
Second wave: 2012 - 2020
During the second wave companies started shifting towards becoming comprehensive platforms with a number of capabilities to service attorneys, rather than single-purpose tools. For instance, Smith.ai, developed a customer engagement platform, while other firms focused on contracts - offering services for drafting contracts, contract storage, and contract analysis.
During this period, Legal Tech companies started to introduce the use of LLMs, though they were not yet fully practical for lawyers. Some of the pioneering companies during this wave began utilizing NLP to enhance efficiency, work quality, and overall customer experience in the legal field, marking a significant step towards a more integrated and effective legal AI ecosystem.
Third wave: 2021 - present
LLMs have evolved significantly, now being trained on extensive datasets of legal language. When developed and trained correctly, these LLMs have the potential to achieve language proficiency on par with that of a highly trained lawyer. Their ability to comprehend, interpret, and generate legal text makes them valuable tools in various legal applications, including document review, contract analysis, and legal research.
This advancement in LLMs represents a transformative leap in the legal industry, as it becomes a human-like assistant for legal professionals, allowing legal professionals to succeed more than ever before. The way LLMs are already enhancing the overall efficiency and accuracy of legal processes is ultimately reshaping the way legal work is conducted.
How is AI being used in the legal industry?
2024 has been a pivotal year for global legal tech. The market size was estimated at $27.32 billion, and is expected to continue climbing at a rapid pace over the next 10 years. By 2034, the market is estimated to be valued at $65.51 billion!
As law firms increase their use of AI, it’s important to understand how attorneys are actually leveraging this technology for. Here are 8 examples:
- AI for legal research: Advanced AI systems analyze vast legal databases to identify relevant case law, statutes, and legal precedents. These tools help attorneys uncover existing case law and insights to develop cases that might otherwise be missed.
- Contract analysis tools: AI-powered contract-analysis tools review contracts to identify risks, inconsistencies, and compliance issues. They assist attorneys in drafting and negotiating agreements by providing detailed analysis of contractual terms.
- Predictive analytics: Data analytics software uses AI to analyze historical case data to predict outcomes, estimate settlement amounts, and assess case risks.
- Anomaly detection algorithms: Companies like Darrow use AI algorithms to scan databases and other publicly available records to detect anomalies that might indicate potential legal violations.
- E-discovery AI software: This software helps attorneys to automatically identify and categorize electronically stored information so it’s easier to locate relevant data, reduce the burden of manual review, and improve the accuracy of document identification.
- Legal chatbots: AI-driven chatbots handle routine client inquiries, provide legal information, and gather initial case details from a firm’s website. They improve client engagement and accelerate the intake process.
- Document review and automation: Attorneys are using AI-powered document management software to analyze and draft legal documents. Software with NLP-capabilities identify errors, flag important clauses, and automate tasks.
- Litigation management software: AI-powered litigation software analyzes case histories, legal filings, and court records to uncover legal trends that shape case strategies. It evaluates factors like judge rulings and opposing counsel’s behavior to predict outcomes and highlight opportunities for stronger arguments.
But can attorneys trust AI? There are a few risks
Are AI tools trustworthy and ethical? While the benefits are undeniable, there are some real liabilities, too.
Here are 5 important risks to keep in mind:
1. Hallucinations
Hallucinations occur when AI generates information that appears accurate but is actually false. This information might look convincing but can include incorrect data, like non-existent case law or misinterpreted statutes.
Here’s an example. In June 2023, two lawyers were caught using ChatGPT to create a legal brief that cited several nonexistent cases and nonexistent quotes and holdings. The judge charged the lawyers a $5000 fine, stating, “Technological advances are commonplace and there is nothing inherently improper about using a reliable artificial intelligence tool for assistance...But existing rules impose a gatekeeping role on attorneys to ensure the accuracy of their filings.”
As legal tech becomes more prevalent, it’s crucial that attorneys don’t solely rely on AI to do their work.
2. Bias
AI learns from the data it’s trained on. An article by the New York State Bar Association states: “This input affects the machines like the process of imprinting. AI bias is the voluntary or involuntary imprinting of one or more human biases in one or more datasets. The model delivers biased results because of fallacious assumptions of the training data provided to the neural network.”
Historical patterns of inequality in legal outcomes can influence the recommendations an AI tool provides. This could mean skewed risk assessments or subtly biased language in documents.
3. Lack of transparency
AI doesn’t always explain its reasoning when providing information or an answer to a question. In a profession where clear reasoning and accountability are key, this lack of transparency can make it hard to trust the AI’s outputs or use them confidently in legal decisions.
4. Data privacy concerns
Lawyers handle highly sensitive client information, and AI tools, especially cloud-based ones, introduce risks around data security. If proper cybersecurity and data encryption is not in place, confidential client data might be exposed, creating ethical dilemmas or even legal repercussions. It’s essential to ensure any AI tool meets strict privacy and compliance standards.
How can attorneys counter these risks?
Yes, AI comes with risks, but attorneys have control over mitigating them. To reduce the risk of errors, bias, and ethical challenges, keep the following in mind:
- Verify outputs: Use AI as a starting point, not the final word. Always review AI-generated content for accuracy and ensure it aligns with legal standards to ensure there are no hallucinations.
- Choose high-quality tools: Opt for AI tools specifically trained on reliable, high-quality legal data. Tools with rigorous development processes and clear documentation reduce the chances of bias and errors.
- Understand the technology: Familiarize yourself with how the AI works, including its limitations and decision-making processes. Transparency from the tool’s provider is key to building trust and understanding outputs.
- Apply ethical oversight: Combine AI insights with human judgment to maintain ethical standards.
- Prioritize data security: Use tools that comply with data protection laws and implement strong encryption and security measures. Avoid exposing sensitive client information to systems that don’t meet strict privacy standards.
Legislative oversight
The risks associated with AI, coupled with the growing instances of unethical practices by lawyers using these tools, underscore the need for legislative oversight.
While federal legislation regarding AI does exist, it’s currently limited in scope.
Two primary examples include:
- Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence: On October 30, 2023, President Biden established new standards for AI safety and security. This order established guidelines to ensure the safe, secure, and trustworthy development and use of AI technologies across various sectors.
- The White House Blueprint for an AI Bill of Rights: Provides five principles and associated practices to help guide the design, use, and deployment of AI systems.
There has also been a lot of talk in the Senate about creating more specific laws surrounding the use of AI, and there are several measures in the works. Additionally, at least 45 states enacted legislation pertaining to AI in 2024 alone.
We’ve also seen existing laws applied to oversee AI use, much like how the 1988 Video Privacy Protection Act is leveraged to regulate modern online streaming services.
For example, the Federal Trade Commission (FTC) combats deceptive pricing and unethical business practices. Its mission doesn’t specifically mention AI–but it doesn’t exclude it either.
So, on September 25, 2024, as part of its Operation AI Comply, the FTC presented five cases exposing AI-related deception. One of these FTC complaints was against DoNotPay, which marketed itself as "the world's first robot lawyer" and an "AI lawyer.” The FTC claimed that DoNotPay did not live up to its claims, inherently misleading consumers. As a result, DoNotPay agreed to a proposed Commission order settling the charges against it. The settlement required it to pay $193,000 to consumers who subscribed to the service between 2021 and 2023.
AI in law: moving forward
AI is transforming the way lawyers work, taking everyday tasks like legal research, document analysis, and contract drafting to the next level. AI is no longer just a buzzword—it’s a crucial tool being integrated into law firms across the country. However, leveraging AI smartly means pairing its speed and efficiency with human judgment and expertise.
While AI has changed how attorneys perform certain aspects of their jobs, there are elements to being a lawyer that no machine can replicate. For example, strategizing complex cases, maintaining client relationships, litigating in the courtroom, and making judgment calls rooted in empathy and ethics are an important part of any attorney’s job.
Interested in finding your next big case with the help of AI? Contact us.
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