Is Generative AI just the new buzzword or will it play an important role in business? Legal is one industry to watch as more organizations prioritize innovation . Many businesses and enterprises have already recognized the value of artificial intelligence (AI)-powered technology that can detect relevant data and produce better results.
AI tools are routinely used for document review, settlement evaluation, litigation analysis, internal investigations, regulatory compliance, and strategic decisions. This is transformative and proven to deliver better results at a faster pace. Improved results build trust and are slowly beginning to transform an industry known for hesitation into one that embraces innovation. But does this pattern apply to generative AI? Read on to learn more about what generative AI is and why the legal industry should be interested in this trending technology.
The scoop on generative AI
Generative AI works on deep learning models that combine algorithms to quickly create content in response to user input. In fact, it’s been around since the 1960s when the first chatbots appeared, and while this isn’t considered “new” technology, recent advances have made these tools more popular. What is the technology behind this? Machine learning in Transformer makes training on large datasets easier, better understanding, and more robust responses. The result is a new language model that can make more connections with words and phrases to produce compelling content.
From the ability to answer questions conversationally to generating detailed images and videos, generative AI has captured a lot of attention over the past few months. Users are fascinated by how easy ChatGPT is to understand commands and respond in seconds. From answering simple questions to writing poetry to passing standardized tests like Bar and MCAT. Or how Stable Diffusion generates high-quality, realistic images based on textual descriptions. These are just a few of the trends in generative AI tools out there.
A key question to ask is how generative AI differs from other tools that legal professionals and their clients are already using. Predictive coding tools such as TAR are widely accepted for identifying important documents and themes early in the problem and efficiently managing data evaluation and review. These tools have matured since their introduction and there are now tools that can also perform sentiment analysis and pattern processing. There are even portable AI models that can be used for various problems. AI is also being used for contract management and analytics, entitlement checks, privacy law compliance, and more. Like other types of AI, generative AI needs training to understand natural language. The difference lies in what the underlying algorithms and technologies output. Other AI tools (such as TAR) process the input data to aid in classification, pattern detection, and decision making during document review. Generative AI creates new content and chat answers based on your prompts.
How will generative AI be integrated into business and legal processes? This is interesting. Demand can quickly materialize, so it’s important to be proactive about technology trends. Balancing benefits and risks empowers attorneys to make informed decisions about use cases, stay innovative, and enhance their ability to advise clients.
Here are four reasons why the legal industry should monitor the development of generative AI.
- The potential use cases are plentiful. Template building, eDiscovery, motion drafting, contracting, and research are some of the things that could be trending in the next few years. Innovation is taking the legal industry by storm, so evaluating new technologies is critical to staying competitive.
- Clients will use this technology and ask questions. Staying up to date allows us to advise on usage, policy drafting and risk management.
- The ethical obligations of lawyers are ever-increasing. In other words, it should be an integral part of your risk analysis. Some generative AI can waive privileges and compromise attorney-client relationships. Consider these factors before entering sensitive information into a generative AI tool.
- New technologies always raise cyber concerns, as attackers are looking for every possible way to compromise data. When using generative AI, organizations should consider cyber risks and include relevant information in their anti-breach initiatives. Also, keep an eye out for content created by attackers for phishing investigations, as access to generative AI tools can help create more realistic attempts.
As use cases expand and research takes shape, it becomes easier to realize the true benefits of generative AI in business and perform risk analysis. In some cases, this can be another tool in your technical toolbox that can improve efficiency and keep costs down. Check out Epiq Angle’s blog next week for Part 2 of this topic. This topic details what ChatGPT is, how it works, and the limitations that the legal community must consider.