The main challenges
In the context of Finland, the challenge lies in enabling AI to interpret legislative text in relation to government proposals, along with existing legal precedents, such as those established by the Supreme Court. This becomes especially pertinent while performing certain types of legal work, such as conducting lawsuits. Here, the challenge is to make a holistic interpretation of the law's letter (statute), spirit (government proposal), and practical application (judiciary). It's also necessary to consider European Union legislation and case law, soft law, legal literature, sector-specific, and international agreements.
In matters of contracts, challenges, complaints, and responses, there is more repetitiveness, which makes it easier for AI to learn. For example, there is more predictability and regularity in contract clauses or procedural elements of a complaint, which AI can learn from and use to assist in drafting similar documents in the future.
In contrast, in the United States, precedents are crucial, and the role of AI extends to becoming a proficient search engine. It’s expected to sift through and pull out relevant case laws and precedents that could influence the outcome of the legal matter at hand. It's not just about interpreting the written law, but also understanding and applying past legal decisions relevant to the case. Moreover, it's important to note that the American market already hosts dozens of services based on artificial intelligence, indicating a burgeoning landscape of AI-enhanced legal practice.
Here’s how we see that AI can positively impact legal work in the future:
1. Utilizing a large amount of data to answer complex legal questions
Imagine a lawyer working on a complicated intellectual property case involving patent laws across multiple jurisdictions. Here, an AI system can be a lawyer’s best ally as it’ll be able to process and analyze an enormous amount of data from various legal databases, legal journals, case precedents, and government law suggestions – providing an accurate interpretation of international patent laws translating them and also explaining them in layman’s terms. AI can highlight similar cases and their resolutions, which will enable lawyers to understand the legal landscape better and form an effective strategy for their client in a matter of days instead of weeks.
But keep in mind that Generative AI still needs human validation. This is because it can provide incorrect information and struggle with complex or niche questions. Long documents also pose difficulties due to limited memory, but this won’t be a problem for long as the technology continues to progress.
2. Time-saving document drafting
The drafting of legal documents is another area where AI shows promise. For instance, if a lawyer has to draft an intricate licensing agreement, instead of starting from scratch, they can use generative AI which has learned from thousands of legal documents.
The AI system should be used to generate a first draft, incorporating all the necessary clauses tailored to a client's needs. The lawyer then only needs to review the document, saving valuable hours and allowing her to focus on other crucial aspects of her case.
3. Empowered decision-making
AI systems will also play a vital role in decision-making. As one example, let’s take a class-action lawsuit where the lawyer is uncertain about proceeding to trial or opting for a settlement. AI will be able to analyze data from similar lawsuits and case precedents, identifying a pattern if cases like the one in question favored defendants in trials.
Keep in mind that generation of information may be inaccurate or non-existent. For instance, a generative AI tool might generate a law or legal provision that doesn't actually exist, based on patterns it has learned. This could potentially lead legal representatives down incorrect paths, causing them to provide inaccurate advice or pursue unfeasible legal strategies. That’s why Generative AI insight still needs careful human validation.
4. Efficient legal research
Generative AI will drastically cut down the time spent on legal research. For instance, if a lawyer was assigned an emerging cybersecurity case, they face the daunting task of understanding rapidly evolving cyber laws. A generative AI system can efficiently sift through numerous resources, providing the lawyer with a compiled summary of relevant laws, their government law proposals, regulations, and recent legal developments.
One thing to keep in mind is that Generative AI has difficulty dealing with recent concepts as there is often no teaching material available yet. In this case, material has to be inputted and taught to the system before actual work with Generative AI can start.
5. Enhanced due diligence
In corporate law, due diligence is a task that demands meticulous attention to detail. In a high-profile merger case, lawyers have to assess potential risks and liabilities. Generative AI will quickly analyze a vast array of corporate documents, identifying potential regulatory issues that were previously overlooked. These findings allowed lawyers to mitigate risks and ensure a smoother merger process.
Minimizing the risk of confidential information leaks
When AI tools are shared across multiple organizations, there is a risk of confidential information leaking. For example, a legal representative may input confidential information into a generative AI tool as part of a query or task. If the AI tool isn’t designed with strict data isolation, it could theoretically use this input to inform future responses, potentially leaking confidential information to other users.
This situation poses a considerable risk, particularly in the context of legal representation where maintaining client confidentiality is of paramount importance. An inadvertent leak could potentially lead to a breach of attorney-client privilege and result in serious professional and legal consequences. That means any AI tools used by lawyers should be designed with this in mind.
But overall, generative AI can change the way that lawyers work. AI can assist greatly in legal tasks but it can’t replace human lawyers due to the complex legal issues that require strategic thinking and nuanced interpretation of the law. Hence, while AI may transform the legal profession, it’s unlikely to eliminate the need for human lawyers.