Legal AI for Midmarket and Enterprise

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This month, through my Women in Modern Law roundtable series, I convened a group of women from around the country who work in corporate legal departments. My goal is to build a community – a space where we, as female in-house legal professionals, can share experiences, ideas, solutions and challenges. Sometimes we get so caught up in our own work that we can really benefit from hearing from others doing the same thing in a different place.

The group included women working for large companies, small organizations and government entities. The conversation was easy and far-reaching. Even though I’m the CEO of a legal tech firm, the goal wasn’t to sell our product. Instead, it was to learn from each other so that we can all do our jobs better and help our own institutions thrive.

Here are a few take-aways from this virtual event that I host monthly:

1. Although the pandemic was hard, many of the participants found that it allowed them to achieve a better work-life balance. It also focused attention away from simple productivity, and instead shined a light on the value of personal relationships and strategic thinking. One participant worried about what is called “quiet quitting,” where workers get in, get it done and get out. They ignore the effort it takes to develop relationships; they stop trying to improve themselves or win the next promotion. This participant believes this movement will force employers to realize that they need to more appropriately value their corporate lawyers for their strategic thinking and the benefits they bring rather than only focusing on how many forms, contracts and documents they can complete. Employers that realize this will retain talent. And lawyers working in this environment will see their leadership skills, intelligence and value appreciated.

2. Lawyers involved in legal operations have real value – and it’s important for the rest of the organization to recognize their worth. It’s easier to see the value of legal operations when people are working together in the same space.

3. If you work in legal operations, don’t be afraid to eavesdrop. Yes, eavesdrop. When you hear employees talking about something that you feel should be run by the legal department, speak up. Introduce yourself as the legal operations expert and explain how you can help the employee avoid future problems by coming to you and your department in advance, before problems occur. Additionally, ask HR for time during the onboarding process or at an all-hands meeting to introduce yourself and the role of legal operations so that every employee understands from their first day on the job the importance of the legal operations department.

4. Managing the amount of time worked – and expectations of how much time one should work – is important. Just because we’re living in a 24x7 connected world doesn’t mean we should be expected to work – or be on call - 24x7. Delegate duties and explain that you don’t need to be involved in every conversation or every decision. Have the conversation around when legal is really needed and how. When you’re going on vacation, leave your laptop and your phone at home. If it’s a staycation, lock them up to avoid being called to them.

5. Appreciate the benefits of collaborating on documents in a group setting. This could be in virtual meetings or in person. One participant explained how editing documents on a shared screen saves her and her organization time and frustration.

6. Use technology to save time and money and make your work as a corporate lawyer more joyful. Make sure to choose the right platform to achieve your specific goals. For example, some legal artificial intelligence (AI) software can enforce legal guardrails in contracts and notify in-house counsel before problems occur. Some of the same technology can also allow collaboration across departments.

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Most companies know they should implement a Contract Lifecycle Management (CLM) system to keep track of the lifecycles of their business contracts and agreements. And those that have started the process understand how overwhelming it can quickly become.

In fact, some companies that start down the CLM path quickly give up, frustrated by the process or the fear they won’t realize an appropriate return on investment.

I’ve heard from corporate lawyers of two main pain points when it comes to CLM:

1. They try to sign up for a solution where the price seems reasonable. However when evaluating different vendors, it quickly becomes an enormous time sink to book demos, get quotes, and compare features and costs.
2. Once they start down the CLM journey and look at the implementation process, it quickly becomes overwhelming. They learn it may take one or two fulltime employees to manage the process that will take six months to prepare to launch. This may not have been clear in the purchasing process! Then, they fear the whole thing won’t be worth the effort, face a low adoption rate by stakeholders, and will ultimately fail. Or, they fear the system must be constantly modified and maintained, defeating the purpose of implementing CLM in the first place.

What’s another solution? How about a CLM system with lower costs, quicker and easier implementation, minimal training, and the ability to launch on a small scale rather than going all in from the very beginning?

The key is finding a way to make a smaller bet on CLM.

That is possible with the right system. Most companies have some form of a CLM system - from a simple document repository to very fancy contract management tools. Most enterprises will have a big, robust complicated set of processes either encoded into a CLM system or haphazardly created in documents that outline how to manage their contract lifecycles. The complexity of onboarding a new CLM system is proportionally related to how complex a company’s legal processes are, generally tracking to the size of the business.

While some highly organized, ground-up tech companies will have implemented a slick internal CLM system, the same can’t be said for all businesses.

Consider the overworked in-house counsel who gets way too many e-mails and phone calls and tries to manage them with a home-grown Excel tracking system or – worse yet – a slew of sticky notes tacked to a white board. This is how they manage the contracts coming in and going out. This system is impossible to scale.

Most companies would benefit from a CLM system that – at the very least – allows them to manage document generation and execution of the contracts.

Rather than going through an arduous months-long process to launch a robust CLM system that takes significant training and full-time employees to manage, consider a CLM service provider that can quickly take a business’s home-grown CLM process, integrate with it, and take over one part of the lifecycle. Imagine a low-cost, low-friction solution that involves sending your business’s sales contracts to the CLM provider and having a custom system set up in 48 hours, ready for your sales team to log in, modify the contract, and send it to the legal team for quick turn-around. This is possible with non-disclosure agreements, licensing agreements, consulting agreements, equipment lease agreements and purchase agreements as well.

By picking a vendor that allows you to make a small bet first, at a low price, and with a short implementation time, a company can understand and evaluate a solution in their unique situation before committing to a more robust implementation. In the best-case scenario, that bet is a success, and you’ve laid a foundation for a future effective and worthwhile CLM. In the worst case, you’ve learned important information that you can use to make a better decision on how to manage the contract lifecycle, with only a minimal investment of effort in the process.

Ideally, companies should look for a low-cost solution that leverages what they already have, a system that allows them to try out the CLM offerings without committing to significant costs and a huge implementation effort.

When it comes to implementing a CLM system, don’t be afraid to start small. Be wary of partners that want you to sign the world away. Be comfortable with people who let you try a small bite first.

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I have always enjoyed reading the posts on social media about the crazy things we did growing up that seem absolutely absurd today. These include piling 12 or more people in a station wagon with nobody wearing a safety belt, letting kids go out and play all day without a clue as where they were going, and drinking from the garden hose in the backyard when you got thirsty.

So down the road what will we look back on and ask “What were we thinking?” regarding activities we do today? One quickly jumps to mind in the business world: trying to maximize company efficiency and effectiveness while not using artificial intelligence (AI) when working with legal documents. Some of the questions that will be asked by those slow to adopt:

• Were we expecting our legal department to be miracle workers? How were they easily able to keep up with the vast number of quickly changing legal changes in every state and beyond that affected each document? With regard to government sanctions, were they expected to know of every subsidiary of a major company they were engaged in business with?
• Did we really used to spend a ridiculous amount of money to send our salesforce to conventions and expect every company they met to not want to negotiate? Once back in house, repeatedly hearing reps respond to questions about their sales figures with, “Well…we made some great contacts and got some traction” should have been a wakeup call. If we have learned anything from “Shark Tank,” that question should be answered with a number, not prose.
• Why did our in-house legal burn the midnight oil to put an agreement together when the almost exact same document was constructed for another client a week ago?
• Did we think as a company we were running on all cylinders when our sales reps referred to the compliance department as the “Sales Prevention Team,” our legal department called the salesforce “Gunslingers With No Aim,” and a frequent task for management was to tell staff, “After three e-mails back and forth with another department, please just pick up the phone and call them!” Legal AI can unite everyone onto the same team. Input may be needed from multiple departments, opening up channels of communication. Scenarios that only one department might normally see receive empathy from another department that had never considered that situation.

The base for using AI for legal work started more than four decades ago when documents went from the filing cabinet to the computer. Legal AI works as your organizer, memory bank, tickler system and contract updater. For a department like procurement, it allows employees to go on autopilot with legal guardrails in place. AI lets you compliantly take the process of generating a contract all the way to closing a contract to what was weeks or months down to possibly a few minutes.

So why don’t children drink from the garden hose anymore? For me, it was Mrs. Anderson from our neighborhood saying, “Kids, that’s disgusting. Come inside and use clean glasses and get water from the pitcher in the refrigerator.”

If we have hired and trained our employees to the best of their ability, our product/service has been fully marketed and time-tested, and there is only so much time in the day, what else can we possibly do to speed up our processes and free our employees to focus on strategy instead of redundant mundane tasks? Evolve with the times. Use legal AI.

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As more enterprises automate away the tedium faced by in-house departments, a question looms: why haven’t in-house legal departments caught up? Internal legal processes for drafting, analyzing, and managing simple legal documents are still manual and tedious. What is stopping legal departments from automating away the pain?

As it turns out, a major barrier for adoption lies in the most common means of automation itself: Machine learning.

Contract Lifecycle Management (CLM) software streamlines and automates several stages of the contract lifecycle - from the initial drafting stages all the way up to negotiation, signature, and the final expiration of a contract. Most CLM platforms rely solely on one type of artificial intelligence (AI) for automation: Machine learning. Machine learning (ML) is a self-learning branch of AI, built for recognizing patterns in large pools of data. The problem with ML in the context of CLM software is that legal contracts are much more structured and nuanced than just any pool of data.

Although there are areas of the contract lifecycle where ML is useful – it can scan for key dates in third party paper or learn your negotiation habits – it is not a suitable tool for the more nuanced stages of the lifecycle. Mainly, contract drafting and analysis are too complex for a ML algorithm to perform reliably.

Both document drafting and analysis are stages of the lifecycle that require an artificial intelligence system to understand the content of a contract and the law itself. However, ML AIs are not trained to do this – they are simply built to recognize and act upon patterns. Thus, the way a ML AI would learn to write and read contracts is by analyzing thousands of documents. However, no matter how smart the AI, it is not possible to learn the entirety of the law just by reading legal contracts. As a result, ML AI is quite unreliable at writing or analyzing legal documents.

Though almost all industries rely on ML in some capacity for automation, its wide margin of error is especially problematic for legal work. Unlike a sales department, which would suffer no consequences for chasing a bad lead, the stakes of the legal department are far too high for Swiss-cheese contracts. Thus, while Sales is happy that their ML AI sends 70% of emails to the right people, Legal would explode if only 70% of contractual clauses were valid. Legal must therefore take extra precaution in their automation processes and use more tightly controlled AI for document generation and analysis.

In areas where ML fails, there are other types of AI to fill in the gaps. Instead of deploying self-learning AI such as ML for legal contract creation and analysis, enterprises should consider AI methods that are human-trained and tightly controlled. This way, instead of having the system learn the law by itself, legal professionals train the AI and set guardrails. A “Knowledge Graph” is a perfect example of a tightly controlled and human-trained AI.

“A Knowledge Graph is essentially a giant mesh of relationships linking entities together to represent real world facts, concepts, and ideas. By mapping the relationships that each clause has to each law, jurisdiction, and party, we weave a deep understanding of a contract into the system,” says Chetan Desh, Chief Technology Officer of CLM platform Advocat AI. “By using a Knowledge Graph AI instead of ML AI, legal insight is trained into the system, acting as a growing knowledge base over time. By understanding the content and context of a legal document, a Knowledge Graph AI can navigate nuance, allowing it to create solid legal documents and notify users when a contract needs attention.”

Though ML is the common favorite in the AI toolkit, the stakes of a legal contract are too high and the nature of the law too nuanced to leave this to ML alone. Thus, in areas of the contract lifecycle that are too complex and important for ML, legal departments should reach for the more suitable tool to get the job done. By deploying more controlled and trainable AI such as Knowledge Graph technology, legal departments too can automate away tedious tasks and start to focus on strategy.

According to the English Oxford Living Dictionary, AI can be defined as “the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” AI has frequently been misunderstood and seen as a threat to human jobs because of this very definition. However, Advocat’s goal is not to eliminate jobs but to actually make attorneys’ lives better and allow them to spend less time on tedious tasks such as the back and forth of emailing questions to clients.

Adam Nguyen, a Harvard grad states, “As a group, lawyers tend to be miserable because a significant portion of our work is tedious and doesn’t require much analytical skills. Many of us hadn’t entered the profession expecting to spend much time on tasks like copying and pasting, document summarizing or assembling document binders” (ABA Journal). With a service such as Advocat, hours spent on tedious tasks can be shortened significantly, leading to increased focus on analytical and more satisfying tasks. This can make lawyers more productive and overall happier with their careers.

Source: ABA Journal

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There is a gradual but consistent shift to in-house legal departments. Advocat Technologies is hard at work to create the platform and tools to help with increased productivity. We invite you to be the first ones to know,

Source: https://www.law.com/corpcounsel/2020/12/18/legal-techs-next-big-audience-law-departments-seeking-better-productivity/

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According to the American Bar Association's Model Rules of Professional Conduct, lawyers must maintain competence and keep up with new technology. Comment 8 states, “a lawyer should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology.“ This means that as new technology such as AI is being developed and can significantly reduce workload of tedious tasks, lawyers should consider studying the implications of it on improving the quality and efficiency of their work. Spending less time on legal research and drafting will allow lawyers to provide more value through increased focus on analytical work.

Source: ABA Model Rules of Professional Conduct

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Dismissal of legal departments does not mean the dismissal or reduction of legal needs of an organization. This actually leads to unhappy business users / employees. Advocat Technologies’ solution is designed specifically to assist organizations’ in-house legal attorneys and departments with their growing needs by increasing productivity and and making them cost efficient. We invite you to visit us our website to learn more and to sign up for a demo.

https://lnkd.in/gZU_aMC

Source: https://www.law.com/corpcounsel/2021/02/12/benjamin-moore-rationing-legal-requests-after-in-house-layoffs/

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For years, artificial intelligence (AI) has already been changing the ways we work and we live without our own realization. We may not realize, but we interact with AI every time we open Facebook, every time we execute a Google search, or every time we search for Expedia recommendations.

There was a time when people were afraid of it because they thought it made them expendable. Not anymore. Through better understanding AI, we now recognize and accept that it will not replace humans, but will instead save them from mundane and repetitive tasks that lead to errors; it is hard to imagine a single job that could not benefit from adopting AI in some way, shape, or form. Humans will be able to direct their attention, skills, and focus on interesting and valuable work. Companies that do not accept and adopt technology will soon become obsolete and will not be able to survive. It is only through this advent in technology that we will be able to build solutions to meet the demand of today’s and tomorrow’s needs and problems

LegalTech is no different. For whatever reason, the legal industry has been a straggler in adopting technology. However, technology will be woven into the new tools and platforms while providing such a great user experience that lawyers, paralegals, and other end-users will not even realize that these tools are elevating their deliverables. These solutions will make in-house attorneys more efficient and productive and enable them to bring a higher quality of work and standardization across the organization while providing autonomous and continuous security and compliance – an impossible feat without the integration of technology. And organizations can accomplish all this while achieving two key C-level priorities: minimizing time spent, cost savings, and more importantly, compliance, data privacy and security.

Advocat Technologies is hard at work to build a modern AI-enabled platform that uses the most recent technologies to assist in-house attorneys with their legal research and drafting needs. These include Speech to Text, NLP (Natural Language Processing), NLU (Natural Language Understanding), cognitive services and machine learning platforms such as Azure Cognitive Services and Language Understanding (LUIS) from Microsoft, and the NLG (Natural Language Generation) platform such as GPT-3 from OpenAI.

The timing could not be better! These platforms have used hundreds of millions (175 billion for GPT-3) of parameters to train their systems, which provide robust and rich platforms for us to build on and create the most effective solutions for our customers right from the get-go. The best part is that attorneys can continue to work as before, without spending any time learning new ways of working, yet receive a richer user experience and be able to achieve more.

We invite you to be among the first ones to learn about how Advocat Technologies can help your organization. Please visit www.advocat.ai or send us a quick email at demo@advocat.ai to sign up for a demo and get started today!

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In the rapidly changing landscape of legal technology today, it is crucial for law firms to adapt to the new tools available in order to stay competitive. By utilizing new technologies such as AI and machine learning, firms are now able to discover, index and process information at a fraction of the time and expense. “It may even be considered legal malpractice not to use AI one day”, says renowned civil litigator Tom Girardi.

Although utilizing AI to do legal research will decrease the amount of billable hours for lawyers, the enhanced effectiveness and strategic advantage gained far outweighs the lost hours. At the end of the day, clients hire lawyers to solve problems as efficiently and inexpensively as possible. By not taking advantage of legal technologies in order to bill more hours, firms will put themselves at a competitive disadvantage which will eventually lead to less clients.

Source: Forbes

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According to a recent Ernst & Young’s report, there is a disconnect among the C-level despite the common goal of increasing efficiencies while reducing costs. This has become a priority for them as workloads are being increased by 25%. The report further says that 94% of the companies have struggled with their management systems. An important finding in this report is that 78% of the respondents indicated savings by in-sourcing more work; however, only 3% of in-house leaders anticipate adding attorneys.

Advocat.ai has specifically developed a platform and a solution that resonates well among legal departments, in-house attorneys and the C-level. Legal departments within corporations will be able to increase productivity and efficiencies while achieving overall savings. We are eager to talk with you to understand your challenges and discuss how we can help achieve your goals.

Source:  https://www.law.com/corpcounsel/2021/04/08/you-just-dont-get-me-disconnect-between-gcs-and-ceos-on-technology-workloads-revealed-in-ey-survey/

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Looks like corporations are displeased with and questioning the antiquated system of billable hours with law firms.  Modern AI based solutions make it so much easier for in-house legal departments to get their work done much faster and cost effectively.  More importantly it brings consistency in legal obligations across the company’s legal documents.  In fact, these very law firms will be left with no choice but to use these solutions.  It is just a mater of time.  Visit www.advocat.ai to learn about our solution that assists in-house attorneys with their legal intake, research and drafting needs.

Source:  https://www.law.com/corpcounsel/2021/05/10/get-rid-of-the-billable-hour-say-in-house-leaders/

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According to a recent McKinsey Global Survey, COVID-19 has been one of the key drivers in accelerating the adoption of technology and digital transformation across industries, including the legal sector. The increase in productivity and standardization across organization with reduced risks and costs make it imperative for these to become an integral part of the legal function going forward.

According to Gartner, in-house legal departments will increase their technology investments three-fold by 2025. However, technology solutions will have to mindful of human behavior and port existing workflows into these solutions to provide a rich user experience.

Law firms, who presently have a different business model, will be coerced into adopting these technology solutions to continue and expand relationships with their clients.

Source: https://www.law.com/corpcounsel/2021/06/21/law-firms-demonstrate-digital-savvy-to-deepen-relationships-with-gcs/

In-house legal departments are frustrated with law firms for not providing digitized data to their organizations for better analytics and decision Making.  I think it is just a matter of time when organizations will require and possibly work with law firms that can provide access to digitized data.

Source:  https://www.law.com/corpcounsel/2021/07/28/frustrated-legal-department-leaders-want-law-firms-to-improve-data-reporting/

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Increased workload due to shrinking budgets and personnel are causing additional pressure on in-house legal departments to function more like other corporate business divisions. Also, according to a recent Wall Street Journal article, the future of work is hybrid, where employees could be working from anywhere. This requires them to think, plan and execute differently than how they have in the past. The only way to address this is by incorporating technology to help them meet the new and intensified legal demands of the modern corporation.

Unfortunately, few corporations, including technology companies, have in-house development resources to help build technology solutions for their own legal departments. Therefore, they must look outside the company to find the right tech solutions they need to help them work more efficiently.

Corporate legal departments must have clear communication with their technology solution providers about their needs. The solution should seamlessly address the requirements, workflows and challenges they have, with little to no training or education necessary. Any required help should be built into the product to assist a smooth transition to the new tech solution.

One of the challenges corporate C-level executives worry about involves integrating the new tech solution with the company’s existing tech stack. Any established legal department will already have some technology (such as Salesforce, DocuSign, Microsoft OneDrive, Microsoft Teams, Box, etc.). Ideally, the new technology should integrate seamlessly with the company’s existing tech stack.

Another concern C-level executives have is keeping the appropriate people updated and informed of progress or lack or, or any critical failure in the process. The solution should have appropriate notifications built in, which assigns ownership and increases accountability.

The new trend and way of working where employees can work from anywhere has introduced an immediate need for corporations to incorporate additional security and compliance at the platform level. Employees have access to sensitive corporate and client data. In the past they worked from behind the safety of the corporate firewall, but now there might be no such thing.

Lastly, the User interface (UI) and user experience (UX) are super important for the modern solution. It should help users complete the same tasks faster and accurately. It should be highly customizable and fuse with the existing corporate software, so users do not think of it as a separate solution. It should allow analyzing data and generate customized report to provide actionable insights that help make better decisions.

Considering the above, it is imperative that an organization engage with a solution provider that has an attorney as an integral member of the team, who has lived the pain and clearly understands the workflows and requirements. They should work with a provider with experience in developing enterprise-grade SaaS platforms and solutions that are highly compliant and secure.

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The disruptive technology of artificial intelligence has made massive strides in the past decade, playing a prominent role in the growth of businesses and companies. Nowadays, AI is viewed as a necessity for maintaining competitive advantage in some of the world’s biggest industries. More specifically, the healthcare industry has invested heavily in AI with the hope that the technology can enable better efficiency and accuracy in the medical field.

The global AI in healthcare market size is expected to grow from USD 4.9 billion in 2020 to USD 45.2 billion by 2026. One of the main factors driving this massive growth is the demand for software solutions to handle the increasing volume of healthcare data. For example, UnitedHeath Group is currently developing their own healthcare analytics service called OptumIQ, which aims to use artificial intelligence to gather and analyze patient data in order to predict and solve healthcare problems for its customers. Services such as OptumIQ aim to not only provide more accurate results for its customers in shorter times, but also reduce the costs of diagnostics and making healthcare more affordable.

More recently, the race to find a vaccine for COVID-19 fueled the demand for AI in healthcare even further as pharmaceutical and biotech companies across the world find ways to expedite their drug development process. The Cambridge-based AI drug discovery firm AI VIVO was able to use artificial intelligence to identify Dexamethasone as a high potential COVID-19 treatment 10 weeks before clinical trial results confirmed it.

The healthcare industry is a prime example of how AI has established itself as a necessity in today’s world, from helping with routine health diagnostics to finding treatments for COVID-19. With its massive expected market growth in the next decade, the potential power of AI is unlimited.

Sources:

https://www.aivivo.co/covid19june/

https://www.healthrecoverysolutions.com/blog/the-growth-of-artificial-intelligence-ai-in-healthcare

https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-healthcare-market-54679303.html

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With globalization and increasing costs of legal services disrupting corporate legal departments, there is an unprecedented pressure for in-house counsel to be more efficient than ever before. To stay ahead of the competition, legal departments need to shift their business model – from reactive and rigid to preventative and fluid, transforming in-house counsel from a cost center to a profit driver. Automation through AI liberates attorneys from dwelling on repetitive tasks, allowing them to focus on strategy and the future. With more and more corporations automating as much as possible, legal departments must invest in innovative technology to stay ahead of the competition.

https://www2.deloitte.com/content/dam/Deloitte/us/Documents/finance/us-advisory-legal-department-of-the-future.pdf

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Every day we hear more and more about the benefits of artificial intelligence (AI) – how it can save time, easily provide answers to difficult questions and preserve resources. Despite this trend, few know what legal AI really does, the benefits and drawbacks. Can lawyers, law firms and large corporate legal departments actually benefit from AI? If so, what should those in the legal profession know about this technology before employing it in their work?

There are two ways to think about how AI is used and how accurate it must be. If you are a retailer like Amazon that is selling products, or you are a social media platform, a 2 percent error rate in AI outcomes is fine. In these scenarios, failing to make a successful prediction is as harmless as a customer being recommended a product they really don’t want or a social media user seeing an article in their news feed they aren’t particularly interested in. But in other industries, such as healthcare, autonomous vehicles, computers and law, such an error rate is unacceptable. Bringing AI into these categories is hard because there is simply no room for error.

Legal professionals interested in AI should understand the basics and avoid the hype.

How AI works:

AI enables a computer to make complex decisions using inputted data – or “features.” It is good at answering certain kinds of questions:

• What is this? (Classification)
• How should these things be grouped? (Clustering)
• Is something weird or out of place? (Anomaly detection)
• How do these two things relate to each other? (Regression)
• What comes next? (Forecasting)

Types of data:

AI can empower answers to these questions with data that is either labeled, resulting in “supervised learning,” or unlabeled, resulting in “unsupervised learning.”

In supervised learning, an algorithm is developed to make decisions on an often laboriously manually labeled data set. For example, an existing library of legal cases could be labeled according to whether or not they went to trial. AI could then be used to predict the likelihood that a case not in the data set will go to trial, which could impact litigation or settlement strategies.

In contrast, unsupervised learning works with data sets that are not labeled. These use cases often involve evaluating the similarity of members in a data set, typically by grouping or clustering items. For example, a data set may include a large number of contracts, and the AI would determine which are similar to each other and which are significantly different from the norm. This “difference metric” could then be used to help identify potentially risky contracts. An additional unsupervised use case involves e-discovery, when culling through thousands of potentially discoverable e-mails. If a lawsuit involves employee fraud, using AI to sort through e-mail would remove those unrelated to the facts of the case, such as those focused on lunch or happy hour.

Transparency is key:

It’s imperative that AI and machine learning algorithms are transparent. When culling through data and excluding certain pieces, i.e. e-mails involving lunch or happy hour, information must be included so that a judge ruling on the case understands why certain pieces of evidence were not included. Courts are unlikely to accept “an algorithm that we are unable to evaluate or explain determined this to be the case.”

When using AI to create legal contracts, for example, it’s important that there is an explanation for every decision the AI makes. If the AI is generating a risk score for each clause, a lawyer should be able to review the reasons why a high or low score was assigned. This information can turn an opaque, frustrating AI decision into a useful tool for aiding a lawyer in contract analysis. For example, lawyers using the software our company, Advocat AI, has developed for creating contracts, are able to drill down clause by clause using different “document lenses” to glean more information about the characteristics of each clause. This includes explanations about how risk scores were assigned, citations to legal research or related clauses, or simply a log of analysis and decisions AI systems made for that clause.

Whether or not an AI’s decisions can be made transparent is frequently dependent on the fundamental implementation of the technology. A key takeaway is that when considering adding a legal AI solution, always determine the level of transparency you will need and c

How are lawyers using AI now?

Almost exclusively, the legal community uses AI software, tools or platforms purchased from third parties. AI is deployed in due diligence tools to research such things as individual background reports, business names, patents, and intellectual property. Others use tools that employ AI to quickly create general contracts that must be customized.

But lawyers should never trust AI 100 percent of the time. I recommend that a human always be involved in the decision pipeline. AI can be used to more quickly and easily make decisions, but final decisions must be reviewed by a real person.

For example, a business might feed standardized templates and data into a database and use AI to help create customized sales, non-disclosure or employment contracts. The AI technology can do the majority of the work to generate a near-final contract. But a lawyer should always review the contract and sign off on it.

The legal community is in the process of embracing AI and machine learning. Lawyers hope it will allow them to spend less time doing the boring, repetitive work that takes up so much of their time. AI is easy to use when one has all the data needed to make a decision and the data is reviewed. However, most lawyers – rightly - don’t completely trust the AI they are relying on.

It’s imperative that lawyers understand the AI tools being used and deploy them wisely.

U.S. companies should heed the government’s directive to carefully check all contracts to make sure they are not violating U.S. sanctions on Russia. Companies that fail to do so could not only get into trouble, but are also in effect helping the Russian government in its war against Ukraine.

All U.S. companies that do international business can comply with this government order by running the names of all companies they contract with and the companies’ beneficial owners through the U.S. Treasury Department’s Office of Foreign Assets Controls (OFAC) and Specially Designated Nationals and Blocked Persons (SDN) lists.

OFAC administers and enforces economic sanctions and publishes a list of individuals and companies that are subject to sanctions. Their assets are blocked and U.S. individuals and businesses are generally prohibited from dealing with them.

Not all Russian individuals and companies are on the list, which can change as often as daily. To keep up with the changes, some U.S. companies designate specific employees to manually monitor the list, with the ultimate responsibility left to the chief financial officer and finance departments, general counsel and legal departments, or chief operations officer. Other companies use technology to do this for them. Technology that monitors contracts can also help determine which companies are owned by or otherwise connected to entities on the sanctions list. Monitoring beneficial ownership and/or control is harder to do, but is still required.

The sanctions laws have a reasonableness standard to them, but they expect U.S. companies to ferret out the ownership of companies they are doing business with if it is available and accessible. Time and money necessary to do the research are not considered adequate reasons not to find the information – especially because the names of sanctioned individuals and companies are available in the government’s databases.

It is, however, more difficult to find the owners of sanctioned companies, information not always readily available in the database. It’s not unusual for ownership to change rather quickly – think about all those Russian oligarchs who no longer own their big yachts, which are suddenly owned by newly formed LLCs.

There is precedent for what happens to companies that don’t follow sanctions. In the 1980s, Toshiba Machine Co., a Toshiba subsidiary, got into big trouble in the United States when it sold military machinery to the Soviet Union. Although Toshiba is not a U.S. company, the U.S. Senate threatened to ban U.S. companies from buying products from Toshiba because of sanctions against such sales. Ultimately, Toshiba’s president and chairman resigned and Toshiba spent plenty of money and time clearing its name so that it could once again do business with U.S. companies. The company lost much more than it would have if it had simply complied with the sanctions.

Companies that violate sanctions can face financial penalties, criminal proceedings, reputational damage, and the risk of being sanctioned themselves, depending on how egregious the violation is.

Even when Russia’s war against Ukraine ends, it’s quite likely the sanctions will remain. The U.S. still maintains its sanctions on Cuba, Iran, North Korea, and Syria. Sanction programs are rarely fully lifted; but individuals and companies can certainly be removed from the sanctions list.

How can technology help?

One of the easiest ways for companies to stay on top of the sanctions regulations – among other things - is to employ technology that routinely searches the content of the contracts they have and notifies the company of important updates. Such technology monitors changes to government databases to easily keep up with changes on which foreign individuals and companies are included and who owns or controls them. Such technology frees up valuable employee time for other work related to the company’s bottom line.

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