Current thinking

Sir Geoffrey Vos KC, Master of the Rolls, recently said that “The day is coming, and soon, when professionals and others will be legally on the hook for not using generative AI”, and suggested that AI was more likely to be used directly by consumers, rather than just by lawyers who advise them; this clearly shows the direction in which AI is likely to be going in the legal sector. 

Humans -v- AI

The International Monetary Fund, in January 2024, said that “Artificial Intelligence will affect up to 40% of jobs worldwide”, it suggested that jobs that require nuanced judgment, creative problem-solving, or intricate data interpretation - traditionally the domain of highly educated professionals - may now be augmented or even replaced by advanced AI algorithms, this could rise to 60% of roles in advanced economies like the UK - but it is believed that, in half of these cases, AI will benefit the workforce.

What is AI?

The Information Commissioner defines AI as, “Algorithmic systems that solve complex tasks by carrying out functions that previously required human thinking.”

AI differs from ordinary IT systems in relation adaptivity, in that it can make inferences that it was not explicitly programmed to produce, which means it can be harder to explain the system’s decisions. Some AI systems can make decisions without the express intent or ongoing control of a human, which can make it harder to say who is responsible for the system’s outputs.

Components of AI:

• Machine learning – a way of achieving AI, which is based on the idea that systems can learn from data, identify patterns and make decisions with minimal human interaction.
• Deep learning – technically machine learning and functions in a similar way, but its capabilities are different. Deep learning is especially good at recognizing patterns in unstructured data sets likes images, audit files, and textual content.
• Natural language processing – involves the interactions between computers and humans through natural language.
• Robotics – focuses on different branches of AI and applications of robots.
• Knowledge representation – involves techniques for encoding all the knowledge a computer needs to solve complex tasks, such as diagnosing a medical condition or having a dialogue in a natural language.
• Expert systems – computer systems that emulate the decision-making abilities of a human expert.

National AI Strategy

There are a number of guiding principles being proposed, namely:

• Safety, security and robustness
  • Choose systems carefully to make sure they will meet your needs.
  • Test all systems thoroughly before bringing them into use.
  • Train and supervise your staff in what is and is not a safe and acceptable use of your systems and other uses of AI.
  • Encourage staff to practice asking effective questions of AI, and if possible, provide training, to gain the best results.
    
    
• Transparency and explainability
  • Make sure that you, and staff who can access the system, can understand how it operates and makes decisions, and that you can explain this to clients.
  • Tell clients when you will be using AI with their case, and how it will operate.
    
    
• Fairness
  • Be sure that any AI you use is only processing personal data in ways that people can reasonably expect.
  • Monitor the outputs of an AI carefully to make sure it is not producing biased or inaccurate outcomes.
  • Make sure that you introduce, train and operate AI in a way that protects confidentiality.
  • Follow all data protection principles when operating any AI, remembering that all normal rules still apply.
    
    
• Accountability and governance
  • Supervise AI systems, and staff use of them, to make sure that they are working as expected and providing accurate results.
  • Have supervision systems that can cope with the increased speed of AI.
  • Remember that you cannot delegate accountability to an IT team or external provider: you must remain responsible for your firm’s activities.
    
    
• Contestability and redress
  • Provide routes for people to contest AI decisions they disagree with.
  • Make sure that your complaints procedures can handle questions about AI use.
  • You might need to decide whether to tell clients that they can speak to a human before making decisions based on AI information.

AI regulations

Regulation is still being created in this relatively new area, but there are some existing regulations and standards that cover AI, including:

• Existing non-AI regulation (Equality Act, GDPR, SRA Codes of Conduct)
  
  
• AI-specific laws (EU AI Act, China Generative AI Law)
  
  
• AI specific standards (ISO, IEC)
  
  
• Amendments to existing laws and regulations to apply to AI (product liability and IP regimes)

Ethics in AI

AI systems reflect the biases, values and decisions of those who create them and can have significant social ramifications, but mitigating bias and unfairness can be done through:

• Use of diverse and representative data
  
  
• Bias detection
  
  
• Transparency
  
  
• Continuous monitoring and feedback
  
  
• Regulations and standards

Opportunities from AI

There are a number of opportunities that came be gained from using AI, including:

• Speed and capacity
  
  
• Cost savings
  
  
• Transparency
  
  
• Skill development

How can AI affect law firms?

There are a number of ways that AI lawtech is and can be used, including:

• Managing the business
  • People and resources management; finance and operations, managing client relations
    
    
  • Risk identification and prediction; automates routine compliance tasks such as those that can support part of the anti-money-laundering checks. More advanced uses include analysing cases to predict the chance of success.
    
    
• Managing and performing law-related tasks
  • Knowledge management; matter management; risk management; legal rights management
    
    
• Performing work
  • Profiling; involves tasks such as identifying consumers’ understanding, classifying documents or prioritising cases.
  • Searching:; automates work such as document discovery or identifying precedents for litigation, providing an efficient first step for law firms when preparing cases or considering their approach.
  • Text generation; involves directly producing content, such as contract drafting, client letters or any other form of written communication or document.

Professional indemnity insurance considerations

There is no current caselaw around professional liability where AI is involved, so it is strongly recommended that firms speak with their insurers if they are looking to implement AI systems, particularly in relation to potential areas of liability, including:

• Negligence in decision to delegate work to AI
  
  
• Negligence in the implementation of AI (instruction, training, monitoring of AI)
  
  
• Strict liability for errors by AI – e.g. where no human fault in relation to the two points above
  
  
• Vicarious liability? – e.g. liability of firm if outsourced

The future of AI and law firms

It is likely that we will see AI becoming more autonomous and adaptive and this could bring about solutions to global challenges. Those working within the legal sector should ensure they keep abreast of developments in the use of AI, and where appropriate, adopt it.

Firms that don’t engage with AI are very likely to lose out to firms that do!

Takeways

• Understand how AI may benefit your firm’s operations
  
  
• Create an effective implementation plan if AI is to be used
  
  
• Carry out a data protection impact assessment before starting an AI project
  
  
• Ensure you can comply with your regulatory obligations
  
  
• Seek advice from your firm’s PII insurers
  
  
• Train staff accordingly