AI Is Reshaping Legal Work: Why Understanding the Terminology Matters

Artificial intelligence (AI) is transforming industries worldwide, and the legal sector is no exception. From automating document review to predicting case outcomes, AI-powered legal solutions are streamlining workflows and improving decision-making. As AI legal technology becomes more sophisticated, legal teams have to understand the language behind it.

Without a solid grasp of AI terminology for legal teams, professionals may struggle to evaluate new technologies, assess compliance risks, or effectively integrate AI technology into their workflows. But you don't need a masterclass in legal AI terms to use AI systems. This article breaks down essential terms and concepts, providing a comprehensive AI glossary for lawyers to navigate the evolving landscape of artificial intelligence in the legal sector.

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The Challenge Legal Teams Face with AI Terminology

Legal professionals are no strangers to complex language, yet AI introduces an entirely new lexicon. Terms like "machine learning," "natural language processing," and "algorithmic bias" are frequently mentioned but not always well understood. The challenge lies in distinguishing between different types of AI, grasping their implications for legal work, and applying this knowledge effectively.

AI terminology originates from the fields of computer science and data science, making it inherently technical. Fortunately, lawyers and legal professionals don’t need to become AI experts to use these technologies. Instead, they need a working understanding of key terms to engage in meaningful discussions with technology providers. Not to mention assess regulatory implications and ensure ethical compliance when using AI systems. Let's discuss. 

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Essential AI Terms Every Legal Professional Should Know

1. Artificial Intelligence (AI)

AI refers to computer systems that can perform tasks typically requiring human intelligence, such as problem-solving, learning, and decision-making. AI is an umbrella term encompassing various technologies, including machine learning and natural language processing.

2. Machine Learning (ML)

A subset of AI, machine learning enables computers to learn from data and improve performance over time without being explicitly programmed. ML is widely used in AI-powered legal solutions for tasks like contract analysis and risk prediction.

3. Natural Language Processing (NLP)

NLP is a branch of AI that allows computers to understand, interpret, and generate human language. In legal settings, NLP is used for document automation, contract review, and e-discovery.

4. Algorithmic Bias

This occurs when an AI system produces unfair outcomes due to biases in training data or algorithm design. Legal professionals must be aware of potential biases in AI legal technology to ensure fair and ethical applications.

5. Explainability

Explainability refers to the ability to understand and interpret how an AI tool reaches its conclusions. In the legal sector, explainability is crucial for ensuring AI-driven decisions comply with regulatory and ethical standards.

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Machine Learning vs Generative AI: Understanding the Difference

Machine learning and generative AI are two distinct AI approaches with different applications in legal technology.

• Machine Learning: Focuses on recognising patterns in data and making predictions. For example, ML can analyse past litigation outcomes to predict case success probabilities.
  
  
• Generative AI: Involves AI models that create new content, such as text, images, or summaries. In legal contexts, generative AI can draft contracts, summarise lengthy case files, or generate legal arguments based on precedent.
  
  

While both technologies play vital roles, understanding their differences helps legal teams select the right AI-powered legal solutions for specific needs.

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Natural Language Processing (NLP) and AI-Powered Document Review

One of the most impactful applications of AI in the legal sector is NLP-powered document review. Traditional document review is time-consuming and prone to human error, but AI significantly enhances this process.

NLP can:

• Identify relevant clauses in contracts within seconds
  
  
• Extract critical information from thousands of case files
  
  
• Flag inconsistencies or potential risks in legal documents
  
  

For example, AI-powered contract analysis tools can instantly identify non-standard terms in a commercial agreement, reducing the time required for manual review. By leveraging NLP, legal teams can focus on higher-value tasks, such as strategy development and client advocacy.

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AI Bias, Explainability, and Ethical Considerations in Legal Tech

AI's increasing role in legal decision-making raises ethical and regulatory concerns. Algorithmic bias is a significant issue—if an AI system is trained on biased data, it may produce discriminatory or unjust outcomes.

Consider a scenario where an AI tool assesses the risk of litigation based on historical case data. If past cases reflect systemic biases, the AI model could perpetuate these biases, leading to unfair recommendations.

To mitigate such risks, legal professionals must:

• Demand transparency from AI providers regarding data sources and model training
  
  
• Advocate for fairness and accountability in AI-driven decision-making
  
  
• Stay informed on regulatory developments, such as the EU AI Act and other AI governance frameworks (see the EU’s AI regulatory proposal)
  
  

How Safelink Uses AI to Enhance Legal Case Management

Safelink integrates AI across its product suite to enhance efficiency, accuracy, and security in legal case management. That means teams can save time, improve decision-making, and manage sensitive case data securely. Here’s how: 

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Chronologica: AI-Powered Chronology Building

Designed to automate case timelines effortlessly, Chronologica’s AI capabilities allow legal professionals to:

• Extract key facts and events from uploaded documents automatically
• Generate case timelines guided by a chosen narrative
• Receive AI-driven suggestions for additional details and supporting evidence

With Chronologica, legal teams can construct precise case timelines faster and with greater accuracy, ensuring no critical detail is overlooked.

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Lexiti: AI-Enhanced eDiscovery

Lexiti simplifies document review and eDiscovery by using AI to:

• Summarise documents and automatically generate document names
• Identify key entities such as people, places, and dates within case evidence

This streamlines narrative construction, allowing legal teams to locate relevant information efficiently and share data securely with their teams.

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Expero Virtual Data Rooms (VDRs): Secure AI-Powered Collaboration

Safelink’s Expero VDRs provide a secure environment for sharing sensitive documents while ensuring tight access controls. AI capabilities within Expero include:

• Concept search: Identify documents containing concepts related to a legal query
• 'Ask Alex' AI assistant: A question-answering bot that retrieves relevant documents while respecting folder permissions

Rather than being bogged down with routine admin and manual file management, these AI-powered solutions deliver on their promise of allowing legal professionals to work smarter, faster, and at the top of their license. 

As AI continues to reshape the legal industry, Safelink makes it easy to leverage its benefits while getting to grips with AI terminology. Discover what AI can do for your team when it comes to case management, court bundling, and chronologies. Contact us today for a free demo.

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