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AI in eDiscovery

AI in eDiscovery: Balancing Opportunity with Caution

eDiscovery plays a crucial role in litigation, internal investigations, and compliance. However, exploding data volumes force legal professionals to walk a tightrope between identifying all relevant information and managing cost and risk. AI in eDiscovery offers huge benefits in terms of speed and insights, but significant challenges require legal teams to proceed with caution.

Moving from Traditional eDiscovery to TAR

Traditional eDiscovery methods involved using keyword searches to reduce the number of documents to collect for review. In theory, this approach had merit. However, it proved both cumbersome and time-consuming.

In the first place, large volumes of data in various locations and formats make it difficult to access relevant information. Secondly, because keyword searches do not take context into account, they may miss important data.

Enter technology-assisted review (TAR), also known as predictive coding. Using AI algorithms, TAR analyzes document sets, identifying and tagging potentially relevant documents. Humans train algorithms using examples of relevant and non-relevant data. During this training phase, the algorithm learns to make educated guesses about the remaining data.

While courts have approved the use of TAR for several years, recent advances in AI promise even greater benefits.

AI in eDiscovery

AI Delivers Clear Benefits for eDiscovery

AI, including TAR and additional emerging tools, has the power to revolutionize eDiscovery through automating tedious tasks and offering important insights. Advantages of this technology include:

  • Enhanced efficiency – By automating time-consuming tasks such as data tagging, AI can free up valuable human resources. And by prioritizing data with a higher probability of relevance, AI greatly reduces the amount of data for review. AI can also assist with creating summaries and chronologies.
  • Greater accuracy – Generative AI excels at combing through large datasets to extract and highlight relevant information. AI can also assist with automatically detecting and redacting sensitive data such as PII, thus improving compliance with data privacy regulations.
  • Ability to uncover hidden insights – By identifying patterns, trends, and anomalies, AI helps to reveal hidden connections that human reviewers might miss. It can also suggest documents similar to those already identified as relevant, potentially uncovering important information.
  • Improved reliability, reduced bias – AI applies a consistent approach to document review throughout the process. This helps to ensure fairness and reduce inconsistencies.

AI in eDiscovery

Every Lucky Penny Has a Flip Side

However, with great power comes increased risk, and AI introduces several key challenges that legal teams cannot afford to overlook.

  • Data security and privacy – Integrating AI into eDiscovery workflows adds another element to an already complex cyber security and privacy landscape. For instance, LLMs typically reside in cloud services such as Microsoft Azure. Additionally, threat actors can potentially poison the data used to train AI algorithms, significantly affecting output.
  • Unintended bias – The accuracy of AI algorithms depends on the data used for training. An AI model trained on biased data will amplify those biases.
  • Unexpected output and lack of transparency – No AI application can guarantee 100 percent accuracy, and many AI models operate as black boxes. This means that it can prove difficult to interpret how the AI tool reaches decisions. However, ethical decision making and regulatory compliance require transparency.
  • Validating evidence in an era of generative AI – In addition to risks in the eDiscovery process, AI also introduces difficulties in determining the veracity of evidence. Legal teams need to ensure that they are not including deepfakes in submitted evidence.

Responsible Implementation of AI in eDiscovery

Despite these challenges, careful implementation of AI holds immense potential to continue transforming eDiscovery. Legal teams should critically evaluate AI solutions, ensure human oversight, and address ethical considerations throughout the process. With eGovernance, organizations gain access to powerful, proven AI-powered eDiscovery.

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eGovernance eDiscovery Solutions

Providing a set of sophisticated and simple to use tools to search, refine and extract data in support of FOIA requests, litigation or internal audits; eGovernance provides organizations with rapid and efficient data discoveries to meet ever growing regulatory and financial deadlines.

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