A.I it’s not just for term papers anymore!

In recent years, artificial intelligence (AI) has been increasingly used in eDiscovery to assist with tasks such as document review, data analysis, and predictive coding. AI is now an essential and anticipated aspect of eDiscovery. One of the most notable examples of this is the use of language models like OpenAI’s GPT-3 and its competitors such as Google’s TensorFlow, Hugging Face’s BERT, and eDiscovery providers such as Relativity’s ECA AI and Open Text’s Insight Predict, which utilize natural language processing to automatically classify, extract and summarize vast amounts of unstructured data, allowing for faster and more accurate review.

There are many examples of how AI can and is being used in eDiscovery. Here are a few:

  • Contract analysis: AI-powered tools can be trained to extract key information from contracts, such as parties involved, key terms, and expiration dates, which can help legal professionals quickly identify potential issues and reduce the time spent on contract review.
  • Predictive coding: This AI-powered technology uses machine learning algorithms to automatically classify, extract and summarize vast amounts of unstructured data, allowing for faster and more accurate document review.
  • Email threading: AI-powered tools can automatically group and organize emails by thread, making it easier for legal professionals to review and understand communications related to a specific topic.
  • Keyword search and Boolean search: AI-powered search tools can understand and perform more sophisticated search requests than traditional keyword search, such as natural language processing and Boolean search.
  • Early Case Assessment: AI can be trained to quickly identify and extract relevant documents from a large corpus of data, allowing legal professionals to focus their efforts on the most important information.
  • Language Translation: In the event that documents are in multiple languages, AI powered tools can help in quick translation of documents, making the process more efficient.
  • Identifying additional custodians: AI can aid in identifying parties who might be involved in a legal matter but were not previously considered, as well as review documents to identify if additional parties are communicated with.
  • Summarizing and creating summaries: AI can help in summarizing large documents, contracts, or emails, and extract key information, reducing the amount of time that legal professionals need to spend on review.

 

These are just a few examples, the possibilities with AI in the eDiscovery process are quite varied, the above-mentioned examples are the most popular ones. It’s important to mention that, as the technology continues to evolve, there will likely be even more ways that AI can assist with eDiscovery in the future.

A.I is also being incorporated in commercial eDiscovery tools. Relativity’s ECA (Early Case Assessment) A.I is a tool that uses artificial intelligence and machine learning to help legal professionals quickly identify and prioritize relevant information in large collections of data. It’s designed to assist legal teams during the early stages of the eDiscovery process, before document review begins.

ECA A.I can be used to automatically classify, extract, and summarize vast amounts of unstructured data, such as emails, contracts, and other documents. The tool uses natural language processing (NLP) to understand the content of documents and can be trained to extract specific information, such as key terms, parties involved, and dates. The tool also includes predictive coding which can quickly identify and prioritize relevant documents for review.

The tool is integrated with Relativity’s eDiscovery platform, which allows legal teams to perform a variety of tasks on their data, such as searching, analyzing, and producing documents. The integration allows for a smooth workflow, where the ECA A.I’s output can be easily imported into the platform, where it can be further analyzed, search and prioritized by the users.

ECA A.I can also help legal teams identify and extract additional data and parties that may not have been previously considered. It can also help legal teams to quickly identify and prioritize high-risk documents, which may contain sensitive or privileged information. In summary, ECA A.I is designed to help legal teams quickly identify and prioritize relevant information and reduce the time and cost associated with the eDiscovery process.

However, it’s important to remember that while AI solutions can greatly assist in the eDiscovery process, it is crucial to thoroughly check all work product for accuracy, just as a driver should keep their hands on the wheel of a self-driving car, in case human intervention is needed. A.I can assist with many tasks, but it cannot replace the human touch, and legal professionals are responsible for ensuring that all information is correct before proceeding with any actions, as the legal process must be accurate and fair. As Law Technology Today mentions, A.I serves as a sort of “curator” in the eDiscovery process, suggesting the most pertinent documents for further examination, and as an “orchestrator”, adapting and coordinating tasks based on past results. Furthermore, A.I also streamlines the discovery process even before the review phase by utilizing data mining methods that reduce the number of documents to be reviewed and extracts new keywords and search phrases, or even finds additional parties that should be considered for legal hold or interview.

The use of A.I in eDiscovery can help speed up the process and reduce costs by automating time-consuming tasks and identifying relevant documents more accurately. As the technology continues to evolve, it is likely that A.I will play an even greater role in eDiscovery in the future. Advancements like NLP, Machine Learning and integration with Neural network will become more prevalent, which will likely lead to even more efficient and effective document review and analysis, and could potentially even lead to the development of new types of legal tools. Additionally, AI could be used to analyze and make predictions about legal trends and potential outcomes, further streamlining the legal process. Skynet isn’t coming, it’s here!

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