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In the year 2015, a group of high-profile scientists warned that artificial intelligence might be the last invention of the human race. 

Well, it’s 2020, and their statement still holds value.

Today, after so many years, the use of AI in the legal industry has evolved from just focusing on the human vs. robot lawyers debate to the reality of using artificial intelligence in ediscovery to improve the process, as well as an attorney’s ediscovery experience.

Unlike many other industries, artificial intelligence in ediscovery is not about the Siris and Alexas of the world. The use of AI in the ediscovery process helps find essential documents, facts, and details with machine-like accuracy and at highly-accelerated speed.

Here, I will discuss four ways AI can help organizations with their ediscovery process.

1. Faster information identification

Gathering physical and digital information and fusing data from internal and external sources is the first step in the EDRM and also the foundation of the entire ediscovery process. This whole information identification process usually involves human resources, requires time, and incurs extra cost as well.

Artificial intelligence can automate this entire step as a self-service system. Organizations can use AI-based platforms that use statistical inference and natural language processing to do labelling and reviewing of all data while driving faster and more accurate results, as compared to doing it manually. 

2. Preserving the data and finding the missing pieces of information.

Another critical use of AI in the ediscovery process is to organize the data and find those missing pieces of information that are deemed essential. With the help of AI-based tools, organizations can proactively organize the large volumes of data, maintain accurate records, and also quickly provide access to the relevant people when they need it.

3. Increased efficiency with fast due diligence reviews.

Sifting through piles of documents, studying key contract clauses, looking for litigation issues and intellectual property, etc. takes up so much time. The key benefit of implementing AI at this step is automated and faster due diligence reviews, which otherwise, organizations pay to acquire as a service from legal professionals.

4. Predictive coding

With the help of AI, organizations can constantly learn and make better decisions while significantly accelerating the review process through predictive coding, which is also known as technology-assisted review (TAR) or computer-assisted review (CAR).

Predictive coding uses a seed set of data in the form of a sample document that needs to be reviewed. After being marked as relevant or irrelevant (to the case) by an attorney, the software learns the methods by human input and assists with better decisions in the future.

The technique of applying predictive coding and advanced AI algorithms can also help in prophesying if submitted documents are responsive to criteria established by the organization for the ediscovery process. 

Parting Note

All in all, artificial intelligence in ediscovery is a welcome improvement making the whole process faster, better, and cheaper. Organizations that invest in adding AI capabilities to their processes right now will definitely have a distinct competitive advantage for years to come.

About the Author:

Hira Saaed

Hira Saaed

Hira Saaed is an independent tech journalist, and the founder of Digital Doers, a content partner and consulting agency.

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