MCP Insights

‘Big Data’ Is Helping Justice Organizations Address Their Biggest Challenges

Posted on February 28, 2022 by Shay Cleary

“Big data” is an approach used to analyze extremely large, extremely complex, unstructured datasets. While the majority of data that courts create, manage, and are responsible for wouldn’t be considered “big data,” courts can benefit tremendously from recent advances in big data tools.

Such tools leverage artificial intelligence (AI) and machine learning (ML) to identify patterns, anomalies, and even form conclusions across large diverse datasets. These terms often are used interchangeably, but they are not synonyms. AI is a system that appears “smart.” It mimics human behaviors (such as driving a car) to enhance human decision-making but does not replace it. ML is a type of AI that is able to spot patterns and anomalies in very large datasets. AI and ML can be leveraged very effectively to solve some of the most pressing challenges being faced by justice organizations today. The staffing shortage that is afflicting organizations from coast to coast is a big one. Let’s examine a few ways that AI and ML can alleviate the strain of this challenge.

AI/ML-Assisted Document Entry and Processing

Robotic process automation (RPA) involves software applications — also known as software robots, or “bots” — that can run automated tasks. In the justice environment, bots can be used to read documents that have been submitted to a court and then make the appropriate entries into the case management system. The bot accomplishes this by first using ML to identify keywords in the document and then using AI to understand their significance. This capability should be of interest to any court administrator who is dealing with a staffing shortage, i.e., just about every court administrator.

Chatbots and Virtual Assistants

They typically are deployed on the organizations to answer common questions, freeing up staff members to handle more complex tasks. In the beginning, these applications needed to be pre-populated with the questions and answers, but now they leverage natural language processing (NLP)— the same technology used by Amazon Alexa and Google Assistant — to “listen” to the question and provide the answer. They also “learn” when they receive feedback that an answer was spot on or missed the mark. NLP uses AI and ML to give computers the ability to understand text and spoken words. This is a great tool that can be deployed today by organizations that lack counter staff. They’re not yet at the level of Alexa, but they’re rapidly getting better.

AI/ML-Assisted Data Quality Tools

Maintaining proceeding records is a primary responsibility of court systems, and while the data generated often is high quality, big data tools can be used to sift through enormous amounts of information to identify anomalies. This can lead to the discovery of data quality issues that can be corrected via AI and ML. Doing this can free up staff members from having to spend time reviewing exception reports, while also preparing the court’s data to take advantage of other AI and ML opportunities.

AI/ML-Assisted Judicial Decision-Making

Judges and other justice officials have to make many critical decisions. For example, judges have to decide whether the accused should be granted bail, and how high bail should be set. They have to determine appropriate sentencing when the accused is convicted. Later, parole boards have to decide whether an individual should be granted parole. These decisions depend on much more than the evidence presented in the charging documents or during the court proceeding. The problem is that law enforcement agencies, prosecutor offices, and court systems generate an enormous amount of data that would be useful in this regard, but the data usually is not well-integrated, which make it extremely difficult, if not impossible to find and extract relevant information. AI and ML, working in concert with big data tools, can parse and contextualize substantial amounts of data that judges can use to make better-informed decisions.

A future blog will focus on the importance of data governance in the justice sector. In the meantime, please reach out to learn more about how big data can help your situation, and to allow MCP’s data integration services team to develop a customized strategy.

Shay Cleary is an MCP senior project manager. Email him at

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