Natural Language Processing – A Modern Legal Workhorse

Natural Language Processing – A Modern Legal Workhorse

Since the introduction of the computer and all its capabilities, people have been wondering – will technology ever replace human intelligence in the workforce? While this still isn’t a concern in many areas, there are some tedious or menial tasks that can be taken care of by computers now. This has a multitude of benefits for both employers and workers when applied correctly. One example of this is natural language processing – or NLP – in the legal field.

NLP in the Legal Setting

Natural language processing is a combination of computer science, linguistics and statistics to “understand” how language works and what is most likely or most logical in various scenarios. NLP legal applications may include:

  • Question response: Some legal websites may include NLP “chats” to answer basic questions for consumers.
  • Information retrieval: Speech recognition and language pattern prediction can be used to retrieve answers to questions or search queries.
  • Information extraction: This is a common application in the legal field, in which large amounts of audio, raw text or other materials are analyzed by NLP programs to extract key information for contracts, legal documentation and more.

How NLP Makes Litigation Easier

There are many ways in which NLP makes the legal process easier for both clients and legal professionals. The tedious work of extracting information and answering simple questions can be handled by this type of outsourcing, freeing more time for lawyers and legal assistants to perform other tasks for their clients. Additionally, the money saved on man hours by using technology to lessen time means savings that can be passed on to the client via reduced fees or lower overall costs. NLP’s legal applications can lead to a smaller staff, increased focus on important tasks and better representation for clients, as well as fewer costs for providers. It’s a true win-win situation for everyone impacted!

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