In our previous article, we explored several legal implications that artificial intelligence will have on patent law, and the availability of patent protection for AI inventions. In this article, we explore the impact of AI in the legal industry, including new AI tools for legal departments, and how to plan for risk when using these AI tools.
AI in the Legal Sector
Machine learning is an application of AI in which AI’s algorithms learn from past experiences and then apply this knowledge to predict future outcomes.
Because there are many similarities between the law and machine learning, the law is conducive to AI and its machine learning applications. For example, both the law and AI machine learning infer rules from historical examples to apply to new situations. Legal rulings involve applying propositions based on prior precedent to the facts at issue and deriving an appropriate conclusion. AI machine learning uses the same process. The law and AI machine learning are both logic-oriented methodologies (e.g., if X happens, then the result should be Y).
Natural language processing (NLP) is another application of AI in which the AI’s algorithms automatically process and interpret words based on the context in which the words are used. For example, rather than processing a word in isolation, NLP processes the word based on the other words used in the same phrase or sentence in which the word appears, and the topic or application in which the word is used. This is similar to law that requires attorneys to analyze terms in a contract or identify facts of a case that is similar to a case at issue.
Common Uses for AI Tools
Machine learning and NLP have enabled a number of AI tools to be developed to help legal departments reduce costs, develop data-driven strategies, assess risk, and become more productive. Below, we identify some of the AI tools that are available to legal departments.
Excerpted from LegalTech News. To read the full article, click here.
AI in the Legal Sector
Machine learning is an application of AI in which AI’s algorithms learn from past experiences and then apply this knowledge to predict future outcomes.
Because there are many similarities between the law and machine learning, the law is conducive to AI and its machine learning applications. For example, both the law and AI machine learning infer rules from historical examples to apply to new situations. Legal rulings involve applying propositions based on prior precedent to the facts at issue and deriving an appropriate conclusion. AI machine learning uses the same process. The law and AI machine learning are both logic-oriented methodologies (e.g., if X happens, then the result should be Y).
Natural language processing (NLP) is another application of AI in which the AI’s algorithms automatically process and interpret words based on the context in which the words are used. For example, rather than processing a word in isolation, NLP processes the word based on the other words used in the same phrase or sentence in which the word appears, and the topic or application in which the word is used. This is similar to law that requires attorneys to analyze terms in a contract or identify facts of a case that is similar to a case at issue.
Common Uses for AI Tools
Machine learning and NLP have enabled a number of AI tools to be developed to help legal departments reduce costs, develop data-driven strategies, assess risk, and become more productive. Below, we identify some of the AI tools that are available to legal departments.
Excerpted from LegalTech News. To read the full article, click here.