Source:
https://economictimes.indiatimes.com/tech/ites/iit-kharagpur-develops-ai-system-to-read-legal-judgments/articleshow/73296111.cms
Instead of the usual ‘Conditional Random Fields’ that use handcrafted features to train the machine, they have used two deep neural models to understand the rhetorical roles of sentences in a legal case judgment.
Automatically understanding the role of sentences in a legal case judgment is important as it can help in several downstream tasks such as summarization of legal judgments, legal search, case law analysis and other functions.
“For a country like India, which uses a common law system that prioritizes the doctrine of legal precedent over statutory law, and where legal documents are often written in an unstructured way,the difference AI can bring is phenomenal,” said Ghosh.
Taking 50 judgments from the Supreme Court of India, the team has segmented these by first labeling sentences using multiple human annotators (three senior law students from IIT Kharagpur’s Rajiv Gandhi School of Intellectual Property Law), performing extensive analysis of the human-assigned labels and then developing a high quality gold standard corpus to train the machine to carry out the task.
Prior attempts to automate identification of rhetorical roles of sentences in legal documents have depended on handcrafted features such as linguistic cue phrases indicative of a particular rhetorical role. These features depend on legal expert knowledge which is expensive to obtain. Besides, these features are often developed keeping in mind one specific domain. The neural methods used by the IIT Kharagpur team automatically learn the features, given sufficient amount of data, and can be used across domains.
https://economictimes.indiatimes.com/tech/ites/iit-kharagpur-develops-ai-system-to-read-legal-judgments/articleshow/73296111.cms
MUMBAI: IIT Kharagpur researchers have evolved an
Artificial Intelligence-aided method to read legal judgments, which can not
only tell which laws are getting violated but also in the process help minimize
legal costs.
A team of researchers at the premier engineering institute’s Department of Computer Science and Engineering used a novel method to automate the reading of a legal document by using a more evolved Machine Learning technique.
“We are trying to build an AI system which can give guidance to the common man about which laws are being violated in a given situation, or if there is merit in taking a particular situation to court, so that legal costs can be minimized,” said Saptarshi Ghosh, professor at the Department of Computer Science and Engineering, who is leading a team of researchers.
A team of researchers at the premier engineering institute’s Department of Computer Science and Engineering used a novel method to automate the reading of a legal document by using a more evolved Machine Learning technique.
“We are trying to build an AI system which can give guidance to the common man about which laws are being violated in a given situation, or if there is merit in taking a particular situation to court, so that legal costs can be minimized,” said Saptarshi Ghosh, professor at the Department of Computer Science and Engineering, who is leading a team of researchers.
Instead of the usual ‘Conditional Random Fields’ that use handcrafted features to train the machine, they have used two deep neural models to understand the rhetorical roles of sentences in a legal case judgment.
Automatically understanding the role of sentences in a legal case judgment is important as it can help in several downstream tasks such as summarization of legal judgments, legal search, case law analysis and other functions.
“For a country like India, which uses a common law system that prioritizes the doctrine of legal precedent over statutory law, and where legal documents are often written in an unstructured way,the difference AI can bring is phenomenal,” said Ghosh.
Globally, in countries such as US, Britain, Japan,
Singapore and Australia, Artificial Intelligence is being used to perform legal
research, review documents during litigation and conduct due diligence, analyse
contracts to determine whether they meet pre-determined criteria and to even
predict outcomes. However, AI is yet to sufficiently penetrate the legal field
in India.
Taking 50 judgments from the Supreme Court of India, the team has segmented these by first labeling sentences using multiple human annotators (three senior law students from IIT Kharagpur’s Rajiv Gandhi School of Intellectual Property Law), performing extensive analysis of the human-assigned labels and then developing a high quality gold standard corpus to train the machine to carry out the task.
Prior attempts to automate identification of rhetorical roles of sentences in legal documents have depended on handcrafted features such as linguistic cue phrases indicative of a particular rhetorical role. These features depend on legal expert knowledge which is expensive to obtain. Besides, these features are often developed keeping in mind one specific domain. The neural methods used by the IIT Kharagpur team automatically learn the features, given sufficient amount of data, and can be used across domains.
Ghosh’s team consists of his students, Paheli
Bhattacharya and Shounak Paul, as well as researchers from the Tata Research
Development and Design Centre, Pune, and Swansea University, United Kingdom.
The researchers are using network and text analysis to understand if two legal
documents are similar.
Ghosh said that given that IIT Kharagpur has its own law school, it is uniquely suited to carry out research along these lines.
Ghosh said that given that IIT Kharagpur has its own law school, it is uniquely suited to carry out research along these lines.
