Multiple tools are bringing augmented intelligence to legal practitioners.
The key areas of focus today are ediscovery, contract analytics, and knowledge management (KM).
Ediscovery and CAL In ediscovery, the preliminary fact-finding stage prior to litigation or an investigation, the use of machine learning (known as technology assisted review or TAR) is deployed to reduce time to evidence in large data sets.
The newest iteration of TAR leverages reinforcement learning models called continuous active learning (CAL).
Using CAL, each decision an attorney makes when reviewing a document is amplified across the entire dataset and the data is reprioritized bringing the most relevant information forward.
This yields substantially faster (over 50% acceleration) and more accurate results than relying only on humans, freeing up attorneys to focus on case development.
Contract Analytics Machine learning and natural language processing are deployed across large contract portfolios to reduce the time necessary to compare contract clauses to find anomalies, facilitate due diligence, or predictively suggest language in contract generation.
Legal professionals can quickly identify information from current and legacy contracts to ensure that key contractual language and commitments are not missed.
While the efficacy of this type of tool is highly dependent on cleanliness of data and a manmade taxonomy to inform the technology, there are many benefits to the practice of law.
These include increasing consistency across similar contracts, improving compliance, identifying atypical clauses, identifying opportunities to increase revenue, and reducing costs for contract review and generation.
Knowledge Management More art than science, KM is the process of capturing and reusing legal know-how and work product or identifying colleagues with relevant experience.
While most major law firms today have some sort of document management system (DMS), these systems are challenging to extract insight from due to the volume of data.
Machine learning and AI are being deployed to accelerate law firms’ extraction of these types of insights and value from the content they produce.
Advanced machine learning facilitates more accurate retrieval in lieu of relying on unpredictable manual human retrieval and review.
Iron Man, Esquire The difference between AI and augmented intelligence is akin to the Terminator vs.
The former has fully autonomous machines, the latter is comprised of human-centric application of technology that is dependent on a Tony Stark to execute.
The practice of law is more Iron Man than Terminator — technology is accelerating time to insight and informing decision-making but is ultimately dependent on human input.
AI, deep learning and data visualization work with legal practitioners to substantially reduce time to insight, allowing attorneys to focus on the practice of law.
While skynet is not replacing attorneys anytime soon, or ever, Augmented Intelligence is changing the practice of law.
Rather than the mundane and tedious, lawyers today and in the future can focus on the substantive and intellectually engaging aspects of law that brought them to law school in the first place.
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