eLitigation Tools
Description
Addresses errors and speed delays found in exclusively manual human review of voluminous electronic information.
Detailed example
Outputs vary by use case.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Department of Justice components use electronic litigation (“eLitigation”) tools for a broad range of purposes, including support of investigations, litigation, and FOIA and Privacy Act processes. Most of these tools are commercial-off-the-self products that are commonly used outside of government, such as Everlaw, FOIAXpress, and Relativity. These tools increasingly integrate AI capabilities that can assist with tasks core to the mission of the Department, such as surfacing potentially discoverable information in voluminous collections of emails, text messages, or other electronic records; locating potentially inculpatory or exculpatory evidence in voluminous electronic data; and identifying material that may be appropriate for disclosure or withholding according to applicable legal rules and privileges. eLitigation tools can offer substantial benefits over exclusively human review of voluminous electronic information: they can be faster, more accurate and consistent, and more efficient. Please note: These tools are used in contexts that are high-impact, but the nature and details of AI uses vary, which may affect whether particular uses are high impact.
Audit / financial statement impact
Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.