Introduction:
In the realm of eDiscovery, unearthing a “smoking gun” document—a piece of evidence that can significantly impact a case—is a pivotal moment. In this blog post, we delve into a fascinating case study where eDiscovery AI tool played a crucial role in uncovering a smoking gun document. Specifically, we highlight the discovery of former Governor Jeb Bush’s candid opinion on affirmative action. This case study showcases the power of eDiscovery AI in unveiling critical evidence that can shape legal strategies and outcomes.
The Case Context:
Our case study revolves around the 2015 public release of then-Governor Jeb Bush’s email prior to his candidacy for president and review of those documents for several topics. As part of the review process, legal teams were tasked with combing through an extensive volume of electronic documents, including emails, memos, and reports, to gather documents related to various issues.
Harnessing eDiscovery AI for Document Analysis:
To efficiently analyze the vast corpus of documents, the eDiscovery AI team utilized cutting-edge technology powered by large language model AI to assist in document review and categorization. By leveraging the power of AI, the teams aimed to uncover relevant information, including any revealing opinions from key individuals involved.
Identifying Issues:
The emails released by Governor Bush contained many political issues, a few of which were highly controversial at the time. One such issue is affirmative action which generated a lot of passionate engagement from the residents of Florida. We considered any discussion of this issue to be relevant, but we were especially interested in any instances where the Governor himself expressed a personal opinion on the issue.
Crafting Targeted Instructions:
To unearth the smoking gun document related to the governor’s opinion on affirmative action, the eDiscovery AI consultants crafted highly targeted instructions. These instructions incorporated relevant keywords, phrases, and contextual understanding specific to the case. There were also two separate issues created, any general discussion of affirmative action and those considered key documents where Jeb Bush directly expressed his opinion on the subject. The goal was to maximize the likelihood of capturing all documents of interest among the sea of data while also being narrow enough to find any key documents.
eDiscovery AI Analysis and Iterative Refinement:
The eDiscovery AI tool analyzed the vast document collection, utilizing carefully crafted instructions to identify potentially relevant materials. Through iterative testing and refinement, the legal team fine-tuned the instructions based on initial results and feedback from subject matter experts. For example, only after testing and reviewing the results the team learned that the One Florida Initiative was an initiative related to this issue.
Unveiling the Smoking Gun:
The breakthrough came when eDiscovery AI flagged a document that presented the governor’s candid opinion on affirmative action. This document, previously buried within the extensive dataset, was a potentially offensive opinion expressed by a constituent writing to Governor Bush. The key portion of the document was the very brief response from the Governor where he stated, “I concur.” Despite the fact that only 2 words in the entire document were from Mr. Bush, those two words stated is agreement with the insensitive opinion and the AI correctly flagged this as a key document.
Traditional Predictive Coding Challenges in Locating the Key Document:
Traditional predictive coding tools typically require hundreds of examples of the type of document being sought. In this instance, there were nowhere near enough examples to train a traditional tool and without the power of eDiscovery AI there would have been no way to find the few examples in the first place.
Manual Review Challenges in Locating Key Documents:
A manual review of this set of 290,099 documents would have tremendous time and expense commitments that aren’t a concern with eDiscovery AI. Additionally, human reviewers are prone to error, especially in instances where the key information isn’t immediately clear.
Defensibility and Ethical Considerations:
Locating these hard-to-find key, or smoking gun documents is essential for making or defending your case, informing negotiations, and developing overall strategy. Until now there has never been an effective, affordable option. eDiscovery AI can effectively locate these key documents for you and do so incredibly quickly allowing you to know where you stand much earlier in the document review process.
Conclusion:
The discovery of a smoking gun document—revealing Jeb Bush’s candid opinion on affirmative action—highlights the transformative power of eDiscovery AI. By crafting targeted instructions, leveraging advanced document analysis, and engaging in iterative refinement, legal teams can unearth critical evidence that shapes case strategies and outcomes. This case study underscores the importance of adopting innovative technologies like eDiscovery AI to navigate the vast landscape of electronic data and achieve successful outcomes.
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