Spark eDiscovery Blog
eDiscovery in Real Life
Legal practice should use tools that learn from you.
Some questions you should consider asking when adopting a new AI solution:
Who defines the output? If “build a medical chronology” is a pre-loaded skill built by the platform, can user feedback be incorporated? I found that in CoCounsel, it disregarded formatting and structure instructions in my prompt because I had called upon its “generate questions” skill, which determined the output.
Does it empower you to check its work? I often reflect on this question in considering Everlaw’s AI coding tools vs. RelativityAIR for Review — Relativity has defined the defensible workflow and walks you through it, while Everlaw is not prescriptive and may empower overconfidence. Does the AI platform have a spot-checking mechanism built in, such as for medical records? Is it easily linking you its sources and cites, and giving you guidance on where it drew some iffy inferences? In a structured request for feedback, the AI should be building its understanding of the case, your preferences, and the underlying documents. You want to know whether corrections from one session inform the next one, and how. What will happen when the task falls to your least experienced associate?
What makes you special as an attorney is your judgment and experience. Your approach to letters, memos, motions, memory aids, and chronologies are extensions of that experience.
Some of the purpose-built legal platforms have to relearn your preferences and tone on every. single. task. That truly limits their usefulness, because they are forever writing their creators' demand letters, rather than yours.