What is the Verification-Value Paradox? And how does it impact the value of AI? Leigh Vickery of Level Legal discusses that in this article!

The article in ALM’s Law Journal Newsletters, titled (wait for it!) When Efficiency Meets the Duty to Verify: Reflections on The Verification-Value Paradox (available here), discusses Joshua Yuvaraj’s article, The Verification-Value Paradox: A Normative Critique of Gen AI Use in Legal Practice. Yuvaraj discusses how, in serious legal work, the bottleneck isn’t how fast AI can generate text. The bottleneck is what it costs in time, skill, and ethical attention to verify that output.

Yuvaraj starts by describing the now-familiar enthusiasm that machine-learning-based generative AI products are said to “drastically streamline and reduce the cost of legal practice.” That optimism, he notes, rests on an assumption that lawyers can “effectively manage AI’s risks.” When lawyers in numerous countries have now been reprimanded for inaccurate AI-generated submissions, he argues, the paradigm needs to be revisited.

The heart of the paper is what he calls the verification-value paradox. The paradox can be captured as:

Net value of AI = efficiency gains – verification costs.

So, what does Yuvaraj say that the net value of AI will be in many legal contexts once verification is honestly accounted for? And what happens when verification is skipped? Find out here, it’s only one click! I can verify the value of this article! 😉

So, what do you think? How does your organization maximize the value of AI? Please share any comments you might have or if you’d like to know more about a particular topic.

Image created using Microsoft Designer, using the term “robot lawyer looking at scales”.

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