The AI Ethics Waterfall: Disclosure, Governance, and Who's Really Responsible
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The AI Ethics Waterfall: Disclosure, Governance, and Who's Really Responsible
"From invention harvesting and prior art searching to drafting, filing, opinion work, litigation, and licensing, the savvy patent practitioner almost certainly has AI embedded somewhere in their workflow. In some contexts, AI is obvious. Generative tools used for drafting or summarization are hard to miss. In others, AI operates quietly in the background, embedded as a feature within legacy platforms or integrated into research tools with little outward indication of how results are produced."
"These overlapping and often fuzzy responsibilities give rise to what we have coined the "AI ethics waterfall" - a cascading chain of accountability that flows from managing counsel down through foreign associates, third-party vendors, and AI providers, each of whom influences and controls how patent work is performed."
"The central challenge is that AI use does not stop at your own lawyers. A managing firm may not deploy AI directly, but a foreign associate might rely on AI-powered prosecution tools. A third-party vendor may use AI-driven search or analytics. Each link in the chain adds distance between the client and the technology shaping their work."
Artificial intelligence has rapidly become embedded throughout patent practice, from obvious generative drafting tools to hidden features within legacy platforms. This "sneaky AI" often operates without user awareness or clear visibility into how results are generated. The integration creates complex accountability chains flowing from managing counsel through foreign associates, third-party vendors, and AI providers. Each participant in this chain influences how patent work is performed while maintaining distance from clients. The challenge intensifies because AI use extends beyond direct firm deployment—foreign associates may use AI-powered prosecution tools, vendors may employ AI-driven search and analytics, and clients typically lack visibility into the technology shaping their work.
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