Don’t Let AI Slop Muck Up Your Company’s Processes
Generative AI’s gifts come with a hidden danger: decay in the accuracy and quality of organizational knowledge. This decay is the organization-level version of the “workslop” problem. When workslop occurs in sequence across a business’s processes, those processes themselves—and their outputs—start to deteriorate, errors compound and pile up, trust erodes, and the productivity gains of AI disappear. Importantly, this can happen both inside of organizations and in the external flows of information that they rely on. This presents leaders with three challenges: verification, validation, and entropy. To keep knowledge decay at bay, leaders should: 1) Keep track of the provenance of unstructured data, 2) restrict the use of gen AI, 3) define what value is being added, and 4) understand the implications for the entire process.
Tóm tắt nhanh
Generative AI’s gifts come with a hidden danger: decay in the accuracy and quality of organizational knowledge. This decay is the organization-level version of the “workslop” problem. When workslop occurs in sequence across a business’s processes, those processes themselves—and their outputs—start to deteriorate, errors compound and pile up, trust erodes, and the productivity gains of AI disappear. Importantly, this can happen both inside of organizations and in the external flows of information that they rely on. This presents leaders with three challenges: verification, validation, and entropy. To keep knowledge decay at bay, leaders should: 1) Keep track of the provenance of unstructured data, 2) restrict the use of gen AI, 3) define what value is being added, and 4) understand the implications for the entire process.
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