Here are three important considerations before rushing to implement emerging technology, with generative AI as an example use case.
Even if IP isn't at stake, your organization’s information could still be used in unintended ways or provide an advantage to your competitors.to the forefront. Any information made available for large language models to train on, including information from your meetings, will potentially be made available to the public and thus your competitors. Having established acceptable use policies in place is critical for protecting proprietary information.
Another important consideration is the source of your tool. For example, Microsoft has an Azure AI service with a separate, business-friendly version of the OpenAI models that power ChatGPT. Understanding the guarantees about how your information is being used and shared is crucial for determining the safety around using emerging technologies and whether they require new acceptable use policies and controls.
This harkens back to the early days of automation when many were worried that robots would eliminate their jobs. Although automation has eliminated a lot of the drudgery around menial, repetitive and time-consuming tasks, some impacts are always felt by employees when implementing new technology. Still, many people are wary of the unknown, and generative AI begets more fear than most other technologies.
If the answer to any of those questions is yes, it’s worth considering if you need to test run emerging tech before a broad adoption occurs. In the case of generative AI, create a small use case with strong parameters in place to define acceptable use and state measurable outcomes to determine efficacy.
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