Do: Implement guidelines for generative AI usage
The adage of “with great power comes great responsibility” most certainly applies to Generative AI as it can do a great deal of harm if left to its own devices. Before rolling out AI tools in your organization, it’s critical to first establish what purpose AI will serve and how it will be utilized. The question is not what AI is able to do, but what AI should do to improve efficiencies in your organization. Once use cases are established, work internally to create a set of guidelines and policies on how to responsibly engage with AI tools so that they are used for the right reasons.
Don’t: Allow generative AI to operate on autopilot
It’s important to keep in mind that the core function of Generative AI is to produce an output in response to a user’s query, even if the tool doesn’t have the necessary or accurate information to do so. Generative AI tools are largely trained by the data that users feed it, which can be problematic as some data inputs are inaccurate, outdated, or biased. ChatGPT, even after a January 2023 platform update aimed to improve accuracy, still only has accurate data available up until September 2021. Bias results from training data as well. Tidio, a customer service software company, conducted a series of experiments to test the level of bias in AI. They asked one AI tool, StableDiffusion, to generate pictures of a doctor, and it wasn’t until the third try that the tool eventually produced an image of a female doctor. As a result, it’s critical to do your due diligence and both fact check and gut check the output of your AI query to ensure that it does not support the spreading of misinformation or hurtful biases. Treat Generative AI as your co-pilot that works in tandem with human logic and reasoning when producing assets.
Generative AI presents many opportunities to streamline efficiency and spark ideas, but there is still much to unfold as the technology continues to be developed and regulated. The do’s and don’ts above aim to be a general guide to follow, but each organization should proactively discuss how to best experiment with this growing technology — there is a lot of uncertainty, but you don’t want to be left behind as new industry norms develop. For now, using these tools to better define your big ideas, drive better communication across teams, and improve the efficiency of more monotonous tasks is a great place to start.
This space is moving quickly, so keep a pulse on the latest rollouts to understand what tools are available for your consideration.
To learn more about AI, listen to this episode of The Loop Marketing Podcast: