Being responsible about how you use AI
Or how to write an AI usage policy
Whether integrating AI for data analysis, content creation, or automated reporting, it’s essential to ensure that these tools serve your organization responsibly, transparently, and ethically.
Here’s what I’ve learned about using AI responsibly and keeping ahead of the AI curve without creating significant risks for your business.
Know where AI can make a difference.
Begin by identifying where and how AI will be used within your organization. Will AI tools support audience measurement, ad targeting, content creation, or other critical business functions? Outline these applications clearly, considering both in-house AI tools and third-party platforms. This clarity will ensure that all stakeholders understand the scope of AI’s role and any limitations and exclusions the policy covers. What datasets and areas is it safe to use AI, and where do you want to keep AI out of?
Beware the bias!
AI models can inadvertently amplify biases in their training data, leading to skewed outcomes that could harm your brand’s reputation or alienate certain groups. Implementing safeguards to monitor AI outputs regularly is vital. Policies should require fairness checks to prevent discriminatory outcomes and ensure algorithms promote inclusivity. Regular audits, alongside transparency in customer-facing AI outputs, can help build trust and demonstrate your commitment to ethical AI.
Tell people when you use AI.
AI-powered decisions should never operate in a “black box.” Regarding media and advertising, transparency is vital to trust and accountability. The policy should mandate that all significant AI-driven decisions, particularly those affecting customers or end users, are communicated and can be explained. For instance, if an algorithm affects content recommendations or ad targeting, it’s crucial to disclose this appropriately and ensure a path for user feedback and recourse if needed.
Keep AI away from sensitive data.
Data privacy is non-negotiable. A robust AI usage policy must prioritize data security by setting clear guidelines for collecting, storing, and using data. This includes prohibiting employees from inputting sensitive or proprietary information into public AI platforms, which could retain or reuse that data. Define tiers for data sensitivity, with stricter guidelines for handling sensitive data, and mandate data masking and anonymization techniques where necessary to protect user privacy.
Protect your intellectual property.
Your policy should clearly outline ownership rights over AI-generated content. Content generated using company resources should typically belong to the organization, whether it’s a report, ad copy, or metadata. Similarly, specify third-party AI tool usage guidelines, ensuring that licensing and intellectual property considerations are respected. Not all AI tools do, and you should only use those AI tools that align with the IP ownership your business needs.
Don’t trust the robots.
Even the most advanced AI requires a human touch. While AI can efficiently process data, generate insights, and create content, human review is crucial to maintaining accuracy, relevance, and appropriateness. Policies should establish that human employees review critical decisions, public-facing outputs, and client-facing reports before release. This approach ensures AI remains a supportive tool, enhancing human capabilities rather than replacing them.
Avoid vendor lock-in.
Most organizations will rely on third-party AI vendors. As part of your policy, vet vendors carefully for security, reliability, and ethical alignment. Prioritize infrastructure that can accommodate multiple AI providers, offering flexibility if switching vendors becomes necessary. Given the rapidly evolving landscape, start with robust, industry-standard vendors but remain adaptable.
