AI company policies are the governing set of operational rules related to correct usage of AI technology. These help to maintain compliance, ensure data privacy, and maintain digital security.
For your policy to effectively educate on best practices and mitigate risk, it needs to focus on several key areas. These include the following:
This opening section is meant to clarify the intention of your AI company policy. It should also specify who needs to adhere to its requirements, such as externally outsourced individuals or agencies in addition to regular employees.
Here, only the AI-related applications that are approved for use should be listed. Correct access procedures for each can also be specified here to help ensure compliance, though sensitive details such as login credentials should be left out. These can instead be provided by management in a secure manner at the bequest of the individual seeking access and/or during the onboarding process.
Summarizing the due process for AI usage, such as in a bulleted list, helps users understand the appropriate steps and adhere to them. This is an opportunity to implement operational guardrails and communicate how permissions, internal communications, the quality assurance of AI-generated content, and overall data and tool access granted to AI systems should be handled. In addition, it may help to specify what to do if/when a risk or vulnerability related to any of the above is suspected.
This section should clarify when, where, and how the approved AI applications should not be used. If there are specific reasonable exceptions, these should be included here as well. As with the rest of the policy, your chosen verbiage used should be clear, concise, and easy to follow while minimizing the risk of misinterpretation or confusion.
This section reminds your users to review the terms and conditions of the AI tools they are permitted to access, helping protect against misuse and/or liability-related issues. It should also focus on the importance of maintaining data privacy and avoiding plagiarism, respecting intellectual property rights and their holders, and not giving the tool(s) in question access to confidential information.
Here, specify the governing bodies and regulations with which your organization—and by extension, your team—need to maintain compliance when using AI. These should include established governmental acts and any requirements for your legal, security, and/or IT team.
Divided into multiple strategic priorities yet unified in its mission, the Pan-Canadian Artificial Intelligence Strategy seeks to “bring positive social, economic, and environmental benefits for people and the planet.”
This is a collection of research, policy, and engineering documentation focused on advancing AI in an ethical and responsible manner. Microsoft also published their comprehensive Responsible AI Transparency Report in May 2024, which covers everything from mapping, measuring, and managing AI risks to building safe and responsible frontier AI models.
NIST has worked closely with key private-and public-sector stakeholders and federal agencies to develop new AI standards. They are “heavily engaged with US and international AI policy efforts such as the US-EU Trade and Technology Council, OECD, Council of Europe, Quadrilateral Security Dialogue,” and several other initiatives. NIST is also collaborating with the US Department of Commerce’s International Trade Administration and US Department of State as part of these efforts.
In July 2024, NIST also released four publications that are “intended to help improve the safety, security and trustworthiness of AI systems.” These include:
AI ethics involves principles and guidelines that govern the responsible development, deployment, and use of AI systems. It addresses issues like alignment, fairness, accountability, transparency, privacy, risk, and the societal impacts of AI technologies.
A report published by OpenAI researchers (arXiv:2307.03718: Frontier AI Regulation: Managing Emerging Risks to Public Safety) highlights several challenges associated with regulating frontier AI models to help safeguard users. It states that “frontier AI models pose a distinct regulatory challenge: dangerous capabilities can arise unexpectedly; it is difficult to robustly prevent a deployed model from being misused; and it is difficult to stop a model's capabilities from proliferating broadly.”
In addition, the report summary notes that there are “at least three building blocks” needed for regulation:
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