An ethical guideline is a principle or rule for developing and using AI responsibly. In enterprise settings, guidelines align AI applications with regulations, industry expectations, business goals, and financial, legal, technical, and moral responsibilities. section 1.5
Effective guidelines address the main risks and controls surrounding generative AI:
- Require human oversight when outputs influence safety-critical or life-and-death decisions; AI assists while a person makes the final decision. section 1.5
- Anticipate misinformation, fake or malicious content, copyright infringement, bias, stereotypes, harmful ideologies, and hallucinations. section 1.5
- Make users review and edit generated content, understand their accountability, recognize AI involvement, and consult citations where relevant. section 13.3.3
- Publish transparent documentation describing system capabilities and limitations, with practical recommendations for prompting and checking outputs. section 13.3.3
Machinery repair assistant
A chatbot that gives an incorrect recipe may cause little harm, but incorrect instructions for repairing complex machinery can create serious consequences. A guideline therefore requires human review before safety-critical instructions are used. section 1.5
Table 13.2 Application-level RAI mitigations
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Mitigation
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Description
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|---|---|
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Review and edit
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Encourage users to critically assess AI-generated outputs, supporting efficient correction and highlighting potential inaccuracies.
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User responsibility
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Remind users of their accountability for the final content, especially when reviewing suggestions such as code.
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Citations
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If AI content is reference based, cite sources to clarify the origin of the information.
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Predetermined responses
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For potentially harmful queries, provide thoughtful, precrafted responses to maintain decorum and direct users to appropriate policies.
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Input/output limitation
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Restrict input and output lengths to minimize the production of undesirable content and prevent misuse.
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AI role disclosure
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Inform users they are interacting with an AI, not a human, and disclose if the content is AI generated, which may be legally required.
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Bot detection
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Implement mechanisms to prevent the creation of APIs over your product, ensuring controlled use.
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Anthropomorphism prevention
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Anthropomorphism prevention means ensuring that AI systems don’t seem human. It’s about clear communication that AI doesn’t think or feel to avoid confusion and ensure people use AI properly, without expecting it to act like a human. Implement safeguards against AI outputs that suggest human-like qualities or capabilities, reducing misinterpretation risks.
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Structured inputs/outputs
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Use prompt engineering to structure inputs and limit outputs to specific formats, avoiding open-ended responses.
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Use the application-level mitigation table to compare review and editing, user responsibility, citations, predetermined responses, input/output limits, and AI-role disclosure. section 13.3.3
