Policy Deep Dive 13

Title and angle ? Policy Deep Dive 13 delivers practical policy guidance with real-world steps, constraints, and checkpoints readers can apply immediately.

Purpose ? Explain why you need a visual and AI policy: to protect subjects, respect IP, and comply with platform rules. State the scope clearly.

Consent ? Require documented consent for identifiable people and private spaces. Keep signed releases and note any usage limits.

Attribution ? Credit sources, datasets, and collaborators. If AI generated any element, disclose it. Transparency reduces legal and trust risks.

Sensitive content ? Define what is off-limits (medical claims, political deepfakes, likeness misuse). Build a review step for edge cases.

Data handling ? Store assets securely, limit access by role, and avoid embedding private data in filenames or metadata.

Bias checks ? Review AI outputs for demographic bias or stereotypes. Maintain a short checklist and escalate questionable results for human review.

Labeling ? Follow platform rules for synthetic media labels. Keep a standard footer or note so labeling stays consistent across channels.

Retention ? Set timelines for keeping raw files, prompts, and drafts. Delete when contracts allow to reduce exposure.

Incident response ? Define what happens after a mistake: pull assets, notify stakeholders, document fixes, and update the policy.

Training ? Share the policy with staff and vendors. Provide short refreshers quarterly as tools and rules change.

Governance ? Assign an owner to update the policy, track regulatory changes, and answer questions.