A Privacy Policy Is Not a Chatbot Info Card

Decide what a customer needs to know before the first message, then put it beside the chat box. If the answer is buried in a privacy policy, the customer has to leave the conversation, find the right clause, and translate legal language before deciding whether to continue.

That is too much work for a five-second decision. A chatbot info card gives support leaders a practical alternative: one short reference for what the bot can do, where it may be wrong, what happens to conversation data, and how to report a problem.

Singapore's Infocomm Media Development Authority sets out this pattern in its Transparency Guidelines for Generative AI Chatbots. The guidelines are voluntary. They do not impose obligations or replace duties under other laws or sector rules. What they offer is an operator-friendly structure for telling people what matters at the moment it matters.

The Gap a Privacy Policy Cannot Close

A privacy policy answers only part of the customer's question. It may explain which data is collected, who receives it, and how long it is kept. It rarely says whether the bot can check current stock, whether it may give an incorrect answer, which questions need a human, or where to report a bad response.

Those are operating decisions, not legal footnotes. A shopper deciding whether to trust a returns answer needs them in one scan. A support manager also needs one maintained source of truth instead of four different pages owned by legal, product, security, and customer service.

Answer Four Questions, Not Every Question

IMDA encourages at least one substantive disclosure in each of four areas. For a customer-service chatbot, that becomes a manageable editorial checklist:

1. What can this chatbot do? Name the tasks it handles and the boundaries that matter. “Answers questions from our published shipping and returns information” is useful. “Your intelligent shopping assistant” is not.
2. How reliable and safe is it? State the important limitation in plain language. If answers can be wrong or out of date, say so. If prices, stock, medical, legal, or financial decisions need verification, make the next step explicit.
3. How is conversation data used and protected? Summarise what is collected, who can access it, whether it is used for model training, and what controls the user has. Link to the privacy policy for retention periods and full terms.
4. How can someone report a problem? Give a real channel and set an expectation. Explain what kinds of issues can be raised and what acknowledgement or follow-up the user should expect.

The bar is specificity. “We take safety seriously” gives a customer nothing to act on. “This chatbot can make factual errors; verify important product, price, and policy information before relying on it” changes behaviour.

Place the Decision Before the Conversation

A perfect page that nobody sees is not useful disclosure. IMDA encourages a high-level safety statement and a clearly identifiable link to the info card at first use, before the customer starts chatting. The card should remain reachable from within the interface afterward.

For most teams, that does not require a new consent flow or a long modal. A short sentence near the opening prompt and a persistent information link can do the job. The linked page can use headings, bullets, and expandable sections so customers see the essentials first and supporting detail when they want it.

Use the same core card across web and mobile when the bot behaves the same way. If capabilities or data practices differ by channel, name the differences instead of making the customer guess which version they are using.

Give the Card an Owner and a Review Trigger

The page becomes operational only when someone owns it. Put one support or product leader on the review, record the last-updated date, and define the changes that reopen it: a new model, a new capability, a material guardrail change, a new data use, or an unexpected customer use case.

Do not wait for an annual policy review when a meaningful change happens in the meantime. Equally, do not create busywork for routine infrastructure changes that do not alter behaviour or safety. The question is simple: would this change affect how a reasonable customer decides to use the chatbot?

A One-Hour Review for Support Leaders

Open the chatbot as a first-time customer and run this review with support, product, and whoever owns privacy:

• Can a customer tell what the chatbot is for before sending a message?
• Can they find one concrete limitation or precaution?
• Can they understand the main data practice without reading the full privacy policy?
• Can they reach a person or reporting channel when something goes wrong?
• Can the team name who updates this information after a meaningful change?

Any “no” is a drafting task, not a reason to add another generic disclaimer. Start with the four answers, write them in the language your support team already uses with customers, and cut every sentence that does not change a decision.

Where HoverBot Fits

HoverBot helps teams ground customer conversations in their own catalogue, policies, and documentation, while keeping a clear path to human support. The same operating discipline applies to transparency: define the answerable scope, make the limits visible, and keep the customer in control of what happens next.