Explain the tool before asking someone to trust it

What we found in the news

A May 2025 Journal of Medical Internet Research study (opens in a new tab) explored patients’ views of AI in medical care through focus groups in Germany. Participants highlighted:

“comprehensible instructions and explanations of the purpose of AI”

— Jana Gundlack and colleagues

These were perspectives discussed around examples, not measured outcomes from adopting a particular tool. The study gives us a useful invitation to listen: an explanation should address the questions people bring, rather than assume that a technical introduction creates understanding.

Why this matters to us

A screen can be easy to tap while the service behind it remains unclear. Someone may understand where to enter a question but wonder who reads it, whether the answer is checked, or why AI is involved.

Imagine a participant arriving at a community service with a new resource kiosk. Before using it, they choose a picture card that represents the question most important to them: who can help if the answer seems wrong?

The staff member begins there. The device remains available while the person directs the conversation.

At genus, we want an introduction to make the experience more understandable. Confidence should have a basis in what the person has been told and can actually try.

Explain the particular use in ordinary words

Begin with the task the tool supports. Finding public activity information is different from writing a personal summary or making a decision about support.

For the imagined kiosk, the explanation might cover which approved resources it uses and the kind of question it is intended to help with. Details that are still uncertain should be checked before the person is invited to rely on them.

Describe the role of people around the tool. Who maintains the resources, reviews reported problems, and answers a question that needs local knowledge?

Avoid giving every person the same long technical speech. Offer a clear starting explanation, then let their questions determine which detail needs more attention.

Show the limit through a useful example

A small demonstration can make the explanation concrete. Use a public activity question with an answer the staff member can verify.

Then show what happens when a detail is unavailable. Can the person recognize the uncertainty and find a contact who can help? The example should make the next step understandable without requiring them to know how the model works.

Invite the participant to use their own words. They may ask a question that exposes an assumption in the prepared demonstration, such as whether the service can see a private record.

Answer that question accurately for the configured setup. If the colleague does not know, record it for the responsible person and explain how an answer will be provided.

Leave room for a different choice

Understanding a tool does not require choosing to use it. Someone may prefer a printed resource, a conversation, or time to think.

Make the available options clear and usable. If one route provides less information or takes longer, the team should know that and consider what needs improvement.

Ask the person how they would prefer to receive further explanation. A supporter they choose, a short written guide, or another practice opportunity may help.

Review the questions raised during introductions. Repeated uncertainty about the same feature may point to an unclear description, a confusing interface, or an unresolved service decision. Use that evidence to improve the welcome, rather than repeating the same explanation more loudly.

What this means for the people you serve

People can ask why a tool is being used and what it means for their own task. They should have enough information to decide how to participate and where to turn when something is unclear. Their questions can reveal what the service still needs to explain.

The genus connection

Today, genus care-app and care-wall experiences bring together configured content, access, and enabled features. Supported AI guidance has a defined role that should be explained for the particular experience.

We would prepare that explanation alongside the tool itself. Confirm the information it can use, the help available around it, and the alternative routes the organization provides. Then try the introduction with people and listen to the questions that remain.

One question to take away

What would someone need to understand before deciding that this tool is useful for their own purpose?