Role play: a role in a box of the panel matrix

Facilitation (Pronoia)

What role play is for

In an ordinary Delphi the panelist answers as themselves: their expertise is what they bring. In role play the panelist answers from a role they write themselves. The role can be their actual position, a future position (Municipal finance director in 2035) or a perspective they deliberately choose to represent (Young rural entrepreneur).

Role play suits a study when

• you want to make assumptions visible: once the role is written out, the reader sees from which position an argument is made
• you are looking at future actors: the panelist reasons as a decision-maker of 2035 rather than as today's official
• the panel is missing perspectives you want included: a human panelist can take a role, and the facilitator can commission a role from an AI panelist
• the study is used for learning or workshops, and changing perspective is the aim itself.

Role play does not suit a study whose value rests on verified expertise. A self-selected role is a claimed perspective, not a qualification, and it is always marked as such.

Division of work: the facilitator gives the structure, the panelist chooses the box

Role play is built on the panel matrix. The facilitator defines the matrix axes and categories, for example the main axis Expertise with categories Technical, Economy, Administration, Experience and a second axis Stakeholder. The categories are boxes. The panelist writes their role freely and places it in the box it fits best.

The role is a name, the box is a group. Group comparison, pulse group scores and reports group panelists by box, not by role text. This is the key design choice of role play: if every freely written role were its own group, every group would have one member and k≥3 protection would hide them all. The boxes are what make role-play results open to structured analysis.

The facilitator's steps

1. Build the panel matrix (Panelists → Panel matrix). Choose categories with role play in mind: broad enough that each gets at least three panelists, and clear enough that panelists can choose.
2. Switch role play on in the settings and save. The setting explains what the boxes are. If the matrix has no categories, the setting warns you: panelists can then write a role but cannot choose a box.
3. Tell the panel what a role means in this study (template below).
4. Commission AI roles if you want to supplement the panel. On the AI panelists tab, in the add form under Role play: AI role, write the role in the AI role field and choose a box from the same matrix. The AI answers from its role's perspective.
5. Watch the boxes fill before opening the round: a box that stays empty or gets only one or two panelists is not shown as a group.

Template for the panel

In this study you answer from a role. On your own page, on the Role play card, write the role you answer from, for example your own position in 2035 or a perspective you want to represent. Then choose the box your role fits best. Other panelists see your role next to your reasoning, but not your name.

What the panelist sees

The panelist's own page has a Role play card. The panelist writes their role in Your role (at most 120 characters), picks a box on the main axis under Choose a box (and optionally on the second axis), and presses Save role. The card says: “Other panelists see your role next to your reasoning and comments.”

In the discussion the role appears next to the handle, marked:

• self-selected: the panelist wrote the role
• AI role: the facilitator commissioned the role from an AI panelist.

The markers never mix: a role a human chose is never shown as an AI role, or the other way round. When role play is switched off, roles are shown to no one, but the saved role and box are kept.

AI roles as panel supplements

An AI role is useful when the panel lacks a perspective you cannot get from human panelists: young people, future residents, actors from another field. The AI argues from the role's perspective, and its contributions are always marked.

Keep two things in mind:

• An AI role is a proposal, not a voice. It brings arguments into the discussion that people can respond to, but it does not tell you what people in that group actually think.
• The AI counts as a member of the box. The k≥3 threshold counts AI panelists in the group size (facilitator decision, 22 September 2026). A box with two humans and one AI is shown as a group. If you want the anonymity of the human group to be certain, keep at least three humans in each box.

Reading the results

• Compare boxes, not roles. Group comparison shows how the boxes differ. A single role can be read next to its reasoning, but it is not counted.
• A self-selected role is a frame, not a sample. A box's result tells you how the panelists who took that perspective argued, not what a whole profession thinks.
• Separate the AI share. In the distribution the AI share is hatched and the counts are split, so you can see how much of a box's result the AI produced.
• Use roles in interpretation. The combination of reasoning and role is often the richest material in the study: the same claim made from different roles shows where a view depends on position.

Technical description

• The panelist's role is stored in self_selected_role and the boxes in matrix_primary and matrix_secondary. Call: POST /api/respond/{invite}/role with the fields role, matrix_primary, matrix_secondary.
• An unknown box is rejected (role_play_box_invalid). When the matrix has categories, a role without a main-axis box is rejected (role_play_box_required).
• Adding an AI panelist (POST /api/studies/{study}/ai-panelists) takes the same fields; the role is stored as the profile's perspective.
• In the discussion response the role travels in panelist_role and commenter_role only while role play is on.

See also: Anonymity: identity modes and group reporting.