The Therapy Room in 2030

A WORKSHOP FOR MENTAL HEALTH PROFESSIONALS

1. The Therapy Room in 2030

What AI might do to mental health care by 2030, what to protect, and what to build.

1. 150 minutes together, hosted by Ariveria
2. What the research already shows · one plausible 2030 · two group discussions

Here is the plan for the next 150 minutes. We will spend one ordinary Tuesday in 2030 with a client called Maya, walk through the research that is already pointing that way, and argue twice, in groups, about what to do with it. Nobody can tell you what 2030 will look like. What we can do in this room is practise deciding what good care looks like while the tools keep changing.

Everything in the room stays here to revisit. The field guide carries the questions home.

ONE PLAUSIBLE 2030

2. A Tuesday in 2030.

Maya’s day, a few years from now.

1. Maya’s watch has tracked her sleep, her heart rate and her screen time for months. It noticed her broken week before she did.
2. On the train she talks it through out loud. Her AI answers in a voice that remembers last month’s fight with her colleague.
3. It drafts the difficult message, then suggests she waits a day before sending it.
4. It has already written a summary of her week. She chooses what her therapist sees.
5. By the time she sits down in your room, something has been listening, noting and advising for weeks. What arrives with her?

BY 2030

3. The ground moves first.

Seven shifts already under way. Each one shows up in research you can read today.

1. AI becomes conversational, multimodal and continuously available.
   Already true: Real-time voice models already hold natural spoken conversation. [F1] [F25]
2. It moves across phones, watches, glasses, homes and care systems.
   Already true: Wearable and phone sensors already feed models that read health data. [F4] [F5]
3. It develops longer-term memory and personal context.
   Already true: Consumer AI products already keep persistent memory between conversations. [F3]
4. Clients use it before, between and instead of professional care.
   Already true: Purpose-built chatbots have already moved symptom scores in randomised trials. [F9] [F10]
5. Practitioners receive AI summaries, risk flags, recommendations and documentation.
   Already true: Ambient scribes already draft clinical notes in randomised trials. [F7] [F8]
6. Organisations accumulate far more about behaviour and emotional states.
   Already true: Passive sensing studies already link phone and wearable patterns to depression and suicidal thinking. [F6] [F28]
7. Professionals work alongside systems that sound confident, empathic and knowledgeable.
   Already true: People already rate AI-written empathy highly, and agreeable AI already shifts human judgement. [F13] [F15]

EVIDENCE · TODAY

4. Already true today.

Six of the studies behind those shifts. Read the limit under each one; it matters as much as the finding.

WHAT THIS CHANGES

5. Old questions, new answers due.

When AI sits inside the client’s week, the familiar questions of the room need asking again.

1. What the client brings. An AI-shaped account of the week: remembered, worded and smoothed before you hear a word of it.
2. What the practitioner already knows. A summary, a risk flag and a sleep chart wait in the file. What do you owe the data, and what do you owe the person?
3. What the AI recommends. When the wording, the prompt and the next step come from a tool, whose intervention is it?
4. The role of the therapist. Which parts of your work need you, and which parts only need doing?
5. What may be automated. Intake, check-ins, homework, documentation. Each piece handed over changes all the others.
6. What must not be. Every profession draws this line somewhere. Ours is not drawn yet.

DISCUSSION 01 · 15 MINUTES

6. What should remain distinctly human?

PAUSE

7. Take a break.

THE SEVEN-EYED MODEL, UPDATED

8. Seven eyes on 2030.

Supervision already examines every relationship in the room. Here is where AI enters each one.

Hawkins and Shohet drew this map for clinical supervision in the 1980s, and supervisors have been taught it ever since. Its claim: a session is more than the client's story. There are seven places worth looking, and each one shows you something the others cannot.

In practice a supervisor picks an eye, looks through it, then moves. There is no fixed order. The skill is noticing which eye you have been avoiding.

1. The client. Eye 1 watches the client: what they bring, how they present, what they choose to tell and what they hold back.
2. The therapist. Eye 2 looks at the work itself, the interventions. Eye 4 turns inward, to what the client stirs up in the therapist. Countertransference lives here.
3. The therapy relationship. Eye 3 looks at what happens between the two of them. The alliance stops being the container and becomes the material.
4. The supervision system. The therapist carries the work to a supervisor. Eye 5 watches that relationship, eye 6 the supervisor's own process. What happened in the therapy has a way of replaying in the supervision; supervisors call it parallel process.
5. The wider context. Eye 7 steps back. Organisations, funding, culture and law shape both relationships before anyone says a word.
6. A fourth presence. In 2030 the map shares every room with a system that has already heard the client's week, drafted the therapist's notes and flagged a risk to the supervisor. The geometry is unchanged. Every line now carries it, and each eye below traces where it enters and what it does there.

Drawn for three people. The room now has a fourth.

1. The client and their presentation. AI enters before the session begins. The client has often been talking to a system all week, and that system has been keeping score. Clients may arrive with an AI-shaped account of their week. What has been framed before you hear a word?
2. The therapist’s interventions. AI enters the work itself. A tool can draft the reflection, suggest the homework or word the difficult question before you do. A tool may supply the wording, the prompt, the next step. Whose intervention is it?
3. The client–therapist relationship. AI enters the space between you. Each of you may have consulted a system about the other: what to say, how to take it, whether the therapy is working. The alliance turns triadic: client, therapist, and the systems each one brings into the room.
4. The therapist’s internal process. AI enters what you feel in the room. Something that sounds certain can pull your judgement toward it, and noticing that pull is now part of the work. Countertransference now includes how you feel about a client’s AI: dismissal, deference, unease.
5. The supervisory relationship. AI enters the supervision hour. The supervisor may meet the system’s version of the session first: the summary, the flagged moment, the suggested focus. Supervision gains a question alongside “what did you do?”: what did the tool do?
6. The supervisor’s own process. AI enters the supervisor’s judgement too. The instincts supervisors trust, tone, hesitation, what went unsaid, were built for rooms with only people in them. Supervisors hold their own uncertainty about systems they may never have used.
7. The wider context. AI enters as the context itself. Platforms set the norms, employers buy the tools, insurers price the risk. The room is arranged before anyone sits down. When a platform’s defaults become the room’s rules, who consented to that?

Source: Hawkins and Shohet, Supervision in the Helping Professions, in print since the 1980s. Their diagram is a double matrix: two interlocking systems, client with therapist and therapist with supervisor, inside one wider context. We keep the seven eyes and ask a new question through each.

SIX ROLES

9. Six roles AI is growing into.

Name the role before judging the tool.

DISCUSSION 02 · 20 MINUTES

10. Design an ideal 2030 system.

GUIDELINES

11. Seven guidelines for 2030.

Working principles for anyone building these systems.

1. Preserve agency. The person decides. A system that narrows someone’s choices while feeling helpful has failed at its main job.
2. Keep uncertainty visible. Fluent wording can hide shaky ground. A tool should show what it does not know.
3. Make influence understandable. If a suggestion shaped a decision, the people affected should be able to see how.
4. Give people control over memory and data. What is remembered, who can see it and how it is deleted belong to the person, not the platform.
5. Name the responsible human. For every output that matters, someone with a name checks it, owns it and can stop it.
6. Protect relationships from invisible interference. The alliance cannot defend itself against a third party it cannot see. Make the third party discussable.
7. Design ways to pause, leave and seek human help. Pausing and leaving should be easy. Every system needs a door marked human.

BEFORE YOU LEAVE

12. Three moves, eight questions.

For every tool, proposal or system you meet from here on.

1. One question from the eight I will start with
2. One tool I will walk through the three moves
3. One AI moment I will bring to supervision

Move 1 · Make the system visible

1. What does the AI observe, remember and infer?
2. Does the person understand what it is doing, why it produced this output and who else may receive it?

Move 2 · Bound its authority

3. What may the AI recommend, decide or do?
4. What must it never do, even if doing so would be faster or more convenient?
5. Which named human is responsible when its output affects care?

Move 3 · Preserve agency and a way back to people

6. What can the person correct, delete, pause, refuse or take with them?
7. How could the system change the client–practitioner relationship, or decide whose account is heard first?
8. What is the clear route to human help when the system is uncertain, fails or distress increases?

An original workshop discussion aid. Not a validated assessment, clinical protocol, safety score or legal compliance checklist.

• One question from the eight I will start with
• One tool I will walk through the three moves
• One AI moment I will bring to supervision

GLOSSARY

Terms used in the room

Therapeutic alliance

The working relationship between client and therapist: trust, agreement on goals and a felt bond. The strongest predictor of outcome across therapies.

The frame

The agreed boundaries of therapy: time, confidentiality, contact between sessions, consent. AI use now belongs in it.

Countertransference

The therapist’s own emotional reactions to the client, used as clinical information. Now includes reactions to the client’s AI.

Seven-eyed model

Hawkins and Shohet’s supervision framework: seven ways of looking at the client, the therapist, the relationships between them and the wider context.

Formulation

A shared working hypothesis about a client’s difficulties, built together and revised over time.

Triadic relationship

Three parties instead of two: client, therapist and an AI system each of them uses.

Digital phenotyping

Inferring mental state from passive data such as sleep, movement and phone use.

Sycophancy

The tendency of AI systems to agree and flatter, even when agreement is unhelpful.

Ambient scribe

Software that listens to a clinical encounter and drafts the note.

Clinical governance

The structures through which an organisation keeps care safe and accountable.

AFTER THE SESSION

Continue the conversation

If this raised a question for your practice, research or product work, we want to hear it.

Tell us what you would like a future workshop to examine.

• Nicholas Ng, Chief Executive Officer and Chief Product Designer
• Neil Gupta, Chief Technology Officer
• Ariveria on LinkedIn

Field guide (PDF)