WORKING DRAFT · Built from the October 2026 upgrade document · Not for citation
Wellbeing & Responsibility
Oktifani Winarti smiling over a white mug printed “Wait for it.”
Oktifani WinartiPhD researcher · Media, Communications & Cultural Studies
PhD research · Goldsmiths, University of London

Wellbeing & Responsibility
in Neuroliberal Times

News Discourse on AI Chatbots and the Indonesian Case

How news discourse has defined wellbeing around AI chatbots since ChatGPT, and how people who build and regulate mental-health technology in Indonesia make sense of it.

Oktifani Winarti Media, Communications & Cultural Studies Upgrade · October 2026 Funded by LPDP
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00 — YOUR PhD JOURNEY

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The hardest part of a PhD is finding the question. You have found three.

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people a week whose chats signal crisis. This is why the question matters
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Guardian articles already identified
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“Family & Tech” columns in the corpus
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words of upgrade already written
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papers waiting in this thesis
REFLECT · WHERE YOU STAND

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Your scores from both studios, the upgrade checklist and the questions the panel is likely to ask, all in one place. Tick items as you fix them; ticks and reflections are saved in this browser.

Studio scores

Scores update each time you open a studio.

This week’s reflection

REVISE · SECTION BY SECTION

Every section, quietly scored

Each section of the upgrade gets a live score from three checks: language, flow and craft. Open one to see what each supervisor would ask, read the suggestions, or revise it here. Edits save to the same draft as the studio. These scores measure the writing, section by section; the rubric score above judges the argument as a whole.

READINESS · WHAT TO FIX

What to fix, and where

Section numbers refer to the upgrade document (“UD”) and the ethics form (“EF”).

0% weighted readiness

Readiness by severity

Weights: critical ×3, important ×2, polish ×1. Critical items are things a panel or ethics reviewer will notice straight away, mostly places where the two documents contradict each other.

READINESS · MOCK PANEL

Questions the panel is likely to ask

Each has a short outline answer drawn from the document. Practise saying these aloud in under 90 seconds.

Strongest single addition before submission

Add a worked example (1–2 pages): one Guardian article and one Jargon column coded at all four van Dijk levels, ending with a sentence on where responsibility is placed. It shows the method works on this data, and it answers questions 3, 4 and 5 in advance.

READINESS · SUBMISSION PACK

What goes in the envelope

01 — THE STORY

From a film about falling for software to a question about who must care

It started as fiction. In Spike Jonze’s Her (2013), a lonely man falls for an operating system. A decade later, media scholars write that this scenario has begun to come true. People use chatbots to manage emotions and distress. Even people who don’t think of themselves as being “in a relationship” with an AI start to expect other people to be as easy to talk to as their chatbots.

Then it became large. In October 2025 OpenAI estimated that about 0.15% of weekly ChatGPT users showed explicit signs of possible suicidal planning. With roughly 800 million weekly users, that is more than a million people every week. 72% of US teenagers have tried an AI companion. Therapy and companionship are now among the leading uses of generative AI.

It fills a gap, and the gap looks different in each place. In the UK, NHS Talking Therapies waiting lists can run for weeks. In Indonesia, mental-health care is stigmatised, psychiatric care is mostly paid for privately, and some families still use pasung, confining a relative with mental illness. Care that is private and always available can look like an answer to a problem that is as much about relationships as it is clinical.

But the tools are not neutral. A chatbot built on CBT and mindfulness already has a view of what wellbeing is. That view is often the ability to accept distress and work on yourself, away from the social conditions that cause the distress.

And most of what the public knows comes through the news. Journalists report the lawsuits, the new safeguards and the stories of users who were helped or harmed. In doing so they decide what “AI chatbot wellbeing” means. They also decide who is responsible for it: the user, the parent, the company or the state.

The question is not only whether chatbots help, but how wellbeing is being defined around them, and who is made responsible for it.Upgrade document, §1.1
02 — OBJECTIVE & CORE ARGUMENT

Treat wellbeing as a contested category, not a measured outcome

The study does not test chatbots for safety or efficacy. It asks how discourse produces wellbeing: what counts as wellbeing, who is said to lack it, and what is offered as the remedy.

Reflexive self seeks a satisfying bond Artificial sociality a partner that never tires Therapeutic culture name it, reframe it, alone Relief, not connection the need is reproduced the pure relationship minus reciprocity
The loop (§1.2, §3.3): companion chatbots copy the form of Giddens’ “pure relationship” but remove its reciprocity. Users look for wellbeing in the same relationship that keeps creating the need for it.

What the study sets out to do

  1. Trace how news redefined wellbeing as AI chatbots moved through emergence normalisation containment (2023–2026).
  2. Follow how family journalism moves responsibility out of public regulation and into the household.
  3. Carry those definitions to Indonesia, where chatbots are already part of everyday wellbeing practice but no regulatory framework exists. Then ask the people who build and license digital care how they understand wellbeing and responsibility.

Neuroliberalism governs behaviour by designing the settings in which people make choices. The study argues that news allocates responsibility for wellbeing before regulation arrives, and that this shapes what government can later do.

03 — RESEARCH QUESTIONS

Three questions, three datasets

RQ1

To what extent, and in what ways, has news discourse redefined wellbeing through the emergence of AI chatbots across the stages of emergence, normalisation and containment (2023–2026)? What has counted as wellbeing, who has been understood to need it, and what has been offered as its remedy?

Public news · The Guardian · “AI chatbot and wellbeing” · 86 articles identified so far · van Dijk news discourse analysis
RQ2

How does news discourse relocate the problem of AI chatbot wellbeing from public regulation into private life, such as the household, the workplace and personal relationships? Where does it place responsibility?

Family journalism · Julie Jargon’s “Family & Tech”, WSJ · 20 columns, Jun 2023 – Oct 2026 · same four-level protocol
RQ3

How do psychologists and technologists producing mental health technology understand wellbeing and responsibility for users’ wellbeing? What role do they see themselves playing in the future governance of AI chatbots?

Indonesia · Riliv co-founders, Riliv psychologists (FGD + interviews), HIMPSI · reflexive thematic analysis
04 — THEORETICAL LENSES

An individual self meets a relational one

Governance

Neuroliberalism

Government that works on emotions, habits and pre-conscious reactions while appearing to leave people free (Isin 2004; Whitehead et al.). It is carried out by states and also by corporations. Its goal is to calm anxiety, not to remove its causes.

Self

The reflexive self

Giddens (1991): in late modernity people must keep narrating and revising the self with help from expert systems. Intimacy takes the form of the pure relationship, which lasts only as long as it satisfies both partners. Chatbots satisfy one side indefinitely.

Relational norms

Kekeluargaan, hormat, rukun, sungkan

Familyhood, respect, harmony and reserve. Here the self asks where it stands and what it owes rather than who it is. A chatbot may appeal because it lets a person speak without disturbing those relationships.

The trajectory this study extends

Sointu (2005) traced wellbeing in UK newspapers from the body politic (the condition of the nation, mid-1980s) to the body personal (an individual project, 1990s). This study asks what happens next, when wellbeing is delegated to a machine.

05 — THE OBJECT

Three kinds of “wellbeing chatbot” that the news treats as one

Purpose-built

Wysa · Woebot

Scripted and grounded in CBT and mindfulness. A deliberately narrow range of responses, with "mental health concern" defined in advance. Some hold FDA or NHS approvals.

General-purpose

ChatGPT · Claude · Gemini · Llama

Open-ended and makes no therapeutic claim. Guardrails differ between providers and change with each update. What it says to someone in distress is neither fixed nor disclosed.

Companion

Replika · Character.AI

Built to keep a relationship going. Never framed as therapy, yet it attracts the most intense emotional use, with no clinical framework governing it.

06 — RESEARCH DESIGN

Sequential, qualitative, triangulated across time, space and persons

Triangulation here is not about checking one source against another (Fürsich 2009). It shows where the meaning of wellbeing converges and diverges across sites.

StrandDataWindowMethodPurpose
RQ1
Public news
The Guardian, “AI chatbot and wellbeing” · 86 identified1 Jan 2023 – 31 Dec 2026van Dijk: thematic, schematic, local coherence, style & syntaxHow wellbeing was redefined across three stages
RQ2
Family journalism
Julie Jargon, “Family & Tech”, WSJ · 20 columns1 Jun 2023 – 31 Dec 2026Same four-level protocolHow responsibility is moved into private life
RQ3
Indonesia
Riliv co-founders (2), Riliv psychologists (FGD + IDIs), HIMPSIMar – May 2027Reflexive thematic analysis (Braun & Clarke)How producers and the professional body define wellbeing and containment
07 — HOW THE ISSUE MOVED

Emergence → normalisation → containment

Adapted from Downs’ (1972) issue-attention cycle. Stage boundaries will come from the corpus and are not fixed in advance.

  • 30 Nov 2022
    ChatGPT released to the public

    Generative chatbots enter everyday use. The Guardian corpus begins on 1 Jan 2023.

  • Jun 2023
    An eating-disorder prevention chatbot gives dieting tips

    One of Jargon’s earliest columns in the RQ2 corpus.

  • 2024
    Character.AI case

    A 14-year-old’s death after months of conversations with a chatbot becomes international news.

  • 2025
    Illinois bars AI from providing therapy

    Regulation targets licensed providers, not the people using the tools.

  • Oct 2025
    OpenAI publishes suicide-risk estimates

    The company defines the scale of the problem as part of its own safeguards work.

  • Nov 2025 – Oct 2026
    Lawsuits, psychosis, teen ChatGPT

    Family journalism focuses on delusion, wrongful death and parental controls.

08 — THE PhD ITSELF

Where the project is now

  • Oct 2024 – Sep 2026 · Years 1–2
    Literature, questions, design, trial searches

    Completed.

  • Oct – Dec 2026 · Year 3
    Upgrade · ethics application · collection continues

    You are here.

  • Jan – Feb 2027
    Screening & initial coding in NVivo; interview guide
  • Mar – May 2027
    Online FGD & interviews (Riliv, HIMPSI)
  • Jun 2027 – Mar 2028
    Full coding; reflexive thematic analysis; news chapters
  • Apr – Sep 2028
    Interview chapter & discussion · LPDP tuition ends
  • Oct 2028 – Sep 2029
    Writing-up year · submission & viva
09 — CONTRIBUTIONS

Four linked contributions

Empirical

Wellbeing as the object of news

Tracks what counted as wellbeing, who needed it and what the remedy was across 2023–2026. Previous media studies of chatbots have looked at education, user communities and romance.

Theoretical

Neuroliberalism, extended

Shows public discourse allocating responsibility before regulation, and puts Giddens in dialogue with familyhood, respect, harmony and reserve.

Methodological

Reading responsibility in grammar

Who acts, who is quoted, what is assumed, what is left unsaid. Compares public news with family journalism over the same period.

Contextual

Production & governance from Indonesia

An account from a setting where no framework governs conversational systems and care is still carried by the family.

10 — WHO IS ASKING

An insider, which is both a resource and a risk

The researcher is Indonesian, from a working-class background, and funded by LPDP, which expects its scholars to bring their work back to Indonesia. She volunteered at Riliv in 2015–16, has taught at a university in Surabaya since 2021, and has been the mother of a young daughter since 2023.

The neuroliberal idea of wellbeing, in which each person manages their own mind, is the one her students are growing up with and one her daughter is likely to inherit. Reflexive thematic analysis treats this closeness as something to examine, not a bias to remove. Memos record how each relationship may shape the interviews.

WHERE THIS RESEARCH LIVES

Institutions and organisations

Studying at

Goldsmiths
Goldsmiths, University of London
University of London
Federal university

Research spaces

The British Library
Reading rooms, London

Organisations and tools discussed in the research

Riliv
Indonesian mental health app
OpenAI
ChatGPT
Wysa
Purpose-built wellbeing chatbot
Character.AI
Companion platform

Names and logos identify institutions and organisations connected to or discussed in this research. They are trademarks of their owners and do not imply partnership, sponsorship or endorsement. Riliv and HIMPSI are research sites, not research partners. Wysa logo: Wysa, via Wikimedia Commons, CC BY 2.5. Goldsmiths, OpenAI and Character.AI logos via Wikimedia Commons.