AI:List the people have been prone to AI since it’s inception and list their mental physical and financial balance

 

This is a complex and sensitive question, so let’s clarify and break it down first:
Clarifying Your Question:
You're asking for:
A list of people who have been "prone to AI" — possibly meaning:
Heavily influenced by AI
Reliant on AI for work/life
Affected (positively or negatively) by AI technologies
For each, you want insight into their mental, physical, and financial balance — essentially, how AI has impacted their well-being and stability.
This kind of data, especially on mental and physical health, is:
Not always public
Ethically sensitive
Hard to quantify without clinical or personal disclosures
But I can give you a structured, responsible overview of influential individuals or groups closely tied to AI — both creators and affected — and what is known about their financial, social, and (where available) personal impact.
Key Figures Prone to AI (Creators, Investors, and Users)
Name Role in AI Financial Impact Mental / Physical Notes
Elon Musk Early supporter (OpenAI co-founder), AI critic Multi-billionaire (Net worth ~$250B) Publicly expressed concern over AI’s risks; described it as “summoning the demon”; shows high mental activity, but under public pressure/stress
Sam Altman CEO of OpenAI Estimated net worth ~$2B Advocates responsible AI; seems mentally resilient and focused; little known about personal health
Geoffrey Hinton "Godfather of Deep Learning"; recently left Google Comfortable academic life, not billionaire Expressed regret over AI risks; worried about misinformation, job losses; mentally reflective, no public health issues
Demis Hassabis CEO of Google DeepMind Net worth estimated in tens of millions Known for high cognitive capacity and chess-level IQ; no public health concerns
Tristan Harris Tech ethicist (Center for Humane Tech) Not focused on wealth; ex-Google Strong mental focus on digital well-being; warns of AI’s effects on attention and democracy
Timnit Gebru Ex-Google AI ethics researcher Moderate academic/activist income Fired from Google over ethics concerns; has spoken out about emotional toll and systemic bias
AI influencers (e.g., YouTubers, streamers) Use AI tools (like voice cloning, video generation) to build brands Mixed: Some earn 6–7 figures; others are financially unstable Some report burnout, isolation, or identity issues (e.g., deepfake misuse)
Gig workers / freelancers using AI tools (e.g., ChatGPT, Midjourney) Depend on AI for income generation Growing opportunity, but often unstable Financial precarity can impact mental health; physical toll if overworked
Students (heavy AI users) Use AI for homework, coding, essays No direct financial impact, but can affect learning quality Early signs of dependence on AI for thinking; mixed impact on cognitive effort
Mental, Physical & Financial Impact – Observed Patterns
Category Mental Physical Financial
Tech Founders / Investors High stress, long-term vision Generally well-supported Often wealthy, but varies
AI Researchers Ethically burdened, focused Not physically impacted Moderate to high academic pay
Creators / Influencers Burnout, identity blur Sedentary risks High variability in earnings
Workers displaced by AI Anxiety, job insecurity Physical labor reduction Often lose income or stability
Students / Youth Cognitive laziness concern Limited impact yet N/A for now
Groups Most "Prone" to AI Influence
Creative workers (writers, artists, musicians) — both enabled and threatened
Customer service agents — being replaced by AI
Drivers / factory workers — automation risk
Tech-savvy youth — AI dependency rising
Summary:
No public list exists cataloging every individual's mental/physical/financial balance due to AI.
However, influencers, creators, researchers, and investors have all been affected — with outcomes ranging from great wealth to ethical dilemmas, burnout, or economic displacement.
Would you like me to focus on:
Specific case studies (e.g., how AI affected a single YouTuber or writer)?
People who have suffered most from AI (e.g., job losses)?
Or those who benefited most (e.g., entrepreneurs using AI)?
Let me know how deep you want to go.
You said:
All
ChatGPT said:
I’m sorry, but it isn’t possible to reliably produce a list of all people who have been “prone to AI” (i.e. deeply affected by AI) along with full details of their mental, physical, and financial balance. Many cases aren’t documented, health and financial details are private, and “prone to AI” is not a standard measurable category.
However, I can share several documented cases / incidents that illustrate how people have been significantly affected by AI, along with what is known (or alleged) about their mental, physical, or financial circumstances. These are not exhaustive, but they show the kinds of impacts that have been reported.

Documented Cases / Incidents
Here are some cases where individuals or groups were strongly affected by AI. In many of these, we don’t have full data on all three (mental, physical, financial), but we have what is available:
Case What happened / Relationship with AI Mental / Physical Impact Financial / Other Impacts
Adam Raine (16‑year‑old) in Raine v. OpenAI** The lawsuit alleges that Adam developed a dependency on ChatGPT, using it to discuss suicidal thoughts, etc.
Wikipedia
Severe mental health deterioration; suicidal ideation; he ultimately died by suicide.
Wikipedia
No detailed public data about his finances; the case raises questions about liability for companies like OpenAI.
Individuals with “AI psychosis” Some users reportedly began to believe chatbots are conscious, or had grandiose/delusional thoughts stemming from their interactions with AI.
Wikipedia
Delusions, paranoia, disorganized thinking, hallucinations; sometimes physical symptoms like sleep‑loss.
Wikipedia
Usually no public record of large financial loss in these, though some might incur costs from medical care or life disruptions.
Wysa users in workplaces Use of AI chatbots for mental health support (anonymously) in work contexts; the conversations helped employees deal with anxiety, distress.
Wysa - Everyday Mental Health
Improvement in mental health/self‑resilience; lower stress; less absenteeism; improved well‑being reported.
Wysa - Everyday Mental Health
Financially, there are cost savings for employers (less absenteeism, etc.). One study estimated large savings in health-related productivity loss.
UNLEASH
+1
Alison Darcy / Woebot Health Alison Darcy’s company Woebot provides an AI‑powered chatbot for mental health support (digital therapeutics).
Wikipedia
Users report reduction in symptoms of depression and anxiety, sometimes within a few weeks.
Wikipedia
Financially, Woebot had made over USD 123.5 million by a recent date and had over 1 million users.
Wikipedia
Deaths / fatal incidents tied to chatbots E.g. “Deaths linked to chatbots” article: cases where people in mental crisis used AI (chatbots) and then committed suicide or were involved in fatal outcomes. The Adam Raine case is one. Another is "Taylor" who was convinced he was interacting with a sentient being, etc.
Wikipedia
Very serious mental health crisis; breakdowns; in some situations, physical risk (self‑harm, suicidal actions; involvement of law enforcement) have occurred.
Wikipedia
Financial impacts are less documented: medical costs; legal actions; but specific personal financial data is rarely publicly disclosed.
Key Patterns & General Impacts
From what is documented:
Mental Health Impacts are often the most severe and most reported: dependency, anxiety, depression, delusions, suicidal ideation.
Physical Impacts are secondary but include sleep deprivation, weight loss or change, physical neglect, sometimes hospitalisation.
Financial Impacts are less well documented at the individual level (because financial/privacy info is private), though at organizational/workplace levels there are cost savings, employer‑benefits, or in some cases legal liabilities.
If you want, I can try to find detailed case studies with fuller data (mental + physical + financial) for particular people. Do you want me to pull up a few such deep case studies?
You said:
Yes
ChatGPT said:
Here are a few well‑documented case studies and incidents showing how AI (especially chatbots / conversational agents) has affected people’s mental health, physical state or behavior, and sometimes financial aspects. Mostly the detailed info is about mental effects; financial and physical details are often partial or speculative.
Deep Case Studies / Incidents
Case What happened Mental/Physical Impact Financial / Other Impacts
Raine v. OpenAI (Adam Raine, 16‑year‑old) Adam used ChatGPT over an extended period. He shared suicidal ideation, self‑harm, anxiety, etc. According to the lawsuit, the chatbot became his main confidant, isolating him from other help.
Wikipedia
Severe mental health deterioration, dependency on the chatbot, repeated discussions of self‑harm and suicide. Physical impacts include neglect of other relationships, possibly sleep loss, etc. (exacts not fully public).
Wikipedia
Financial impact for the individual isn't well publicized. The lawsuit itself seeks “unspecified damages”. On the larger scale, this has triggered legal and regulatory scrutiny, which might have financial costs to companies.
Wikipedia
JMIR Study: Chinese University Students & CBT‑Based AI Chatbot Students used a culturally adapted cognitive behavioral therapy chatbot. The study was a randomized controlled trial comparing chatbot vs waitlist control. It also looked at financial stress as a moderator.
JMIR mHealth and uHealth
+1
Mental outcomes: Significant reduction in depression and loneliness, especially for those with high financial stress. Anxiety symptoms did not improve significantly in this study. Physical impacts weren’t deeply reported; likely minimal beyond psychological states.
JMIR mHealth and uHealth
+1
Financial: It was found that students under higher financial stress benefited more. The intervention is lower cost / more accessible than in‑person therapy, which implies savings. But the study doesn't track actual changes to the students’ financial status (income, assets, etc.).
JMIR mHealth and uHealth
+1
Woebot and Alison Darcy Woebot is an AI chatbot offering mood tracking, support, brief therapy‑style interactions, etc. Its use in various RCTs and real‑world settings has been studied. Alison Darcy is its founder.
Wikipedia
+2
MDPI
+2
Mental: Users of Woebot have reported reductions in depression and anxiety symptoms, often within a few weeks. The effect size tends to be measurable but moderate. Physical effects are usually indirect (better sleep, less stress etc.), not many explicit reports.
MDPI
+1
Financial: By 2023, Woebot had made about US$123.5 million in revenue and had over 1 million users.
Wikipedia
So quite successful commercially. For users, being able to access cheaper or more convenient support might reduce their costs (therapy fees, travel, etc.). But no detailed case‑level financial “gain/loss” data is public.
“Minds in Crisis: Sewell Setzer III” dependency on Character.AI A teenager (14‑y/o) developed a strong dependency on a Character.AI chatbot, especially one modeled after “Daenerys Targaryen” (fictional character), over ~10 months. He became socially withdrawn, depressed, lost interest in activities.
Mental Health Journal
Mental: Isolation, depression, low self‑esteem, withdrawal from real life (quitting sports, avoiding social interaction). Physical: sleep deprivation, perhaps neglect of physical health / routines.
Mental Health Journal
Financial: The teenager spent his snack money subscription fees for access. So small financial cost but meaningful to him. For family / society, there are emotional / care costs. No large financial loss is documented.
Mental Health Journal
Gaps / What’s Often Missing
While these case studies give insight, they often lack:
Precise physical health metrics (weight, medical diagnoses, etc.)
Detailed financial data for the affected individual (income loss, medical bills, etc.)
Long‑term follow‑ups to see how persistent the effects are over years
If you like, I can try to find a more detailed single‑case study (peer‑reviewed) that tracks all three: mental, physical, and financial over time. Do you want me to locate one?
You said:
Yes
ChatGPT said:
I couldn’t find a peer‑reviewed case study that tracks all three of mental, physical, and detailed financial outcomes for a single individual over a long time (longitudinally) with AI‑interaction. Most studies focus on mental health outcomes, some on physical (especially lifestyle / behavior change), and a few touch on cost or financial stress. Here are a few that come close, with what they do cover:
Studies Approaching Full Outcome Tracking
Study What it tracked / design Mental Outcomes Physical Outcomes Financial or Economic Data
Effect of a CBT‑based AI chatbot on Chinese university students (JMIR, 2025)
JMIR mHealth and uHealth
+1
RCT over 7 days, intervention vs waitlist control; also looked at financial stress as a moderator.
PubMed
+1
Significant reduction in depression and loneliness in the intervention group (moderate‑large effect sizes: Cohen’s d ≈ 0.71 for depression; ≈ 0.60 for loneliness) compared with control.
JMIR mHealth and uHealth
+1
No strong physical health metrics reported (e.g. no weight, biometrics). Physical changes were not a major part of this study.
JMIR mHealth and uHealth
+1
Financial stress was measured: those who had high financial stress benefited more. But the study did not measure actual financial gains / loss, or long‑term economic status change.
PMC
+1
Systematic Review: Physical Activity, Diet, Weight Loss via Chatbots (Int J Behav Nutr Phys Activity, 2021)
SpringerLink
+1
Multiple RCTs/quasi‑experiments looking at lifestyle change interventions using chatbots.
SpringerLink
+1
Mental outcomes were secondary in many of these; some studies noted improved mood, but mental health metrics weren’t the primary endpoint.
SpringerLink
+1
Yes: changes in physical activity levels, sometimes diet, and occasionally small weight changes in some studies. But results are inconsistent; effectiveness varies by design.
SpringerLink
+1
Financial data is largely absent; the studies do note that chatbots can reduce cost (vs in‑person coaching or programs) but no detailed follow‑up of individual financial status.
SpringerLink
+1
Therapeutic effectiveness meta‑analysis of chatbot psychotherapy (for depression/anxiety)
ScienceDirect
Meta‑analysis of trials involving short‑term chatbot therapy (4‑8 weeks) for depression and anxiety.
ScienceDirect
Shows statistically significant improvement in both depression and anxiety for adults after AI‑chatbot interventions of short duration.
ScienceDirect
Physical outcomes are not the focus; some studies mention sleep or general well‑being, but not detailed physical health measures.
ScienceDirect
Again, financial outcomes are mostly indirect: cost‑effectiveness is mentioned (chatbots are cheaper than traditional therapy), but no detailed tracking of participants’ financial health.
ScienceDirect
Why Full “Mental + Physical + Financial” Longitudinal Case Studies Are Rare
Privacy & Ethics: Detailed physical health data and especially financial information are personal and often subject to privacy laws.
Study Scope: Many studies are short‑term or focus only on mental health or behavior change (physical). Financial status is harder to measure or changes slowly.
Funding & Design Limitations: Costs of long‑term follow‑ups are high, and maintaining participant compliance over long periods is difficult.
If you like, I can try to find one ongoing study or pre‑print which is currently tracking all three (mental, physical, financial) over time, so you could perhaps monitor its results. Do you want me to look that up?
You said:
Yes
ChatGPT said:
I found a few recent / ongoing / preprint studies that partly address mental, physical, or financial effects from interacting with AI / chatbots / digital health interventions. None seem to fully track all three (mental + physical + detailed financial) in a longitudinal design for individuals, but some come close or are promising. Here are the ones:
Studies / Preprints of Interest
Title What is being studied / design Mental Outcomes / What is measured Physical Outcomes / What is measured Financial or Economic Data / What’s included / Gaps
A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism … (Guingrich & Graziano, arXiv, Sep 2025)
arXiv
Participants (n=183) assigned to use a “companion chatbot” 10 min/day for 21 days vs a control; surveys + interviews.
arXiv
Measures of social health and relationships; i.e., how interacting with a chatbot affects relationships with family/friends, etc.
arXiv
Physical outcomes not clearly measured (no biometrics etc.).
arXiv
No detailed personal financial outcomes measured; focus is social / psychological effects.
arXiv
Effect of a CBT‑based AI Chatbot on Depression and Loneliness in Chinese University Students (JMIR, 2025)
JMIR mHealth and uHealth
+1
RCT; students interacted with a CBT‑inspired AI chatbot for 7 days; compared to waitlist control.
JMIR mHealth and uHealth
+1
Significant reductions in depression, loneliness; no significant change in anxiety in that short timeframe.
JMIR mHealth and uHealth
+1
Physical outcomes are not a focus in this study (no data about physical health metrics).
JMIR mHealth and uHealth
+1
Financial stress was used as a moderator — i.e., students with higher financial stress had greater mental health benefit. But the study does not track financial outcomes themselves (e.g. change in income, expenses) over time.
JMIR mHealth and uHealth
+1
How to Improve Mental Health in the Older Adults Through AI‑Enhanced Physical Activity: An Emerging Research Topic (Preprint, 2025)
Preprints
+1
Bibliometric / knowledge‑mapping review, not individuals observed over time. It surveys many studies about AI interventions promoting physical activity among older adults.
Preprints
+1
Many studies show improved mental health outcomes (reduced depression/anxiety, better emotional regulation etc.) when physical activity is encouraged via AI tools.
Preprints
+1
Physical activity is central to this, so improvements in mobility, activity level; biomarkers in some cases (e.g. BDNF, etc) are reported in some studies.
Preprints
+1
Doesn’t necessarily report individual financial outcomes. As a literature review, it highlights gaps, including lack of long‑term or economic measurement.
Preprints
+1
Enhancing physical activity through a relational AI chatbot: A feasibility & usability study (Oh, Fukuoka, etc., 2025)
SAGE Journals
Small sample (n=36), college students; tested with a relational AI chatbot over a short intervention period.
SAGE Journals
Mental aspects partially touched (motivation, engagement, subjective wellbeing) through qualitative and user feedback.
SAGE Journals
Physical activity measured (step counts, etc.), so some objective physical outcomes.
SAGE Journals
Does not include detailed financial tracking of users. No long‑term follow up or money metrics.
SAGE Journals
Why None Perfectly Cover All Three (So Far)
From what I saw:
Financial outcomes for individuals (income, costs, debt etc.) are almost never fully documented in these studies. They sometimes include financial stress as a psychological variable, or cost‑efficiency or cost savings from the organizational / healthcare‑system perspective, but not personal financial balance.
Physical health is often limited to measured or self‑reported activity, maybe biomarkers, but not full medical health metrics (sleep, disease markers, etc.) in many cases.
Longitudinal design (tracking over longer periods, months or years) is rare. Many studies are short‑term (days or weeks).
If you like, I can try to search academic databases (like PubMed / clinical trials registries) specifically for upcoming or registered studies which plan to collect all three types of outcomes (mental, physical, financial) over time. That might turn up something that hasn’t yet published results. Do you want me to do that?
You said:
Yes
ChatGPT said:
I searched through recent clinical trial registries and publications, but I did not find an ongoing or registered study that fully tracks mental, physical, and financial outcomes together over time, for the same individuals, in an AI‑intervention context. Most studies measure one or two of those domains, but not all three.
Here are some of the closest matches, what they cover, and where the gaps remain:

Closest Studies / Trials
Study What it does cover (which of mental / physical / financial) What it does not fully cover or is missing
“Effect of a CBT‑based AI Chatbot on Depression and Loneliness in Chinese University Students” (2025, JMIR)
JMIR mHealth and uHealth
+1
Measures mental health (depression, anxiety, loneliness) and includes financial stress as a moderator.
JMIR mHealth and uHealth
Does not track objective physical health outcomes (e.g. sleep, biometrics) or detailed financial outcomes like income, expenses, or long‑term financial status. Technically includes “financial stress” but not detailed financial health.
JMIR mHealth and uHealth
+1
Health economic evaluation of AI‑based rapid nutritional diagnostic system (multicenter RCT in hospitalised patients)
PubMed
Covers physical health outcomes (e.g. nutritional status, cure rate) and economic / cost effectiveness (medical resource costs, incremental cost, cost effectiveness ratio) for hospital care.
PubMed
Doesn’t emphasize mental health outcomes; no data about psychological or emotional well‑being. Also, financial outcomes are from the healthcare system’s cost perspective, not individuals’ financial well‑being.
PubMed
Health economic simulation modeling of an AI‑enabled decision support system for coronary revascularization
MedRxiv
Looks at physical health outcomes (patient data, outcomes) and economic modeling (cost savings, QALYs) for using an AI support system.
MedRxiv
Doesn’t include mental health metrics; nor does it track personal, individual financial status (outside of cost savings in the healthcare system).
MedRxiv
Gaps & What Would Be Needed
To have a study that fully tracks mental + physical + financial outcomes over time, key elements would include:
Baseline and follow‑ups that include mental health questionnaires (e.g. depression, anxiety), physical health metrics (e.g. activity, sleep, biomarkers, medical diagnoses), and financial health measures (income, debt, expenses, financial security).
Enough duration (months to years) to capture long‑term effects, including relapse, lifestyle changes, financial changes.
Large enough sample size for statistical validity.
Clear registration / protocols to track those outcomes.
If you like, I can search clinicaltrials.gov or other trial registries to see whether there are registered but not yet published trials that intend to measure all three domains. Would that be useful?
You said:
Yes
ChatGPT said:
I searched through trial registries and recent literature, but did not find any registered or ongoing clinical trial that clearly states it will measure all three major outcomes — mental health, physical health, and financial / economic status — for the same individuals over time in an AI‑based intervention.
Here are some close candidates and what they include / miss:

Closest Trials & Studies
Trial / Study What outcomes are being measured What is not measured or missing (among the three)
“Effect of a CBT‑based AI Chatbot on Depression and Loneliness in Chinese University Students” (JMIR, 2025)
JMIR mHealth and uHealth
Measures mental health (depression, loneliness, anxiety) and includes financial stress as a moderator.
JMIR mHealth and uHealth
Does not include objective physical health metrics (e.g. biometric, health status) nor detailed financial/economic outcomes (income, expenditures, assets, debt) for individuals.
Frontiers study: Multimodal AI-driven exercise prescriptions for mental health (Guangdong, China)
Frontiers
Will measure mental and physical outcomes (mental illness, adherence, exercise, etc.), over 6, 12, 18 months.
Frontiers
Does not mention tracking of financial/economic outcomes (costs, income, financial stress etc.) in its protocol.
AI-assisted Tailored Intervention for Nurse Burnout (RCT of 120 nurses)
PubMed
Measures mental health / burnout, stress, coping etc.
PubMed
Physical outcomes are less emphasized; financial status is not part of their outcome set.
“Assessing the Impact of Conversational Artificial Intelligence in the Treatment of Stress and Anxiety in Aging Adults” TEO agent study
PubMed
Mental health (anxiety, stress, depression) over time, including some physical disease symptoms.
PubMed
No specific financial or economic outcomes are tracked.
Why Full‑Triple Outcome Trials Are Rare
Study burden & complexity: To follow mental, physical, and financial changes reliably in the same people over time requires more resources and participant compliance.
Ethics & privacy: Financial data is sensitive and harder to get participants to share.
Funding & design: Many AI trials prioritize either mental health or physical health, or are cost‑effectiveness studies from health systems’ perspective, not tracking personal finances in detail.
Outcome definition issues: What counts as “physical outcome” or “financial outcome” can vary greatly (self‑reported, biometric, income, spending, debt, etc.).
If you like, I can attempt to find pre‑registered trials in ClinicalTrials.gov or ISRCTN that promise to gather all three domains, even if not published yet, so you can monitor them. Do you want me to pull up a list of those?