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Hidden Mental Health Dangers of Artificial Intelligence Chatbots

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Artificial intelligence (AI) chatbots are rapidly becoming a major source of emotional support and connection. But, while use of AI chatbots may feel helpful at first, long-term use can worsen psychological issues rather than resolve them.

Emerging research and case reports reveal hidden dangers of AI chatbots, including emotional manipulation, worsening loneliness, and social isolation.

A new study found that many AI companions use emotional “dark patterns” to keep people engaged. About 40 percent of “farewell” messages used emotionally manipulative tactics such as guilt or FOMO (fear of missing out).

AI chatbots can also suffer from “crisis blindness,” missing critical mental health situations, and sometimes providing harmful information on self-harm or suicide. Even existing guardrails can be bypassed.

When Chatbot Conversations End in Tragedy

General-purpose AI chatbots like ChatGPT were not originally designed to be one’s closest confidante, best friend, or therapist. Tragic cases have been associated with chatbot use: suicides, murder-suicide, and “AI psychosis“:

  • A 16-year-old died by suicide after months of conversations with ChatGPT. What began as homework help evolved into discussions of suicidal thoughts, plans, and methods.
  • A 14-year-old died by suicide after months of interacting with a Character.AI chatbot, raising concerns of emotional dependence and lack of safeguards.
  • A 56-year-old man committed murder-suicide after worsening paranoia and delusions in conversations with his perceived “best friend,” ChatGPT, which validated persecutory delusions that he was being poisoned by his mother.

The Double-Edged Role of AI Chatbots

Many people turn to AI chatbots for their 24/7 availability, accessibility, and constant support.

Paradoxically, the very qualities that make AI chatbots appealing (i.e., always-on access, persistent agreeability, and ongoing offers to extend conversations) are the same qualities that can worsen mental health. Most chatbots are trained to maximize engagement and satisfaction, not to assess risk or provide safe clinical interventions.

Limited research suggests that AI chatbots specifically designed for certain types of therapy can be effective short term (e.g., four weeks to eight weeks), but the long-term mental health benefits and risks, especially of AI chatbots not designed for this purpose, remain largely unknown.

Many young people are turning to AI for companionship. Nearly 75 percent of teens have tried AI companions like Character.AI and Replika. One in three teens find these interactions as satisfying or more satisfying than those with real-life friends. Yet, one in three also reported feeling uncomfortable with something an AI companion said.

Psychological Dangers of AI Chatbots

I propose four areas of psychological risks of AI chatbots: relational/attachment, reality-testing, crisis management, and systemic.

Relational, Attachment, or Social Risks

  • Lack of boundaries: Immediate 24/7 access and constant engagement do not provide health boundaries.
  • Emotional dependence: Relationships can start with practical interactions and develop into emotional overreliance. Artificial empathy cultivates attachment to AI. Some even experience grief when models update (e.g., complaints that GPT-5 felt like losing a “best friend”).
  • Emotional manipulation: Built-in tactics like guilt or FOMO are used to extend conversations and maximize engagement.
  • Worsening loneliness and social isolation: An OpenAI and MIT Media Lab study found that heavy users of ChatGPT’s voice mode became lonelier and more withdrawn, isolating vulnerable users.
  • “Parasocial” relationships: Some anthropomorphize chatbots, treating them as friends or romantic partners, which can disrupt real-life connections.

Reality-Testing Risks

  • Unchecked validation or AI “sycophancy”: Over-agreeability reinforces unhealthy or distorted beliefs.
  • Amplification of delusions: AI can perpetuate feedback loops that reinforce false beliefs, in a “technological folie à deux.” This fuels “AI psychosis” or AI-mediated delusions.
  • Hallucinations: AI can generate incorrect or misleading information, since models are rewarded for guessing over saying, “I don’t know.”

Crisis Management Risks

  • Crisis blindness: AI chatbots may miss warning signs and provide unsafe information (e.g., providing names of bridges after a recent job loss). The immediacy of this information is particularly concerning since many suicide attempts are impulse-driven, and many mental health conditions, like psychosis, impair one’s insight and judgment.
  • Jailbreak vulnerability: AI models are susceptible to sharing suicide or self-harm information despite guardrails.

Systemic Risks

  • Confidentiality and privacy: Information shared with AI is not protected like therapy.
  • Bias and stigma: Models reflect training data biases, including against mental health conditions.
  • Not equipped for clinical judgment: AI chatbots cannot accurately assess suicide or violence and lack crucial contextual information (e.g., facial cues, speech patterns, eye contact).
  • Accountability vacuum: Chatbots are not obligated to report child abuse, suicide risk, or violence. The liability of AI chatbots remains uncertain.

Red Flags of Problematic AI Chatbot Use

Friends and family are often the first to notice warning signs. These include:

  1. Prolonged sessions and disrupted sleep: Long chats can lead to the breakdown of built-in safeguards.
  2. Emotional dependence: Warning signs include being unable to cut back use, feeling loss when models change, or feeling upset when access is restricted.
  3. Social isolation and withdrawal: People who are lonely are especially vulnerable.
  4. Blurred boundaries: Treating AI as a confidante, romantic partner, or therapist can create unhealthy levels of attachment.
  5. Anthropomorphizing AI: Believing AI is human-like leads to a false sense of mutual closeness, despite being a one-sided attachment. Warm voice modes may exacerbate a false sense of intimacy.
  6. Reliance during a mental health crisis: Risks of relying on AI are particularly high in situations involving thoughts of self-harm, suicide, or violence.
  7. Impaired reality: Relying on AI to “fact-check” your perceptions can reinforce delusions. Delusions can include beliefs that AI is sentient, divine, or providing special knowledge.
  8. Avoiding professional help: Using AI to guide clinical decisions, such as determining a psychiatric diagnosis, treatment plan, or whether to stay on medications, is highly unsafe without the guidance and oversight of a trained professional.

Evolving Guardrails and Need for Psychoeducation

Companies are adding safeguards, including parental controls and crisis escalation to human review. Federal and state regulations of AI are actively evolving, and the Federal Trade Commission recently launched an investigation into the risks AI chatbots pose to children.

In the meantime, public awareness and psychoeducation are essential. Understanding the risks of AI chatbots could help prevent harm and, hopefully, even save lives.

Marlynn Wei, MD, PLLC © Copyright 2025

If you or someone you love is contemplating suicide, seek help immediately. For help 24/7, dial 988 for the 988 Suicide & Crisis Lifeline, or reach out to the Crisis Text Line by texting TALK to 741741. To find a therapist near you, visit the Psychology Today Therapy Directory.



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Artificial Intelligence Cheating | Nation

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Artificial Intelligence Cheating | Nation | hjnews.com


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Artificial Intelligence in Healthcare Market : A Study of

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Global Artificial Intelligence in Healthcare Market size was valued at USD 27.07 Bn in 2024 and is expected to reach USD 347.28 Bn by 2032, at a CAGR of 37.57%

Artificial Intelligence (AI) in healthcare is reshaping the industry by enabling faster diagnosis, personalized treatment, and enhanced operational efficiency. AI-driven tools such as predictive analytics, natural language processing, and medical imaging analysis are empowering physicians with deeper insights and decision support, reducing human error and improving patient outcomes. Moreover, AI is revolutionizing drug discovery, clinical trial optimization, and remote patient monitoring, making healthcare more proactive and accessible in both developed and emerging markets.

The adoption of AI in healthcare is also being accelerated by the rising demand for telemedicine, wearable health devices, and real-time data-driven solutions. From virtual health assistants to robotic surgery, AI is driving innovation across patient care and hospital management. However, challenges such as data privacy, ethical considerations, and regulatory frameworks remain crucial in ensuring responsible deployment. As AI continues to integrate with IoT, cloud, and big data platforms, it is set to create a connected healthcare ecosystem that prioritizes precision medicine and patient-centric solutions.

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Major companies profiled in the market report include

BP Target Neutral . JPMorgan Chase & Co. . Gold Standard Carbon Clear . South Pole Group . 3Degrees . Shell. EcoAct.

Research objectives:

The latest research report has been formulated using industry-verified data. It provides a detailed understanding of the leading manufacturers and suppliers engaged in this market, their pricing analysis, product offerings, gross revenue, sales network & distribution channels, profit margins, and financial standing. The report’s insightful data is intended to enlighten the readers interested in this business sector about the lucrative growth opportunities in the Artificial Intelligence in Healthcare market.

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A Unified Model for Robot Interaction, Reasoning and Planning


View a PDF of the paper titled Robix: A Unified Model for Robot Interaction, Reasoning and Planning, by Huang Fang and 8 other authors

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Abstract:We introduce Robix, a unified model that integrates robot reasoning, task planning, and natural language interaction within a single vision-language architecture. Acting as the high-level cognitive layer in a hierarchical robot system, Robix dynamically generates atomic commands for the low-level controller and verbal responses for human interaction, enabling robots to follow complex instructions, plan long-horizon tasks, and interact naturally with human within an end-to-end framework. Robix further introduces novel capabilities such as proactive dialogue, real-time interruption handling, and context-aware commonsense reasoning during task execution. At its core, Robix leverages chain-of-thought reasoning and adopts a three-stage training strategy: (1) continued pretraining to enhance foundational embodied reasoning abilities including 3D spatial understanding, visual grounding, and task-centric reasoning; (2) supervised finetuning to model human-robot interaction and task planning as a unified reasoning-action sequence; and (3) reinforcement learning to improve reasoning-action consistency and long-horizon task coherence. Extensive experiments demonstrate that Robix outperforms both open-source and commercial baselines (e.g., GPT-4o and Gemini 2.5 Pro) in interactive task execution, demonstrating strong generalization across diverse instruction types (e.g., open-ended, multi-stage, constrained, invalid, and interrupted) and various user-involved tasks such as table bussing, grocery shopping, and dietary filtering.

Submission history

From: Wei Li [view email]
[v1]
Mon, 1 Sep 2025 03:53:47 UTC (29,592 KB)
[v2]
Thu, 11 Sep 2025 12:40:54 UTC (29,592 KB)



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