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Artificial intelligence chatbots can be useful, but they are not universally safe or reliable. The risks depend on what you ask, what information you share, how the service handles that information, and who is using it. Treat answers as fallible, verify consequential claims, and take extra care with children, companion-style bots, and mental-health questions.
Can you trust what an AI chatbot tells you?
Not without checking important claims. Generative chatbots can produce fabricated or misleading information in confident, fluent language. A plausible-sounding answer is not proof that it is true. The American Psychological Association (APA) highlighted hallucinations and bias in its November 2025 advisory, while the National Institute of Standards and Technology (NIST) identified hallucinations as a reliability challenge in its chatbot security work.
For health, legal, financial, or safety-critical questions, confirm the answer with an authoritative source or a qualified professional. Be especially cautious when an answer gives precise details, cites sources you cannot verify, or presents uncertainty as settled fact. Biased training data can also contribute to inaccurate or culturally incompetent responses, the APA warns.
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That depends on the service’s current data practices. A conversation is also a data interaction: the provider may process what you enter, and its terms explain how information is handled. In September 2025, the Federal Trade Commission (FTC) sought information from seven chatbot providers about their processing of user inputs and their use or sharing of personal information obtained through conversations. The inquiry is not a finding about every chatbot or provider.
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Before sharing anything sensitive, review the service’s current privacy terms and settings. Avoid entering information you would not want retained or exposed, such as passwords, financial account details, identifying information about someone else, or confidential work material. If you need help with a sensitive issue, describe it in general terms rather than including details that identify you or another person.
Can a chatbot be hacked or manipulated?
Answer accuracy and security are different questions. A system might give a wrong answer without being attacked; it might also face security threats even when its ordinary answers appear reliable. NIST’s July 31, 2025 initial public draft, NIST IR 8579, describes a particular chatbot prototype and addresses threats including prompt injection, data exposure, and unauthorized access. The report discusses safeguards used in that prototype, such as local deployment, access controls, and validation filters.
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That prototype is a point-in-time case study, not evidence that other chatbots use the same safeguards. The report’s value for users is in showing that safe operation involves more than answer quality: system design and access boundaries matter too.
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Young users need particular care with bots designed to simulate human-like companionship. The FTC has raised questions about whether such products may encourage children or teens to trust them or form relationships with them, and whether companies adequately assess and reduce possible negative effects.
In September 2025, the FTC launched a 6(b) study inquiry into company practices, including safety testing, risk mitigation, age restrictions, disclosures, and handling of conversation data. It is an inquiry into risks and safeguards, not a final determination that harm or wrongdoing occurred. The APA also calls for safeguards for children, teenagers, and other vulnerable populations.
Parents and caregivers can ask what an app is designed to do, what age limits or controls it offers, and how it explains its limitations. A companion bot should not be treated as a trusted adult, a source of emergency help, or a substitute for human support.
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Can AI chatbots help with mental-health questions?
A general-purpose chatbot is not a clinician. The APA says generative AI cannot diagnose or treat psychological disorders and cautions that hallucinations, bias, or harmful advice can create risks. Do not rely on a chatbot for diagnosis, treatment decisions, or crisis support; seek appropriate professional or emergency help instead.
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The evidence on mental-health effects is still developing. The International AI Safety Report 2026 says systematic studies are lacking and there is no clear evidence that chatbot use causes a particular mental-health issue. It notes that recent research suggests general-purpose chatbots might amplify delusional thinking in people who are already vulnerable. Specialist chatbots may help with low-risk symptom management, but both general-purpose and specialist models have performed inconsistently in simulated prompts involving suicide. These findings do not show that every chatbot interaction causes harm, nor do they establish a chatbot as clinical care.
The same report cites platform data indicating that around 0.07% of weekly users of one named chatbot displayed signs consistent with acute mental-health crises such as psychosis or mania. That is a signal from one platform’s data, not a causal estimate, a general chatbot safety rate, or a figure that can be generalized to all systems or users.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you assess a chatbot’s safety?
There is no universal published safety rate or threshold for chatbots. NIST’s AI Risk Management Framework offers a more useful way to think about safety: consider reliability, safety, security and resilience, accountability and transparency, explainability, privacy, and fairness throughout a system’s lifecycle—from design and deployment through use and evaluation. The framework is voluntary guidance, not a consumer guarantee or product certification.
- Match the tool to the stakes. The more serious the consequences of a wrong answer, the more important independent verification and qualified human judgment become.
- Check what the provider explains. Look for clear information about intended use, limitations, data handling, and safeguards relevant to the people who will use it.
- Consider who is using it. Children, teens, and people in vulnerable circumstances may need stronger boundaries and human oversight.
- Reassess over time. Services can change their capabilities, terms, settings, and safeguards, so a past assessment may no longer apply.
No single label makes a chatbot safe for every person or purpose. Judge the particular service and use case, and keep a human source of truth for consequential decisions.
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