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AI chatbots

Whispers to the Machine: What a Reported Survey Says 1,200 Kenyan Internet Users Share With Chatbots

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AfroTech Horizon reports that nearly half of 1,200 Kenyan internet users surveyed said they had shared personal secrets with generative AI chatbots or sought advice they would hesitate to share with another person. The finding is attributed to a Nendo survey, but the original report and its methodology have not been located, so the result cannot be treated as independently confirmed or nationally representative.

What the reported survey found

In an article published on 2 October 2026, AfroTech Horizon described a survey of 1,200 Kenyan internet users and said nearly half had told a chatbot deeply personal secrets or sought sensitive advice they would hesitate to disclose to another human being. The article does not give an exact percentage for that finding.

The same article reports mixed ratings of chatbot responses in Kiswahili and Sheng:

  • 34.9% reportedly rated responses in those languages “very good” or “excellent.”
  • 35.8% reportedly rated chatbot performance in those languages poorly.

These are respondents’ reported ratings as presented by AfroTech Horizon, not objective performance scores. The article does not provide the survey questions, rating criteria, field dates, or the chatbots and versions respondents assessed. The primary Nendo report was not located, so sampling details and representativeness are unknown. No margin of error or population-wide estimate can be responsibly inferred from the figures available.

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What the figures do—and do not—show

People may use chatbots for sensitive conversations

If accurately reported, the finding points to a meaningful behavior: some respondents use chatbots for disclosures or advice they might avoid sharing with another person. It does not establish why they do so, whether the conversations helped, or what kinds of secrets or advice were involved.

Language ratings are divided, but their cause is unclear

The reported Kiswahili and Sheng ratings suggest that respondents did not have one uniform view of chatbot performance. They do not explain whether a poor rating reflected comprehension, natural phrasing, cultural context, factual errors, or another factor. Nor do they show how any particular chatbot performs on a defined language task.

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Fluent conversation is not proof of expertise

A response that sounds natural or empathetic should not be mistaken for evidence that the chatbot has understood a person’s circumstances or can give expert advice. That is a practical caution, not a measured result of this survey. For consequential health, legal, financial, or safety decisions, use a qualified human source rather than relying on conversational confidence alone.

How to handle private conversations with chatbots

The survey account does not name a chatbot or describe its retention, training, or privacy settings. There is therefore no basis here for a platform-specific privacy assurance. Before sharing sensitive information, check the service’s current privacy information and settings, and consider whether the conversation needs identifying details at all.

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  • Leave out names, contact details, account numbers, exact locations, and other details that could identify you or someone else.
  • Describe a situation in general terms when precise personal information is not necessary to ask the question.
  • Do not treat a chatbot conversation as confidential merely because it feels private or nonjudgmental.
  • For advice with serious consequences, use the chatbot to help formulate questions or organize thoughts, then consult an appropriate qualified person.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Support on Ko-Fi

What would be needed to judge the findings more firmly

A fuller assessment would require the original Nendo report or questionnaire, including how participants were recruited, when the survey was conducted, the exact wording behind “personal secrets” and “poorly,” and which chatbot systems respondents had in mind. Without those details, the reported figures are best read as a snapshot described by AfroTech Horizon—not as a verified measure of all Kenyan internet users or a benchmark of chatbot quality.

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