Is AI Learning Your Information Without Your Knowledge?
As AI tools have exploded in popularity, our lives are changing at a remarkable pace. While AI is increasingly active across chatbots, image generation, coding support, and countless other fields, the risk of personal data leakage lurking beneath the surface has become a serious concern. Many users are not particularly aware that the data they enter may be treated directly as training material for AI — and as a result, they are unknowingly exposed to the possibility that their own information could be leaked. For example, with widely used everyday tools like ChatGPT, Gemini, Perplexity, Claude, and AI agents, the default setting is very often "data training on." This creates the risk that your personal information, confidential data, and even unintended content could be used as AI training data.
This article explains in detail — with concrete examples and real-world corporate cases — the specific risks involved, how they arise, and what you can do to protect yourself. We cover everything from demonstration cases to corporate examples. Please read to the end to build smarter, safer habits for using AI alongside the innovations it brings.
- Are AI Tools' "Default Settings" Dangerous? Understanding How Data Training Works
- The Reality of "Training On" by Default: 10 Major AI Tools Including ChatGPT, Gemini, and AI Agents
- Three Key Points for Using AI with Confidence — How to Check Settings and Prevent Data Leaks
- Summary: Building "Data Defense" Capabilities to Thrive in the AI Era
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Are AI Tools' "Default Settings" Dangerous? Understanding How Data Training Works
Many modern AI tools are designed to automatically incorporate data entered by users as training data to improve the model — driven by the goal of enhancing convenience and performance. For example, in ChatGPT, the "Improve the model for everyone" option within the "Data Controls" section of settings is on by default; unless users opt out, their input data is used for training. Because the data is captured by default without users necessarily being aware of it, personal information entered incidentally — hobbies, names, and even information about others — could potentially be used as AI training data. This setup carries both the benefit of users contributing to AI accuracy improvement, and the ever-present risk of a security exposure.
As a real-world example: at Samsung Electronics in South Korea, engineers input internal source code into ChatGPT to request a check, and the incident revealed the risk of confidential information being sent externally — ultimately leading the company to prohibit the use of consumer-facing AI tools company-wide.
It is also important to pay attention not just to settings issues but to how information that AI incorporates as training data is subsequently used. A 2022 paper on GPT-2 reported that specific prompts could extract personal information and code fragments from the training data. A 2026 study from Stanford University and other research teams confirmed that while the risk has been mitigated by safety mechanisms called "guardrails" in the latest models, it has not been entirely eliminated. For instance, cases have been reported where learned data is quoted directly in AI responses, or where a user's input is associated with individual information in responding to subsequent questions — creating the potential for unintended information disclosure or data misuse. These risks vary significantly depending on how each user handles their information and which tools they use for which purposes, making it essential for each person to take careful precautions.
To understand these risks more concretely, consider the following:
- If the information you enter includes confidential corporate data or personal privacy information, that information may be learned by the AI and later appear in responses to other users.
- Compared to the risk of ordinary document misdelivery or misplacing paper documents, the frequency of any individual incident may be low — but once information is incorporated into training data, controlling it afterward becomes extremely difficult.
Particularly important: when taking protective measures, judgment must be tailored to your own usage context and the sensitivity of the information you handle. Casual conversation and general questions typically pose minimal risk, but for business use, the key is not to carelessly enter any information at all. Building the habit of checking each tool's settings immediately after starting to use it — to prevent unintended data sharing — will ultimately protect both your own information security and your organization's.
The Reality of "Training On" by Default: 10 Major AI Tools Including ChatGPT, Gemini, and AI Agents
In recent years, a diverse range of AI tools have entered the market, and many are now incorporated into daily work and personal use. These include ChatGPT, Gemini, Perplexity, Claude, AI agents, as well as Grok, DeepSeek, Genspark, Canva, and Gamma. Each tool offers its own design philosophy and use case — ChatGPT excels at conversational Q&A and idea generation; Gemini demonstrates refined information processing capabilities. The appeal of these tools is undeniable. However, most of these advanced tools are set to automatically incorporate user input as training data unless the user actively changes the settings.
One type of real corporate case involves a company that used AI to check internal program code and business materials. Due to overlooked settings, there was a risk that confidential information would be incorporated directly as training data, and the possibility of information leakage was flagged. In another demonstration scenario, a fictional company name was entered multiple times, and the result was that "curry" appeared as a signature menu item of the fictional "Anpanman Store" in subsequent AI responses. These cases illustrate how even small amounts of user-entered information can have far-reaching effects — they must be recognized as real problems that cannot be ignored.
The process for changing settings also differs from tool to tool, which means users frequently continue using default settings without making the necessary changes. For example, with ChatGPT, turning off "Data Controls" in the account settings menu will prevent information from being learned — but this setting item is not easily found, and many users overlook it even though it can be changed in the smartphone app. With Gemini, similarly, users must go through "Activity" settings to turn off data transmission. With Perplexity, AI data retention must be turned off as well; otherwise, the default is for information to be used in training. Claude was originally set to "off" for data training, but a 2025 terms of service change set "Help improve Claude" to "on" by default; this can be turned off from Privacy settings. For individual AI agent users on personal Microsoft accounts, "Model training" is on by default and can be turned off from Privacy settings (enterprise users on Microsoft 365 Business, for example, have data training off by default).
The key points about these tools defaulting to training-on can be summarized as follows:
- Most major AI tools are in a data-training-on state after initial registration, and will remain that way unless the user actively changes settings.
- Once information has been learned, it can not only be reflected in future responses but can in some cases lead to unintended data leakage or misuse by third parties.
- While changing settings is technically straightforward, the settings items are often unclear, and many users end up using tools in their initial state — making careful attention necessary.
For a more concrete sense of these risks: ChatGPT users who routinely enter personal information (name, hobbies, parts of emails, etc.) could find that this information is reused in interactions with other users. For example, someone's "friend's name" entered as input might later appear as a candidate name in a response to a different question — the risk of personal information inadvertently spreading broadly is real.
Additionally, Grok (X's AI agent) has had reports of information leaks, and data training is on by default. Turning off "Improve the model" in the settings screen can prevent data from being sent. DeepSeek is an AI service from a Chinese company; entered information is managed on servers in China. Even if training settings are turned off, Chinese law allows authorities to view data — making it a service that requires particularly careful handling.
Three Key Points for Using AI with Confidence — How to Check Settings and Prevent Data Leaks
We've explained in detail how each AI tool uses personal and confidential information as training data by default. Now let's look at specific measures and approaches to security improvement for avoiding these risks and using AI more intelligently.
Many AI tools, if used with default settings, will incorporate input data as training data. Given these risks, here are practical protective measures to take. Note that as new AI tools and updates add or change setting options, reviewing your settings once and never again is not enough — periodic review is key to reducing risk.
Smart AI use first requires risk assessment based on your usage context. Casual conversation and general inquiries may not cause major problems even with some risk of information leakage. But for business use — particularly when corporate confidential information or detailed personal privacy data is involved — the potential for unforeseen problems grows significantly. Against these risks, the following measures are recommended:
- Before using any tool, always check the settings related to "training data" or "data retention," and opt out where appropriate.
- For AI tool use within a company or organization, provide thorough information security training to employees, making clear what types of information should not be entered.
Implementing these measures enables individuals and companies to minimize the risks of AI use as much as possible and build an environment where AI tools can be used with greater confidence. On the provider side as well, there is an obligation to work toward improving the clarity and safety of settings so that users can use services with peace of mind — through improved UI, clear guidelines, and thorough explanation at the time of sign-up about how user data will be handled.
Risk management procedures in the event of data leakage are also essential. Tool providers must have security measures and rapid response procedures in place in advance and must fulfill their accountability to users. At the same time, users are encouraged to develop the habit of regularly checking security update information and confirming that necessary measures have been implemented. These efforts are critically important for establishing a more robust security environment as AI technology continues to evolve.
At the enterprise level, establishing internal AI usage policies, conducting employee training, and building organization-wide information security reinforcement measures are all required. These efforts extend beyond mere tool usage — they lead to the establishment of technology evolution and risk management frameworks for the future.
Summary: Building "Data Defense" Capabilities to Thrive in the AI Era
The first thing to understand is that most AI tools themselves have no malicious intent. Developers aim to analyze vast amounts of data to make AI smarter — and that in itself is a sound technical process. The problem is users operating the tools without understanding how they work.
With the rapid evolution of AI technology, our daily lives and work are becoming dramatically more efficient, with expanding possibilities. At the same time, the reality that many tools default to "data training on" carries the significant risk of unintended information leakage and improper handling of personal information. As explained throughout this article, tools including ChatGPT, Gemini, Perplexity, Claude, AI agents, Grok, DeepSeek, Genspark, Canva, and Gamma are all set to automatically incorporate input data as training data in their default states — meaning ordinary, casual inputs could potentially be misused as personal information or corporate confidential information.
As a user, the most basic and important measure is to always check each tool's settings and, where necessary, follow the opt-out procedure. The posture of constantly being aware of what data you are entering and how it is handled is essential — and education and information sharing to support this should be thoroughly implemented both inside and outside organizations. Additionally, individual users are encouraged to develop self-defense awareness: avoid casually entering private emails, social media content, images, and other highly sensitive information into AI tools. For enterprises, using dedicated corporate services or tools with safety measures pre-configured in their settings can substantially reduce the risk of information leakage. Presentation-creation AI tools like Gamma similarly require settings verification.
As described, using AI intelligently requires individual users to exercise greater care and be mindful of the following points:
- Check the default settings of each AI tool and understand the risk of unintended data training.
- Assess risk by usage context for each piece of information, and avoid carelessly entering personal information or corporate confidential information.
- Regularly check update information from tool providers and implement the latest security measures.
AI technology, precisely because of its enormous potential, brings us immense convenience alongside vulnerability. We must therefore heighten our self-defense awareness while also pressing tool providers to offer users easily understandable guidelines and clear procedures for changing settings. As increasingly advanced technology emerges and more data is utilized, we must constantly face the accompanying risks while working to build an environment where AI tools can be used safely and with confidence.
In summary, for safe tool use in the AI era, the keys are: checking settings, conducting regular risk assessments, and raising information security awareness. Each of us acquiring the right knowledge and taking the right measures to protect our own information, and working toward building an environment where the benefits of AI can be maximized, is the first step toward a secure digital society for the future. New risks will inevitably continue to emerge, but responding to each with accurate knowledge and swift action will enable ever safer AI use.
Reference: https://www.youtube.com/watch?v=Hg1cMstxJ9M
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