5 Potential Dangers When You Provide Personal Information to AI Chatbots

There is no doubt that AI is revolutionizing the world. The explosion of large language models (LLMs), especially since the launch of OpenAI’s ChatGPT in late 2022, has made AI a familiar tool for hundreds of millions of users.

Thanks to its ability to support, suggest and even accompany in many situations, AI chatbots are quickly being used not only to search for information or work, but also as a "companion".

More and more people are sharing intimate aspects of their lives with AI, including sensitive data. But like social media, revealing too much information can have unintended consequences. Here are five reasons to be cautious.

1. Data leaks pose a threat to security

Data breaches are not only a technological risk but also a direct threat to personal privacy and safety. In fact, cybersecurity is becoming one of the fastest growing areas of the digital economy, as the damage is becoming more and more serious.

According to the US Federal Bureau of Investigation (FBI), cybercrime alone caused more than $16 billion in losses in 2024, up 33% from the previous year. Online fraud and personal data breaches were among the three most common types of crime.

Worryingly, only about 24% of generative AI initiatives are fully protected against cyberattacks, putting users at high risk if they share information too freely.

In fact, there have been many data breaches, such as ChatGPT, which was involved in a data breach in May 2023, exposing sensitive information of nearly 100,000 users and forcing the platform to temporarily suspend operations.

That same year, a group of reporters from The New York Times discovered that their personal information had been exposed during a test. These incidents are a stark reminder that sending personally identifiable data to AI chatbots is never a safe option.

2. Deepfakes could become a tool for impersonation scams

Sharing personal information with AI tools not only increases the risk of data breaches, but also opens up a more sophisticated threat: deepfake fraud. Many people today regularly upload their photos to AI-based editing services, from beautifying them to creating entirely new images, with little thought to the consequences.

That convenience inadvertently provides raw material for bad guys to create deepfakes, digitally manipulated images or videos that make a character appear to do or say something that never happened.

This technology is increasingly difficult to detect, capable of fooling both regular users and basic authentication systems. As a result, cybercriminals can easily exploit it to impersonate, commit fraud, blackmail, or seriously damage personal reputations.

While deepfakes built entirely from personally identifiable data are still rare, the ability to recreate vivid voices and images from leaked data has become an existential threat. This is especially dangerous when users’ private data falls into the wrong hands, creating opportunities for increasingly difficult-to-control fraud.

3. AI chatbots remember more than you think

One of the unwritten rules of the digital age is that “the internet never forgets.” This applies not only to Google searches and social media posts, but also to conversations with AI chatbots.

Many people believe that when they press “delete,” their data is gone forever. But the reality is more complicated. For example, OpenAI says that ChatGPT conversations are only “hard-deleted” from the system within 30 days if a user deletes their entire account. For those who continue to use it, specific conversations cannot be permanently removed from history.

A study from the University of North Carolina (USA) shows that deleting data from large language models is possible, but almost impossible to verify with certainty. This means that chatbots are capable of remembering more than users realize.

When personal information is stored long-term, the risks increase significantly in the event of a data breach, targeted cyberattack, or simply a change in policy from the service provider. And in such scenarios, the consequences for users can be dire.

4. Providing data for AI chatbots to learn from can infringe on your intellectual property rights

Modern AI systems are powered by machine learning algorithms that rely on millions of data sets to find patterns and generate appropriate responses. It is important to note that this learning process does not stop once the AI ​​is deployed, and user data during conversations, interactions, and content uploads can become “raw material” for the model to continue to improve.

That means that any information you provide, even if unintentionally, is potentially being used to train AI. In late 2024, social network LinkedIn faced a wave of criticism when it admitted to using user data to train its AI tools. After a backlash, the company was forced to add an opt-out option, but in reality, few people know about it or actively change it.

LinkedIn is no exception. Meta also mines data from Facebook and Instagram, while Amazon uses conversations with Alexa to develop its models. The consequences can lead to serious intellectual property violations, with AI-generated works sometimes bearing too much of the personal imprint of writers and artists, putting them at risk of being “copied” right on the digital platform. This is the cause of many class-action lawsuits and a wave of protests from the creative community.

5. AI Chatbots Can Use Your Personal Information Against You

The risks of sharing personal data with AI go beyond intellectual property infringement to the potential for bias in large language models. Because they are trained on large volumes of data, these tools are susceptible to absorbing social biases, leading to discriminatory decisions or recommendations.

Georgetown University's Center on Privacy and Technology estimates that half of all adults in the United States have photos in law enforcement's facial recognition databases.

At the same time, African Americans make up nearly 40 percent of the incarcerated population. When this data is fed into AI systems, algorithms are more likely to make mistakes in identifying suspects, or matching a face to a text or image description.

The risks are not limited to security, AI technology is also applied to screening job candidates, approving loans or renting houses, and can completely reflect hidden biases.

Amazon was forced to stop its automated recruiting system in 2015 after discovering gender bias. This shows that while it is difficult for individuals to control the data that trains AI, being cautious about sharing information is still a necessary way to protect against technological bias./.