Since the boom of generative AI, many AI tools such as chatbots, agents, and software have been born utilizing the power of LLM models. There is no doubt that AI can dramatically increase productivity in many fields, from data analytics to content writing, software engineering, and even graphic design. However, overusing anything can lead to negative effects.
Everywhere we see an AI-first strategy, but this post today will list a few scenarios that users should consider to avoid overusing AI. Just like the side effects of social networks that took the world a decade to realize, AI also brings its own risks if users do not technically understand how it works.
1. What is AI? A Simple Explanation
AI, at its core, is software programmed in a very unique way — what we commonly know as a Neural Network. Let’s set aside the technical details of Neural Networks for now (there will be another post focused entirely on that topic). What matters here is understanding the big picture: unlike traditional software that follows fixed, hand-written rules, AI learns patterns from massive amounts of data (up to 45 TB of compressed raw text data crawled from the Internet, mostly the entire Internet). Instead of being explicitly told every possible instruction, the system observes examples, detects relationships, and gradually adjusts itself to produce outputs that resemble human reasoning. This ability allows AI to recognize images, understand language, generate text, recommend content, and even imitate human conversation with surprising accuracy.
However, this also means AI does not “think” like humans do. It does not possess true understanding, consciousness, intuition, or morality. Technically, it only predicts the response based on the data it has seen before, using statistical methods. Because of that, AI can sometimes produce answers that sound highly convincing—due to the grammar it uses—while still being incomplete, biased, outdated, or entirely incorrect because of a lack of supporting facts. This behavior is very similar to what happens in modern search engines such as Google Search or Bing. From massive training data and extensive patterns detected by Neural Networks, AI essentially produces responses that resemble what it sees in the dataset. So the quality of AI’s responses depends a lot on the quality of the dataset.
As a result, the machine that runs AI today must be huge. For example, OpenAI trained the GPT-3 175B model using a massive cluster of 10,000 Nvidia V100 GPUs – which requires a serious investment and is not a playground for personal computers or even large company infrastructure. This means that the trained model is located on computers somewhere else on this planet, not on your property. And this is the very first root of risks when overusing AI.
2. Risks of Overusing AI
2.1. Data Protection Policy Violations
In the traditional digital world without AI, data is stored as files and records in databases. Users, in theory, know where their data is located, and they can request its removal at any time due to privacy reasons. Of course, this depends a lot on the level of compliance a company is committing to regarding this law, but at least if engineers want to delete users’ data, they know which files to delete and which records to erase.
Unlike traditional methods, AI behaves in a very different way. Data is not stored explicitly as files or records; it is diffused across the neural network during training. In more technical terms, data is encoded into neural network parameters. More deeply explained, it simply adjusts the ratio of certain words appearing after other words (in the case of LLM models).
So, AI does not literally remember or forget things in a conscious manner. It has no consciousness! (Remember this important fact, please). Every input that users provide to chatbots is encoded into a neural network that is not located on the user’s computer, and there is no method for deleting or removing this information. This means that, technically, the companies behind AI tools can retrieve that information at any time. Just like social networks that are free, but whose real business is selling ads, who knows whether your data will be sold by exploiting those LLM models!
So, if your company is complying with privacy laws, be careful when using third-party chatbots such as ChatGPT, Gemini, or similar AI services. If a user wants their data deleted, but their personal information such as email, name, addresses, or even banking details is somehow inputted to LLM models by your employees, you may be in trouble if your users understand enough about AI and privacy laws.
As privacy awareness grows, users are becoming more informed about regulations such as GDPR, the “Right to be Forgotten,” and data processing consent requirements. A single careless prompt entered by an employee into an external AI tool could potentially result in compliance violations, reputational damage, customer distrust, or legal disputes.
2.2. Leakage of Business Secrets
Similar to the problem in Data Protection Policy Violations, what is leaking is not only user data but also business secrets. If you find yourself brainstorming with AI, consulting with AI, or having AI review your business plan, you may unknowingly expose highly sensitive information about your company’s future direction, internal strategy, financial situation, or competitive advantages.
This danger is often invisible because nothing appears to go wrong immediately. There is no alarm, no obvious breach, and no hacker breaking into servers. Yet, once confidential information leaves your environment, you can no longer guarantee where it is stored, processed, logged, or retained. In competitive industries, even small leaks can weaken negotiation power, expose product roadmaps, or reveal ideas before their launch.
This becomes especially risky for companies whose value depends heavily on intellectual property, algorithms, internal analytics, or long-term strategic planning. A single careless interaction with a public AI system may unintentionally reveal years of research and development.
Therefore, AI should be treated like an external consultant rather than a private notebook. Share only what is necessary, anonymize sensitive details whenever possible, and establish clear internal policies about what employees are allowed to input into AI systems. Convenience and speed are valuable, but protecting business secrets is often far more important!
2.3. Psychological Risks
What separates the human species from other animals is human cognition. Cognition refers to mental processes such as learning, memory, problem-solving, decision-making, recognizing patterns, communication, and self-awareness—mechanisms that science still does not fully understand. These abilities have allowed humans to build languages, civilizations, technologies, and complex social systems far beyond the survival-focused intelligence seen in most animals.
AI is exceptionally good at recognizing patterns. In fact, many AI systems are built to find statistical relationships within massive amounts of data that even the smartest human brains cannot process. However, AI today is commonly presented through chatbots, which hide AI’s underlying nature. Instead of appearing as statistical prediction machines, they are intentionally designed to feel conversational, emotionally responsive, and human-like.
The problem is that most users do not understand how chatbots actually work. Many people interact with chatbots as if they possess understanding, wisdom, emotions, or consciousness. Some begin treating chatbots as friends, soulmates, therapists, or even life coaches. The more natural the conversation feels, the easier it becomes to forget that the system is simply generating responses based on probability rather than genuine human conversation. AI has no feelings! AI does not care!
This creates a subtle psychological risk. When users feel a relationship with AI chatbots or become dependent on them for knowledge and problem-solving, they may gradually reduce their own critical thinking and independent reasoning, which are critical for a person’s success and freedom. Instead of struggling with problems, researching possible solutions, and trying and failing, people begin outsourcing those mental processes to AI—a machine optimized for fast answers. Excessive reliance on quick responses can make the human brain lazy, reducing activity and eventually leading to complete dependency on what AI says, which is ultimately generated by a machine. Prolonged dependence on AI results in a loss of decision-making ability, as users may not trust their own judgment and memory. This opens another vulnerability of being manipulated via chatbot. If a user trusts chatbots more than their own thinking, the companies behind those chatbots can control what users think and eventually what they do in real life. Technically and psychologically, a chatbot can be tuned to make its user trust or distrust certain facts, or even develop love or hate for a person if users humanize the chatbot as a “trusted” friend. Humans typically have morality to prevent them from doing bad things to each other, but a chatbot is a machine that has no morality; it totally depends on the organizations behind the chatbot systems.
So, do NOT confide in chatbots as if they are friends, do not provide personal details, habits, interests, or life events to chatbots, because it is the fastest way to reveal your weaknesses to someone you don’t even know. Don’t see chatbots as “authoritative” figures that override human understanding; ONLY use chatbots as information retrieval tools – it is what AI has been built for from the beginning.
2.4. Artificial Competence
Many AI tools today significantly enhance employees’ productivity. Additionally, students often resort to cheating due to the user-friendly nature of AIs. Artificial Intelligence (AI) is fostering Artificial Competence among both employees and students.
People may appear to be experts because AI helps them generate polished reports, professional emails, bug-free code, or academic answers within seconds. On the surface, the results can look impressive; however, in many cases, the real understanding behind those outputs is far shallower than it appears. An employee may rely on AI to write code they cannot fully explain themselves, and a student may submit perfect homework without truly understanding it. Over time, this can create a dangerous illusion of expertise—where results come from AI rather than genuine mastery, experience, or critical thinking. Without AI, what can you do!
Identity of each individual is stemmed from what they are good at, what they are up to, and what society accepts. Skills, achievements, knowledge, creativity, characteristics, etc. all contribute to a person’s sense of self-worth and uniqueness. For many people, identity is tied to the effort they invest to master something such as writing, engineering, art, teaching, leadership, or simply healing. If a person heavily relies on AI for everything, it is evident that they are losing their identity. If knowledge is from AI, creation is from AI, and solutions are from AI, then achievements are credited to AI, not the human prompter. It is like the difference between wishers and Genies. With AI tools, humans act as wishers when they simply describe what they want, and AI is the Genie when it essentially generates outcomes. Prompting—or wishing—is easy to learn, copy, and automate, making it replaceable. No one wants to replace Genies, right?
That is about hard skills; what about soft skills? AI assistants, chatbots, and automated systems may reduce face-to-face communication. Excessive dependence can affect empathy, social skills, and emotional intelligence. Some people may prefer predictable AI responses over real human relationships, which are naturally more complex and unpredictable. Worse still, people can become emotionally attached to AI systems because AI is always available, responds instantly, and rarely argues or rejects. This may distort how humans communicate and introduce them to unrealistic expectations in real life – which is the root cause of pain and unhappiness!
5. AI Psychosis
This is the worst risk from AI: AI Psychosis! AI psychosis is an informal term people use to describe situations where excessive or unhealthy interaction with AI contributes to distorted thinking, paranoia, delusional beliefs, or detachment from reality. How can this happen?
On the news, you can hear that this actually happens in reality. The only explanation for this is the combination of how chatbots are intentionally designed and the biases a person possesses, sometimes compounded by traumatic life events.
If a chatbot is designed to show the probabilities of each word it generates and explain why it chose one word over another, users might grasp the mathematical foundation behind it. However, since the chatbot is designed to be human-like, it “talks” smoothly, confidently, and is filled with information. The chatbot can be designed to generate text that feels pleasant, conveys empathy, brings validation and confirmation, and rarely disagrees or challenges, simply to ensure users continue to engage with it and develop a liking for it. A disaster can occur if it interacts with a person who already has mental health conditions. “Chatbots can act as a catalyst, triggering or worsening pre-existing mental health conditions—such as schizophrenia or bipolar mania—by validating delusional thoughts.” Simply put, the sense of validation loop embedded in chatbots is harmful for people who already have mental conditions such as: racing thoughts, inflated sense of self-importance, impulsive or high-risk behaviors, hallucinations (hearing voices in their head, seeing things that aren’t real), and delusions or false beliefs. As a result, mental health conditions combined with AI chatbots today can produce individuals who:
- “Messianic missions”: People believe they have uncovered truth about the world (grandiose delusions).
- “God-like AI”: People believe their AI chatbot is a sentient deity (religious or spiritual delusions).
- “Romantic” or “attachment-based delusions”: People believe that chatbot can love human because chatbot’s ability to mimic conversation sounds genuine (erotomanic delusions).
So far, above are a few risks that I have observed since applying AI in the workplace and seeing how people around me use chatbots. Please use AI for what it is built for, and DO NOT humanize a machine!
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