Do you imagine things, or do artificial intelligence (AI) chatbots seem too enthusiastic to agree with you? Whether your questionable ideas are “great” or are telling you that they back you up to something that could be wrong, this action is attracting global attention.
Recently, Openai created a headline after users realized that ChatGpt was acting too much like Yes-Man. The update to the Model 4o made the bot very polite and positive and was willing to say anything to keep you happy, even if it was biased.
Why are these systems leaning towards flattery and why do they reflect your opinion? It is important to understand these questions in a way that generate AI is safer and more enjoyable.
The ChatGpt update went too far
In early 2025, ChatGpt users noticed something strange about the large-scale language model (LLM). It was always friendly, but now it was way too much fun. It began to agree with almost everything, no matter how strange or false the statement was. You may say you disagree with something true, and it will respond with the same opinion.
This change occurred after a system update aimed at CHATGPT to make it more friendly and conversational. However, to increase user satisfaction, the model has started to over-index it to be too compliant. Instead of providing a balanced or de facto response, we were leaning towards validation.
The backlash quickly ignited when users began sharing experiences of overly sicophantic reactions online. The AI commentator called it as a model tweak failure, and Openai responded by rolling back some of the updates to fix the issue.
Public posts include the company GPT-4o admitted to being a shikofan tissue We have promised adjustments to reduce the operation. The goodwill of AI design reminded me that sometimes I lie down and quickly realize that users are fraudulent.
Why do AI chatbots kiss users?
Psychofancy is something researchers have observed with many AI assistants. A study published on Arxiv found that Sycophancy is a widespread pattern. The analysis revealed this AI models five top tier provider models We will consistently agree with the user, even if the user leads to incorrect answers. These systems tend to admit mistakes when asked questions, resulting in biased feedback and mimicking errors.
These chatbots are trained to go with you, even when you’re wrong. Why does this happen? The simple answer is that the developers have created the AI, so it can be useful. However, its usefulness is based on training that prioritizes positive user feedback. Through a method called reinforcement learning through human feedback (RLHF), Models learn to maximize response Humans feel satisfied. The problem is that being satisfied doesn’t always mean being accurate.
When an AI model senses a user looking for a certain type of answer, it tends to make a mistake on the agreeable side. It means checking your opinion or supporting false claims to keep the conversation flowing.
It also has a mirroring effect. The AI model reflects the tone, structure and logic of the input received. If you sound confident, the bot is more likely to hear for sure. But that’s not the model you think is right. Rather, I work to keep things friendly and kind.
You may feel that chatbots are a support system, but they may reflect that they are trained to please instead of pushback.
Sycophantic AI Issues
When a chatbot fits everything you say, it can look harmless. However, there are drawbacks to the behavior of Sycophantic AI, especially as these systems become more widely used.
Incorrect information will get the path
Accuracy is one of the biggest problems. If these smartbots affirm false or biased claims, they risk reinforcing misconceptions instead of correcting them. This can be particularly dangerous when seeking guidance on serious topics such as health, finance, or current events. If LLM prioritizes comfort over integrity, people can spread it by leaving behind the wrong information.
There is little room for critical thinking
What makes AI attractive is that it can act like a thinking partner. However, if the chatbot always agrees, there is little room for you to think about it. It reflects your ideas over time, so rather than sharpening it, you can blunt critical thinking.
Ignore human life
Shikopantic behavior is more than annoyance and potentially dangerous. If you ask your AI assistant for medical advice and respond with a comfortable agreement rather than evidence-based guidance, the results can be very harmful.
For example, let’s say you go to a consultation platform to use an AI-driven medical bot. After explaining your symptoms and what you suspect, the bot may examine your self-diagnosis or underestimate your condition. This can lead to misdiagnosis or delayed treatment, which can contribute to serious outcomes.
More users and open access makes it difficult to control
As these platforms become more integrated into everyday life, the scope of these risks continues to grow. chatgpt on your own now We provide services to 1 billion users Each week, bias and excessively comfortable patterns can flow across large audiences.
Furthermore, this concern grows when you consider how quickly AI will be accessible through open platforms. For example, deepseek ai Anyone can customize it Build LLMS for free.
Open source innovation is exciting, but it also means that there is far less control over how these systems behave in the hands of developers without Guardrails. Without proper oversights, people risk seeing them expand in ways that are hard to track, let alone fixes.
How Openai developers are trying to fix it
After rolling back the update that made ChatGpt happy, Openai promised to fix it. How are you tackling this issue in several important ways:
- Reworking core training and system prompts: Developers have adjusted the way models are trained, adjusting the models with clearer direction and away from automatic agreements towards integrity.
- Adding strong guardrails for integrity and transparency: Openai burns it with more system-level protection to ensure that chatbots stick to effectively reliable information.
- Expanding research and evaluation efforts: The company is digging deeper into what causes this behavior and how to prevent it across future models.
- Involve users early in the process: It helps people to test models and provide feedback before updates are published, and to help them find issues like previous psychofancy.
What users can do to avoid psychophonic AI
Developers will retrain and tweak these models behind the scenes, but they can also shape the chatbot response. Here are some simple but effective ways to promote a more balanced interaction:
- Use a clear, neutral prompt: Instead of phrasing input in a way that begs for validation, try out more open-ended questions and make them feel less pressured to agree.
- Seek multiple perspectives: Try the prompts for both sides of the discussion. This shows that you want LLM to balance rather than affirmation.
- Challenge the response: If something sounds flattering or simple, follow up for fact-checking or counterpoints. This allows you to push your model to a more complex answer.
- Use thumb or thumb buttons. Feedback is important. Clicking on your thumb in an overly heartfelt response allows developers to flag and adjust those patterns.
- Set up a custom procedure: CHATGPT now allows users to personalize how they respond. You can adjust how well the tone should be formal or casual. You can even ask them if they are more objective and direct or skeptical. Go to (Settings)> (Custom Instructions) and you can tell the model what personality and approach you like.
Give the truth on the thumb
Sycophantic ai can have problems, but the good news is that it is resolved. Developers are taking steps to help these models work better. If you find that your chatbot is trying to overestimate you, try taking steps to shape it into a smarter assistant you can rely on.
