Initially, when AI tools and ChatGPT came out, they were appreciated and applauded for how they have made our lives easier. They were used blindly everywhere; from developers to writers, doctors to students; in short everyone relied on them for their tasks.
But with time, when we started getting familiar with these tools, we came to know that they can’t be trusted every time, especially in the tasks where we are not experts and we cannot identify the errors by ourselves. It does not mean they are not helpful. But being helpful never means always being trustworthy.
As a writer, many times I depend on these tools but I have learned how to use them wisely and where it is very important to verify the information or tasks done by AI.
Now, the question is how I came to know that something is fishy with information my AI tool is giving me.
Actually, I was working on a research article and for that purpose I wanted references from the related articles. Suppose my research topic was, “How semaglutide helps in weight loss?”.
I asked my tool to give me information from authentic scientific journals about the research experiments that involve some pilot testing of semaglutide as weight loss drug. My tool very confidently generated fabricated information about pilot tests which were never done and gave me names of scientists with universities and links to some articles. When I cross checked those links, I came to know that no such scientists and research ever existed and the links were also misleading and referred me to some other totally unrelated articles.
Initially, that was a shock but from that onward I never trusted AI especially for the things I know least about and I can’t identify by myself whether information given by a tool is right or wrong.
In this blog, I will guide you how to use AI wisely and when to trust AI and when not!
What Does Trusting AI Blindly Means?
Trusting AI blindly means believing its replies without questioning and cross checking facts. People often copy-paste AI’s content because the answers sound very confident but they ignore the fact that AI predicts answers based on the patterns it has learned from data.
While using AI, we have to keep it in mind that confidence never corresponds to truthfulness because confidence often tricks users into believing the answer is correct, even when it may be incomplete, outdated, or wrong.
One more thing, there is a difference between using AI and depending on AI. AI can only act as your assistant but it can’t take over your whole responsibility. You can use it wisely but cannot depend on it to make decisions or provide final answers without review, especially in important situations.
Read about Knowledge Grounded AI!
What Are the Technical Reasons AI Generates Fabricated Information?
AI does not have a brain but a knowledge base on which it is trained. If the knowledge base is outdated and contains false information then obviously the outcome and responses will be false and fabricated too.
There are many technical reasons behind fabrication. Let’s go through some of them!
1. AI Hallucination
AI hallucination is a situation in which AI produces information that sounds confident and plausible but is factually incorrect and ungrounded.
AI may hallucinates because:
- These models are trained on large datasets. They are designed on pattern based prediction. This means that if they don’t have enough information they simply guess to fill the gaps and these gaps can be very wrong because they prioritize fluency and coherence over factual accuracy
- AI models don’t know how to say NO. Therefore, when they don’t have information they just create it.
2. Data Poisoning
Data poisoning happens when the training data contains malicious information and the model is intentionally or unintentionally trained with tempered data. It is very contagious because even a small data can infect the whole model as it learns the wrong pattern.
Poisoning happens due to deliberate manipulation by attackers who injects false training datasets. Or many AI systems use third-party or crowd-sourced data for training. If these sources are compromised, the model can be affected during training.
3. Lack of Real-World Understanding
In the real world, things are far away from perfection and idealism. Many problems occur unexpectedly, and decisions often depend on background, timing, and surroundings and answers to many things change when the context or the background changes.
Whereas AI relies on the same learned pattern for replies and has no real world understanding. In such cases, answers no longer fit the situation and definitely become falsified.
4. Ambiguous or Poorly Worded Prompts
For output, AI models totally rely on the information you provide them as a prompt. If your input is vague, unclear, and does not provide enough instruction for the task, AI’s output can be vague and not aligned with goals you have set in your mind.
5. Confidence Calibration Issues
AI systems struggle to accurately express how sure they are about the answer. Therefore low-confidence answers also seem high-confidence and accurate. But in reality, they are non-factual and readers assume them certain because of their confident tone. This mismatch is especially dangerous in high-stakes topics.
Common Situations Where Blind Trust in AI Is Risky
There are some situations where depending merely on AI can create a life and death situation. In these situations, you have to be very wise and use AI with caution.
1. Medical Advice
AI is being used in the field of medicine for predicting diseases and ailments based on symptoms but trusting them blindly can be very dangerous because sometimes these systems may not fully understand the complexity of patient symptoms, medical history, drug interactions, or nuanced diagnoses. And as a result, they can make incorrect diagnoses or inappropriate care decisions.
2. Financial Decisions
Financial markets depend on human behavior, regulations, politics, and unexpected events. These situations are not understood by AI truly. And if in finance, you follow AI recommendations without using your own or experts’ logics, you might end up in loss.
3. Legal Information
Legal systems are highly precise, with specific citations, statutes, and precedents. AI sometimes invents legal references instead of verifying facts. In real legal settings AI-generated court filings
4. Safety-Critical Decisions
AI is used in many safety systems. But when AI misinterprets a situation, the consequences can be serious. For example, an AI security system once flagged a student’s clarinet as a weapon, triggering a school lockdown before humans reviewed the alert.
In safety-critical environments, AI errors can lead to false alarms, missed threats, or unsafe actions. That’s why human cross-checking is essential.
When AI Is Safe and Useful to Trust (Balanced View)
Everything has its pros and cons, so does AI have them too. AI is not always unreliable; rather you can use it beneficially and wisely for many purposes. Let’s see when these models are very useful and ease your burden!
1. Writing Drafts and Initial Content
You can use AI to prepare draft for your articles and blogs but do not use draft as it is for publication. Only use AI to outline main points, suggest structure, and overcome writer’s block. Moreover, make it your practice to always review, edit, and fact-check any AI-generated draft.
2. Summarizing Information
AI is very good at automatic summarization especially when you have short of time and you want to grasp key ideas from articles, reports, or research papers without reading everything in full.
3. Brainstorming Ideas
Just before initiating writing, it can help you in brainstorming ideas by suggesting topics, angles, examples, and alternate perspectives. This makes it especially helpful in academic research, marketing, and creative writing.
4. Automating Repetitive Tasks
AI is excellent in doing repetitive tasks which require human energy but not creativity. For example, answering daily routine questions in call centers like how to change passwords, How to check account details, etc. Organizations can use AI to take over repetitive tasks and leave the creative and judgement based part to humans. This can not only reduce the burden of employees but increase efficiency and effectiveness, too.
How to Use AI Wisely
First of all you have to keep it in mind that AI models are your assistants and you cannot rely merely on them for your tasks. You can use it wisely by taking advantage of its strengths and keeping in mind its limitations.
1. Always Verify Important Information
AI depends on its training and knowledge base for its output. Sometimes, it produces inaccurate responses because of inadequate information because AI fills the gaps with prediction. Moreover outdated information may be due to old dataset used in training. So, it’s really very important to double-check an AI answer against trusted, credible sources such as official websites, peer-reviewed research, or expert publications.
2. Use AI for Suggestions, Not for Final Decisions
Consider AI content as a suggestion rather than basing your whole decision over given content. Always review and refine AI outputs before using them, especially in high-impact areas like legal, financial, or medical topics.
3. Keep Humans in the Loop
Many ethical AI guidelines recommend human oversight for any AI output that affects decisions with real consequences. This ensures accountability and prevents harmful consequences from automated errors.
FAQs about Why you Should not Trust AI Blindly
1. Is AI always accurate?
Never, AI is not always correct. It sometimes gives outdated information and sometimes it totally makes up information to fill in the gaps. Despite outdated and inaccurate content, AI presents it in an authoritative and very clear way that people consider it as accurate without cross-checking it.
2. Why does AI give wrong answers?
There are many reasons behind AI giving wrong answers. Sometimes, the data that was used to train AI models is outdated or inaccurate. Other times, it makes up completely fabricated information in order to fill in the gaps where information is unavailable because they are made on predictive design. AI cannot show how accurate the reply is, it always presents its answers confidently to make people think that nothing can be more true than this information.
3. Can AI be trusted for important decisions?
For important decisions especially in fields like healthcare, finance, law, or safety; AI cannot be trusted. They can only be used for suggestions and as support tools or assistants but not as a decision-maker. Otherwise many mishaps can happen because AI cannot understand the context and has no real world experience.
4. Does AI understand what it says?
No, AI does not truly understand what it says. It does not have awareness, emotions, or real-world understanding. AI produces responses based on how words usually appear together, which can make answers sound intelligent without genuine comprehension.
5. Will AI replace human decision making?
AI is only a part of the support team, it can act as assistant in your tasks but not as a decision maker. Human cognition and thought process is totally different and based on context and real world experiences. AI can suggest and help you in making decisions but it can’t take over human thought processes completely.