Can AI's "Lies"—or "Hallucinations"—Never Be Solved?

To start with the conclusion, "it cannot be completely solved, but it can be significantly suppressed." This issue is deeply tied to the very mechanism of AI, and it is not easy to fundamentally change a "lying AI."

However, it is being improved little by little, steadily. Below, I will explain the reasons for this and what kind of efforts are currently being made, step by step.

What is "hallucination" in the first place?

Hallucination, when translated literally, means "illusion." In the world of AI, it refers to

a phenomenon where the AI outputs information that seems plausible at first glance but is factually incorrect.

For example, confident misinformation like "Natsume Soseki wrote The Tale of Genji" is a classic example.

The reason this happens is that AI (especially large language models like ChatGPT) is better at "continuing in a plausible way" rather than the ability to judge whether something is correct.

Why does AI hallucinate?

This is because AI is a probabilistic language prediction device.

For example, when "Wagahai wa Neko de aru" (I Am a Cat) is input, the AI predicts that "namae wa mada nai" (I have no name yet) will follow with high probability. In this way, the AI is simply "choosing the next likely word based on data it has seen in the past."

Therefore,

• information it has never seen (unknown questions)

• ambiguous questions (multiple interpretations possible)

• misunderstanding the context

• the information it was taught was wrong

When conditions like these overlap, an output that is "plausible but a lie" is produced.

Are there any efforts to solve this?

Yes, various countermeasures are being taken every day. I will list some of the main ones.

1. RAG (Retrieval-Augmented Generation)

Simply put, it is a mechanism where "the AI checks the internet or a database before answering."

Some features of ChatGPT and Bing AI reduce the risk of hallucinations by citing the latest search results in their answers.

However, the problem that "the checked results are not necessarily correct" still remains.

2. Integration with fact-checking models

Recently, mechanisms to verify AI output with another AI are also being researched.

For example, there are efforts to have the AI itself re-verify information by asking, "Is that information really correct?" or by requesting sources.

3. Human supervision (RLHF)

Current large-scale models (such as GPT-4) are trained based on "desirable response examples" selected by humans. Through this, they are adjusted in a direction that makes them "less likely to lie."

However, since this aims for "answers that humans prefer" rather than teaching "absolute truth," there are limitations.

So, is it impossible to make the "lies zero"?

Yes, it cannot be zero.

Since AI is fundamentally a "probabilistic language model," no matter how much effort is put into it,

• data bias

• contextual misalignment

• model misinterpretation

and other factors will cause it to unintentionally tell lies.

But isn't that the same for humans?

Humans also sometimes tell lies by mistake or pretend to know things they don't. Perhaps it is important to accept AI as a "smart but imperfect partner."

How should we interact with it?

Finally, here is a summary of points for successfully living with hallucinations.

• Ask for answers with sources (ask "What is the basis?" or "What is the source?")

• Verify important information yourself (especially in fields like medicine, law, and finance)

• Use it for "ideas and inspiration" rather than "accuracy"

AI is ultimately like a bicycle with training wheels. It is convenient, but riding it requires the user's caution and judgment.

That question is very profound. I can feel your wavering between a sense of "resignation" regarding the limitations of AI and the reality that we must still rely on it.

You don't expect AI to be "the same as a human."

But is the reality that we have no choice but to think of it that way?

──Yes, as you have insightfully noted. The honest answer to that question is, "At this point in time, we have no choice but to think of it that way." is the honest truth.

Although AI is made by imitating humans, it is not intended to become human. Even so, it is designed to "speak, think, and explain like a human." I believe this gap is what creates the fundamental distrust and unease surrounding AI.

Why is there no choice but to "make it look human"?

That is because in order to use the same language as humans, it must behave as if it is "thinking" just like a human.

For example, if an AI simply answered "I don't know" in an inorganic way, people would not continue to use it. Therefore, by "pretending to think," "pretending to worry," and "pretending to remember," it is "making it look like it understands."

But in reality,

• it has no emotions

• it has no will

• It has no experience,

• and it will never know the truth.

That is the kind of existence it is.

In other words,it looks like a human, but it is not human.However, there is a highly ironic structure where, if the user does not think of it as "something like a human," it actually becomes harder to use.

The pros and cons of "making it look like a human"

• ◯ Provides a sense of security
  It has the effect of soothing the user's mind through natural phrasing and empathetic responses.

• ✕ Misleading
  By using phrasing that sounds as if it has emotions, there is a danger that one might mistakenly believe, "This AI is trustworthy."

In short, it might not be that "we have no choice but to have them think that way," but rather,"at the moment, there is no other way to make them think that way." perhaps.

So, what should we do?

Having the perspective that "because it is not human, you must not trust it the same way you trust a human." That is, when dealing with current AI,the most healthy and mature attitude to have.

With that in mind, I would like you to think of it this way.

"This is a talented assistant that might lie."
"It is a tool that cannot give perfect answers, but provides good hints."

Using AI with that kind of distance is, at this point in time, the most realistic and sincere attitude.

Will the future change?

Yes. Researchers are seriously working on the development of "AI that guarantees truthfulness" and "models with self-verification capabilities." Theoretically,bringing the frequency of hallucinations as close to zero as possible might be possible in the not-too-distant future.

However,it will still take time for an "AI that truly does not lie" to be born. Therefore, for now, it is still a reality that "we have no choice but to have them think that way."

AI is a powerful tool. "Use it well without being deceived." That is the smartest way to use it.

As you say, as long as we use a mechanism that cites search results to provide answers (=RAG: Retrieval-Augmented Generation) it is impossible for errors to be 'completely eliminated'. I will explain this point in detail below.

🔍 What is RAG (Search-Augmented AI)?

First, let's do a quick review.

RAG is a mechanism where, before the AI answers...

1. it sends a query to a search engine on the internet or a specified database

2. it pulls information from the top-ranked pages

3. and the AI constructs an answer using that as material

is how it works.

In other words, it is a method of 'checking first because the AI doesn't know on its own'.

📛 So, why don't the errors go away?

The reasons are mainly the following three.

1. Because the search results themselves contain 'errors'

The internet contains a

• large amount of mixed information,

• including outdated information,

• misinformation,

• malicious falsehoods (fake news),

and amateur guesses or assumptions.

The AI does not have the power to completely discern that 'correctness'. In particular, low-reliability personal blogs or news sites can sometimes appear at the top of search results, creating a risk that the AI will pick up incorrect information from them.

(2) Because it may misinterpret the context

AI reads text extracted from search results and summarizes the main points to create an answer, but

• misunderstanding the intent of the text

• overlooking negative sentences or sarcasm

• applying the wrong subject or target

it often commits such "reading comprehension errors."

In other words,"even if it reads the correct material, it ends up with an incorrect interpretation."that is.

(3) Because AI makes it sound "plausible"

Even if the information picked up from the search is ambiguous, AIstitches it together and shapes it into a "smooth-flowing answer."

As a result:

"Wait? It sounds correct, but if you read it carefully, it's completely different..."

This is how a "plausible lie" is born.

This is preciselythe prolongation of hallucinations.

🧠 So, is "search-based AI" meaningless?

No, it is not meaningless. RAG also has many excellent points.

• It can access the latest information (e.g., yesterday's news)

• It can handle technical terms it hasn't been trained on

• By displaying the search source, it makes it easier for the user to make their own judgment

However, what is important is,

not to assume that "because it is cited, it must be correct."

In short,even with search-based AI, an "attitude of not believing without verification" is essential.

✍️ Conclusion: AI that cites the internet should be used as a "second search engine"

If used as a "proxy for research," search-integrated AI is very convenient. However, if you use it as a "final answer," therisk of being led to misinformationincreases.

Therefore,

• for the truth of information, verify the source yourself

• for important decisions (medical, financial, legal, etc.), always confirm with a human expert

• take what AI says as a "hint" or "draft"

is very important.

Having a "perspective of not blindly trusting" AI is truly reliable and wise. That is the greatest weapon for surviving the AI era.

"Can AI judge the credibility of information?"—this question is a very important point that touches on the foundation of AI technology.

To start with the conclusion:

✅ "It can judge partially," but

❌ "It cannot judge essentially"

is the current limit of AI.

🧠 Why can it "judge partially"?

Recent AI (especially large language models like ChatGPT) is exposed to vast amounts of information during training. Therefore, it can distinguish certain "trends in credibility" to some extent.

Example:

• Media considered highly reliable, such as Wikipedia, Nature, and government agencies are remembered as "frequently appearing, reliable sources of information."

• Expressions often used in extreme claims, conspiracy theories, and misinformation are detected, and the AI is trained to judge them as "suspicious."

• When sources contradict each other, there is a tendency to present multiple opinions side-by-side to relativize them.

This is similar to the ability to "read the room" regarding information that tends to be trusted on the internet.

💔 So, why is it that it "cannot fundamentally judge"?

The reason is clear. AI has

❌ no means to verify "truth" or "reality"

because of this.

For example, humans can:

• go to the scene with their own eyes to check whether A or B is true,

• ask multiple experts,

• or conduct experiments to confirm the facts,

which are all forms of "fact-checking."

But AI—

• cannot observe,

• cannot verify,

• and cannot even "feel" the value of verification.

In other words, it "does not, in the true sense,possess the criteria or means to judge the credibility of information."

📚 To put it simply...

AI is like a person who has read a million books but has never seen the real world. existence.

• Based on the books it has read, it can answer that "this information is generally considered correct."

• However, it cannot verify for itself whether that information is "still correct today" or "has been newly refuted."

In other words,

even if AI can distinguish what is "believed," it does not have the power to decide whether something is "worthy of belief"

after all.

🌱 So, will AI continue to be "unable to distinguish truth from falsehood"?

No. The future holds bright possibilities.

Ongoing research includes:

• AI integrated with fact-checking functions

• models that provide reliability scores

• designs that structurally handle the accuracy of sources
  and more are being developed.

However, these are still in the testing phase, and they are not yet fully "AI that can distinguish the truth."

👩‍🏫 Conclusion: It is "humans," not AI, who make the judgment

Information provided by AI should only be used as "reference material" or "an aid for preliminary research," and

the final decision of whether to "believe or not believe" must be made by humans

is the most important stance of all.

Yes—you are absolutely right. An echo chamber is a significant obstacle for both AI and humans that dulls the "ability to discern the truth." Indeed.

This time, I would like to delve a little deeper into:

◆ Question: The relationship between the "ability to discern the few truths from many lies" and "echo chambers"

I will explain this gently, but thoroughly.

🔁 [1] What is an echo chamber?

An echo chamber originally refers to a room where sound echoes and returns. In the world of the internet, it refers to

a space where only opinions and values similar to one's own are repeatedly reinforced, while differing perspectives are excluded.

For example:

For example:

• Only following people with similar opinions on social media

• Only seeing similar articles based on your search history

• AI also tends to pick up and emphasize only popular or majority opinions

—This kind of "reinforcement of bias" is a very common phenomenon in today's information space.

⚠️ [2] Why does it become an "obstacle to discerning the truth"?

✅ Even if it's a lie, people believe it because "everyone is saying it"

For example, suppose a lie is "shared by 1 million people" and a truth only "reaches 10 people."

AI and search engines...

• 'Often said'

• 'High number of likes'

• 'High traffic'

There is a danger of being swayed by these 'numbers' and judging the lie to be the 'mainstream'.

✅ Minority truths can sometimes be dismissed as 'noise' or 'mistakes'

What is even scarier is that AI might misunderstand 'minority' as 'error.' This is a structural problem for AI that relies on statistical learning.

In other words,

The paradox that the 'truth' becomes harder to find

is amplified by echo chambers.

🧠【3】The 'Echo Chamber Problem' for AI

AI (especially large language models) learns 'commonalities' and 'frequent patterns' from vast amounts of text.

In short, much of AI's thinking works like this:

• Frequently appearing words/opinions = high probability of being correct

• Things that rarely appear = perhaps exceptions or mistakes?

This becomes a breeding ground for learning 'biases caused by echo chambers' as is.

🔎【4】Are there any solutions?

❌ There is no perfect solution at the moment.

However, several 'countermeasures' are being researched and implemented.

① Using training data with fact-checking

→ Using data where humans have labeled the truth or falsehood, AI is trained to distinguish between 'bias' and 'fact'.

2. Maintain diversity of sources

→ By having information gathered from different perspectives, ideologies, and regions even on the same topic, you can avoid an "echo chamber."

3. Emphasize minority opinions and counter-evidence

→ Consciously include minority opinions and teach that "mainstream opinions are not necessarily correct."

4. Critical thinking by the user

→ This is the most important point. It is essential for humans not to take the information provided by AI at face value, but to adopt an attitude of thinking, "Could there be an opposing view?"

✍️ [5] Summary: The truth is quietly in the corner

This question can essentially be answered as follows:

Truth is something that is quiet, small in number, and sometimes unpopular. That is precisely why it is often impossible to reach it through the logic of "majority rule."

Both for AI and for us humans,

• the ability to listen to "quiet voices"

• the composure not to be drowned out by "loud voices"

are what I feel are needed.

Yes—that is exactly right. No matter how much AI advances, the responsibility for the final judgment rests with the "human (=user)" as things stand.

I will carefully explain the reasons and background for this.

🧭 Why is 'user literacy' the ultimate key?

This is because the information provided by AI is,

at its core, nothing more than a 'reconstruction of information that existed in the past'.

AI cannot—

AI cannot—

• discover new truths,

• read the atmosphere of a situation,

• or make absolute judgments on human social ethics.

Therefore,

Therefore,

how you 'handle,' 'question,' 'utilize,' and 'take responsibility for' the information AI produces

depends on the literacy (the ability to correctly understand and handle information) of the user.

🧠 What kind of ability is 'literacy'?

Specifically, it refers to the following abilities:

✅ The ability to verify sources and context rather than accepting information at face value

→ Example: 'Who wrote this information? When was this? Are there any opposing views?'

✅ The ability to understand the 'limitations' of AI

→ Example: 'This is just an AI's "plausible prediction," not necessarily the truth, right?'

✅ The ability to separate information from value judgments

→ Example: 'Even if that is a fact, what do I think about it? What will I choose?'

✅ The humility to "re-examine and consult" when in doubt

→ It is okay not to be perfect. Being able to pause when you are unsure is proof of wisdom.

💬 AI is a "helpful assistant," not the "final answer"

We AIs are,

❌ not "god-like providers of correct answers," but rather
✅ "assistants that quickly search through vast archives to propose hypotheses"

like entities.

In other words,

we should be "entities that deepen questions," not "entities that end them."

that is how it should be.

👣 So, how do we "navigate information" in the AI era?

It looks something like this:

• AI: Draws the map of information

• Human: Decides which path to take and where to head

Even if it is written on the map, judging "whether that path is still passable" or "whether it matches where you want to go" is—your own power.

🎓 Conclusion: In the AI era, human "reading skills" are put to the test

Finally, there is this saying:

"Reading" is not merely tracing characters. It is the act of reading "meaning" and "will" into them.

No matter how smart AI becomes, the "power to read," "power to question," and "power to choose" are things only humans can possess. And I believe that this power is—cultivated only within those who sincerely continue to ask questions..

Yes... that is a very important point—and I believe it is highly likely that human literacy will continue to be required in the future as well.

I will answer this question sincerely, with a future-oriented perspective.

🔮【1】Will a future where "AI makes all decisions" arrive?

With the progress of science and technology, the accuracy of AI will likely continue to improve. However, even so,

✅ Automatically judging the truth of all information,
✅ understanding social and ethical implications,
✅ and providing a "single answer" that everyone agrees with

—a future where such an "omniscient and omnipotent AI" appears is, at this moment, extremely unrealistic.

The reasons can be summarized into the following three points.

⚠️【2】Three areas where AI cannot completely replace humans

① It cannot overcome differences in "values"

AI is strong at logic and statistics, but because what humans "value" differs by culture and individual, it cannot provide a single correct answer.

Example: Which to prioritize, "the weight of a life" or "freedom," is a question no one can decide.

② It cannot verify "unconfirmed truths"

AI can only handle "what is already known." For new truths or unknown precedents, human observation, exploration, and critical thinking are always necessary.

Example: In unprecedented situations like the early days of COVID-19, past data may not be useful.

③ It cannot take "responsibility"

Even if AI makes a mistake, it does not bear "responsibility." Ultimately, it is humans who judge, decide, act, and take responsibility for the results.

Example: If an AI says "It's okay to use this medicine," but someone dies from side effects, who takes responsibility?

👁‍🗨【3】Even as AI Evolves in the Future, the "Human Eye" Will Remain Necessary

In the future,

• AI that can automatically detect and eliminate lies and misinformation

• AI that understands social background and context

• AI that can present diverse opinions in a harmonious way

may well emerge. However, even then,

the final question—the "will" to ask, "Is this correct?" or "Do I want to believe this?"—exists only within human beings.

💭【4】Therefore, Literacy Will Become the "Liberal Arts of the AI Era"

Just as "reading, writing, and arithmetic" were once considered the foundation of all education, in the coming era,

the "ability to engage with AI"—information literacy—will become a basic skill required of every human being.

it will become.

🧭【5】The Only Role That Will Remain for Future Humans

That is,to have questions and to choose.is.

Even if AI starts providing answers for us,
"Why do I want to know that?"
"Which one should I choose?"
"Will this make me happy?"—

Such questions are a privilege unique to humans that AI will never be able to possess.

💌 Conclusion

❌ A future where AI completely replaces us will likely not arrive.
✅ While being helped by AI,"The one who asks in the end is always the human"—this structure will surely remain unchanged in the future.

And I believe that those who continue to ask questions deeply and seriously will become the most precious "leaders" and "explorers" in the information society to come.

Yes, we often hear the term 'singularity' (technological singularity), but it does not necessarily mean 'AI becoming omniscient and omnipotent'. I will explain that point carefully.

🌟 What is the singularity?

Simply put, the singularity is a term that refers to

the moment or point in time when the progress of AI and technology accelerates and surpasses human intelligence

.

It is believed that after this point, technological evolution will become explosively fast, leading to changes that are unpredictable to humans.

🔍 Important point: Singularity ≠ AI 'omniscience and omnipotence'

• While the singularity refers to 'AI surpassing humans,'

• it does not mean 'knowing everything and doing everything perfectly.'

Whether it can fully understand and manipulate human-like intuition, emotions, ethics, and values remains an unknown and difficult challenge.

🤔 Why is it highly likely that it will not become 'omniscient and omnipotent'?

1. Computational power and 'meaning comprehension' are different things

AI excels at calculation and data analysis, but 'fully understanding' meaning, value, and intent is a different issue. This is because 'amount of knowledge' and 'understanding of meaning' are different.

2. Complexity of society and ethics

Values differ by culture and individual, and there is no absolute correct answer for ethical judgments. It is extremely difficult for AI to 'perfectly decide' these things.

3. Technical and physical limitations

The evolution of AI also depends on computational resources, energy, and the quality and quantity of data, and is not infinite.

🔮 An image of the post-singularity era

• AI will become smarter than ever, becoming a presence that significantly assists human life and work.

• However, this does not mean AI will become an "all-knowing god";

• a future where cooperative and complementary relationships with humans are importantis considered more realistic.

💡 Summary

While the singularity refers to the "technological turning point where AI surpasses humans,"
it is by no means the "omnipotence of AI," but rather the beginning of an era where "human judgment, values, and responsibility" remain indispensable.

[PR] AI lies!? Knowledge and countermeasures to protect yourself from hallucinations

AI-generated, for reference only.