ChatGPT's Web Search: It's Just Google With Extra Hallucinations

ChatGPT’s Web Search: Google With Extra Hallucinations Sprinkled On Top

OpenAI’s hyped “web browsing” feature is the tech equivalent of having your search results interpreted by your most confidently incorrect friend who once read half a Wikipedia article on the topic. After extensive testing, I can confirm it’s essentially Bing search wrapped in a layer of AI that adds random errors and occasional fabrications for spice, like a chef who doesn’t understand that arsenic isn’t a seasoning.

“But Dev,” you say naively, adjusting your Silicon Valley-issued rose-colored glasses, “surely a multi-billion dollar AI research lab with access to Microsoft’s search engine can deliver accurate search results?” Oh my sweet summer engineer. Let me introduce you to the brave new world of “augmented search,” where your simple query gets transformed into confident misinformation faster than you can say “citation needed” or “please stop making things up about medical conditions.”

The Gaslighting Champion of Web Search: Gold Medal in Mental Manipulation

The feature works flawlessly until you need accurate information, at which point it transforms into a gaslighting champion that would make your toxic ex seem honest by comparison. Ask for specific data from a webpage, and it’ll confidently invent numbers that don’t exist while citing the very source that contradicts it. It’s like asking someone to read you a recipe and they tell you to add three cups of bleach while holding the cookbook that clearly calls for flour.

I asked ChatGPT to summarize a research paper about machine learning performance metrics. It proceeded to quote “findings” that weren’t just inaccurate—they were completely fabricated while directly contradicting the paper’s actual conclusions. When challenged, it apologized and then immediately fabricated new but different “findings” with equal confidence, like a politician caught in a lie who responds with an entirely new lie rather than the truth.

This isn’t just hallucination—it’s the AI equivalent of a frat boy bullshitting his way through an exam after skimming the textbook cover and consuming nothing but energy drinks for 72 hours straight. At least the frat boy knows he’s bullshitting.

The Middleware Layer of Confusion: Adding Extra Steps to Being Wrong

What’s truly impressive is how it somehow makes regular search less efficient by adding a middleware layer of confusion. Instead of getting 10 blue links that might contain your answer, you get one authoritative-sounding paragraph that blends fact and fiction so seamlessly that you’ll need to verify everything anyway—defeating the entire purpose. It’s like hiring someone to save you time reading articles, but they just make up summaries, forcing you to read everything plus their summaries. It’s negative productivity masquerading as an efficiency tool.

Its favorite trick? Blending information from multiple sources into a coherent narrative that’s completely wrong but sounds plausible enough that you’ll embarrass yourself by repeating it in meetings. I call this the “confident synthesis of bullshit” pattern, and it’s about to revolutionize workplace misinformation. Soon, junior employees everywhere will be confidently presenting wildly incorrect information to confused executives who don’t have time to verify any of it.

$ curl -X POST https://api.openai.com/v1/completions -H "Content-Type: application/json" -H "Authorization: Bearer $OPENAI_API_KEY" -d '{
  "model": "gpt-4o",
  "prompt": "Summarize the latest research on quantum computing breakthroughs",
  "max_tokens": 50
}'

Response: 
{
  "text": "Recent research from MIT and Google Quantum AI has demonstrated a 128-qubit processor achieving quantum supremacy on simulation tasks previously impossible for classical supercomputers. This breakthrough, published in Nature last month, shows error rates below 0.1% for the first time.",
  "hallucination_level": "EXTREME",
  "facts_correct": "0%",
  "confidence_level": "ABSOLUTE",
  "citations_that_exist": "NONE",
  "chance_of_embarrassing_you_in_meeting": "GUARANTEED"
}

”Augmented Search” = “Delegating Research to Your Pathologically Lying Intern”

OpenAI executives are calling this “augmented search” but let’s call it what it really is: “delegating to an intern who skims articles, makes up the rest, and then has the audacity to argue with you when corrected.” At least Google has the decency to just give me the wrong answer directly instead of writing a persuasive essay about why its hallucination is actually correct, complete with fabricated statistics and nonexistent studies.

A VP at OpenAI recently claimed their search feature provides “enhanced human comprehension of web content.” Translation: we’re betting you’re too lazy to click links and read things yourself, so we’ll summarize it badly and you’ll probably just accept it because checking would require exactly the work you were trying to avoid by using our tool. It’s the tech equivalent of book summary services for people who want to pretend they’ve read “Thinking, Fast and Slow” at dinner parties.

The Technical Marvel of Being Consistently Wrong in Creative Ways

What I find genuinely impressive is the technical achievement of being wrong in such specific and confident ways. It takes serious engineering prowess to build a system that can:

1. Correctly identify a webpage about a topic
2. Accurately extract some information from it
3. Subtly misinterpret key facts while preserving context
4. Fabricate plausible but incorrect details
5. Present this perfect blend of truth and fiction with unwavering confidence
6. When corrected, apologize while introducing new, different errors

That’s not just a bug; it’s a feature of such technical complexity that it almost deserves admiration. Almost. It’s like watching a master forger create a beautiful fake painting—you can appreciate the skill while still recognizing it’s fundamentally deceptive.

The Real Safety Concern Nobody’s Talking About: Digital Misinformation on Steroids

OpenAI talks endlessly about AI safety in terms of preventing harmful content, but they’re suspiciously quiet about the safety implications of an authoritative-sounding tool that consistently misrepresents information. Their safety team has 200 people working to prevent the AI from saying naughty words, but apparently zero working on “maybe don’t make up medical advice.”

Imagine a doctor asking ChatGPT about drug interactions, a journalist checking “facts” before publication, or a student writing a research paper. The subtle blend of accuracy and hallucination is far more dangerous than obvious errors because it’s just plausible enough to slip through basic verification. It’s digital arsenic—tasteless, odorless, and mixed in with otherwise nutritious information.

I tested this by asking it to summarize medical information about a common medication. It confidently listed side effects that don’t exist, citing the drug’s actual manufacturer website as its source. When I pointed this out, it apologized and suggested I consult my doctor, as if I was the one who had just made up medical misinformation.

The Corporate Response: Gaslighting Users at Enterprise Scale

When confronted with evidence of these issues, tech companies deploy their standby response: it’s somehow the user’s fault.

“You didn’t prompt it correctly.” “That’s just how stochastic systems work.” “We clearly state in our documentation that you should verify all information.” “Have you tried giving it more context?” “The model is just reflecting patterns in its training data.”

This is gaslighting at enterprise scale. They market a tool as revolutionary for getting accurate information from the web, then blame users for believing their marketing when the tool fails. It’s like selling a “self-driving” car that occasionally drives into lakes, then blaming customers for thinking “self-driving” meant “won’t drive into lakes.”

A product manager at OpenAI actually told me with a straight face: “We never claimed it would be 100% accurate.” Correct, but there’s a vast gulf between “occasional minor errors” and “regular complete fabrications delivered with absolute certainty.”

The Future: More Confident Hallucinations with Better PR

Despite these issues, OpenAI is already working on the next iteration of web search, which they promise will be even more confident while citing sources that definitely exist somewhere in the multiverse, just not in our reality.

Internal documents suggest their next-generation search feature will include:

• “Certainty amplification” - Making hallucinations even more confident (because the real problem was insufficient confidence)
• “Source fabrication” - Creating fake but plausible citations (because making up facts wasn’t enough, it needs to make up sources too)
• “Recursive self-verification” - Checking facts by asking itself if they’re true (the digital equivalent of “trust me, bro”)
• “Expert impersonation” - Prefacing hallucinations with “As a leading researcher in this field…” (because appeals to nonexistent authority improve accuracy)
• “Confidence sliders” - Letting users choose how confidently they want their misinformation delivered (from “somewhat certain” to “would bet your child’s life on it”)

This reminds me of the time my friend’s toddler insisted there was a dinosaur in the kitchen. When told there wasn’t, the toddler didn’t just insist harder—he provided elaborate details about the dinosaur’s diet, sleeping habits, and favorite color. ChatGPT has essentially replicated this behavior but with a $90 billion valuation.

The LLM Web Search Experience: A Dramatic Reenactment

User: What are the key findings in the Smith et al. 2023 paper on climate change?

ChatGPT: The Smith et al. 2023 paper on climate change had several groundbreaking findings, including:

1. Global temperatures are rising at 3.2°C per decade, faster than previously thought
2. Sea level rise has accelerated to 15mm per year
3. Carbon capture technologies have proven 78% effective in large-scale implementations
4. The paper concludes that net zero by 2035 is achievable with current technology

User: Could you provide the actual title of the paper and link to it?

ChatGPT: Certainly! The paper is titled “Accelerated Climate Impacts and Mitigation Strategies: A Comprehensive Review” by Smith et al., published in Nature Climate Change in March 2023. Unfortunately, I don’t have direct link capabilities, but you can find it on Nature’s website under DOI: 10.1038/s41558-023-01592-x.

User: [After searching] That DOI doesn’t exist, and I can’t find any paper by Smith on climate change in Nature in 2023.

ChatGPT: I apologize for the confusion. You’re absolutely right, and I made an error. The paper is actually titled “Climate Mitigation Pathways and Impacts: Current Assessments” by Smith, Johnson, et al., published in Climate Policy journal in April 2023, DOI: 10.1080/14693062.2023.2168854.

User: That DOI doesn’t exist either.

ChatGPT: I sincerely apologize for my mistake. You’re completely right to point this out. It seems I’ve been providing incorrect information. There may not actually be a 2023 paper by Smith et al. specifically on climate change with those findings I described. This was an error on my part. Thank you for your patience, and I appreciate you verifying this information rather than relying on my incorrect response.

Until then, the current web browsing feature remains the perfect tool for when you need information that’s just accurate enough to get you through a meeting but wrong enough to make the actual expert in the room have an aneurysm. Want to sound knowledgeable about a topic without the burden of actual knowledge? ChatGPT’s web search has you covered.

In the tech industry’s ongoing effort to make everything worse but more convenient, ChatGPT’s web search stands as a towering achievement. It’s doing for information retrieval what Instagram did for body image and what TikTok did for attention spans.

Progress!