AI-Assisted Patent Search Tools Exacerbate Inventor Biases

AI chat tools have two problems: over-simplification and hallucination. These two problems mimic inventor’s biases when doing patent searches, leading to bad results.

Inventors and entrepreneurs might love the idea of using an AI‑powered search tool to check “Did I do something new?” fast and cheap. It sounds smart. It sounds responsible. I am a big fan of startup companies doing patent searches, as they make the patents more valuable and ultimately reduce costs.
But here’s the uncomfortable truth: those tools don’t eliminate bias – they reinforce it. And when you combine that with the inventor’s own cognitive distortions, you are not improving your patent strategy.

You are creating a liability.
In this post I’ll unpack how the real problem isn’t the lack of data. It’s your interpretation of the data, and how using AI tools makes your weaknesses worse, not better.

The Real Problem: Inventor Bias, Not Lack of Information

Inventors are too close to their inventions to see clearly. They misjudge what novelty looks like. They mis‑assess the scope of their claim. And that is not a search problem — it’s a judgment problem.

Inventions always revolve around nuance. The invention must be described in a context, with the actual “invention” hinging on one phrase.

In patent preparation and prosecution, the patent attorney is trained to focus on that nuance, figure out what it might be, then express it in a way the examiner can see it.

During the prosecution phase, the examiners can blow right past that key phrase, and the patent attorney calls them out on it.

The nuance of the invention is key, and finding that nuance in a sea of prior art is extraordinarily difficult.

Inventors fall into two traps:

• “There is nothing like it.”
• “This is completely logical – everyone would do it this way.”

Inventor Psychology is Always a Roadblock

“This is nothing like my invention!”

Inventors can face a lot of pressure when doing a patent search. They have an invention, and they really, really need it to turn into a solid patent.

This happens when they promised investors, told their boss, or set the direction of their company based on the invention. For startup companies, the entire business might hinge on the invention.

The inventor has immense pressure to be “correct.” (This type of pressure is also why you should never let your own patent attorney do a search, either.)

The deep-seeded fear of this inventor is that they might not be as smart as they think. Deep down inside, there is a small voice telling them they are just not that smart, and they are determined to prove that voice wrong.

This inventor can be very dismissive when doing a patent search. They skim over killer prior art and, without getting into the deep nuance that might be in that prior art, declare “this is nothing like my invention!”

“They obviously would have done it my way!”

Another psychological block is that the inventor sees their invention from a logical, methodical progression. Once we defined this problem, which is “obvious” to “everybody,” the “obvious” way to solve it is my way.

This inventor often fails to grasp that they have identified a problem that nobody has seen before, or they have looked at the solution with a different point of view.

The “invention” and insight could well have been the identification of the problem, not the identification of the solution.

This inventor looks at prior art and assumes that someone else who is in a closely related field saw the same thing and therefore, “because it is obvious,” would have assumed the same solution.

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AI Tools Mirror (and Magnify) Inventor Psychology

AI tools, especially Large Language Models (LLMs) used to power chat-based tools, have two structural problems which mimic the inventor’s biases exactly.

Over-summarization

The first structural problem is that LLMs over-summarize.

When you query an LLM to examine a 40 page patent or scientific paper for a specific and very nuanced invention, the LLM has a tendency to summarize and blow past the nuance.

This is a structural issue with an LLM.

LLMs are trained on existing text and not your nuanced invention. By definition, the invention is “new” and has never been done before, so it was never taught to recognize it.

In other words, the structural, functional design of LLMs mimic the cognitive bias of the inventor doing their own search.

The LLM blows past the key phrase that defines the invention and gives results that prove to the inventor that their invention is better than sliced bread.

Hallucinations

On the other hand, LLMs are well known for their inherent ability to hallucinate.

When you ask an LLM to give you certain results, it will try to produce those results even if there is no basis whatsoever. It will make up information if you push it to give you an answer (even if your prompt is not inherently biased, the LLM will try to give you an answer).

This structural, inherent behavior of LLMs will piece together your invention into the prior art and, incorrectly, assume that your invention was shown in some patent application – even when that reference never said that specifically.

This structural design of LLMs duplicates the second bias of the inventor when doing a search – everything is obvious.

“You Hear What You Want to Hear, and You See What You Want to See”

LLM-based search tools – by their very design – will reinforce whatever bias you bring to it when doing patent searches.

In every case, the AI-driven searches will make matters worse, not better.

• If you’re leaning optimistic (“there’s nothing like it”), the tool over-summarizes the prior art, skips over the nuance to reassure your deep-seeded need to be correct.
• If you’re leaning pessimistic (“of course they did it that way”), the tool infers (read: hallucinates) that the invention was somehow contained in the prior art, reinforcing your belief that you did not really invent anything.

You end up with a search result that confirms what you want to believe. That is the trap.

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The Missing Nuance — Why AI Can’t Find What Matters

Let’s be clear: patent law is less about “did anyone write these words?” and more about “does this claim, in the broadest reasonable interpretation, meaningfully differ from the prior art in a way that matters commercially and legally?”
AI search tools are terrible at that. They:

• Focus on keywords, classifications, and what might (or might not) be in the prior art, but not on why your invention matters.
• Miss the one pivot‑point – the nuance – that creates value and enforceability.
• Fail to interpret your invention the way an examiner or infringer will interpret it.

Maybe someday LLMs might be trained to examine patents within the legal context of examination or litigation, but it is not today.

Emotional Damage — The Psychological Risk of Seeing Prior Art Too Soon

When you’re using AI or DIY searches, you also expose yourself to major emotional risk that can lead to bad business decisions.

• You find “something similar” and suddenly your confidence dips. You question whether you were right to start. That can cause strategic paralysis or hasty pivots.
• You find nothing “obvious” and you feel invincible — even though your search was shallow. That overconfidence can lead to weak claims or missed disclosure.
  Either way, your emotional state influences your reading of results. Panic, pride, denial — none of those are conducive to sound patent strategy.
  And the cost isn’t just legal. It’s business. Investors hear you say “we did our own search, everything’s clean” and they rely on it. You make product decisions, you raise money, you go to market — all based on what may be a false sense of security.

And the cost is not just legal, it is business. Investors hear you say “we did our own search and everything’s clean.” They rely on that. You rely on it for your strategy, for your business negotiations, for your long term goals.

Lots of money might be made or lost based on the perception of what the search really means.

What is the Best Search?

When doing patent searches, if you have not found the killer prior art that blows you out of the water, it just means you have not found it YET.

For patentability searches prior to filing, most people spend a bit of time and money doing searches. A typical pre-filing search and analysis might be $2000 or so. For ultra-high value patents, such as pharmaceutical patents, they may spend $100,000 or more.

When patents are litigated, a second search is done to try to invalidate or kill the patent. If there are millions or billions of dollars at stake, patent searches might cost $500,000 or more.

Remember that whatever patent searching you do beforehand, the only patent search that actually matters is the one the examiner does. The art of patent drafting is to highlight the invention in a way that the examiner will be able to either find that nuanced inventive element quickly, or not find it at all.

The Legal Bomb — Duty to Disclose

Now here’s the kicker: if you conduct your own search (or you rely on an AI tool) and you find prior art, you are legally obligated to disclose any art that is “material to patentability” under 37 CFR 1.56 and the Manual of Patent Examining Procedure (MPEP 2000) rules.
And “material” doesn’t mean what you think. It means what someone else — an examiner, a competitor, a litigator — might argue as important.
If you misinterpret or ignore something because you “felt” it wasn’t important, you’re opening the door to inequitable conduct, unenforceable patents, or triple damages in litigation. Your DIY search just became a liability, not an asset.