AI + IQ testing (human vs AI)

👋 Hi, I'm Alan. I was a former Chairman for Mensa International (gifted families), and I've been revealing the IQ of post-2020 AI models since my groundbreaking 2020 Mensa article, The New Irrelevance of Intelligence, presented to the World Gifted Conference. Join thousands of my paid subscribers from places like Harvard, RAND, Microsoft AI, Google AI, and Pearson (Wechsler).
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By request, here's a simplified version of this full GPT-4 vs human viz; easier to read on a big screen! Download source (PDF)

Download source (PDF)

Download source (PDF)
Tests: View the data (Google sheets)
Trivia test (by WCT): Human: 52%, GPT-3: 73%, J1: 55.4%

Older viz

Older viz
Note: While I would love to facilitate cognitive testing of current language models, nearly all popular IQ instruments would preclude testing of a ‘written word only’ language model; the most common instruments from Wechsler and Stanford-Binet require a test candidate who is using verbal, auditory, visual, and even kinaesthetic… For this reason, AI labs generally use customised testing suites focused on written only. A selection of these benchmarks have been visualised below. Please see the full data for context and references. (Update Dec/2022: This note is now outdated, and we can test AI models on some IQ tests like Raven’s, though specialized AI benchmarks are still standard.)

On SAT questions, GPT-3 scored 15% higher than an average college applicant.
On trivia questions, models like GPT-3 and J1 score up to 40% higher than the average human.

Download source (PDF)
Tests: View the data (Google sheets)
Trivia test (by WCT): Human: 52%, GPT-3: 73%, J1: 55.4%

Download source (PDF)

Notable events in IQ testing AI models

Date Summary Notes
May/2023 PaLM 2 breaks 90% on WinoGrande (PDF, Google) For the first time, a large language model has breached the 90% mark on WinoGrande, a ‘more challenging, adversarial’ version of Winograd, designed to be very difficult for AI. Fine-tuned PaLM 2 scored 90.9%; humans are at 94%.
May/2023 GPT-4 achieves 100% on ToM (Johns Hopkins) Johns Hopkins: ‘GPT-4 reached ceiling accuracy of 100% [Two-Shot CoT plus SS Thinking]. Human performance in these scenarios was 87%
Mar/2023 GPT-4 = IQ 152 GPT-4 had an IQ of 152 on a Verbal-Linguistic IQ Test via Prof David Rozado. This would place it in the 99.9th percentile.
Mar/2023 GPT-4 outperforms humans across various exams OpenAI: GPT-4 ‘…we tested on a variety of benchmarks, including simulating exams that were originally designed for humans. We proceeded by using the most recent publicly-available tests (in the case of the Olympiads and AP free response questions) or by purchasing 2022–2023 editions of practice exams. We did no specific training for these exams.’
Feb/2023 GPT-3.5 mental state of 9yo child Stanford: text-davinci-003 ‘solved 93% of [theory of mind] tasks, a performance comparable with that of nine-year-old children… ToM-like ability (thus far considered to be uniquely human) may have spontaneously emerged as a byproduct of language models’ improving language skills.’ [Update 15/Mar/2023: Adjusted down to seven-year-old for GPT-4 due to new, more conservative benchmarks.]
Feb/2023 Kosmos-1 ‘sees’ Raven’s IQ tests ‘Kosmos-1 is able to perceive abstract conceptual patterns in a nonverbal context, and then deduce the following element across multiple choices. To the best of our knowledge, it is the first time that a model can perform such zero-shot Raven IQ tests [with vision]… there is still a large performance gap [9.3% above chance] between the current model and the average level of adults…’
Jan/2023 ChatGPT = IQ 147 ChatGPT had an IQ of 147 on a Verbal-Linguistic IQ Test via Prof David Rozado. This would place it in the 99.9th percentile.
19/Dec/2022 GPT-3.5 outperforms humans on some tasks in symbolic Raven’s IQ tests UCLA psychology tested GPT-3.5 [28/Nov/2022 release] using a symbolic model of Raven’s Progressive Matrices (RPM): ‘We found that GPT3 displayed a surprisingly strong capacity for abstract pattern induction [in text only, not vision], matching or even surpassing human capabilities in most settings’
4/Nov/2022 Anthropic’s testing on MMLU benchmarks find that model AND human outperforms model OR human …we find that human participants who interact with an unreliable large-language-model dialog assistant through chat—a trivial baseline strategy for scalable oversight—substantially outperform both the model alone and their own unaided performance… large language models can productively assist humans with difficult tasks… present large language models can help humans achieve difficult tasks in settings that are relevant to scalable oversight. — Anthropic, Nov/2022.
10/Feb/2022 GPT-3 has intelligence GPT-3 has its own form of fluid and crystalline intelligence. The crystalline part is all of the facts it has accumulated and the fluid part is its ability to make logical deductions from learning the relationships between things. – OpenAI, Feb/2022
8/Dec/2021 DeepMind Gopher on par with students for SAT reading questions NYT reported “In December 2021, DeepMind announced that its L.L.M. Gopher scored results on the RACE-h benchmark — a data set with exam questions comparable to those in the reading sections of the SAT — that suggested its comprehension skills were equivalent to that of an average high school student.”
RACE-h as complex reading comprehension questions for high-school students:
Average human (Amazon Turk worker) = only 69.4%, ceiling 94.2% (link)
PaLM 540B = 54.6% (few-shot).
Gopher 280B = 71.6%
2/Nov/2020 GPT-3 is Artificial General Intelligence. In November 2020, Connor Leahy, co-founder of EleutherAI, re-creator of GPT-2, creator of GPT-J & GPT-NeoX-20B, CEO of Conjecture, said about OpenAI GPT-3: “I think GPT-3 is artificial general intelligence, AGI. I think GPT-3 is as intelligent as a human. And I think that it is probably more intelligent than a human in a restricted way… in many ways it is more purely intelligent than humans are. I think humans are approximating what GPT-3 is doing, not vice versa.”
— Connor Leahy (November 2020)

ChatGPT achievements

ChatGPT achievements: View the full data (Google sheets)

Binet assessment with Leta AI

An early version of the Binet (1905) was run with Leta AI in May 2021. It is very informal, only a small selection of questions were used, and it should be considered as a fun experiment only.

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Dr Alan D. Thompson is an AI expert and consultant, advising Fortune 500s and governments on post-2020 large language models. His work on artificial intelligence has been featured at NYU, with Microsoft AI and Google AI teams, at the University of Oxford’s 2021 debate on AI Ethics, and in the Leta AI (GPT-3) experiments viewed more than 2.5 million times. A contributor to the fields of human intelligence and peak performance, he has held positions as chairman for Mensa International, consultant to GE and Warner Bros, and memberships with the IEEE and IET. He is open to consulting and advisory on major AI projects with intergovernmental organizations and enterprise.

This page last updated: 23/May/2023.