Against the Empathizing-Systemizing Theory of Autism

The Empathizing–Systemizing (E–S) theory of autism, proposed by Simon Baron-Cohen, claims autism arises from an imbalance between two cognitive traits:

Empathizing (E): the capacity to recognize others’ mental states and respond to them appropriately
Systemizing (S): the drive to analyze, construct, or understand rule-based systems

The theory claims men tend toward type S brains (higher systemizing than empathizing), while women tend toward type E brains (higher empathizing than systemizing). Autism reflects an extreme male brain—very high systemizing and very low empathizing.

I critique E-S theory on two grounds:

Empirical evidence suggests autistic traits correlate more strongly with low empathizing than with high systemizing.
The systemizing quotient (SQ) conflates systemizing with interest in stereotypically male topics, calling into question whether men are genuinely more systemizing—whatever “systemizing” actually means—or just more interested in things like cars, computers, sports, and stocks.

The Association Between Autism and Empathizing/Systemizing

If autism is caused by “extreme systemizing,” we would expect the systemizing quotient (SQ) to be strongly and positively correlated with the autism quotient (AQ). But most studies find a much stronger negative correlation between the empathizing quotient (EQ) and the AQ, and only a weak positive correlation between the SQ and AQ.

In Morsanyi et al. 2012, the EQ has a partial correlation of –0.45 with the AQ; the SQ has a partial correlation of +0.10.
In Svedholm-Häkkinen et al. 2018, the EQ has a correlation of -0.66 with the AQ; the SQ has a correlation of +0.11.
In Pan et al. 2022, autistic children differ from controls by 1.75 SD on the SQ and 0.73 SD on the EQ.
In Sindermann et al. 2019, partial correlations with AQ:
- Males: EQ = -0.36, SQ = +0.26
- Females: EQ = -0.31, SQ = +0.30
In Reed 2017, both EQ and SQ mediate the sex–autism link, but EQ shows stronger effects.
In Baron-Cohen et al. 2003, individuals with Asperger differ from controls by 1.75 SD on the EQ and 0.46 SD on the SQ.

The data is consistent. Autism is more closely associated with low empathizing, rather than high systemizing. Additionally, a closer analysis of the EQ shows most of the negative correlation between the EQ and the AQ is due to a deficit in social skills.

In Groen et al. 2015, the partial correlations between the AQ and the subfactors of the EQ break down as follows:

Emotional Empathy: –0.03
Cognitive Empathy: –0.07
Social Skills: –0.62

These results imply that the association between the EQ and autism may not reflect an emotional deficit, but rather difficulty navigating social situations.

Measurement Bias in the Systemizing Quotient

The SQ does not measure a general drive to understand rule-based systems. Instead, many items measure interest in male-dominated technical domains—a distinction that matters. If men score higher on the SQ because the items are male-coded, then the observed sex differences may be artifacts of item content rather than cognitive style.

A factor analysis of the SQ reveals six correlated factors:

Technical Curiosity
Technical Understanding
Analytic Information Seeking
Naturalistic Curiosity
Attention to Detail
Linguistic/Musical Structural Awareness

Only the first three show large sex differences. The others are relatively neutral. When systemizing is operationalized in terms of neutral items–such as nature, language, or detail orientation—rather than male-coded items—such as cars, computers, sports, or stocks—the sex bias largely disappears.

These results suggest that the SQ measures domain-specific interests, not domain-general cognitive drives. A more domain-neutral test of systemizing would likely show weaker sex differences.

Tailcalled’s Analysis

Independent analysis by Tailcalled reinforces the concerns above.

In Empathy/Systemizing Quotient is a poor/biased model for the autism/sex link, two of the factors they find are an Empathy factor and a Systems Interests factor. The Empathy factor breaks down into a Mind-Reading factor (which has a significant autistic-allistic difference, with non-autists scoring higher) and a Compassion factor. The Systems Interests factor breaks down in Tech Interests (which has a significant male-female difference, with men scoring higher) factor and a Details Interests factor (which has a significant autistic-allistic difference, with autists scoring higher).

In a factor analysis of the SQ (including filler items), they find four orthogonal factors:

Technical Interests
Nature Interests
Social Difficulties
“Jockyness”

Only the Technical Interests factor is strongly sex-differentiated, consistent with my observations above.

Conclusion

The E–S theory of autism conflates three distinct phenomena:

A sex difference in interests, reflected in high SQ scores among men
A deficit in social skills, which correlates with autism traits
A vague construct called “systemizing” that may not describe a real cognitive trait at all

The theory claims autism is an “extreme male brain,” but the evidence is stronger for “low social skills” than “high systemizing.” The SQ, one of its primary measurement tool, is too confounded with sex-stereotyped content to isolate a domain-general trait. And the EQ, once decomposed, shows autism is related to specific social impairments rather than a general lack of empathy.

The E-S theory of autism is false.

Appendix

My Factor Analysis of the Systemizing Quotient

Factor 1 – Technical Curiosity

S33: If I were buying a stereo, I would want to know about its precise technical features. (0.74)
S5: If I were buying a car, I would want to obtain specific information about its engine capacity. (0.72)
S13: I am fascinated by how machines work. (0.7)
S20: If I were buying a computer, I would want to know exact details about its hard drive capacity and processor speed. (0.7)
S57: I am not interested in understanding how wireless communication works. (-0.69)
S7: If there was a problem with the electrical wiring in my home, I’d be able to fix it myself. (0.58)
S11: I rarely read articles or webpages about new technology. (-0.57)
S15: In maths, I am intrigued by the rules and patterns governing numbers. (0.54)
S32: I do not tend to watch science documentaries on television or read articles about science and nature. (-0.42)
S12: I do not enjoy games that involve a high degree of strategy. (-0.36)
S51: When I’m in a plane, I do not think about the aerodynamics. (-0.35)
S34: I find it easy to grasp exactly how odds work in betting. (0.34)
S37: When I look at a building, I am curious about the precise way it was constructed. (0.3)
S25: If I had a collection (e.g. CDs, coins, stamps), it would be highly organised. (0.28)
S43: If I were buying a camera, I would not look carefully into the quality of the lens. (-0.27)
S18: I find it difficult to understand instruction manuals for putting appliances together. (-0.27)
S41: When travelling by train, I often wonder exactly how the rail networks are coordinated. (0.25)

Factor 2 – Naturalistic Curiosity

S48: When I look at a mountain, I think about how precisely it was formed. (0.73)
S55: I am interested in knowing the path a river takes from its source to the sea. (0.72)
S53: When I am walking in the country, I am curious about how the various kinds of trees differ. (0.66)
S26: When I look at a piece of furniture, I do not notice the details of how it was constructed. (-0.56)
S19: When I look at an animal, I like to know the precise species it belongs to. (0.55)
S60: I do not care to know the names of the plants I see. (-0.54)
S37: When I look at a building, I am curious about the precise way it was constructed. (0.52)
S23: When I cook, I do not think about exactly how different methods and ingredients contribute to the final product. (-0.52)
S41: When travelling by train, I often wonder exactly how the rail networks are coordinated. (0.52)
S45: When I hear the weather forecast, I am not very interested in the meteorological patterns. (-0.52)
S6: When I look at a painting, I do not usually think about the technique involved in making it. (-0.41)
S51: When I’m in a plane, I do not think about the aerodynamics. (-0.41)

Factor 3 – Technical Understanding

S24: I find it difficult to read and understand maps. (-0.72)
S49: I can easily visualise how the motorways in my region link up. (0.72)
S31: I find it difficult to learn my way around a new city. (-0.59)
S40: I find it difficult to understand information the bank sends me on different investment and saving systems. (-0.5)
S18: I find it difficult to understand instruction manuals for putting appliances together. (-0.37)
S34: I find it easy to grasp exactly how odds work in betting. (0.02)

Factor 4 – Attention to Detail

S56: I do not read legal documents very carefully. (-0.62)
S42: When I buy a new appliance, I do not read the instruction manual very thoroughly. (-0.47)
S35: I am not very meticulous when I carry out D.I.Y. (-0.39)

Factor 5 – Analytic Information Seeking

S29: When I read the newspaper, I am drawn to tables of information, such as football league scores or stock market indices. (0.58)
S28: When I learn about historical events, I do not focus on exact dates. (-0.48)
S38: When an election is being held, I am not interested in the results for each constituency. (-0.37)
S4: I prefer to read non-fiction than fiction. (0.28)

Factor 6 – Linguistic/Musical Structural Awareness

S30: When I learn a language, I become intrigued by its grammatical rules. (0.61)
S1: When I listen to a piece of music, I always notice the way it’s structured. (0.53)
S44: When I read something, I always notice whether it is grammatically correct. (0.39)

Factor Correlation Matrix

	Technical Curiosity	Naturalistic Curiosity	Technical Understanding	Attention to Detail	Analytic Information Seeking	Linguistic/Musical Structural Awareness
Technical Curiosity	1.00	+.63	+.63	+.58	+.59	+.54
Naturalistic Curiosity	+.63	1.00	+.49	+.51	+.61	+.65
Technical Understanding	+.63	+.49	1.00	+.54	+.53	+.30
Attention to Detail	+.58	+.51	+.54	1.00	+.52	+.50
Analytic Information Seeking	+.59	+.61	+.53	+.52	1.00	+.51
Linguistic/Musical Structural Awareness	+.54	+.65	+.30	+.50	+.51	1.00

Factor Correlations with Gender

Technical Curiosity (r = +.42)
Technical Understanding (r = +.34)
Analytic Information Seeking (r = +.33)
Naturalistic Curiosity (r = +.11)
Attention to Detail (r = +.06)
Linguistic/Musical Structural Awareness (r = +.02)