2nd October 2026

How misinterpreted science is shaping perceptions of women in tech

How distorted science is sabotaging women in tech
Science misinterpretation occurs when a highly specific, nuanced academic finding is fed into the cultural meat grinder and emerges as a sweeping, generalised soundbite. In the technology sector, no misunderstood research has been more damaging than the “biological blueprint” myth. The narrative is deceptively simple: Men are naturally wired for machinery and systems, while women are wired for people and empathy. Therefore, the argument goes, attempting to achieve a 50/50 gender balance in technology is not just difficult; it is a futile war against human biology. But how did we get here? How did niche observations of infant behaviour morph into a justification for systemic inequality?

The origin: Babies, mobiles, and faces

The roots of this modern myth trace back to developmental psychology, most notably the work of researchers like Simon Baron-Cohen. In a widely cited 2000 study led by Jennifer Connellan and Baron-Cohen, researchers tested over 100 human neonates (newborns who were, on average, a day and a half old). The premise was to observe them before social and cultural factors could heavily influence their behaviour.

The infants were shown two stimuli: a social object (the researcher’s moving face) and a physical-mechanical object (a customised mobile). The researchers concluded that, on average, male infants showed a stronger visual interest in the mechanical mobile, while female infants showed a stronger interest in the human face. Baron-Cohen used these findings to argue that the female brain is predominantly hard-wired for empathy, while the male brain is hard-wired for understanding and building systems.

The scientific nuance that got left behind

In the academic world, these findings were immediately met with vital context and critique, nuances that never made it into the public consciousness.

  • Methodological Flaws: In her book Delusions of Gender, psychologist Cordelia Fine pointed out significant blind spots in the study’s design. The researcher conducting the experiment was not blind to the sex of the babies. Because the researcher was physically presenting her own face and holding the mobile, unconscious biases, such as inadvertently moving the mobile more for boys or widening her eyes for girls—could have easily influenced the results.
  • Failing the Replication Test: A massive recent meta-analysis spanning from 1968 to 2021 analysed 31 studies and 1,936 neonates. It found no significant gender difference in visual fixation on human faces at birth, directly challenging the claim that girls are innately more socially perceptive than boys from day one.
  • Averages vs. Absolutes: The original findings highlighted statistical averages, not absolute binaries. Many boys preferred faces, and many girls preferred mobiles. Yet, in the hands of the public, overlapping bell curves were flattened into two mutually exclusive biological destinies.

The mutation: From the nursery to Silicon Valley

The leap from “infant boys look slightly longer at a mobile” to “women cannot architect cloud infrastructure” is a staggering misinterpretation of science. Yet, this exact leap became the intellectual shield for the tech industry’s demographic disparities.

The most explosive example of this occurred in August 2017, when Google software engineer James Damore circulated an internal memo titled “Google’s Ideological Echo Chamber”. In it, Damore argued that the gender gap in tech was not the result of workplace discrimination, but rather biological differences between men and women. Mirroring the infant studies, he claimed that women naturally have a stronger interest in “people rather than things” relative to men, making them biologically less suited for core engineering roles.

Damore’s memo went viral, perfectly encapsulating the mutation of the original science: weaponising biology to explain away a stark professional gender gap. By claiming that preferences and abilities differ “due to biologic causes”, the narrative absolves the industry of responsibility. If the gap is nature’s doing, corporate diversity programmes are framed as unnatural, discriminatory, and fundamentally counterproductive.

Knowledge as liberation from gendered expectations

Tracing this pseudo-scientific determinism back to its flawed origins is not just an academic exercise; it is an act of liberation. When we understand exactly how a single, heavily contested neonatal study was weaponised, we strip the “biological blueprint” myth of its power. Exposing this bad science liberates the entire tech ecosystem from suffocating expectations, freeing both women and men to work, build, and lead authentically. This knowledge reshapes the industry in four critical ways:

  1. Lifting the “prove it” tax from women: Understanding that the biological barrier is a fiction means female engineers no longer have to start from a presumed deficit. They are freed from the exhausting burden of constantly proving they are not anomalies fighting their own nature, allowing their technical brilliance to simply stand on its own merit.
  2. Freeing men from the “machine” archetype: The myth that men are innate, unempathetic “systemisers” is a cage of its own. Debunking it liberates male engineers from the pressure to conform to hyper-competitive, emotionally detached archetypes. It allows them to openly value empathy, collaboration, and human-centric design without feeling they are betraying their “culture fit.”
  3. Erasing the “people vs. things” divide: Armed with the truth, the industry can stop funnelling talent into rigid, gendered buckets. The artificial wall between “hard engineering” and “human skills” collapses. Tech professionals of all genders are empowered to embrace hybrid skill sets, proving that the best cloud infrastructures and software systems require both rigorous logic and profound human insight.
  4. Mandating corporate accountability: Knowledge completely removes the intellectual alibi for systemic failure. When executives can no longer shrug off a lack of diversity as “nature’s doing,” they are forced to confront reality. Companies are compelled to actively fix broken promotion pipelines, dismantle the boys’ club mentality, and foster genuine meritocracies.

The narrative that men are wired for machines and women for people is a relic of gross oversimplification that ignores neuroplasticity, socialisation, and the infinite adaptability of the human mind.

Discarding this myth does more than just correct the scientific record. It frees the tech industry from a self-imposed straightjacket, allowing us to stop categorising talent by outdated biological blueprints and start building the future with the full, unconstrained potential of every individual.

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