When Algorithms Learn “Bro Code”

For years, marketers and agencies have understood that algorithms reward engagement. The more interaction a post receives, the more visibility it gains. Simple enough in theory.

But what happens when the behaviours driving engagement are themselves culturally biased?

A growing conversation across platforms like LinkedIn suggests that communication styles commonly associated with male leadership may be automatically amplified more than others.

The discussion intensified after LinkedIn changed its algorithm in January 2025. Later that year, business leaders Jane Evans and Cindy Gallop conducted a widely shared social media experiment highlighting perceived gender disparity on professional platforms, humorously termed “cracking the bro code”.

The experiment suggested that identical posts published by women reached significantly fewer people than those shared by male colleagues. The findings sparked widespread industry discussion and led to international calls for greater platform accountability.

You can read more on the Fairness in the Feed campaign.

Women across business, media and marketing have since reported experimenting with more ‘male coded’ language in posts by using more assertive phrasing, dominance signalling and self-promotional language. Some even reported changing gender identifiers and then seeing materially higher reach and engagement.

There is no evidence that platforms are deliberately prioritising men. The issue is likely more systemic and far more subtle than that. Algorithms learn from historical behaviour. And historically, digital business environments have often rewarded confidence over nuance, certainty over collaboration, and performance signalling over reflection. In many cases, those traits have traditionally aligned with masculine corporate communication styles.

The result is what some commentators now describe as “bro coding” or algorithmic “bro code”. Not intentional discrimination, but systems optimising for patterns that already existed.

For marketers, this raises important questions:

• Are platforms rewarding the best thinking, or simply the loudest signalling?

• Are we optimising content for human connection, or for algorithmic approval?

• And if visibility increasingly favours a narrow communication style, what voices are being unintentionally suppressed?

Algorithms are no longer just distribution tools. They actively shape professional culture, influence leadership visibility and ultimately affect who gets heard.

The irony is that many of the qualities brands claim to value, including empathy, authenticity, emotional intelligence and collaboration, are often the very traits least rewarded by engagement systems built around attention velocity.

As media professionals, we should pay close attention to this. Not simply from an equity perspective, but from an effectiveness one. Because if every brand begins sounding the same in pursuit of reach, audiences eventually stop listening.

The future of good marketing may not belong to those who master the algorithm. It may belong to those brave enough to sound human despite it.