♦Image generated with ChatGPTSomeone published a Substack article listing ten people to follow on AI. The list was thoughtful, well intentioned, widely shared. All ten names were men.
When Karen Smiley, a technologist and writer, messaged the author to point this out, the response was honest, if a little deflating. He simply had not come across any women writing about AI.
Karen had been on the platform for less than a year at that point. In her first few months, she had already found and subscribed to 34 women writing seriously about AI.
That detail stays with me.
Not because it is surprising. Because it is so precisely the shape of the problem. Not a lack of work. Not a lack of expertise. A failure of visibility. And more specifically, a failure of the systems that decide what gets seen.
Visibility Is InfrastructureKaren did not wait to be added to someone else’s list.
In December 2024, she built one. SheWritesAI started as a directory. A simple idea, executed with intent. By March 2026, it had grown into a community of more than 600 women and non-binary writers across 60 countries, all writing seriously about AI and data. No heavy marketing. No growth hacks. No artificial momentum. Just signal finding signal.
The writers were already there. They just were not connected to each other, and not to the readers who would recognise the depth of their work.
We talk about visibility as if it is an individual achievement. A strong post. A moment of attention. A spike in reach.
It is not.
Visibility is infrastructure. It is built through recommendations, citations, invitations, shared references. It compounds quietly over time. If you are outside of it, your work stays local no matter how strong it is. And if enough people are outside of it, the system starts to look like truth.
AI as a Condition of the WorkI see this from inside the work itself.
I am a design consultant with over 20 years working across digital transformation, design strategy, and experience design. Automotive, retail, financial services. Large programmes, complex systems, organisations that rarely move as cleanly as the diagrams suggest.
AI is no longer a topic I step into. It is the air in the room.
It shows up in the products I help design. In the tools I use every day.
It shapes the decisions organisations are making and sits underneath the questions clients are trying to answer, and increasingly, the ones they do not yet know to ask.
You feel it before you name it. A shift in how decisions are made. A quiet redistribution of control. A different kind of dependency forming between people and the systems they rely on.
And this is where visibility becomes something more than representation. Because who is visible shapes who is trusted. And who is trusted shapes what gets built.
The Quiet Cost of Who Is MissingWomen make up around 22% of the global AI workforce. At senior leadership level, that number drops below 14%. At the same time, over half of women in tech report observing gender bias in generative AI systems.
These numbers are not abstract. They show up in the product.
Not always in ways you can screenshot or easily explain. More often in the moments that feel slightly off. The assumption that does not quite hold. The flow that works in theory but not in life. The friction that feels personal, even when it is structural.
As designers, we talk about edge cases. But this is not about the edge. This is about the centre being defined too narrowly.
When the room is homogeneous, blind spots do not feel like blind spots. They feel like consensus. Diverse perspectives are not about fairness in the abstract. They are about accuracy. They are how you see what would otherwise remain invisible.
What Happens When the Room ChangesThis is where SheWritesAI becomes something more than a directory.
Recently, the community published its first book. AI Everywhere, Volume 1: How Women Are Changing The World With Artificial Intelligence. Twenty six authors. Fourteen countries. Five continents.
Each chapter approaches AI from a different angle. Ethics. Education. Creativity. Healthcare. Design. Automotive. Agriculture. Cybersecurity.
The range is deliberate. Because the reality of AI is not singular. It is distributed across contexts, across industries, across lived experience. And yet the mainstream narrative often feels narrow. Repetitive. Confident in ways that flatten the complexity.
This book does the opposite.
I contributed Chapter 15, on power, cost, and care in automotive AI. Writing it forced a kind of clarity. The questions that mattered were not technical. They were structural.
Who holds decision authority when a system makes a choice on your behalf. What it costs when you cannot see how your data is being used. What it would mean to treat care as a technical discipline, something designed into systems rather than added on as reassurance.
These questions do not belong to automotive. They sit underneath almost every AI powered product being built right now.
Being part of a book with 25 other writers, each approaching these questions with rigour and honesty, shifted something for me. It changed the feeling of the room.
The Work Was Never MissingIf you are reading this, you already know the work is happening.
Women are writing about AI with depth, with technical understanding, with the kind of practical grounding that comes from building, not just observing. That is what this publication has always been built around.
What has been missing is not capability. It is compounding visibility. The lists. The recommendations. The informal networks that determine whose work travels and whose stays contained.
SheWritesAI is part of a different approach. Not asking to be included. Building something that makes the original exclusion less structurally viable.
Because once the infrastructure exists, the dynamic shifts. Discovery becomes intentional. Connection becomes easier. Visibility starts to compound in new directions.
A Different Centre of GravityThere is a quieter change happening here. One that moves away from inclusion as permission and toward inclusion as infrastructure. It is less visible in the moment. There are no headlines for it. No single point where you can say, this is when it changed.
But over time, it alters the centre of gravity.
The AI conversation is already happening. Women are already in it, writing seriously, building in public, shaping thinking at the edges where the most interesting work tends to emerge.
If you are not seeing that, it is worth asking why. Not as a critique. As a question about the systems you rely on to decide what is visible.
Because once you see the gap for what it is, it becomes harder to accept it as natural. And easier to do something about it.
There is a quieter change happening here. One that moves away from inclusion as permission and toward inclusion as infrastructure.
It is less visible in the moment. There are no headlines for it. No single point where you can say, this is when it changed.
But over time, it alters the centre of gravity.
The AI conversation is already happening. Women are already in it, writing seriously, building in public, shaping thinking at the edges where the most interesting work tends to emerge.
If you are not seeing that, it is worth asking why. Not as a critique. As a question about the systems you rely on to decide what is visible.
Because once you see the gap for what it is, it becomes harder to accept it as natural. And easier to do something about it.
SheWritesAI is at shewritesai.substack.com (you can follow and subscribe there). The book is available via aiEverywhereBooks.com and on Amazon.
If you are a woman or non-binary person writing seriously about AI, both the community and the book are worth knowing about. They are part of the same movement, expressed in different ways.
The infrastructure is being built. You do not have to wait for a list that includes you.
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♦The Women Already Writing AI was originally published in Code Like A Girl on Medium, where people are continuing the conversation by highlighting and responding to this story.