AI is for everyone

Recently, I had the displeasure of seeing the manosphere in action, targeting a female co-founder in AI.

She was told – in public on this very platform for everyone to see – that women do not belong in AI.

Aside from the obvious misogyny, this view exposes those who espouse it as fundamentally misunderstanding a crucial point about AI: it is the greatest enabler, equaliser, and accessibility catalyst we have ever invented.

AI doesn’t care what’s in your pants

Before we get into why, I wanted to address the misogyny.

First, the co-founder in question has created an amazing company which is genuinely helping a tonne of people navigate this whole AI mess. She’s also not alone. Across AI and tech in general, women are pivotal.

I know this not just because I’ve seen the impact of their work first hand, but have repeatedly been the beneficiary of it too – I would not be where I am today without women in tech.

When I struggled professionally post-pandemic, it was a woman who helped me out of the rutt. When I was ready to run on AI, it was a woman who opened the door for me. As I’ve been trying to get my own startup going, it’s largely been women who have been willing to take a chance on me - and none of what I’ve achieved so far would’ve been possible without the incredible woman I am infinitely lucky to have as my partner.

The notion they don’t belong is objectively false. Rather, what we should be looking to evict from tech is male insecurity.

But more to the point, AI doesn’t care what’s between your legs – it only cares what’s between your ears.

You can be a man, woman, or fabulously non-binary. AI works just the same. What does limit you, however, is closed-minded stubbornness and longing for a version of the 1950s that never existed to begin with.

Age isn’t a barrier

Likewise, age is no barrier. In fact, I have a preference for working with older professionals: if you type with your index fingers, use double spacing after sentences, and spell email with a hyphen, you’re exactly who I love working with.

With more senior clients, you’re getting decades of knowledge and expertise. However, tech has moved fast and left many of these guys isolated – that index-finger typing speed is a bottleneck to how rapidly they can apply what’s in their head.

With AI, we can remove that entirely.

I’ve had clients so ecstatic when I’ve shown them how to use voice-to-text that it’s a borderline HR intervention.

Good AI coaching should be hands on, no powerpoints, and built around penny drop moments. You effectively want to front load these cognitive shifts early on, then cheers folks on as they let rip.

You combine that with Wispr Flow, and suddenly Bob from Accounts is now your latest poweruser.

The madder, the better

The other group I love working with is my very own neurodiverse community. My own journey with AuDHD has been entirely symbiotic with the road I’ve walked on AI. Even before then though, I was beginning to see research come through which pointed to the neurodiverse having a strong advantage in AI.

In my own experience, AI is rocket fuel for AuDHD. It allows us to take our constant stream of batshit ideas and turn them into something real. Combined with hyperfocus on a steady stream of dopamine, and we can lock in for 12 hours+ with relative ease.

AI’s also acted as a coach, an executive function backstop, and venting buddy for when the sea’s been rough.

This has reflected what I’ve seen in practice. Across an organisation, without proper coaching, fluency and literacy is spikey. Rates will be low, but then you’ll find the odd superuser.

The profession doesn’t really make a difference – this same spikiness exists in technical and non-technical professions alike – but I almost always find that the superuser is either ADHD, ASD, or both.

The point here isn’t neurodivergence, but divergence itself. As with the manosphere, what can end up happening is a monoculture – for example, the engineering-heavy mindset guiding AI hyperscalers. This is the antithesis of innovation – you want mixed backgrounds, talents, skillsets, and perspectives to generate bigger and better ideas.

This is why neurodivergent folks excel – we’re hardwired to come up with a million ideas a minute and AI gives us a catalyst to turn them into reality. But when we’re doing AI at scale – as a group, company, or a wider community of people in AI – that divergence is achieved through diversity.

Seize the means of automation

The financial picture around AI is something of a paradox. On one hand, it’s a billionaire bonanza. The mindboggling sums behind the hyperscalers could very well stumble, and far little attention is paid to what failing adoption rates could very well mean. If organisations fail to make this jump, they will fall – the consequences could be far more catastrophic than is widely realised.

Meanwhile, the way AI is ploughing into our lives – in every surface we touch, as datacentres in our local areas, into all our online social spots – makes this feel very much like something forced onto us by the wealthy, and something they only stand to profit from.

There is, however, another argument.

While all of the above may be true, it could also be a ‘Leopard’s ate my face’ moment for the 0.1%.

Much of the capital piling in did so on the assumption that AI would replace people, and adoption wasn’t a barrier. Neither of these things have turned out to be true.

Worse, what may be true instead is that it’s not people which get replaced, but entire business models. Lumbering incumbents are aircraft carriers, while nimble AI-native disruptors are the $50k surface-to-sea hullcracker drones.

This is because AI offers the average individual incredible capabilities – something Microsoft’s AI chief Mustafa Suleyman has predicted will match the power of nation states one day. Meanwhile, large organisations are cumbersome behemoths which are slow to react.

For someone like myself who came from a poor background, that strikes me as opportunity. The question of where one applies such capability is down to the individual – you’re the world’s leading expert in where you could apply AI in your life and work, not me.

But the barrier to entry has now been massively lowered. With specialist knowledge and the ability to get stuff done on tap, resources are no longer a showstopper.

There’s no “you must be at least this wealthy to ride the rollercoaster” signs.

There’s just your vision and the ability to execute on it.

You’re slamming the gate on yourself

If there is a limiting factor in AI, it’s the gatekeepers which inspired this piece. Not because they are successful in blocking access – but because they limit themselves.

This type of thinking is linear, presupposes the outcome, and highly inflexible to other schools of thought or ways of approaching a problem.

AI, on the other hand, is divergent, Bayesian. You’re not looking to prove you’re right, you’re actively celebrating when you’ve got something wrong because you can then update your priors.

The differentiator here is the vision and level of ambition, not what’s in between your legs, or the colour of your skin, or how much money is in your bank account.

It entirely comes down to your cognitive architecture: how you think, how you think about thinking, and how you turn those thoughts into action.

The only real gatekeeper to AI… is you.

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