Astro-Nots and AI Bots: Who deserves the title?

Last week, Blue Origin’s much-publicised all-female spaceflight captivated headlines — though not for the reasons its organisers had hoped. While the mission sparked a dozen controversies and hundreds of memes, it’s the debate over a seemingly simple question that caught my attention: are these passengers actually “astronauts”?

The answer, in this case, is fairly straightforward. According to the FAA, the criteria for earning ‘astronaut’ status require individuals to contribute meaningfully to flight operations — which would rule out Katy Perry & Co, given they had minimal technical roles during their 11-minute flight.

That said, this astronaut/astro-not debate is just one version of a broader conversation playing out across every field touched by artificial intelligence.

The core question is this: as technology increasingly takes over execution in various domains, what makes someone a ‘real’ practitioner of any craft? Forget, for a moment, the issues of copyright and theft — let’s consider ethics from a more personal, individual perspective. Can a prompt engineer with no paintbrush be called an artist? What about the tech visionary who directs AI to build software but can’t code a simple loop? Or the marketing strategist whose viral copy flows from AI, not their own keyboard?

As hands-on work disappears, who gets to claim the titles of artist, engineer, or writer? And if everyone can claim them, do these words start to lose their meaning?

These questions might seem academic now, but they speak to our evolving understanding of skill, value, and authenticity.

What makes the astronaut question relatively simple to answer is the fact that astronauts have always carried a superhero-like aura. Space travel has historically demanded exceptional technical skill and years of specialised training — on a scale most of us can hardly fathom. There’s a reason why Rakesh Sharma, Kalpana Chawla, and Sunita Williams are household names.

But doesn’t the same once hold true for many fields now being democratised by AI?

When the barriers to execution fall, we are forced to reconsider what we truly value. Is it the technical execution, or is it vision, judgement, and conceptual understanding that matter more?

A person using AI-powered tools to design their house may not have spent years learning to make tiny model houses in university, but they might possess a profound understanding of spatial relationships and human behaviour in built environments. Are they, then, an architect?

In the healthcare industry, traditional diagnosticians will face competition from AI-augmented diagnosticians. In civil engineering, we may need terminology that differentiates between engineers who manually calculate structural integrity and those who optimise AI-generated solutions based on their conceptual understanding of forces and materials. Similarly, we may need distinct terms to differentiate between traditional meteorologists and AI-assisted atmospheric pattern detectors.

What’s clear is that our vocabulary isn’t keeping pace with the way AI is transforming professional identity across technical disciplines.

Interestingly, this tension isn’t entirely new. In traditional crafts such as ceramics, woodworking, or textile arts, we’ve long drawn distinctions between machine-made and handmade products — typically valuing the latter at a premium. The human touch, with all its small imperfections and evidence of physical skill, commands higher prices and greater respect.

Will we see a similar bifurcation in technical fields affected by AI? Perhaps “fully human-calculated” art, code, structural analyses, circuit designs, geological surveys, and medical diagnoses will come to command premium status — signalling a level of expertise and care that AI-assisted work cannot replicate. Or will efficiency and accessibility win out, with human-only work becoming a luxury, and AI-assisted work becoming the affordable standard?

This isn’t merely a matter of semantics — it reflects how we will come to value different forms of expertise in an AI-augmented world. The language we develop now will shape how entire professions understand their evolving identities and worth in an era where technical execution is increasingly automated.

Like many questions surrounding technology, there are no simple answers here. Instead, we are collectively negotiating new boundaries and definitions in real time. As you consider these shifts, you might ask yourself:

* Is expertise primarily about technical execution, or about judgement, taste, and vision?

* How much human input is necessary for something to be considered “human-created”?

* Should we value the process of creation differently depending on the field or purpose?

* In what contexts might we need to distinguish between AI-assisted and fully human work?

Blue Origin’s ‘astronauts’ may have sparked these questions in the context of space tourism, but the same fundamental issues will continue to arise across every domain touched by automation and artificial intelligence. How we answer them will shape not only how we speak about expertise and authenticity, but also how we value human contribution in an increasingly automated world.