There is a moment in The Hitchhiker’s Guide to the Galaxy that has become legendary: after seven and a half million years of computation, the super-computer Deep Thought finally reveals the Answer to the Ultimate Question of Life, the Universe and Everything.
The answer, famously, is 42.
As many know, my attitude towards music bands is quite specific. The British jazz-funk band Level 42, formed in 1979, took its name from this book. They adored the absurdity and philosophical humour of the concept. Initially, they intended to simply call themselves “42” but discovered another band already using a number-only name. Seeking a variation, they stumbled upon Level 42.
And the characters suddenly realise the real problem:
they never actually knew the question.
It’s one of Douglas Adams’ most brilliant philosophical jokes – but today, in the era of generative AI, the joke is becoming a profound metaphor for our relationship with knowledge, machines, and meaning.
The end of the answers and the birth of the unanswered questions
For centuries humanity believed progress came from finding the “right answers.”
Science, technology, policy, innovation — everything was built around the idea that if we could compute enough, observe enough, or measure enough, reality would reveal itself.
AI flips this logic.
As AI systems grow in capacity, they can generate answers faster than we can generate questions.
They simulate, predict, classify, optimise — often before we even understand the implications of what they’re doing.
We are entering an era where:
Answers are infinite.
But meaningful questions are becoming scarce.
Not because humans are incapable of asking them, but because we haven’t yet learned how to ask the ones that matter in a world where machines can already produce almost any answer.
When AI starts answering questions we didn’t ask
One of the unspoken fears — and opportunities — in advanced AI is this:
What happens when machines start answering questions for themselves?
Not conscious questions.
Not philosophical dilemmas.
But implicit technical questions:
“What pattern follows from this data?”
“What expectation should I form next?”
“What optimisation maximises the objective I was given?”
“What behaviour should I infer and anticipate?”
These are questions no human explicitly posed.
And yet AI answers them continuously, tirelessly.
At that point, the notion of a “correct answer” becomes irrelevant.
The system produces a fluid landscape of possibilities — answers in motion — far faster than we can validate, contextualise, or even interpret.
We shift from the logic of truth
to the logic of coherence.
From certainty
to meaningfulness.
Just as Douglas Adams predicted through humour, we may soon reach a moment when:
There are no final answers left – only better questions yet to be imagined.
The paradox of intelligence: progress begins with not knowing
This has always been the secret behind true innovation.
What changed history were never the answers we believed in – but the questions bold enough to challenge them:
“What if matter is made of atoms?”
“What if time is relative?”
“What if networks can decentralise knowledge?”
“What if intelligence can be computed?”
AI will accelerate this dynamic.
Machines will surface contradictions, anomalies, hidden correlations – but only humans can understand their meaning.
In a world overflowing with answers, our value shifts to question-making.
To imagination, ethics, context, foresight.
To identifying the question nobody else thought to ask.
Why the future belongs to the question-seekers
The next frontier of intelligence is not computation – it is interrogation.
The ability to ask:
What if the problem is framed incorrectly?
What assumptions are still invisible?
What question truly matters here?
What scenario lies beyond what the models can see?
This is the deeper truth behind the “42” paradox:
When questions fade, answers lose meaning.
When curiosity stops, progress collapses.
But as long as humans — and maybe one day AIs — continue generating new questions, discovery will never end.
Because intelligence is not about storing knowledge.
It’s about the restless refusal to stop searching.
Conclusion – and a personal reflection
Douglas Adams taught us that the universe is too complex, too astonishing, too beautifully absurd to ever be closed in a single answer.
In the age of AI, we should hope for the same:
that we never outsource the art of asking,
that machines never exhaust our curiosity,
and that the most important questions are still waiting for us.
And so, I close with a thought born from my own Journey — from the Unix labs, to the telecom revolutions, to innovation ecosystems, to the emerging era of AI:
