Quantum Information, Game Theory, and the Future of Rationality
When the Waters were Changed
As quantum computing enters the mainstream, it’s becoming harder to separate genuine progress from overhyped promises. While real breakthroughs unfold quietly in labs, influencer culture and viral narratives often blur the line between science and spectacle. The main message of this post is how to differentiate the two — following the advice of the greatest proponent of science I have known, Carl Sagan.
Faisal Shah Khan, PhD
7/1/20254 min read


Khidr — the evergreen, elusive guide of the Sufis — once offered a warning to humankind: a time would come when all the water in the world would vanish, save for a small amount carefully preserved. The water would return, yes, but not as it was. It would flow differently, reversing meaning itself — not through chaos or collapse, but through quiet inversion: what was up would become down, what was left would become right, and most importantly, what had once been right would now be wrong, and what was wrong would be declared right. (Idries Shah, “When the Waters Were Changed”)
One man took Khidr seriously. He stored his water, waited, and watched as streams dried and wells gave up their last drops. Then the new water came. From his shelter, he watched the world drink. Outwardly, everything looked the same — people laughed, lived, worked — but something had shifted. What once made sense now seemed absurd; and more disturbingly, what had been silly, incoherent, or plainly false was now treated as sensible, even self-evident.
He tried to speak, but no one could follow. They listened with concern, then confusion, then alarm. Eventually, they tried to have him committed. In time, the solitude became unbearable. He drank from the wells of the new water. They welcomed him back. They called him sane — even the divinely cured wise one.
That story is, of course, metaphor — but one shaped by close observation of something fundamental about how societies change: how meaning shifts silently and collectively; how inversion becomes consensus; how madness can pass for wisdom, once everyone drinks from the same polluted source.
And while the water in Khidr’s tale flows through mystical tradition, the tragedy of Jonestown, USA was all too real. In 1978, more than 900 people died after consuming a poisoned fruit drink — not actually Kool-Aid, but close enough — under the influence of cult leader Jim Jones. Since then, the phrase “drinking the Kool-Aid” became, for a time, cultural shorthand for this kind of surrender — belief so absolute it overrides reason, skepticism, even survival. Its origins may be fading from memory, but the dynamic it describes is still very much alive.
Hold that story in your head for a moment — and now turn to quantum computing, where the waters, too, have begun to shift in ways that feel eerily familiar.
Across research labs and university departments, the work remains what it has always needed to be: serious, methodical, and deliberately slow. Physicists and computer scientists are deep in the trenches, wrestling with quantum error correction, probing the strange geometry of topological phases, and designing architectures that might, someday, support scalable, fault-tolerant quantum computation. Institutions like MIT, Delft, Oxford, Toronto, and others are not chasing headlines; they are asking difficult, foundational questions — and accepting, without complaint, that many of the answers may take decades to arrive. This is what real progress looks like: quiet, rigorous, unglamorous, and defiantly resistant to shortcuts.
And the same, in many cases, holds true within the internal teams at major tech companies, where — behind the noise of the occasional breathless press release — researchers are engaged in the same careful, unpublicized grind. These are people who know, from the inside, just how hard-won every inch of advancement really is. They carry the scars of decoherence battles, the memory of long nights debugging readout fidelities, and the endless, delicate tuning of cryostats and gate operations. They are not selling miracles — they are, piece by piece, trying to build them.
This isn’t just systems engineering or product-market fit. It’s quantum physics, complex projective linear algebra, complexity classes, and noise modeling — disciplines that demand years of immersion and the kind of fluency that, in principle, cannot be faked. I say this not as an outside observer, but as someone who works in the field — a quantum researcher who still finds joy in the geometry and structure of the complex projective Hilbert space, where the abstract meets the possibility of technological revolutions.
But of course, it can be faked — and often is. The real issue is not merely the presence of impostors, but the fact that many people either can’t tell the difference, or would rather not. In a world tuned for visibility over depth, it’s often easier to judge a speaker by charisma, confidence, and narrative control than by the substance of their work. And in a culture shaped by social media — an influencer culture on speed — the rewards for performance often outweigh the incentives for understanding. In such an environment, the faker isn’t just tolerated; they’re rewarded, followed, retweeted, funded.
As in so many corners of society, the signal struggles not because it’s weak, but because the noise now comes with better fidelity. Carl Sagan once offered a kind of compass for moments like this:
“We wish to find the truth, no matter where it lies. But to find the truth we need imagination and skepticism both. We will not be afraid to speculate, but we will be careful to distinguish speculation from fact.” —Carl Sagan, Cosmos: A Personal Voyage, Episode 1: The Shores of the Cosmic Ocean (1980)
He was right — and his words ring especially true in quantum computing, where the terrain is still largely unmapped and the temptation to confuse metaphor with mechanism is everywhere. Perhaps this is the measure — or at least one measure — of the genuine quantum scientist versus the performer: not whether they speculate, but how. The real ones dream, yes, but they anchor those dreams in hard, technical ground. They let imagination stretch, but only as far as their equations can reach. They don’t confuse abstraction for achievement, and they know the difference between a research direction and a marketing slogan.
Quantum computing needs both: the wild dreamers and the hard experimentalists. It needs metaphor and math. Vision and verification. But we must learn to tell the difference between the cathedral — slowly, painstakingly built stone by stone — and the carnival outside, loud, fast, and eager to sell tickets. One is hard to enter but built to last. The other is easy to love but quick to collapse.
Because when the waters change, and meaning begins to drift, the only way to stay sane is to remember what the old water tasted like — even if doing so means standing apart, and standing alone.