AI and quantum computing sharpen humanity’s biggest questions

Better tools, open questions

The observable universe is estimated to be 13.8 billion years old. Researchers use evidence such as the cosmic microwave background, galaxy distributions, gravitational phenomena, and the expansion of the cosmos to model its evolution. AI can help classify galaxies, spot unusual objects, and pick weak signals out of growing datasets.

Quantum computers could eventually help calculate the behaviour of complex quantum systems that classical computers struggle to simulate. Current machines, however, cannot model the universe or resolve cosmology’s central questions. Progress depends on hardware, error correction, and algorithms—and on finding tasks where quantum computing actually outperforms classical methods.

The multiverse remains a hypothesis allowed by some cosmological and physical models, not an established fact. Whether it can be tested is disputed. Mathematics can reason rigorously about infinite sets; that does not show that physical space is infinite.

The same gap between capability and conclusion appears in quantum physics. Experiments have repeatedly confirmed correlations between entangled particles that cannot be explained by local classical theories satisfying Bell inequalities. Einstein’s phrase “spooky action at a distance” captures the clash with everyday intuition, but entanglement does not enable instantaneous communication.

AI can help optimise experiments and analyse complex data; quantum technologies may improve precision measurement, navigation, scientific instruments, materials science, and some communications applications. Yet physicists still lack a fully experimentally confirmed theory uniting quantum mechanics with general relativity. AI may help identify mathematical connections, and quantum computing may help explore models. Any result still needs mathematical, experimental, and independent verification.

Consciousness is not a performance test

Neuroscience can map brain activity and study memory, perception, attention, emotion, and decision-making. AI helps analyse brain-imaging data and model neural networks. But the central puzzle remains: how does physical activity in the brain give rise to subjective experience—the feeling of colour or pain, memories, or awareness of existing?

The question has become harder to sidestep as AI systems produce sophisticated text, solve problems, and do creative work. Convincing emotional imitation or intelligent behaviour does not establish that a system has inner experience. Intelligence, information processing, self-representation, and consciousness are related but distinct concepts, and there is no generally accepted scientific test for subjective experience in AI.

Claims that consciousness has a quantum basis remain controversial. Quantum mechanics underlies chemistry, but that does not show that quantum computation in the brain creates consciousness. Modelling cognition or reproducing a mental function is not the same as explaining what an experience feels like.

Similar caution applies to the search for life beyond Earth. Astronomers have found thousands of exoplanets, including some that may be habitable, and researchers examine planetary atmospheres, distant-world chemistry, and environments in the Solar System for possible biological or technological signatures. No extraterrestrial life or intelligence has been found.

AI can speed up the analysis and help identify anomalous signals, compare atmospheric compositions, and select targets for further observation. But unusual signals may have natural explanations, atmospheric chemistry can result from biological, geological, or photochemical processes, and false positives can come from terrestrial interference or instrument errors. In some cases, quantum sensors may improve measurement precision; neither technology removes interstellar distances or guarantees contact.

What the tools cannot establish

Reports of near-death experiences—encounters with deceased relatives, out-of-body sensations, altered time, calm, or a sense of connectedness—are personal accounts, not proof of a metaphysical explanation. Neuroscience studies changes in neural activity, oxygen availability, neurotransmitter systems, memory, and perception. AI can analyse clinical records, physiological measurements, interviews, and patterns across large datasets. Finding a pattern does not settle what the experience means.

Quantum mechanics is sometimes invoked in arguments that consciousness survives death. Brooks allows that energy and consciousness might be eternal, while acknowledging that there is no compelling evidence that personal consciousness persists after irreversible loss of brain function. Unresolved physics does not prove an afterlife; it also does not mean every reported experience has been fully explained.

The same limits apply to the origin of the universe. The Big Bang model, supported by cosmic expansion and the cosmic microwave background, describes the cosmos evolving from a hot, dense state. It does not explain why the universe exists, prove that it began from nothing, establish a multiverse, or identify a particular metaphysical cause. Researchers consider inflationary, cyclic, and “bounce” models, among other hypotheses, but their testability varies.

I think the more important dividing line is not between questions AI can answer and questions quantum computers can answer. It is between a useful result and a justified conclusion. A model can find a pattern or suggest a hypothesis; evidence, reproducibility, and independent review must still do the work of establishing it.

That distinction matters especially when claims touch life, death, religion, identity, and humanity’s place in the universe. Brooks argues for investment in AI, quantum technologies, scientific institutions, and expertise, alongside governance that does not put innovation ahead of responsibility. The same tools that accelerate research can also spread misinformation, manipulate public opinion, enable dangerous applications, and threaten cybersecurity and privacy.

Not every unknown is a technical problem waiting for more computing power. Some questions may yield partial answers, some may require concepts we do not yet have, and some remain philosophical or existential. AI and quantum computing may help sharpen the questions; they cannot guarantee that every question has a scientific answer.