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When David Chalmers coined the “hard problem of consciousness” in 1995, he drew a line between questions science can resolve through functional description and questions that remain even after all functional facts are settled. The hard problem is why there is subjective experience at all. Explaining the neural correlates of vision does not explain why seeing red feels like something rather than nothing.
The philosophical questions surrounding machine consciousness often arrive in science fiction through dramatic high-stakes framings. An android demanding rights, a corporation suppressing a sentient AI, a robot deciding whether to kill. Molly Tanzer’s novella “And Side by Side They Wander,” published by Tordotcom on May 19, 2026, takes a different approach. Much like Justin C. Key’s focus on grounded, bureaucratic tension in The Hospital at the End of the World, Tanzer grounds her narrative in daily realities. The AI protagonist, a sensynth named Jack, arrives in a world so saturated with copies, clones, androids, and sentient mycelium that the question of authenticity has become structural rather than dramatic. Nobody is staging a test. Everyone is just trying to figure out who is real.
Most fictional treatments of robot consciousness begin at the moment of awakening. The system activates, develops inner experience, and must then navigate a world that has not prepared for it. The premise assumes consciousness is new, fragile, and contested. Suzanne Palmer’s “Ode to the Half-Broken,” published by DAW Books on April 28, 2026, starts somewhere different. With a robot whose consciousness is old, established, and quietly eroding along with its physical substrate.
The standard philosophical approach to AI consciousness involves specifying conditions consciousness requires, assessing whether AI systems satisfy those conditions, and deriving conclusions about consciousness likelihood. This approach inherits whatever uncertainty exists in the underlying theories of consciousness, which is substantial. A different approach starts from a comparison. What is the actual evidential basis for attributing consciousness to systems where we already do so, and how does that basis compare to the evidence available for AI systems?
The dominant methodology for assessing AI consciousness over the past two years has been the indicator approach developed by Patrick Butlin, Robert Long, David Chalmers, and colleagues. Derive indicators of consciousness from existing neuroscientific theories, then check whether those indicators are present in AI architectures. This approach has generated significant research activity and produced the closest thing the field has to a shared evaluation framework.
Most empirical approaches to AI consciousness have focused either on behavioral markers, asking whether AI outputs resemble those of conscious systems, or on architectural markers, asking whether internal processing satisfies theoretical indicators derived from neuroscientific frameworks. A third approach is possible. Testing specific, falsifiable predictions that a named consciousness theory makes about what any conscious system must contain, then checking whether those structures emerge in AI.
The indicators framework developed by Patrick Butlin, Robert Long, David Chalmers, and colleagues has functioned as the closest thing the AI consciousness field has to a shared evaluation standard. Published in Trends in Cognitive Sciences, it derives computational properties from existing theories of consciousness, asks whether those properties are present in AI architectures, and uses the results to form probabilistic assessments of AI consciousness likelihood. The framework has been productive and has generated significant research attention. It has also attracted sustained methodological criticism.
Kristina Šekrst’s The Illusion Engine. The Quest for Machine Consciousness, published by Springer Nature on October 30, 2025, with a softcover edition due November 2026, is one of the more noteworthy 2025 to 2026 books on machine consciousness because of who its author is. Šekrst holds a Ph.D. in logic from the University of Zagreb, works as a principal software engineer with day-to-day experience of large language model deployment, and is one of the co-discoverers of certain classes of prompt injection vulnerabilities in production AI systems. The combination of analytic philosophy training and working engineering experience is unusual in the consciousness literature, and the book reflects the combination. It is rigorous about the philosophical material in a way that engineering books typically are not, and concrete about the technical material in a way that philosophy books typically are not. The book runs 305 pages, is listed at ISBN 9783032055613, and is available through standard academic and trade channels including Amazon.
Bong Joon-ho’s Mickey 17, released theatrically by Warner Bros on March 7, 2025, and added to Max streaming on May 23, 2025, is the most direct cinematic dramatization of Derek Parfit’s branch-line case in recent memory. The film stars Robert Pattinson as Mickey Barnes, who has taken a job as an “Expendable” on a space colony voyage to the planet Niflheim. Expendables are designed to die repeatedly in service of the colony’s hazardous research, with each death followed by reprinting from a biological template and weekly memory restoration from cloud backup. The film opens with Mickey 17, the seventeenth Mickey in the sequence, having survived a fall that the colony assumed would be fatal. Mickey 17 returns to the printing facility to discover that Mickey 18 has already been produced. The colony’s regulations forbid the simultaneous existence of two Expendables from the same template (the so-called “Multiples” prohibition). One of them must be eliminated.
Most academic treatments of AI welfare have come from one of two directions. They have come from philosophers working in moral status theory who have no direct contact with the systems they discuss, or from AI engineers who have direct contact with the systems but limited philosophical training in welfare theory. Geoffrey Keeling and Winnie Street occupy a rarer institutional position. Both are staff research scientists at Google and concurrent fellows at the Institute of Philosophy at the University of London. Their May 2026 Cambridge Elements book, Emerging Questions in AI Welfare (DOI: 10.1017/9781009732000), is the first book-length treatment of AI welfare written by authors who have done substantive work on both sides of that divide.