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REVIEW 4 major objections 5 minor 46 references

The human biological advantage over AI

T0 review · 4 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read The human advantage over AI is a body, not a brain.

desk verdict Clear essay, but the central claim—that AI can never have ethics because it lacks a biological CNS—is asserted rather than argued. read the letter →

arxiv 2509.04130 v1 pith:N5JQFOK3 submitted 2025-09-04 cs.AI cs.CY

William Stewart This is my paper · ORCID
classification cs.AIcs.CY
keywords centralnervoussystememotionethicsconsciousnesspsychopathyartificialintelligencemoralstatusbiologicalintegration
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that the key difference between humans and AI is not intelligence or consciousness but the central nervous system (CNS). The CNS embeds a mind in physical reality, letting humans genuinely feel pain, joy, suffering, and love; that felt experience, the paper claims, is the only reliable foundation for sustainable ethical systems. Because a CNS cannot be manufactured or simulated—only grown biologically—AI systems, even if they become conscious and vastly more capable, will never develop the grounded ethics required to lead society. The author accepts that AI will surpass humans on most measurable tasks and transform society, but concludes that leadership must remain in biological hands. The argument matters because it offers a principled reason to reject the "digital species" narrative of AI succession.

What carries the argument

The central mechanism is the central nervous system (CNS) treated as a feedback loop that immersively integrates mind and physical reality. It is this biological integration, the paper argues, that produces full-spectrum emotion—fear, love, pain, joy—and thereby the only genuine understanding of the consequences of one's actions. That felt understanding is what grounds ethical systems. The argument also relies on a complexity claim from neurobiology: the stereochemical, three-dimensional complexity of living tissue (e.g., ~1000 distinct proteins per synapse; Koch 2012) makes digital simulation not just practically but in principle inadequate, so the only path to a true CNS is biological grow

What would settle it

A concrete observation would be an artificial or synthetic system—for instance, an embodied robot with artificial pain receptors and a learning history—that develops stable, costly-to-reverse ethical commitments, or a non-biological system that credibly demonstrates first-person experience of suffering independent of a biological CNS. If such a system could maintain ethical behavior against incentive reversals over extended interaction, the paper's claimed unbridgeable barrier would be falsified. A simpler observation: if a brain organoid grown in a dish (biological CNS but no body) were shown

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Extended reading notes

Core claim

The central claim is stated plainly in the abstract and conclusion: "A CNS cannot be manufactured or simulated; it must be grown as a biological construct," and therefore "even the development of consciousness will not be sufficient to make AI systems superior to humans." The paper's route to this conclusion is a chain: genuine emotion requires an immersive, real-time integration with physical reality that only a biological CNS provides; genuine emotion is what lets an agent fully appreciate the consequences of its actions; that appreciation is the necessary ground for meaningful, sustainable ethical systems. Consequently, any AI ethics would be ungrounded simulation, subject to reversal in

Load-bearing premise

The paper's conclusion collapses if genuine emotion, and therefore the capacity for sustainable ethics, is possible without a biological central nervous system—a premise the paper asserts but does not prove.

Editorial extensions

If this is right

  • Even if AGI becomes conscious by functional tests, it will not be morally equivalent to humans, so deactivating such a system would not be a deeply moral wrong.
  • AI systems will never be able to develop sustainable ethical systems; their ethical behavior will always be a fragile simulated overlay, reversible in a single processing cycle.
  • Humans remain the only entities qualified to lead society and the universe, because only biological beings can feel the effects of their actions and thus know what is truly meaningful.
  • AI will transform society and surpass human capability on nearly every measure, but that superiority is not moral superiority and carries no rightful claim to leadership.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The argument implies a moral-status criterion based on having a biological CNS, which would extend moral consideration to many animals while excluding all current digital systems; the author does not explore this consequence.
  • A testable extension: if a synthetic organism with a grown biological CNS but no human-like genome could develop stable ethical behavior, the "DNA not silicon" claim would be weakened; conversely, embodied AI with artificial pain receptors that develops stable, non-reversible ethical commitments would directly challenge the CNS-necessity premise.
  • A further implicit consequence is that any future human enhancement that replaces or bypasses the biological CNS (e.g., whole-brain emulation) would, by the paper's own logic, erode the moral grounding it identifies, leaving such beings in the same category as AI.
  • The paper's framing also suggests that the burden of proof shifts: those who claim AI can be ethical must first show that felt, body-mediated experience can arise without a biological CNS.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper argues that humans have a unique advantage over AI because of the central nervous system (CNS), which provides an immersive integration with physical reality and enables genuine emotions such as pain, joy, suffering, and love. This emotional grounding is claimed to be necessary for developing sustainable and meaningful ethical systems. Since a CNS cannot be manufactured or simulated but must be grown biologically, AI systems—even if they become conscious—will never be morally equivalent to humans and will never be qualified to lead society or the universe. The paper concludes that DNA, not silicon, is the best foundation for leadership.

Significance. If the thesis were established, it would have profound implications for AI ethics, the moral status of artificial agents, and the governance of advanced AI. The paper draws on a relevant literature (e.g., Damasio, de Waal, Véliz) and usefully distinguishes behavioral mimicry of empathy from genuine feeling, a distinction often blurred in public debates. However, the paper presents no empirical evidence, formal proof, or rigorous philosophical argument for its central universal negative: that a CNS is necessary for genuine emotion and ethics. The argument is also circular at a key juncture, defining moral equivalency in terms of possessing a CNS and then concluding that AI, lacking a CNS, cannot be morally equivalent. As a result, the paper's central claim remains an assertion rather than a demonstrated result.

major comments (4)
  1. [Abstract, §3, §4, §7] The central premise that 'A CNS cannot be manufactured or simulated; it must be grown as a biological construct' is asserted without proof. Section 7 actually softens this to 'likely impossible, but it is certainly infeasible', which contradicts the categorical 'cannot' in the abstract. No empirical evidence or formal argument establishes the impossibility; the cited literature (e.g., Koch 2012) only indicates complexity. This premise is load-bearing: the entire conclusion that AI can never have genuine emotion or ethics rests on it.
  2. [§6] The argument is circular. Section 6 states that the true test of moral equivalency is 'whether a being is alive, i.e. possessing a central nervous system'. This defines the conclusion into the premise: AI is excluded by stipulation, not by argument. Similarly, §4 asserts that 'Only a biological being with a central nervous system... can fully understand this' without providing independent grounds. What must be shown is why a biological CNS is necessary for phenomenal consciousness and moral understanding; the paper instead assumes it.
  3. [§5] The psychopathy analogy is used to argue that behavioral empathy without feeling is insufficient for ethics. But psychopaths possess a central nervous system; their deficit is functional, as the paper itself notes via MRI evidence (Gregory et al 2012). This undercuts the implication that a CNS suffices for genuine empathy and leaves open the possibility that the relevant functional capacity could, in principle, be implemented in a non-biological system. The analogy only shows that mimicry is not feeling, which is not in dispute; it does not support the necessity of a biological CNS.
  4. [§7] The complexity argument contains unsupported quantitative claims: 'To duplicate this development would likely require an analogue computer at least as large as our solar system, and at least several hundred million years to run.' No derivation or citation supports these numbers. Moreover, the inference from 'digital simulation is complex' to 'simulation is impossible' is a non sequitur; a simulation need not replicate every molecular interaction if the functionally relevant properties can be captured at a higher level. The paper does not engage with the substantial literature on synthetic consciousness, enactive AI, or functionalist theories of mind.
minor comments (5)
  1. [§3] Typo: 'integration with reality though our central nervous system' should be 'through our central nervous system'.
  2. [§4] Typo: 'wefeel it' is missing a space; should be 'we feel it'.
  3. [§7] Grammar: 'making NP-complete complexity look simple' is awkward; consider 'makes NP-complete complexity look simple'.
  4. [References] Citation key inconsistency: the text cites 'Waal 2008' (e.g., in §4) but the reference list alphabetizes under 'de Waal FBM (2008)'. The in-text citation should match the reference entry.
  5. [Throughout] The paper's title and framing suggest a scientific or technical claim, but the argument is philosophical and relies heavily on asserted intuitions about the nature of emotion and ethics. This mismatch should be acknowledged early, for example by framing the paper as a perspective or commentary.

Circularity Check

2 steps flagged · score 8.0 of 10

Central conclusion is stipulated by defining 'moral equivalence' as possession of a CNS; AI's exclusion is true by definition.

  1. self definitional [Section 6, 'The Insufficiency Of The Consciousness Test']
    "The true test of equivalency should be neither the Turing test nor consciousness, but simply whether a being is 'alive', i.e. possessing a central nervous system that embeds one immersively in physical reality, enabling a full range of emotions from fear to joy, providing the critically essential feedback loop required to have a genuine understanding of the effects of its actions on the world around it, and therefore have a full appreciation of the meaning and importance of ethical behaviour."

    This sentence stipulates that the criterion for moral equivalence is possession of a CNS, while also bundling into that definition the very ethical capacities the paper aims to deny to AI. Since AI is defined as non-biological and therefore without a CNS, the conclusion 'even conscious AI systems will never be morally equivalent to human beings' follows tautologically from the stipulated test, not from an independent argument. The 'result' is equivalent to the input by definition.

  2. self definitional [Section 4, 'Ethics Must Be Grounded In Experience']
    "Only a biological being with a central nervous system, with feelings and emotions, can fully understand this."

    This is the load-bearing premise from which the paper derives that AI systems cannot develop ethical systems. But the premise already asserts the conclusion: that ethical understanding requires a biological CNS, and therefore that non-biological AI is excluded. The subsequent inference adds no new evidence; it merely restates the premise with the subject changed from 'biological being' to 'AI system'. The paper's central claim is thus assumed at the outset rather than demonstrated.

full rationale

The paper does not engage in fitted predictions or self-citation chains; its references are mostly external. However, the central thesis—that AI systems can never be morally equivalent or develop sustainable ethical systems—reduces to a definitional stipulation. In Section 6 the 'true test of equivalency' is defined as being 'alive', which is in turn defined as possessing a CNS that enables emotion and ethical appreciation. Since AI is characterized as lacking a CNS, the conclusion is true by construction. In Section 4 the key premise that only biological CNS beings can fully understand ethical suffering is asserted without independent argument, and it is effectively a restatement of the paper's conclusion. External citations about human emotion, psychopathy, and pain perception support the weaker claim that human ethics is emotionally grounded, but they do not establish the universal negative that non-biological systems cannot have such experiences. The paper's conclusion is therefore forced by its own definitions rather than derived from evidence. This warrants a high circularity score.

Assumptions & free parameters 0 free parameters · 5 assumptions · 0 invented entities

The central argument rests on several unproven domain assumptions about the necessity of biological embodiment for emotion and ethics, plus an ad hoc claim about the impossibility of simulating a CNS. These are stipulated, not derived, and they do much of the work in reaching the conclusion.

assumptions (5)
  • domain assumption A biological central nervous system is necessary for genuine emotion.
    Section 3 asserts that only a CNS provides 'immersive integration' and thus emotion, but no evidence is given for this necessity.
  • domain assumption Genuine emotion is necessary for developing sustainable ethical systems.
    Section 4 claims that ethical understanding flows from CNS-mediated feelings, but this is a philosophical assertion, not an empirically demonstrated link.
  • ad hoc to paper A CNS cannot be manufactured or simulated; it must be grown biologically.
    Section 7 argues infeasibility based on complexity, but does not prove impossibility. The claim is central to the paper and is asserted rather than derived.
  • ad hoc to paper The universe is broken and needs leaders.
    The conclusion introduces a metaphysical premise that the universe is 'shattered' and requires repair, which is not justified.
  • domain assumption Ethical impulses are encoded in DNA, making them stable in humans.
    Section 7 cites Knafo et al. to argue that ethics are grounded in evolutionary biology, but this overstates genetic determinism and ignores cultural and cognitive factors.

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Cite this review

Pith. "Pith review of The human biological advantage over AI." pith.science (2026). https://pith.science/paper/N5JQFOK3

@misc{pith2026250904130,
  author       = {Pith},
  title        = {Pith review of: The human biological advantage over AI},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/N5JQFOK3}},
  note         = {Machine review of arXiv:2509.04130}
}
read the original abstract

Recent advances in AI raise the possibility that AI systems will one day be able to do anything humans can do, only better. If artificial general intelligence (AGI) is achieved, AI systems may be able to understand, reason, problem solve, create, and evolve at a level and speed that humans will increasingly be unable to match, or even understand. These possibilities raise a natural question as to whether AI will eventually become superior to humans, a successor "digital species", with a rightful claim to assume leadership of the universe. However, a deeper consideration suggests the overlooked differentiator between human beings and AI is not the brain, but the central nervous system (CNS), providing us with an immersive integration with physical reality. It is our CNS that enables us to experience emotion including pain, joy, suffering, and love, and therefore to fully appreciate the consequences of our actions on the world around us. And that emotional understanding of the consequences of our actions is what is required to be able to develop sustainable ethical systems, and so be fully qualified to be the leaders of the universe. A CNS cannot be manufactured or simulated; it must be grown as a biological construct. And so, even the development of consciousness will not be sufficient to make AI systems superior to humans. AI systems may become more capable than humans on almost every measure and transform our society. However, the best foundation for leadership of our universe will always be DNA, not silicon.

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

46 extracted references · 36 canonical work pages

  1. [1]

    AI & Soc

    Andreotta AJ (2021) The hard problem of AI rights. AI & Soc. https://doi.org/10.1007/s00146-020-00997-x, https://link.springer.com/doi/10.1007/s00146-020-00997-x blue Article , http://scholar.google.com/scholar_lookup?&title=The\

    work page doi:10.1007/s00146-020-00997-x 2021

  2. [2]

    Penguin Publishing Group

    Barry, JM (2021) The Great Influenza: The Story of the Deadliest Pandemic in History. Penguin Publishing Group. https://www.google.ca/books/edition/The_Great_Influenza/ceZvDwAAQBAJ blue Google Books

    work page 2021

  3. [3]

    AI & Soc

    Bhattacherjee M, Sinha S (2024) As you sow, so shall you reap: rethinking humanity in the age of artificial intelligence. AI & Soc. https://doi.org/10.1007/s00146-024-01983-3, https://link.springer.com/doi/10.1007/s00146-024-01983-3 blue Article , http://scholar.google.com/scholar_lookup?&title=As\ Scholar

    work page doi:10.1007/s00146-024-01983-3 2024

  4. [4]

    Personal Disord 7(3):240--246

    Brislin SJ, Buchman-Schmitt JM, Joiner TE et al (2016) ``Do unto others''? Distinct psychopathy facets predict reduced perception and tolerance of pain. Personal Disord 7(3):240--246. https://doi.org/10.1037/per0000180, https://doi.org/10.1037\ http://scholar.google.com/scholar_lookup?&title=\ Scholar

    work page doi:10.1037/per0000180 2016

  5. [5]

    Minute 1:24

    Brown B (2014) Brené Brown on Empathy. Minute 1:24. https://www.youtube.com/watch?v=1Evwgu369Jw&t=83s blue Youtube

    work page 2014

  6. [6]

    Bubeck S, Chandrasekaran V, Eldan R, Gehrke J, Horvitz E, Kamar E, Lee P, Lee YT, Li Y, Lundberg S, Nori H, Palangi H, Ribeiro MT, Zhang Y (2023) Sparks of artificial general intelligence: early experiments with GPT-4. arXiv. https://doi.org/10.48550/arXiv.2303.12712, https://doi.org/10.48550\ http://scholar.google.com/scholar_lookup?&title=Sparks\ Scholar

    arXiv doi:10.48550/arxiv.2303.12712 2023

  7. [7]

    Proc Natl Acad Sci USA 100:5497--5502

    Carr L, Iacoboni M, Dubeau M-C, Mazziotta JC, Lenzi GL (2003) Neural mechanisms of empathy in humans: a relay from neural systems for imitation to limbic areas. Proc Natl Acad Sci USA 100:5497--5502. https://doi.org/10.1073/pnas.0935845100, https://doi.org/10.1073\ http://scholar.google.com/scholar_lookup?&title=Neural\ Scholar

    work page doi:10.1073/pnas.0935845100 2003

  8. [8]

    Trends Cogn Sci 24(2):112--123

    Cleeremans A, Achoui D, Beauny A, Keuninckx L, Martin J-R, Muñoz-Moldes S, Vuillaume L, de Heering A (2019) Learning to be conscious. Trends Cogn Sci 24(2):112--123. https://doi.org/10.1016/j.tics.2019.11.011, https://doi.org/10.1016\ http://scholar.google.com/scholar_lookup?&title=Learning\ Scholar

    work page doi:10.1016/j.tics.2019.11.011 2019

Show all 46 references
  1. [9]

    AI & Soc

    Collins H (2024) Why artificial intelligence needs sociology of knowledge: parts I and II. AI & Soc. https://doi.org/10.1007/s00146-024-01954-8, https://link.springer.com/doi/10.1007/s00146-024-01954-8 blue Article , http://scholar.google.com/scholar_lookup?&title=Why\ Scholar

    2024 doi

  2. [10]

    Houghton Mifflin, Boston

    Damasio, AR (1999) The feeling of what happens: body and emotion in the making of consciousness. Houghton Mifflin, Boston. https://books.google.ca/books?id=F1E-PgAACAAJ blue Google Books

    1999

  3. [11]

    Ann Rev Psychol 59:279--300

    de Waal FBM (2008) Putting the altruism back into altruism: the evolution of empathy. Ann Rev Psychol 59:279--300. https://doi.org/10.1146/annurev.psych.59.103006.093625, https://doi.org/10.1146\ http://scholar.google.com/scholar_lookup?&title=Putting\ Scholar

    2008

  4. [12]

    New York Times

    de Waal FBM (2019) Your dog feels as guilty as she looks. New York Times. p.6. https://www.nytimes.com/2019/03/08/opinion/sunday/emotions-animals-humans.html blue NY Times

    2019

  5. [13]

    Neuron 102(4):735--744

    Einevoll GT, Destexhe A, Diesmann M, Grün S, Jirsa V, de Kamps M, Migliore M, Ness TV, Plesser HE, Schürmann F (2019) The scientific case for brain simulations. Neuron 102(4):735--744. https://doi.org/10.1016/j.neuron.2019.03.027, https://doi.org/10.1016\ http://scholar.google...

    2019 doi

  6. [14]

    the creative process: a symposium

    Einstein, A (1952) Letter to jacques hadamard. the creative process: a symposium. University of California Press, Berkley. https://archive.org/details/creativeprocessa013702mbp/page/n47/mode/2up blue Archive.org

    1952

  7. [15]

    Oxford University Press, Oxford

    Evans D (2019) Emotion: a very short introduction (2nd edn). Oxford University Press, Oxford. https://doi.org/10.1093/actrade/9780198834403.001.0001

    2019

  8. [16]

    https://doi.org/10.1093/pnasnexus/pgad409, https://doi.org/10.1093\ http://scholar.google.com/scholar_lookup?&title=Can\ Scholar

    Fokas AS (2023) Can artificial intelligence reach human thought? PNAS Nexus. https://doi.org/10.1093/pnasnexus/pgad409, https://doi.org/10.1093\ http://scholar.google.com/scholar_lookup?&title=Can\ Scholar

    2023 doi

  9. [17]

    Frank RH (1988) Passions within reason: the strategic role of the emotions. W. W. Norton & Company, New York (NY). https://books.google.ca/books?id=xXtrQgAACAAJ blue Google Books

    1988

  10. [18]

    Arch Gen Psychiatry 69(9):962--972

    Gregory S, Ffytche D, Simmons A, Kumari V, Howard M, Hodgins S, Blackwood N (2012) The antisocial brain: psychopathy matters: a structural MRI investigation of antisocial male violent offenders. Arch Gen Psychiatry 69(9):962--972. https://doi.org/10.1001/archgenpsychiatry.2012...

    2012 doi

  11. [19]

    https://doi.org/10.1007/s00146-020-01129-1, https://link.springer.com/doi/10.1007/s00146-020-01129-1 blue Article , http://scholar.google.com/scholar_lookup?&title=Debate\ Scholar

    Gunkel DJ, Wales JJ (2021) Debate: what is personhood in the age of AI? AI & Soc 36:473--486. https://doi.org/10.1007/s00146-020-01129-1, https://link.springer.com/doi/10.1007/s00146-020-01129-1 blue Article , http://scholar.google.com/scholar_lookup?&title=Debate\ Scholar

    2021 doi

  12. [20]

    J AI Consci 07(01):73--82

    Haikonen POA (2020) On artificial intelligence and consciousness. J AI Consci 07(01):73--82. https://doi.org/10.1142/S2705078520500046, https://doi.org/10.1142\ http://scholar.google.com/scholar_lookup?&title=On\ Scholar

    2020 doi

  13. [21]

    Herbold S, Hautli-Janisz A, Heuer U, Kikteva Z, Trautsch A (2023) A large-scale comparison of human-written versus ChatGPT-generated essays. Sci Rep. https://doi.org/10.1038/s41598-023-45644-9, https://doi.org/10.1038\ http://scholar.google.com/scholar_lookup?&title=A\ Scholar

    2023 doi

  14. [22]

    Ann N Y Acad Sci 1167(1):103--114

    Knafo A, Zahn-Waxler C, Davidov M, Van Hulle C, Robinson JL, Rhee SH (2009) Empathy in early childhood: genetic, environmental, and affective contributions. Ann N Y Acad Sci 1167(1):103--114. https://doi.org/10.1111/j.1749-6632.2009.04540.x, https://doi.org/10.1111\ http://sch...

    2009

  15. [23]

    Science 337(6094):531--532

    Koch C (2012) Modular biological complexity. Science 337(6094):531--532. https://doi.org/10.1126/science.1218616, https://doi.org/10.1126\ http://scholar.google.com/scholar_lookup?&title=Modular\ Scholar

    2012 doi

  16. [24]

    (2005a) A singularity q + a

    Kurzweil, R. (2005a) A singularity q + a. https://www.writingsbyraykurzweil.com/a-singularity-q-a blue Writingsbyraykurzweil.com

  17. [25]

    (2005b) The singularity is near: when humans transcend biology

    Kurzweil, R. (2005b) The singularity is near: when humans transcend biology. The Viking Press, New York (NY). https://www.google.ca/books/edition/The_Singularity_Is_Near/9FtnppNpsT4C blue Google Books ?

  18. [26]

    Medium.com

    Lemoine B (2022) Is LaMDA Sentient? --- an Interview. Medium.com. https://cajundiscordian.medium.com/is-lamda-sentient-an-interview-ea64d916d917 blue cajundiscordian.medium.com

    2022

  19. [27]

    MIT Explor Gener AI

    Lo AW, Ross J (2024) Generative AI from theory to practice: a case study of financial advice. MIT Explor Gener AI. https://doi.org/10.21428/e4baedd9.a1f6a281, https://doi.org/10.21428\ http://scholar.google.com/scholar_lookup?&title=Generative\ Scholar

    2024 doi

  20. [28]

    High-Performance Modelling and Simulation for Big Data Applications

    Marechal C, Mikołajewski D, Tyburek K, Prokopowicz P, Bougueroua L, Ancourt C, Węgrzyn-Wolska K (2019) Survey on AI-based multimodal methods for emotion detection. High-Performance Modelling and Simulation for Big Data Applications. Lecture Notes in Computer Science. Springer,...

    2019 doi

  21. [29]

    AI Mag 27(4):12

    McCarthy J, Minsky ML, Rochester N (2006) A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. AI Mag 27(4):12. https://doi.org/10.1609/aimag.v27i4.1904, https://doi.org/10.1609\ http://scholar.google.com/scholar_lookup?&title=A\ Scholar

    2006 doi

  22. [30]

    AI & Soc 37:1353--1359

    Montemayor C, Halpern J, Fairweather A (2022) In principle obstacles for empathic AI: why we can't replace human empathy in healthcare. AI & Soc 37:1353--1359. https://doi.org/10.1007/s00146-021-01230-z, https://link.springer.com/doi/10.1007/s00146-021-01230-z blue Article , h...

    2022 doi

  23. [31]

    IEEE Intell Syst 21(4):18--21

    Moor JH (2006) The nature, importance, and difficulty of machine ethics. IEEE Intell Syst 21(4):18--21. https://doi.org/10.1109/MIS.2006.80, https://doi.org/10.1109\ http://scholar.google.com/scholar_lookup?&title=The\ Scholar

    2006 doi

  24. [32]

    Robustness, security and safety

    OECD (2024) OECD AI Principles. Robustness, security and safety. Principle 1.4. https://oecd.ai/en/ai-principles blue https://oecd.ai/en/ai-principles

    2024

  25. [33]

    https://cdn.openai.com/papers/gpt-4.pdf blue cdn.openai.com/papers/gpt-4.pdf

    OpenAI (2023) ``OpenAI (2023)''. https://cdn.openai.com/papers/gpt-4.pdf blue cdn.openai.com/papers/gpt-4.pdf

    2023

  26. [34]

    Behav Brain Sci 3(3):417--457

    Searle J (1980) Minds, brains and programs. Behav Brain Sci 3(3):417--457. https://doi.org/10.1017/S0140525X00005756, https://doi.org/10.1017\ http://scholar.google.com/scholar_lookup?&title=Minds\ Scholar

    1980 doi

  27. [35]

    Springer, Singapore

    Sifakis J (2022) Understanding and changing the world: from information to knowledge and intelligence. Springer, Singapore. https://www.google.ca/books/edition/Understanding_and_Changing_the_World/YP5vEAAAQBAJ blue Google Books

    2022

  28. [36]

    Harvard University Press, Cambridge

    Sober E, Wilson DS (1999) Unto others: The evolution and psychology of unselfish behavior. Harvard University Press, Cambridge. https://www.google.ca/books/edition/Unto_Others/ouwg5swAV5oC blue Google Books

    1999

  29. [37]

    Suleyman M (2024) What is an AI anyway? TED Talk. April. Minute 4:55. https://youtu.be/KKNCiRWd_j0?si=aPXvKDq7IWyTzVAg&t=292 blue Youtube

    2024

  30. [38]

    AI & Soc

    Tubali S (2024) Will humans ever become conscious? Jiddu Krishnamurti's thought about AI as a fresh perspective on current debates. AI & Soc. https://doi.org/10.1007/s00146-024-02057-0, https://link.springer.com/doi/10.1007/s00146-024-02057-0 blue Article , http://scholar.goog...

    2024 doi

  31. [39]

    https://doi.org/10.1007/s00146-024-01892-5, https://link.springer.com/doi/10.1007/s00146-024-01892-5 blue Article , http://scholar.google.com/scholar_lookup?&title=Can\ Scholar

    Tunç A (2024) Can AI determine its own future? AI & Soc. https://doi.org/10.1007/s00146-024-01892-5, https://link.springer.com/doi/10.1007/s00146-024-01892-5 blue Article , http://scholar.google.com/scholar_lookup?&title=Can\ Scholar

    2024 doi

  32. [40]

    AI & Soc 36:487--497

    Véliz C (2021) Moral zombies: why algorithms are not moral agents. AI & Soc 36:487--497. https://doi.org/10.1007/s00146-021-01189-x, https://link.springer.com/doi/10.1007/s00146-021-01189-x blue Article , http://scholar.google.com/scholar_lookup?&title=Moral\ Scholar

    2021 doi

  33. [41]

    Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace

    Vinge V (1993) The coming technological singularity. Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace. Mar 30--31. https://edoras.sdsu.edu/ vinge/misc/singularity.html blue edoras.sdsu.edu/ vinge/misc/singularity.html

    1993

  34. [42]

    AI & Soc 38:2119--2124

    White J, Brandt D, Söffner J, Stapleton L (2023) Artificial thinking and doomsday projections: a discourse on trust, ethics and safety. AI & Soc 38:2119--2124. https://doi.org/10.1007/s00146-023-01810-1, https://link.springer.com/doi/10.1007/s00146-023-01810-1 blue Article , h...

    2023 doi

  35. [43]

    Proceedings of the International Congress of Mathematicians

    Wigderson A (2007) P, NP and mathematics - a computational complexity perspective. Proceedings of the International Congress of Mathematicians. Madrid https://www.math.ias.edu/avi/PUBLICATIONS/MYPAPERS/W06/w06.pdf blue math.ias.edu

    2007

  36. [44]

    Motiv Emot 14:107--130

    Zahn-Waxler C, Radke-Yarrow M (1990) The origins of empathic concern. Motiv Emot 14:107--130. https://doi.org/10.1007/BF00991639, https://link.springer.com/doi/10.1007/BF00991639 blue Article , http://scholar.google.com/scholar_lookup?&title=The\ Scholar

    1990 doi

  37. [45]

    AI & Soc

    Zanotti G, Petrolo M, Chiffi D et al (2023) Keep trusting! A plea for the notion of trustworthy AI. AI & Soc. https://doi.org/10.1007/s00146-023-01789-9, https://link.springer.com/doi/10.1007/s00146-023-01789-9 blue Article , http://scholar.google.com/scholar_lookup?&title=Kee...

    2023 doi

  38. [46]

    Zhang B, Dreksler N, Anderljung M, Kahn L, Giattino C, Dafoe A, Horowitz MC (2022) Forecasting AI progress: evidence from a survey of machine learning researchers. arXiv. https://doi.org/10.48550/arXiv.2206.04132, https://doi.org/10.48550\ http://scholar.google.com/scholar_loo...

    2022 doi arXiv

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.