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Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe?

T0 review · 2 major / 2 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read Two large surveys, one of 582 AI researchers and one of 838 US adults, find that both groups regard AI systems with subjective experience as more likely than not to exist by 2100 (median 70% and 60%) and that majorities in both groups…

desk verdict A solid, preregistered survey that gives the first direct comparison of AI researchers and the US public on AI subjective experience; the headline forecasts are broadly credible, but the construct validity question deserves a sensitivity analysis before the specific numbers are taken as precise. read the letter →

arxiv 2506.11945 v1 pith:S2XD57HW submitted 2025-06-13 cs.CY cs.AI

Noemi Dreksler , Lucius Caviola , David Chalmers , Carter Allen , Alex Rand , Joshua Lewis , Philip Waggoner , Kate Mays
show 1 more author
Jeff Sebo
This is my paper
classification cs.CYcs.AI
keywords AIsubjectiveexperiencepublicopinionsurveyexpertconsciousnessforecastinggovernancemoralstatusofsentientsafeguards
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 reports a survey of 582 AI researchers and 838 US adults asking whether and when AI systems might have subjective experience — an internal life from a single point of view, such that there is "something it is like" to be the system — and how such systems should be treated and governed. The central finding is that both groups regard such systems as more likely than not to exist by 2100, with median probabilities of 70% among AI researchers and 60% among the public, and no statistically significant difference between the groups' timelines. The public is markedly more open to the possibility that such systems will never exist (median 25%, versus 10% for researchers) and is more cautious about building them. Yet majorities of both groups agree that AI developers should implement safeguards now (68% of researchers, 85% of the public) and that such systems, if created, should be held accountable and behave ethically, even as views on rights and moral status are divided. If the results are right, there is broader agreement than is often assumed — both on the realistic possibility of machine minds this century and on precautionary action in the meantime.

What carries the argument

The load-bearing instrument is the survey battery itself, anchored by a stipulated definition: subjective experience is "the ability to experience the world from a single point of view, including experiences such as perceiving... and feeling," so that an AI system with it would have "something it is like" to be that system — a definition that subsumes common conceptions of consciousness and sentience. Forecasts were elicited in two framings, fixed dates (2024, 2034, 2100) and fixed probabilities (10%, 50%, 90%), and each respondent's answers were encoded as a continuous probability distribution by a sequential fitting procedure — metalog, then a quantile-parameterised distribution, then a three-component skew-normal mixture, then a shifted log-normal — which allows group-level aggregation by mean and by median. A separate question asking for the probability that such systems will never exist does independent work: it exposes a public-researcher split (median 25% versus 10%) that the timeline questions alone would have concealed. The conjoint safeguard experiment, in which explicitly noting the absence of safeguards lowered support for a hypothetical AI project, serves as a behavioral check on the stated governance attitudes.

What would settle it

Two concrete tests would settle the matter: re-contacting the same respondents weeks later to see whether the median 2100 probabilities hold, and re-running the survey with alternative definitions — one emphasizing valenced experience (pleasure and pain, which the paper's own auxiliary results show shifts timelines later) and one that adds a "never" option to the fixed-probability framing. If the medians fall below 50% under either change, the headline "more likely than not by 2100" result is a framing artifact rather than a stable belief.

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Extended reading notes

Core claim

The paper's claim, stated on its own terms, is that technical AI researchers and the general US public hold similar, policy-relevant beliefs about AI subjective experience. Both groups think current systems almost certainly lack it (median probability 1% and 5% for 2024), put a 25% and 30% median chance on it within a decade, and a 70% and 60% median chance by 2100; fitting each respondent's forecast into a continuous probability distribution puts the median 50% likelihood at 2050 for both groups. Both groups think we would be only somewhat more likely than not to recognize such a system if it existed (median 60%), believe that between "somewhat" and "moderately" confident would be enough to grant some moral consideration, and rate technical AI researchers, neuroscientists and psychologists, and AI ethics researchers as the most important voices in any determination. On treatment and governance, majorities in both groups agree that such systems should be held accountable for their actions and should behave well, and that developers should start implementing safeguards now; support for protecting their welfare is real but far weaker than support for protecting animals or the environment, and socio-political rights are rejected by pluralities. The paper reads this pattern as evidence that both groups take machine subjective experience seriously as a live possibility this century, while remaining uncertain about the timeline and divided on the response.

Load-bearing premise

The survey results stand or fall on the assumption that respondents understood "subjective experience" the way the paper defines it and that their answers reflect stable beliefs rather than snap judgments about an abstract and unfamiliar topic; the paper itself flags this, noting that responses may have been formed ad hoc during the survey and could be unstable or sensitive to question framing.

Editorial extensions

If this is right

  • Policymakers can build on a shared majority premise: both experts and the public want AI developers to implement safeguards against risks from subjective AI now, years before such a system is plausibly claimed to exist.
  • Future AI-forecasting surveys should include a "never" probability question, because the timeline questions alone concealed a significant public-researcher difference in skepticism.
  • Governance debates should expect a public that is more precautionary than the technical community — more supportive of bans, of regulation now, and of never building such systems — while researchers are readier to build.
  • Any credible process for determining AI subjective experience will need to combine technical AI, neuroscience, psychology, and AI-ethics expertise; both groups rated policymakers' views as least important.
  • Even if subjective experience in AI were established, welfare protection would face an uphill political path: support sits far below that for animals and the environment and close to that for business corporations.

Reading between the lines

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

  • The 70% and 60% medians likely overstate stable belief: the paper's own auxiliary results show that only about half of each sample regards subjective experience as required for consciousness or sentience, and the authors report strong framing sensitivity, so a deliberative or repeated elicitation would probably produce lower and more divided numbers.
  • The public's higher "never" probability (25% versus 10%) may foreshadow political friction: as AI systems become more human-like, the public's greater tendency to see inner life in them could push for stronger precaution than the technical community, which mostly thinks advanced performance needs no experience, is willing to accept.
  • Because both groups would act on only moderate confidence, the real governance question is not "are they conscious?" but how institutions should behave under diagnostic uncertainty — a question the paper documents but does not itself answer.
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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

2 major / 2 minor

Summary. The paper reports a large survey of 582 AI researchers who published in leading venues and 838 nationally representative US participants, asking about beliefs concerning AI systems with subjective experience. It measures probabilistic forecasts for when such systems might exist, views on how we could determine and recognize subjective experience, and attitudes toward the moral status, rights, responsibilities, and governance of such systems. The headline findings are that median respondents in both groups give roughly 70% (AI researchers) and 60% (public) probability that AI systems with subjective experience exist by 2100, that the public assigns a higher probability than AI researchers to the possibility that such systems will never exist (median 25% vs. 10%), and that majorities in both groups support implementing safeguards now, while views on rights, welfare protections, and whether such systems should be created are divided. The authors emphasize that the forecasts should be treated as descriptive of current attitudes rather than as predictive indicators.

Significance. If the results hold, this is the first large-scale comparative survey of AI researchers and the public on AI subjective experience, providing a valuable empirical foundation for policy and ethics debates. The study is preregistered, uses a large expert sample with a neutral recruitment message, applies Holm-Bonferroni corrections for multiple comparisons, and includes unusually careful and detailed limitations sections. The authors are appropriately cautious that the forecasting numbers reflect attitudes, not predictions. The central construct-validity issue—whether respondents are answering about the stipulated definition of subjective experience—is raised in the authors' own limitations but needs a direct empirical response, because it bears on the paper's main descriptive claim.

major comments (2)
  1. [Section 3.1 and SI Section A.2, Figure 13] The headline forecasts (median 70% by 2100 for AI researchers, 60% for the public) are claimed to describe beliefs about the stipulated definition of subjective experience, which 'subsumes common conceptions of both consciousness and sentience.' However, the survey's own preliminary capacity task shows that only about half of each sample selected 'subjective experience' as required for sentience (public 49%, AI researchers 55%) or for consciousness (AI researchers 53%). This is direct evidence that a substantial fraction of respondents used a different folk concept even after reading the definition. The consequence is not merely a caveat: if a large minority were forecasting 'AI consciousness' in a looser sense, the reported medians and the 'more likely than not by 2100' statement are not estimates of the same quantity for the full sample. Because the survey contains within-subject data, this is testable. I request that the authors report the forecasting and governance results separately for respondents who, in the capacity task, treated the stipulated subjective experience as required for sentience/consciousness, and for those who did not. If the restricted analyses materially change the headline estimates, the abstract and executive summary should be qualified accordingly. This analysis is load-bearing because the paper's central claim and policy conclusions are meant to track the stipulated concept, not a folk variant.
  2. [Section 2.1 and Section 3, Figure 1(B), Table 2] The authors acknowledge that the fixed probability framing omitted a 'never' option and may have biased forecasts earlier (executive summary; Section 2.1). Yet the paper's combined aggregate forecasts—e.g., the statement in the Discussion that 'the median AI researcher and member of the US public believed there is a 10% chance... by 2030, a 50% chance... by 2050, a 90% chance... by 2100'—are built by pooling both framings and fitting distributions. If one framing is systematically biased, the pooled aggregate inherits that bias. The authors note that 'it is reasonable to take the fixed date results as more reliable than the fixed probability results,' but then present the pooled results as headline summaries. I request that the main text present fixed-date-only and fixed-probability-only aggregates as the primary summary (as in Table 2), or provide a sensitivity analysis showing that the pooled '90% by 2100' claim is robust to excluding the fixed probability framing. Without this, the pooled claims in the Discussion are not fully supported by the authors' own reliability assessment.
minor comments (2)
  1. [Section 2.1] The sentence 'An independent samples t-test revealed a statistically significant difference in the mean probability estimates between AI researchers in the two groups' contains a phrasing error: the comparison is between AI researchers and the public, not 'between AI researchers in the two groups.'
  2. [Abstract and Executive summary] The abstract states that 'Both groups perceived a need for multidisciplinary expertise to assess AI subjective experience,' but Figure 3 shows several substantial and significant between-group differences in which expertise sources are valued (e.g., AI ethics researchers, the AI system's own outputs, the public). Consider noting in the abstract or summary that the public places greater weight on several non-technical sources than AI researchers do.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the paper is a descriptive opinion survey, and its headline forecasts are direct summaries of elicited responses rather than derived quantities.

full rationale

The paper makes no formal derivation claims. The central results—median probabilities of 70% and 60% for AI subjective experience by 2100, and majority support for safeguards—are descriptive statistics computed directly from survey responses, not quantities derived from fitted parameters that were themselves calibrated to those responses. The distribution-fitting procedure (Section 6.3.1) encodes each respondent's elicited quantiles into a continuous distribution and then re-aggregates them; this is a summary of the data, not a prediction manufactured from an input. No fitted input is relabeled as a prediction, and no claim depends on an imported uniqueness theorem. The manuscript contains self-citations by co-authors (e.g., Chalmers, Sebo, Dreksler, Zhang et al. 2022), but these appear only in the literature review and framing sections, and none is load-bearing for the survey findings; the cited prior surveys are independent external benchmarks. The skeptical concern about construct validity—whether respondents answered about the stipulated definition of subjective experience—is a measurement-validity limitation, explicitly acknowledged in Section 3.1, and is not a circularity of derivation. Accordingly, the paper is self-contained as an empirical measurement study, and no circular step can be exhibited by quoting equations or reductions.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

No mathematical derivation underlies the descriptive claims. The main assumptions are sampling and construct-validity assumptions, all acknowledged in the paper.

assumptions (3)
  • domain assumption Survey responses reflect participants' genuine beliefs about the concept of subjective experience as defined.
    Central to interpretation; flagged by authors in Section 3.1 Folk conceptions.
  • domain assumption The AI researcher sample drawn from top-venue authors is representative of AI researchers broadly.
    Used to generalize from 582 respondents; authors note 6.2% response rate and 85% male sample in Section 6.1.
  • domain assumption The US public sample recruited via Prolific with representativeness criteria is representative of the national public.
    Prolific samples may differ from the general population; authors discuss in Section 6.1 and limitations.

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Cite this review

Pith. "Pith review of Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe?." pith.science (2026). https://pith.science/paper/S2XD57HW

@misc{pith2026250611945,
  author       = {Pith},
  title        = {Pith review of: Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe?},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/S2XD57HW}},
  note         = {Machine review of arXiv:2506.11945}
}
read the original abstract

We surveyed 582 AI researchers who have published in leading AI venues and 838 nationally representative US participants about their views on the potential development of AI systems with subjective experience and how such systems should be treated and governed. When asked to estimate the chances that such systems will exist on specific dates, the median responses were 1% (AI researchers) and 5% (public) by 2024, 25% and 30% by 2034, and 70% and 60% by 2100, respectively. The median member of the public thought there was a higher chance that AI systems with subjective experience would never exist (25%) than the median AI researcher did (10%). Both groups perceived a need for multidisciplinary expertise to assess AI subjective experience. Although support for welfare protections for such AI systems exceeded opposition, it remained far lower than support for protections for animals or the environment. Attitudes toward moral and governance issues were divided in both groups, especially regarding whether such systems should be created and what rights or protections they should receive. Yet a majority of respondents in both groups agreed that safeguards against the potential risks from AI systems with subjective experience should be implemented by AI developers now, and if created, AI systems with subjective experience should treat others well, behave ethically, and be held accountable. Overall, these results suggest that both AI researchers and the public regard the emergence of AI systems with subjective experience as a possibility this century, though substantial uncertainty and disagreement remain about the timeline and appropriate response.

Figures

Figures reproduced from arXiv: 2506.11945 by the authors.

Figure 1
Figure 1. Forecasts of AI researchers and the US public for when AI systems will have subjective [PITH_FULL_IMAGE:figures/full_fig_p009_1.png] view at source ↗
Figure 2
Figure 2. Determining AI subjective experience likelihood and confidence needed for moral [PITH_FULL_IMAGE:figures/full_fig_p012_2.png] view at source ↗
Figure 3
Figure 3. Perceived importance of different groups’ opinions and expertise in determining if an AI system [PITH_FULL_IMAGE:figures/full_fig_p013_3.png] view at source ↗
Figures from the paper (24 more)
Figure 4
Figure 4. Figure 4: Percentage of AI researchers and members of the US public who thought that different AI [PITH_FULL_IMAGE:figures/full_fig_p015_4.png]
Figure 5
Figure 5. Figure 5: Agreement with protections, rights, and responsibilities for AI systems with subjective [PITH_FULL_IMAGE:figures/full_fig_p016_5.png]
Figure 6
Figure 6. Figure 6: Agreement with welfare protection of different groups [PITH_FULL_IMAGE:figures/full_fig_p017_6.png]
Figure 7
Figure 7. Figure 7: Mean agreement on what AI developers and governments should do in regard to the [PITH_FULL_IMAGE:figures/full_fig_p018_7.png]
Figure 8
Figure 8. Figure 8: Percentage breakdowns for views on what AI developers should do in regard to the governance [PITH_FULL_IMAGE:figures/full_fig_p019_8.png]
Figure 9
Figure 9. Figure 9: Percentage breakdowns for views on what governments should do in regard to the governance [PITH_FULL_IMAGE:figures/full_fig_p020_9.png]
Figure 10
Figure 10. Figure 10: Percentage breakdowns for the public’s and AI researchers’ risk and benefit perceptions of AI [PITH_FULL_IMAGE:figures/full_fig_p021_10.png]
Figure 11
Figure 11. Figure 11: Discrepancies between when the US public and AI researchers predict an AI system will exist [PITH_FULL_IMAGE:figures/full_fig_p042_11.png]
Figure 12
Figure 12. Figure 12: Distribution of responses of how confident the US public and AI researchers were about their [PITH_FULL_IMAGE:figures/full_fig_p043_12.png]
Figure 13
Figure 13. Figure 13: Percentage of US public and AI researchers who say that each mental capacity is required to [PITH_FULL_IMAGE:figures/full_fig_p045_13.png]
Figure 14
Figure 14. Figure 14: Percentage of US public and AI researchers who say that AI systems will have each mental [PITH_FULL_IMAGE:figures/full_fig_p046_14.png]
Figure 15
Figure 15. Figure 15: Mean contribution and percentage breakdowns for to what extent eight capacities of mind [PITH_FULL_IMAGE:figures/full_fig_p047_15.png]
Figure 16
Figure 16. Figure 16: Mean support for hypothetical state-of-the-art AI project at a tech company that they believe [PITH_FULL_IMAGE:figures/full_fig_p048_16.png]
Figure 17
Figure 17. Figure 17: Distribution of median forecasts for AI subjective experience by level of generative of AI use [PITH_FULL_IMAGE:figures/full_fig_p058_17.png]
Figure 18
Figure 18. Figure 18: Effect of demographic and psychographic variables on AI researchers’ AI subjective [PITH_FULL_IMAGE:figures/full_fig_p060_18.png]
Figure 19
Figure 19. Figure 19: Effect of demographic and psychographic variables on the public’s AI subjective experience [PITH_FULL_IMAGE:figures/full_fig_p060_19.png]
Figure 20
Figure 20. Figure 20: Effect of demographic and psychographic variables on AI researchers’ views on the [PITH_FULL_IMAGE:figures/full_fig_p061_20.png]
Figure 21
Figure 21. Figure 21: Effect of demographic and psychographic variables on the public’s views on the importance of [PITH_FULL_IMAGE:figures/full_fig_p061_21.png]
Figure 22
Figure 22. Figure 22: Effect of demographic and psychographic variables on AI researchers’ views on the [PITH_FULL_IMAGE:figures/full_fig_p062_22.png]
Figure 23
Figure 23. Figure 23: Effect of demographic and psychographic variables on the public’s views on the [PITH_FULL_IMAGE:figures/full_fig_p063_23.png]
Figure 24
Figure 24. Figure 24: Effect of demographic and psychographic variables on AI researchers’ views on whether the [PITH_FULL_IMAGE:figures/full_fig_p064_24.png]
Figure 25
Figure 25. Figure 25: Effect of demographic and psychographic variables on the public’s views on whether the [PITH_FULL_IMAGE:figures/full_fig_p064_25.png]
Figure 26
Figure 26. Figure 26: Effect of demographic and psychographic variables on AI researchers’ views on the [PITH_FULL_IMAGE:figures/full_fig_p065_26.png]
Figure 27
Figure 27. Figure 27: Effect of demographic and psychographic variables on the public’s views on the governance of [PITH_FULL_IMAGE:figures/full_fig_p066_27.png]

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Forward citations

Cited by 2 Pith papers

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Reference graph

Works this paper leans on

53 extracted references · 52 canonical work pages · cited by 2 Pith papers

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