paper
active
2021
paper:isal-a-00465

Can Being Aware of the Illusion of Self Augment an Agent's Affordances: Integrating Buddhist Philosophy, Cognitive Science, and Artificial Life

ByThomas Doctorⓘ·Elizaveta Solomonovaⓘ·Bill Duane·Olaf Witkowskiⓘ84000: Unlocking the Tibetan Buddhist Canon for All, Bill Duane and Associates + 16 more
DOI 10.1162/isal_a_00465
Care and CognitionCare-Intelligence EthicsConsciousness, self, and biological computationCare-based cognition and selfless AIAffordancesArtificial LifeAgencyContemplative ScienceCognitive ScienceInformation Theory Of IndividualityContemplative PracticeMahāyāna BuddhismDistributed/distributable and dynamic selfPhilosophy of mindEmpowermentEnvironmental affordancesIllusion of SelfIntegration (Tononi's measure)+15 more

TL;DR

Awareness of the illusion of self — drawn from Buddhist 'no-self' (anātman) doctrine, contemplative neuroscience, and lucid dreaming research — can expand an agent's affordances, and this claim is amenable to formal modeling via artificial life frameworks. The paper's central move is to map three convergent domains: Mahāyāna Buddhist philosophy (specifically Maitreya-Asaṅga's rejection of singular, enduring selves), empirical findings linking 'selfing'-reduction practices to increased social connectedness (Hutcherson, Seppala & Gross, 2008) and prosocial behavior (Luberto et al., 2018 meta-analysis), and artificial life tools including predictive information (Bialek, 2001), empowerment (Klyubin et al., 2008), and integrated information (Tononi et al., 1994). The proposed integrative framework — which the paper terms an artificial life model of illusory selfhood — uses toy cognitive systems to simulate the effects of reduced self-reification without requiring direct interaction with meditating humans, thereby disentangling causal mechanisms. Lucid dreaming, documented to alter environmental affordances by enabling actions unavailable in waking life (Tholey, 1989), serves as a second empirical anchor alongside contemplative practice. The paper argues this implies that non-human intelligences in AI and artificial life, if designed or trained to treat selfhood as distributed and dynamic rather than fixed, may access qualitatively novel ranges of action — potentially yielding new fundamental principles for AI science and new categories of technology.

What to take away

  1. 1. Buddhist 'no-self' philosophy, specifically Mahāyāna sources such as Maitreya-Asaṅga's Mahāyānasūtrālaṃkāra, frames the self as an imputation over constantly changing causal factors rather than a substantial individual, which the paper treats as a design-relevant hypothesis for artificial agents.
  2. 2. Contemplative practices that reduce 'selfing' (the reification of an independent self) are empirically linked to increased social connectedness (Hutcherson, Seppala & Gross, 2008) and, per Luberto et al.'s 2018 systematic review and meta-analysis, to increases in empathy, compassion, and prosocial behaviors.
  3. 3. Lucid dreaming — dreams in which the dreamer knows they are dreaming (LaBerge & Rheingold, 1991) — is documented by Tholey (1989) and Stumbrys et al. (2014) to expand environmental affordances by enabling actions (e.g., flight) impossible in waking life, serving as a lived proof-of-concept that altered self-perception changes the action space.
  4. 4. The paper introduces an integrative artificial life modeling framework that proposes using information-theoretic measures — predictive information (Bialek, 2001; Ay, 2008), synergistic information (Edlund et al., 2011), multi-information (McGill, 1954), and Tononi et al.'s 1994 integration measure — to formally quantify shifts in an agent's affordances when self-boundaries are treated as permeable.
  5. 5. Empowerment, formalized by Klyubin, Polani & Nehaniv (2008) as the mutual information between an agent's actions and future sensory states, is nominated as the primary functional metric for operationalizing 'augmented affordances' in the proposed model.
  6. 6. Edlund et al. (2011) provide a precedent by showing that integrated information increases with fitness across generations of evolved animats in PLoS Computational Biology, suggesting that self-boundary manipulation is already tractable in artificial life simulations.
  7. 7. The paper raises an open question about whether insights from first-person contemplative practice — inherently private experiences — can be extracted as meaningful behavioral or informational data and transferred to non-human cognitive systems, identifying this extraction-and-integration problem as the central methodological challenge.
  8. 8. A researcher wishing to replicate the proposed modeling approach could operationalize 'reduced selfing' in a simulated agent by gradually expanding the boundary of the agent's sensorimotor loop (following Varela, 1997 and Beer, 2014's glider model) and measuring resulting changes in empowerment scores across conditions.
  9. 9. The Tibetan Buddhist practice of dream yoga (Holecek, 2016; Wallace & Hodel, 2012) is hypothesized to work through gradual realization of the illusory nature of dreamworld interactions, which then generalizes to waking self-perception — a staged transfer mechanism the paper suggests could be architecturally mimicked in AI training curricula.
  10. 10. The paper hypothesizes that non-human intelligences explicitly modeled with distributed, dynamic rather than fixed selfhood may access qualitatively novel affordance categories unavailable to standard agent architectures, predicting that this will generate new fundamental principles in AI science beyond incremental performance improvements.

Peer brief — for seminar discussion

This paper, presented at ALIFE 2021 and emerging from the Center for the Study of Apparent Selves in Kathmandu, advances a cross-disciplinary theoretical program: it argues that representing the self as illusory and distributed — rather than singular and enduring — can expand an agent's affordances, and that artificial life modeling is the right vehicle to test this formally. The argument runs through three domains. First, Mahāyāna Buddhist philosophy, specifically Maitreya-Asaṅga's Mahāyānasūtrālaṃkāra, holds that persons are imputations over impermanent causal factors, and that recognizing this generates prosocial reorientation. Second, empirical cognitive science supplies traction: Luberto et al.'s 2018 meta-analysis links meditation-based reductions in 'selfing' to increased empathy and prosocial behavior, Hutcherson, Seppala & Gross (2008) document rises in social connectedness after loving-kindness meditation, and Tholey (1989) and Stumbrys et al. (2014) document that lucid dreaming expands environmental affordances by unlocking actions unavailable in waking life. Third, the paper proposes an integrative artificial life framework — its introduced method — that connects information-theoretic tools (predictive information from Bialek 2001, Tononi et al.'s 1994 integration measure, Klyubin et al.'s 2008 empowerment metric) to formal agent models such as Beer's 2014 glider analysis, in order to simulate the effect of reduced self-reification without requiring first-person experimental access to meditating subjects. An alternative method the framework displaces would be direct neuroimaging or EEG studies of meditators, which have been the dominant empirical approach in contemplative neuroscience but cannot isolate the causal role of self-boundary plasticity in affordance change. The load-bearing prediction is that artificial agents architecturally designed with permeable, dynamic self-boundaries will exhibit measurably expanded empowerment scores and access qualitatively novel affordance categories, pointing toward new classes of AI technology. What a critical reader would most productively push back on is the inferential gap between the cited empirical findings and the modeling proposal: the prosocial effects documented in Luberto et al. (2018) and Hutcherson et al. (2008) are outcomes measured in human practitioners with years of training, and it is far from established that 'selfing reduction' can be operationalized in an artificial agent in any way that preserves the relevant mechanism rather than merely superficially mimicking boundary conditions. The framework remains programmatic — no simulation results are reported, no specific agent architecture is specified, and the connection between empowerment as a scalar metric and the qualitative richness of affordance change described in the Buddhist and contemplative literature is asserted rather than derived. Whether Tononi et al.'s integration measure or Klyubin et al.'s empowerment can actually capture what Buddhist philosophy means by recognizing interdependence is the paper's deepest open question, and its resolution would determine whether this framework is genuinely explanatory or merely analogical.

Frameworks (5)

  • Artificial Life
    Computational modeling approach studying living/cognitive systems; used to test hypotheses about self-illusion effects without direct intervention.
  • Contemplative Science
    Wallace's (2009) convergence of Buddhist contemplative practice and cognitive neuroscience.
  • Information Theory Of Individuality
    Formal framework by Krakauer et al. (2020) for defining an individual based on information theory.
  • Mahāyāna Buddhism
    The broad Buddhist tradition to which Madhyamaka and Zen belong, emphasizing emptiness and compassion.
  • Philosophy of mind
    Philosophical field dealing with nature of mind, self, and consciousness.

Claims (12)

Hypotheses (4)

Questions (2)

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