claim

active

claim:intrinsic-links-between-ontology-and-ethics-are-evident-in-how-all-intelligent-agents-respond-to-perceived-mismatch-between-what-is-and-what-should-be

Intrinsic links between ontology and ethics are evident in how all intelligent agents respond to perceived mismatch between what is and what should be.

Bridges descriptive model (SCI loops) to normative framework (ethics).

Source paper

extracted_from

Toward an ethics of autopoietic technology: Dukkha, care, and Intelligence

(2023) · Witkowski, Olaf · Doctor, Thomas · Solomonova, Elizaveta · Duane, Bill +1

Neighborhood — ranked by edge-count

Thinkers (1)

thinker

Martin Heidegger
cites
Philosopher whose distinction between poiesis and modern technology (Gestell/enframing) grounds the paper's ethics framework.

Communities (3)

community

Active inference & agent ecology
members_of
Free energy minimization, Markov blankets, trust gradients, and multi-agent rhythm/deferral frameworks
Functional criteria for moral patienthood
members_of
Framework grounding ethical consideration in goal-directedness and agency rather than substrate or origin, addressing moral status of novel intelligences.
Ontology-ethics stress-care link
members_of
Intelligent agents respond to is/ought mismatch through stress and care feedback loops.

Concepts (1)

concept

"only the true brings us into a free relationship with that which concerns us from out of its essence"
supports
Heidegger's prescription for free relationship to technology; foundational to authors' ethics of care-based technology engagement.

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

Intrinsic links between ontology and ethics via stress-care feedbackclaim0.856
Authors' central interpretive assertion: all intelligent agents respond to homeostatic mismatch; this observation grounds an ethics not requiring permanent essences.
All intelligent agents, regardless of their substrate, can be understood as needing to respond to a perceived mismatch between what is and what should be.claim0.774
Foundation for the SCI loop model.
Contingent properties like composition, origin, or similarity to human brains should not define ethical consideration for novel agents.claim0.768
Ethics must be based on empirically-determined cognitive properties (goals, preferences, concerns) rather than parochial markers.
What degree of concern and care should we exhibit toward the many diverse agents around us, and what criteria do we use to identify sentience, capacity for suffering, and other properties that have moral implications?question0.763
Central question motivating the paper.
Biology embraces a process ontology in which perspectives and agency are primary; change drives intelligence.claim0.759
Concluding synthesis claim.
In the agentic AI ontology, there is no difference between the policy and the effective agent, but for GPT, there is.claim0.758
Key insight distinguishing GPT from traditional agent models.
Agents and their interactions are intrinsic to studying information flow in computation, not peripheral to classical information theory.claim0.756
Central thesis: traditional static information theories fail to capture dynamic interaction necessary for understanding modern computing.
Conceptual advances in the links between machine learning and evolution now provide quantitative formalisms with which to begin to develop testable models of collective intelligence across scales.claim0.753
Asserts that the time is ripe for formal models.