claim

active

claim:reductionist-analysis-is-increasingly-impossible-for-current-and-future-machines-just-as-it-is-for-living-systems-because-modern-ai-and-swarm-systems-resist-bottom-up-explanation

Reductionist analysis is increasingly impossible for current and future machines, just as it is for living systems, because modern AI and swarm systems resist bottom-up explanation.

Argument that resistance to reductionism no longer distinguishes life from machines

Source paper

extracted_from

Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior

(2021) · Joshua Bongard · Michael Levin

Neighborhood — ranked by edge-count

Frameworks (1)

framework

Machine Behavior
supports
Emerging multidisciplinary field at interface of artificial life, machine learning, and synthetic bioengineering that provides updated understanding of machines.

Concepts (1)

concept

Deep Learning
supports
Learning hierarchical representations of non-decomposable functions; proposed as formal equivalent to ETI process.

Methods (1)

method

Backpropagation of Error
supports
Primary training method for neural networks; cited as surprisingly effective even to its inventors, illustrating resistance to full reductionist understanding

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.

Modern machines are increasingly resistant to reductionist analysis and explanation.claim0.886
Deep neural networks, swarms, and complex autonomous systems require holistic ethological and cognitive approaches.
Many recent discussions of AI, and its impact on individuals and on society, are importantly incomplete because they neglect Diverse Intelligence, synthetic morphology, and developmental biology.claim0.787
Central thesis of the paper — the framing premise from which all other arguments follow
Recent AI advances are revolutionary but far from recapitulating human-like cognitive abilities or consciousness.claim0.783
Progress in machine behavior science and biohybrid engineering breaks down the simplistic dualism of life vs. machine, revealing a continuum of emergence, rational control, and agency.claim0.779
Second central claim: life and machine form a continuous multidimensional space, not discrete bins
Evolution often produces general-purpose problem-solving machines whose capacities cannot be inferred from the default invariant course of development.claim0.779
A claim about the outcome of the MCA-enhanced process.
Languages that cannot be automatically evaluated inevitably contain unresolvable paradoxes; constructive computation avoids this by building representations over simple step-by-step operations.claim0.778
Paper's interpretation of Gödel's incompleteness result as motivating computationalism
AI systems need to be able to deal with reality as it actually is, not with the way that we think it is.claim0.777
Paraphrase of Cantwell Smith's argument; aligns with Buddhist emphasis on seeing reality without conceptual imposition.
our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.quote0.777
Key takeaway from abstract, amended version.