claim

active

claim:information-increase-in-computation-is-observer-dependent-relative-to-the-computational-direction-chosen

Information increase in computation is observer-dependent, relative to the computational direction chosen.

Extension of information dynamics: direction of information increase (e.g., forward multiplication vs. reverse factorization) depends on observer's goals.

Source paper

extracted_from

Information, Processes and Games

Abramsky, Samson

Neighborhood — ranked by edge-count

Communities (3)

community

Design principles for care-centered systems
members_of
Cross-scale frameworks linking spatial patterns, diagrams, and simplicity as expressions of care in design.
Information dynamics in computational systems
members_of
Studies how information flow, increase, and explicitness emerge from computation relative to observers and subsystems, grounded in domain theory and order-theoretic formalism.
Observer-relative computational information theory
members_of
Information increase and flow reframed as subsystem- and observer-dependent, not absolute thermodynamic quantities.

Questions (1)

question

Does information increase in computation?
answered_by
Fundamental puzzle motivating the paper: how can computation produce new information when output is logically implied by input and thermodynamics suggests information cannot increase?

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.

The direction of information increase is relative to the observer or user of the computationclaim0.898
Example: 3×5→15 is a natural computation, but 15→3×5 (prime factorization) is also useful, showing that the 'gain' depends on the choice of normal form.
Information can increase in computation only relative to subsystems and observersclaim0.893
The author argues that while total system information is conserved (thermodynamic), computation gains information for the observer by making implicit information explicit and discarding irrelevant data.
Information increase in computation arises from data reduction and making implicit information explicit, not logical increase.claim0.852
Author's proposed resolution to the information increase paradox: computation gains utility through extraction and filtering, not creation of logically new content.
information increase in computationconcept0.845
The puzzle that computation appears to gain information despite logical closure; resolved by relative to subsystems/observers.
Information flow and increase must be understood relative to subsystems and their interaction with environment.claim0.819
How can information increase in computation if output is logically implied by input?question0.798
Estimates of intelligence are observer-dependent and depend on the observer's limitations as much as the system.claim0.782
An epistemological claim of TAME that agency is not an objective property but is empirically determined by prediction and control efficiency.
Agents and their interactions are intrinsic to studying information flow in computation, not peripheral to classical information theory.claim0.777
Central thesis: traditional static information theories fail to capture dynamic interaction necessary for understanding modern computing.