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Expanding Observability via Human-Machine Cooperation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F22%3A10448510" target="_blank" >RIV/00216208:11230/22:10448510 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=iJo5S80fmh" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=iJo5S80fmh</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s10516-022-09636-0" target="_blank" >10.1007/s10516-022-09636-0</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Expanding Observability via Human-Machine Cooperation

  • Original language description

    We ask how to use machine learning to expand observability, which presently depends on human learning that informs conceivability. The issue is engaged by considering the question of correspondence between conceived observability counterfactuals and observable, yet so far unobserved or unconceived, states of affairs. A possible answer lies in importing out of reference frame content which could provide means for conceiving further observability counterfactuals. They allow us to define high-fidelity observability, increasing the level of correspondence in question. To achieve high-fidelity observability, we propose to use generative machine learning models as the providers of the out of reference frame content. From an applied point of view, such a role of generative machine learning models shows an emerging dimension of human-machine cooperation.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50601 - Political science

Result continuities

  • Project

    <a href="/en/project/LX22NPO5101" target="_blank" >LX22NPO5101: The National Institute for Research on the Socioeconomic Impact of Diseases and Systemic Risks</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Axiomathes

  • ISSN

    1122-1151

  • e-ISSN

    1572-8390

  • Volume of the periodical

    32

  • Issue of the periodical within the volume

    Suppl. 3

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    14

  • Pages from-to

    819-832

  • UT code for WoS article

    000864311400001

  • EID of the result in the Scopus database

    2-s2.0-85139435175