Feeding the Beast: Can Computational Demographic Models Free Us from the Tyranny of Data?

E. (Eric) Silverman, J. (Jakub) Bijak, J. (Jason) Noble

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    Since its inception, ALife has moved from producing large
    numbers of highly-idealised, theoretical models towards
    greater integration with empirically collected data. In con-
    trast, demography — the interdisciplinary study of human
    populations — has been largely following the principles of
    logical empiricism, with models driven mainly by data, and
    insufficient attention being paid to theoretical investigation.
    Such an approach reduces the ability to produce micro-level
    explanations of population processes, which would be coher-
    ent with the phenomena observed at the macro level, without
    having to rely on ever-increasing data demands of complex
    demographic models. In this paper we argue that by bring-
    ing ALife-inspired, agent-based methods into demographic
    research, we can both develop a greater understanding of the
    processes underlying demographic change, and avoid a limit-
    ing over-dependence on potentially immense sets of data.
    – But you are paying a lot of money for the dragon!
    – And what, should we just give it to the citizens in-
    stead? [...] I see you know nothing about the principles
    of economics! Export credit warms up the economy and
    increases the global turnover.
    – But it also increases the dragon as such – I
    stopped him. – The more intensely you feed him, the
    bigger he gets; and the bigger he gets, the higher his
    appetite. What kind of a calculation is it? He will fi-
    nally devour you all!
    Stanisław Lem, Po˙zytek ze smoka [The Use of a
    Dragon] (1983/2008: 186)
    Original languageEnglish
    Title of host publicationArtificial Life Conference Proceedings
    PublisherMIT Press Journals
    Number of pages8
    ISBN (Print)9780262297141
    Publication statusPublished - 12 Aug 2011


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