• @[email protected]
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    53 days ago

    No it is not acceptable to just spout an idea without testing it someway, not if ‘Science’ is your game. A feeling about a particular outcome is not nearly enough to convince others that your intuition is valid. Show me the numbers.

    If you are expressing an idea about systems with simple rules that produce complex outcomes and you don’t run the numbers, you haven’t even really done the work yet. It remains in the realm of armchair philosophy (aka probably wrong).

    These type of simulations using Avida are a lot cheaper than wet lab experiments and the group that developed the platform has confirmed the outcome of insilico studies with decades-long wet lab experiments.

    As a science funder, I would never fund a decade-long wet lab research program when a cheap desktop PC can validate your working model in silico, first.

    • @AbouBenAdhem
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      3 days ago

      I’m not disputing the value of simulations (although I think you’re overstating it a bit—by your criteria all of 20th-century science that didn’t include new lab results should be dismissed as “armchair philosophy”). But I think simulations should focus on testing those implications of a theory that aren’t predictable without a simulation—on getting answers you don’t already know. Like in this case, say: what happens when you introduce multiple traits and a polygenetic genotype-phenotype map? Such a simulation would confirm the same things this one does while also potentially advancing the theory in new ways.

      • @[email protected]
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        2 days ago

        All good points but my deeper point is not that complicated. It’s more realpolitik than anything. There are lots of ways to ‘science’ but many fewer ways to get your science funded.

        If your work depends on a conceptual model or framework that can be simulated cheaply, no one will ever fund your real world experiments to validate that model/framework. Not until you run the sims.

        There’s enough research on models that use simple rulesets that produce sometimes surprising behavior to show that our intuition about those systems is not reliable.

        Any frazzled grant reviewer would rightly dismiss a request to commit to a grand wet lab program that hadn’t done this kind of model work.

        So where I am coming from is that, yes, let’s say there is a 90% chance your intuition might be right about the behavior of a specific complex system. That’s still not good enough in our current funding environment. It’s just a practical necessity for most.