The dog community has also taken a keen interest in vital normativity. Thanks to @biopoetics for bringing one along for the conference! Here pictured enjoying the break between lectures.
Daston articulating that there may be a deeper reason why (aesthetic) pleasure is a good epistemic navigation standard (a.k.a. why you should follow beauty and fun in your research activity)
@nathiaas raziskuje izvore digitalnega v filozofiji G.W. Leibniza. @MaksValencic razpravlja o tem, kaj medijske študije zgrešijo pri digitalni tehnologiji. @panic_evolved razloži, kako je mišljenje neobhodno zvezano z jezikom in socialnostjo. 3/
My professor of phisiology once said something along the lines that most of the research in neurophsyiology is seriously handicapped because it was done on anesthetized, stationary, organisms
Basically 👏take 👏 enaction 👏 seriously
Funkcionalna motorična omrežja v embrijih vinske mušice se samoorganizirajo s povratno informacijo zaznave lastnega telesa v prostoru. #zbritoff
https://t.co/SukwKJHGCF
Biologization is used like a slur for universalist tendencies, but I'd argue that that's just a vulgar surface view of biology as that which seeks to understand some fixed and invariable structures.
To act is to simplify the world, to instrumentalize it. It is to colapse a set of possibilities given by our body schema into one. If we take that cognition arises through action in an environment it is thus no wonder we are prone to instrumentalizing the world.
... Removing trust from the discussion on knowledge just invites conspiracy theorists. This dichotomy of either being all accessible or else given by an authority should be elaborated into what kind of knowledge is trustworthy or trustworthy enough.
All knowledge is not accessible to understanding by everyone. There is simply not enough time for everbody to understand everything. Trust is thus an essential part of any intersubjective knowledge including science.
Models trained on human produced data contain human like biases. Models furthermore are built on certain assumptions made by their makers that necessarily exclude aspects of the problem. Far from a neutral judge, algorithms are human-laden.