Re: <nettime> Algorithms that Matter Symposium 2020: Call for contributions

[Hanns Holger Rutz <contact@sciss.de>]

Hi Francis,

thanks for your reflection on this, and apologies for being slow on the
reply. I appreciate your comments, and indeed we share many of your
arguments. First of all, let me clarify that we are very careful not to
talk of "the algorithm", indeed I have looked a while back at the
principles of "its" reification and questioned the identity function of
algorithms (its processual core seems to constantly undo identity). I
prefer to think of "the algorithmic" as the specific medium of
computation (what Luciana Parisi would call 'mode of thought', I guess).

When we conceived ALMAT back in 2015 (?), we were very much thinking of
the heritage of computer (sound) art, and how things have somehow
shifted in the past years in terms of the role of computation, with
'mattering' of course having the double reference of matter/meaning,
referring thus, among other things, to the physical world, but also
various discourses such as "new materialism". In this way, we would
never assume a clear fissure between algorithm/data, and already the
classical works on computation by Turing, von Neumann etc. were based on
the idea that data=code. Last not least, let's be reminded with
Hans-Jörg Rheinberger that the term should actually be 'fact' ('made')
not 'data' ('given').

In any case, we were mostly interested in coding practices, retroaction
and speculative reason, and so 'data' was never in the focus of our
attention (along with 'big data', 'machine learning', 'models' etc.). We
don't discount it, but simply approach the theme from artistic practice
as writing processes. Logic, classical cybernetics and information
theory are all important for this, but form only part of the truth.

I have a few objections, though. For example you write: "If we for
instance look into how bias enters software, we usually won't find much
in algorithms". This of course depends on the definition of bias. If you
take a step back and look at "computational thinking" as a world view,
then the bias is there from the very beginning in the very conception of
the types of objects we're dealing with, so I think this very much
applies to algorithms as well. With all the discourse on algorithmic
governance, algorithmic ethics and so on, we've become accustomed to
think that's just about creating 'balanced' models and data sets, but
this is too short-sighted. We need to question the entire axioms of
communication/control metaphors.

This discussion is very important. Would you mind if I add it to the
symposium RC page?

Best,

.h.h.


On 10/10/2019 23:20, Francis Hunger wrote:
> Hi Hanns and everybody,
>> Rather than understanding algorithms as existing and transparent tools,
>> the ALMAT Symposium is interested in their genealogical, processual
>> aspects and their transformative potential. We seek critical approaches
>> that avoid both mystification and commodification, that aim at opening
>> the black box of "wonder" that is often presented to the public when
>> utilising algorithms.
> 
> That's very much needed. And I think there is a conceptual problem,
> which this conference shares with many others that talk about "the
> algorithm".
> 
> I agree, that the specialized field of generative art concentrates on
> algorithms (that generate the visual or auditive experience) and that
> algorithms on a larger scale matter in optimization (like b-tree
> sorting, fast gradient step method in pattern recognition).
> 
> However from a perspective of "gray media" (Fuller/Goffey), "logistical
> media" (Rossiter) on the one hand, and "habitual media" (Wendy Hui Kyong
> Chun) on the other, I think "algorithm" is wrong terminology.
> Approaching it from a perspective of the database and referring to
> actual practices of application programming I would argue, that
> algorithms are a minor issue.
> 
> Of much more importance is the information model. The information model
> is usually the decision, which information and subsequently data, should
> be included into the processable reality of computing, and what to
> exclude. In short: data is, what gets included according to the
> information model. Everything else is non-data or non-existent (under
> the closed world assumption) to the computer.
> 
> So if you aim to look into the genealogy of algorithms, you may look
> into mathematics and maybe operational reserch. You will however miss
> out on looking at the genealogy of _data_ and the material qualities of
> the _information model_.
> 
> If we for instance look into how bias enters software, we usually won't
> find much in algorithms. A b-tree sorting or the training of a neural
> network is always tied to weights, and actually needs and creates bias.
> Since a computer can not understand meaning, meaning needs to be
> ascribed (through classification), which is done by the mentioned
> algorithms moving numerical weights towards a certain result that is
> meaningful to humans.
> 
> Much more relevant for the question of bias is, how the _information
> model_ is organized, because it inscribes the reality of the computable.
> Much more relevant is the question of how _data_ is collected, curated
> und used, as we can see in the current projects of Adam Harvey
> (https://megapixels.cc/) or !Mediengruppe Bitnik
> (https://werkleitz.de/en/ostl-hine-ecsion-postal-machine-decision-part-1),
> or the Data Workers Union (https://dataworkers.org/).
> 
> I get, that 'algorithm' is often used as common notion, in a similar
> blurry way as is 'digital'. However a stronger concern for the
> information model and for data would open up the avenue for a stronger
> political stance, since it looks into who decides about inclusion and
> exclusions, and how these decisions are shaped. I'm talking about
> identifying addressable actors who are being hold responsible.
> 
> So let's look further into the trinity: information
> model–––data–––algorithm (and the infrastructure in and around it).
> 
> best
> 
> Francis
> 
> 
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