Dear all,

Algorithmic Pattern is a new festival and conference for people curious about 
the practice and culture of algorithmic pattern-making, across algorithmic 
arts, music and craft. The first edition will take place both in Sheffield UK 
and online, during September 2025.

The call for talks/papers has been open for a while, and we have now opened a 
call for performances and workshops. The deadline is early June, but we 
encourage early submissions for performance and workshop proposals, to help 
with our planning and fundraising.

Please see our website for details:
  https://2025.algorithmicpattern.org/call/

*Background*
Algorithmic Pattern aims to bring people together who value deep, human 
curiosity into patterns. We hope this call excites you whether you are 
exploring patterns in heritage crafts or contemporary algorithmic art.

Humans have always explored algorithmic patterns, as creative, 
culturally-embedded ways to work beyond our imaginations.

But *what is an algorithmic pattern?* We invite contributions that focus on one 
or more of the following aspects:
 • *Procedures for making*, whether notated or passed on through oral culture. 
These ways of making may be arrived at through playful experimentation, and 
perhaps reasoned about in terms of geometry, models and representations. Simple 
procedures (shifting, reversing, etc) in combination can give us complex 
results.
 • *Material behaviours*, in that pattern-making is always a dialogue between a 
human maker and their material, and a pattern notation is only complete when 
considered in terms of the material at play.
 • *Pattern-making culture* is what brings meaning to the procedures and 
materials of pattern-making, whether through ritual, sharing, collaboration, 
decoration, trade, or the collective experience of making (or dancing!) 
together.
We look for a future informed by the past, at the point where ‘information age’ 
technologies are now becoming ancestral, joining a long history of 
pattern-making technologies in being passed from one generation to the next.

Best wishes

Alex

--
Research Fellow, Then Try this
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