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Creation and Creativity in Algorithmic Culture

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In 2014, twitter revealed that almost 10% of its users are bots posing as human account holders. This comes as no surprise to many since most of the content posted online is not written by humans, but generated by machines.
We have recently witnessed the rise of new forms and formats for art creation - be it in music, the visual art, literature and poetry - inspired by or produced by means of automation and digitization.
This lecture overviews some of the questions raised by automated content production and algorithmic production of art. Rethinking the status of terms such as "chance," "found art" and arbitrariness in today's creation, I inquire into the possibilities of these new forms for producing art.

Which avenues opened for art making? What are the new formats that have appeared thanks to non-human creation and to non-human audience?
How are traditional art containers such as books, art exhibitions and even music composition reconfigured in algorithmic culture?

Veröffentlicht in: Technologie
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Creation and Creativity in Algorithmic Culture

  1. 1. ‫האלגוריתמים‬ ‫בעידן‬ ‫ויצירתיות‬ ‫יצירה‬ ‫על‬ ‫דצמבר‬2015 ‫ד‬"‫מיקולינסקי‬ ‫רומי‬ ‫ר‬
  2. 2. ‫היום‬ ‫נדבר‬ ‫מה‬ ‫על‬? .1‫והדיגיטציה‬ ‫האוטומציה‬ ‫בגלל‬ ‫ליצירה‬ ‫קרה‬ ‫מה‬? .2‫לתוכן‬ ‫קרה‬ ‫מה‬?‫תרבותיים‬ ‫אובייקטים‬ ‫של‬ ‫למעמד‬ ‫מסורתיים‬? .3‫לקהל‬ ‫קרה‬ ‫מה‬? .4‫כיוצרים‬ ‫לנו‬ ‫נפתחו‬ ‫אפשרויות‬ ‫אלו‬,‫מעצבים‬?
  3. 3. ‫חלק‬1-‫אלגוריתמים‬ Michael Najjar, nasdaq_80-09, from the series high altitude, 2008-2010
  4. 4. ‫אלגוריתם‬ ‫מסוימת‬ ‫משימה‬ ‫לביצוע‬ ‫שיטתית‬ ‫דרך‬ ‫הוא‬ ‫אלגוריתם‬ ‫במספר‬‫סופי‬‫צעדים‬ ‫של‬
  5. 5. ‫אלגוריתם‬ ‫תהליך‬‫ממוחשב‬‫סדור‬‫שמשתמש‬‫בערכים‬‫או‬‫בערך‬ ‫כלשהו‬‫כקלט‬‫בכדי‬‫ליצר‬‫ערך‬‫או‬‫ערכים‬‫נוספים‬ ‫כפלט‬. ‫אלגוריתם‬‫הוא‬‫רצף‬‫של‬‫צעדים‬‫ממחושבים‬‫שהופכים‬ ‫פלט‬‫לקלט‬.
  6. 6. ‫יצירתיים‬ ‫אלגוריתמים‬ ‫פוגשים‬ ‫אנחנו‬ ‫איפה‬?
  7. 7. ‫יצירתיים‬ ‫אלגוריתמים‬ ‫פוגשים‬ ‫אנחנו‬ ‫איפה‬? ‫באלגוריתמים‬ ‫יצירתיים‬ ‫שימושים‬ ‫פוגשים‬ ‫אנחנו‬ ‫איפה‬?
  8. 8. Pentametron (Ranjit Bhatnagar)
  9. 9. Two Headlines
  10. 10. Darius Kazemi http://tinysubversions.com/talks/eyeo/
  11. 11. Darius Kazemi https://twitter.com/tinysubversions/lists/darius-kazemi-s-bots/members
  12. 12. Darius Kazemi Monetizing concern • http://www.regardingspectatorship.net/mone tizing-concern-2/
  13. 13. MedienGruppe Bitnik/ Random Darknet Shopper
  14. 14. MedienGruppe Bitnik/ Random Darknet Shopper «Can a robot, or a piece of software, be jailed if it commits a crime? Where does legal culpability lie if code is criminal by design or default? What if a robot buys drugs, weapons, or hacking equipment and has them sent to you, and police intercept the package?» http://www.theguardian.com/technology/2014/dec/05/software-bot- darknet-shopping-spree-random-shopper
  15. 15. ‫חלק‬2-‫תוכן‬
  16. 16. http://listen.hatnote.com/
  17. 17. Algorave Algorave is made from “sounds wholly or predominantly characterised by the emission of a succession of repetitive conditionals“. These days just about all electronic music is made using software, but with artificial barriers between the people creating the software algorithms and the people making the music. http://algorave.com/about/
  18. 18. Using systems built for creating algorithmic music, such as IXI Lang, overtone, puredata, Max/MSP, SuperCollider, Impromptu, Fluxus, Tidal, Gibber, and Sonic Pi these barriers are broken down, and musicians are able to compose and work live with their music as algorithms. This has good and bad sides, but a different approach leads to interesting places. Algorave
  19. 19. Algorave This is no new idea, but Algoraves focus on humans making and dancing to music. Algorave musicians don’t pretend their software is being creative, they take responsibility for the music they make, shaping it using whatever means they have. More importantly the focus is not on what the musician is doing, but on the music, and people dancing to it.
  20. 20. Algorave Algoraves embrace the alien sounds of raves from the past, and introduce alien, futuristic rhythms and beats made through strange algorithm-aided processes. It’s up to the good people on the dancefloor to help the musicians make sense of this and do the real creative work in making a great party
  21. 21. James Bridle – ship a drift www.shipadrift.com
  22. 22. James Bridle - dronestagram
  23. 23. James Bridle - dronestagram
  24. 24. Kenneth Goldsmith From readership to “thinkership” https://www.moma.org/explore/multimedia/videos/251/1210
  25. 25. Eran Hadas http://eranhadas.com/code/
  26. 26. Eran Hadas "‫קוד‬”‫בחמשת‬ ‫שחבויים‬ ‫ההייקו‬ ‫שירי‬ ‫כל‬ ‫את‬ ‫להציג‬ ‫שתוכנת‬ ‫ספר‬ ‫הוא‬ ‫התורה‬ ‫חומשי‬. ‫סקאלה‬ ‫בשפת‬ ‫קטנה‬ ‫תוכנה‬ ‫כתבתי‬ ‫בתחילה‬,‫מספר‬ ‫פרק‬ ‫שקוראת‬ ‫הייקו‬ ‫שירי‬ ‫בו‬ ‫ומוצאת‬ ‫בראשית‬.‫היפנית‬ ‫המסורת‬ ‫מן‬ ‫שיר‬ ‫צורת‬ ‫הוא‬ ‫הייקו‬. ‫בהייקו‬3‫ו‬ ‫שורות‬-17‫הברות‬.‫הראשונה‬ ‫בשורה‬5‫הברות‬,‫בשנייה‬7 ‫ובשלישית‬ ‫הברות‬5‫הברות‬.‫ומשונים‬ ‫שונים‬ ‫תפקידים‬ ‫מילאו‬ ‫הייקו‬ ‫שירי‬ ‫והמערבית‬ ‫היפנית‬ ‫בשירה‬,‫בדיון‬ ‫טענה‬ ‫העלאת‬ ‫כמו‬,‫בעונת‬ ‫רגע‬ ‫תיאור‬ ‫היתולית‬ ‫הלצה‬ ‫סתם‬ ‫או‬ ‫שנה‬.‫התעלמתי‬ ‫אלו‬ ‫מכל‬,‫את‬ ‫רק‬ ‫לשמר‬ ‫ובחרתי‬ ‫ה‬ ‫הקסמי‬ ‫המקצב‬-‫ז‬-‫ה‬,5-7-5.‫למעשה‬,‫נוספת‬ ‫בתכונה‬ ‫חייב‬ ‫הייקו‬,‫קירו‬– ‫חיתוך‬,‫חתכתי‬ ‫אלא‬ ‫השירים‬ ‫את‬ ‫כתבתי‬ ‫שלא‬ ‫כך‬ ‫מתוך‬ ‫מושגת‬ ‫היא‬ ‫אך‬ ‫אחר‬ ‫הקשר‬ ‫תוך‬ ‫אל‬ ‫התורה‬ ‫מתוך‬ ‫אותם‬.
  27. 27. Eran Hadas “‫ישראל‬ ‫שמע‬ ‫אלהינו‬ ‫אדוני‬ ‫אחד‬ ‫אדוני‬” ‫היהדות‬,‫כך‬‫אומרים‬,‫ניחנה‬‫בתכונה‬‫מקודשת‬.‫יש‬‫לה‬‫מקצב‬‫אוניברסלי‬. ‫טוענים‬‫כי‬‫תפילת‬“‫שמע‬‫ישראל‬”‫נפתחת‬‫בהייקו‬.‫זאת‬‫כמובן‬‫בהנחה‬ ‫שסופרים‬‫את‬‫השווא‬‫הנע‬‫במילה‬‫שמע‬‫כהברה‬…‫וגם‬‫בהנחה‬‫שאת‬‫שם‬ ‫השם‬‫הוגים‬(‫וכותבים‬)‫כאדוני‬.‫מבחינתי‬,‫ב‬-”‫שמע‬‫ישראל‬”‫יש‬4‫הברות‬ ‫ולכן‬‫אין‬‫זה‬‫הייקו‬.‫כדי‬‫להוסיף‬‫דרגות‬‫קושי‬,‫אגלה‬‫שלמעשה‬‫ביפן‬‫אין‬ ‫סופרים‬‫הברות‬‫אלא‬“‫שהיות‬”morae)),‫וגם‬‫לעברית‬‫התנ‬”‫כית‬‫סיבוכים‬ ‫דומים‬:‫חטפים‬,‫שיש‬‫הנוהגים‬‫לספור‬‫אותם‬‫כחצאי‬‫הברות‬,‫וכמובן‬ ‫השווא‬,‫מתעלל‬‫סדרתי‬‫בלשונאים‬.
  28. 28. Frederic Kaplan -
  29. 29. Darius Kazemi Street View Experiments : Messing around with Google Street View.
  30. 30. ‫חלק‬3-‫הקהל‬
  31. 31. Algorithmic Culture
  32. 32. Algorithmic Culture The ways in which computers, running complex mathematical formulae, engage in what’s often considered to be the traditional work of culture: the sorting, classifying, and hierarchizing of people, places, objects, and ideas. https://medium.com/futurists-views/algorithmic-culture-culture-now-has- two-audiences-people-and-machines-2bdaa404f643#.p9br67aky
  33. 33. Algorithmic Culture Facebook engages in much the same work in determining which of your friends, and which of their posts, will appear prominently in your news feed. The same goes for shopping sites and video or music streaming services, when they offer you products based on the ones you (or someone purportedly like you) have already consumed. https://medium.com/futurists-views/algorithmic-culture-culture-now- has-two-audiences-people-and-machines-2bdaa404f643#.p9br67aky
  34. 34. What do you want?/ Beautiful Data II http://metalab.harvard.edu/2015/09/a-bit-in-the-abyss/
  35. 35. What do you want?/ Beautiful Data II
  36. 36. Bot or Not?
  37. 37. ‫חלק‬4–‫חדשות‬ ‫אפשרויות‬
  38. 38. Metalab – New tools new approaches http://metalab.harvard.edu/about/
  39. 39. Metalab – New tools new approaches
  40. 40. Templated Authorship + Random Input + Context Darius Kazemi’s formula: http://tinysubversions.com/talks/eyeo/
  41. 41. Thank you! rominating.tumblr.com -