In seiner Funktionalität auf die Lehre in gestalterischen Studiengängen zugeschnitten... Schnittstelle für die moderne Lehre
In seiner Funktionalität auf die Lehre in gestalterischen Studiengängen zugeschnitten... Schnittstelle für die moderne Lehre
Recent developments in smart systems, that aim live up to, what Alan Turing called “thinking machines”, give us the possibility to evaluate their place in our creative practice. This thesis analysis their potential for the human capabilities of innovation and art while describing potential processes and rules for collaborating with these unfamiliar new actors.
Die jüngsten Fortschritte in der Entwicklung intelligenter Systeme, die dem, was Alan Turing als „Denkmaschinen“ bezeichnete, versuchen gerecht zu werden, geben uns die Möglichkeit, ihren Platz in unserer kreativen Praxis zu bewerten. Diese Arbeit analysiert ihr Potenzial für die menschlichen Fähigkeiten von Innovation und Kunst und beschreibt mögliche Prozesse sowie Regeln für die Zusammenarbeit mit diesen unbekannten –fremden Akteuren.
Ever since industrialisation [1] (Figure 1) people dreamed of bright futures where scientific development would allow most to sit back and watch machines do all the work. Today, with the recent signs of phenomenal progress in Machine Learning, this dream becomes more and more feasible. A new hype of applying machines in decision-making positions is followed equally by hope and fear of job loss [2] or other unintended outcomes [3].
We want to discuss these new developments from a slightly positive angle, as we imagine this technology as merely an additional tool for the—already highly digitalised— repertoire of modern creatives. We hypothesise that there is artistic value, and autonomy for the individual, to be gained from workflows that integrate not only thoughts and ideas of humans, but also machines.
We have to make clear that we do not want, to call human creative output as redundant and replaceable by machines. This is neither our intention nor our motivation. We assume that, even if it would be possible, in an infinite amount of time, the output would still be less valuable then collaboration of machines and humans. This belief is based on our evolutionary philosophy, that diversity, and different perspectives, of any kind, enrich the results. We will argue why robots won’t take over creative practice all by themselves, but augment our existing processes.
In the following chapters, we will explain our definition of creativity to paint a clear picture of how current machines can or cannot be creative and how methods of human-machine co-creation could be established. Furthermore, we will describe and conclude an experiment we carried out to test possible co-creation processes.
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