HUMAN-COMPUTER CO-CREATION

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1 HUMAN-COMPUTER CO-CREATION Anna Kantosalo CC-2017 Anna Kantosalo 24/11/2017 1

2 OUTLINE DEFINITION AIMS AND SCOPE ROLES MODELING HUMAN COMPUTER CO-CREATION DESIGNING HUMAN COMPUTER CO-CREATION CC-2017 Anna Kantosalo 24/11/2017 2

3 DEFINITION Human-computer co-creativity is collaborative creativity where both the human and the computer take creative responsibility for the generation of a creative artefact. - Kantosalo, Toivanen, Xiao and Toivonen, 2014 CC-2017 Anna Kantosalo 24/11/2017 3

4 DEFINITION Human-computer co-creativity is collaborative creativity where both the human and the computer take creative responsibility for the generation of a creative artefact. - Kantosalo, Toivanen, Xiao and Toivonen, 2014 CC-2017 Anna Kantosalo 24/11/2017 4

5 DEFINITION Another frequently used definition is for Mixed-Initiative Co- Creativity: the task of creating artifacts via the interaction of a human initiative and a computational initiative. Yannakakis, Liapis and Alexopoulos, 2014 CC-2017 Anna Kantosalo 24/11/2017 5

6 DEFINITION Another frequently used definition is for Mixed-Initiative Co- Creativity: the task of creating artifacts via the interaction of a human initiative and a computational initiative. Yannakakis, Liapis and Alexopoulos, 2014 CC-2017 Anna Kantosalo 24/11/2017 6

7 DEFINITION CC-2017 Anna Kantosalo 24/11/2017 7

8 DEFINITION Presentation Name / Firstname Lastname 24/11/2017 8

9 AIMS The goal of human-computer co-creativity is to enhance both, human and computational creativity. CC-2017 Anna Kantosalo 24/11/2017 9

10 AIMS The goal of human-computer co-creativity is to enhance both, human and computational creativity. Support for both, human and computational creativity E.g. distributing tasks by strengths: Human does what humans are good at, and computer does what computers are good at CC-2017 Anna Kantosalo 24/11/

11 AIMS The goal of human-computer co-creativity is to enhance both, human and computational creativity. Support for both, human and computational creativity E.g. distributing tasks by strengths: Human does what humans are good at, and computer does what computers are good at Creating new ways to create E.g. new intelligent digital instruments for musicians CC-2017 Anna Kantosalo 24/11/

12 SCOPE Human- Computer Co- Creativity Computational Creativity Human- Computer Interaction Creativity Support Systems Psychology of Creativity Social Creativity Interaction Design CC-2017 Anna Kantosalo 24/11/

13 SCOPE Application domains vary from recreational to serious applications: Serious examples: Fields: Design, Interior Design, Architecture, Education DarwinsGaze (DiPaola and Gabora, 2009), Poetry Machine (Kantosalo, Toivanen, Xiao and Toivonen, 2014) Recreational examples: Games, Maker-culture Drawing Apprentice (Davis, Hsiao, Singh, Li and Magerko, 2016) CC-2017 Anna Kantosalo 24/11/

14 ROLES How do we start about discussing human-computer co-creation? CC-2017 Anna Kantosalo 24/11/

15 ROLES Lubart (2005): How can computers be partners in the creative process Nanny Support work activity Pen-Pal Feedback manager Coach Technique trainer Colleague Autonomous creator CC-2017 Anna Kantosalo 24/11/

16 ROLES Lubart (2005): How can computers be partners in the creative process Nanny Support work activity Pen-Pal Feedback manager Coach Technique trainer Colleague Autonomous creator Maher (2012): Who s being creative? Support Tools and techniques Enhance Extend abilities Generate Generate artefacts + Human roles: Model and Generate CC-2017 Anna Kantosalo 24/11/

17 ROLES Lubart (2005): How Maher can (2012): Who s Nakakoji being (2006): Meanings computers be partners creative? in the creative process of tools, support, and uses of creative design processes Nanny Support Dumbell Support work activity Tools and techniques Training creativity Pen-Pal Enhance Running Shoes Feedback manager Extend abilities Creating faster Coach Generate Skis Technique trainer Generate artefacts Creating something Colleague + Human roles: different Autonomous Model creator and Generate CC-2017 Anna Kantosalo 24/11/

18 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH To be able to discuss problems and difficulties in human computer co-creation from a computational perspective a computational model is needed. The Alternating co-creativity model extends Wiggins Creative Systems Framework to an iterative co-creative scenario Look for full definition in article Kantosalo and Toivonen 2016 CC-2017 Anna Kantosalo 24/11/

19 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH It is described for two participants, but in principle, it scales up indefinitely When reduced to the case of one praticipant, it becomes Wiggins original model It assumes indirect interaction via the generated artefact! CC-2017 Anna Kantosalo 24/11/

20 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH U U Sets of all possible concepts that the human and the computer can process R R Sets of valid concepts E E Sets of appreciated concepts T (c) T c Sets of concepts reachable in n steps from c t (c) t The concept produced after c The above sets are defined by the respective rules,,,,, CC-2017 Anna Kantosalo 24/11/

21 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH The co-creative process is described by cycles of two operations: c =t c c =t c The computational participant computes the ith iteration of the artefact from the (i- 1)th iteration of the artefact, produced by the human participant. The human participant computes the (i+1)th iteration of the artefact from the ith iteration of the artefact, produced by the human participant. CC-2017 Anna Kantosalo 24/11/

22 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH The co-creative process is described But wait! by cycles of two operations: Creativity is supposed to c =t c The computational participant computes the ith produce iterationboth of thevalid, artefact from the (i- 1)th iteration and of valuable the artefact, produced by the human objects! participant. c =t c The human participant computes the (i+1)th iteration of the artefact from the ith iteration of the artefact, produced by the human participant. CC-2017 Anna Kantosalo 24/11/

23 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Valid of artefacts in Wiggins framework are described with set R. Valid artefacts in co-creation: R R Appreciated artefacts in Wiggins framework are described with E. Valid artefacts in co-creation: E E CC-2017 Anna Kantosalo 24/11/

24 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Valid of artefacts in Wiggins framework are described with set R. Valid artefacts in co-creation: R R Appreciated artefacts in Wiggins framework are described with E. Valid artefacts in co-creation: E E What if the computer doesn t appreciate any concepts considered valid by the human? E.g. E R = CC-2017 Anna Kantosalo 24/11/

25 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Universal Mismatch c U or c U Conceptual Mismatch c R or c R Artistic Disagreement Generative Impotence c E or c E T c = or T c = CC-2017 Anna Kantosalo 24/11/

26 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH How to tackle the problem? Allow skipping turns Asymmetric alternating co-creativity Transformational creativity Change,, (or,, ) to allow the understanding and evaluation of an artefact In the case of Artistic Disagreement, the computer can also give up on its own creative goals. Finally, we can separate the creative tasks under Wiggins model and participate only partially, via defining the conceptual space, or value of the artefacts, or by only generating them. This is called Task-divided co-creativity CC-2017 Anna Kantosalo 24/11/

27 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Ultimately, the strategy chosen to deal with Universal Mismatch, Conceptual Mismatch, Artistic Disagreement and Generative Impotence affects who controls the creation and whose artistic vision is pursued in alternating co-creativity. From computational perspective the role of the computational participant can therefore be categorised as complete vs. incomplete and pleasing vs. provoking, depending on which strategies are chosen to solve the problems! CC-2017 Anna Kantosalo 24/11/

28 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Complete co-creative agents Are capable of identifying, generating, and evaluating some concepts in a space Can participate in symmetric alternating cocreativity if transformational Currently best fit: Tanagra (Smith, Whitehead, and Mateas 2010) Incomplete co-creative agents Are only capable of some, not all creative tasks Can only participate in taskdivided co-creativity Most current co-creative systems, e.g. evolutionary systems where human acts as the evaluator CC-2017 Anna Kantosalo 24/11/

29 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Pleasing co-creative agents: A pleasing agent seeks to modify its behavior by transforming its rulesets to better comply with the human s needs A pleasing agent may essentially limit its own creativity Provoking co-creative agents: Provoking agents resist changes to their rulesets based on human preferences alone May outright challenge the human creator and in general may be difficult to work with CC-2017 Anna Kantosalo 24/11/

30 MODELLING HCCC ITERATIVE CO-CREATIVITY AS A SEARCH Lack of communication is a general challenge for this model. With another communication channel Human and computer could better agree how to make creative transformations Search could be directed to specific alternative routes via discussion The co-creative partners could better agree when to stop Evidence suggests that human co-creators also work somewhat iteratively, but their discussions often go to the meta-level, for example discussing alternate artefacts prior to settling to a specific change made to the artifact CC-2017 Anna Kantosalo 24/11/

31 DESIGNING HCCC In designing human-computer co-creative applications, the skills, needs, and goals of the human participant become an integral part of the design process. Interaction Design and Human-Computer Interaction can be utilized to achieve good results. Sometimes the goals of the human users and computational creativity creators can be in contrast! Algorithms may need to be dumbed or tuned down to achieve better results Usually humans are given more responsibility in the creation: They often decide the search space and end the search when they are happy with the results CC-2017 Anna Kantosalo 24/11/

32 CONCLUSIONS Human-computer co-creativity aims to enhance human and computational creativity The human and the computational co-creator can take different roles within the co-creative process These roles usually describe the purpose of the participant, but can also explain the capability of the participant within co-creation Computational models are important as they can help to recognize important pitfalls when designing systems So far a focus on interaction and communication between the cocreative participants has received little focus Designing HCCC has so far focused on responding to human needs and identifying what role the system can take within the context CC-2017 Anna Kantosalo 24/11/

33 REFERENCES DiPaola, S.; McCaig, G.; Carlson, K.; Salevati, S.; and Sorenson, N Adaptation of an autonomous creative evolutionary system for real-world design application based on creative cognition. In Proceedings of the Fourth International Conference on Computational Creativity. June 12-14, 2013, Sydney, Australia, Kantosalo, A. and Toivonen, H Modes for Creative Human-Computer Collaboration: Alternating and Task-Divided Co- Creativity. In Proceedings of the 7th International Conference on Computational Creativity, June 27- July 1, 2016, Paris, Kantosalo, A.; Toivanen, J. M.; Xiao, P.; and Toivonen, H From isolation to involvement: Adapting machine creativity software to support human-computer cocreation. In Proceedings of the Fifth International Conference on Computational Creativity. June 10-13, 2014, Ljubljana, Slovenia, 1 8. Lubart, T How can computers be partners in the creative process: classification and commentary on the special issue. International Journal of Human-Computer Studies 63(4): Maher, M. L Computational and collective creativity: whos being creative? In Proceedings of the Third International Conference on Computational Creativity. May 30 -June 1, Dublin, Ireland, Nakakoji, K Meanings of tools, support, and uses for creative design processes. In International Design Research Symposium 06, Seoul, Korea, Smith, G.; Whitehead, J.; and Mateas, M Tanagra: A mixed-initiative level design tool. In Proceedings of the Fifth International Conference on the Foundations of Digital Games. June 19-21, Monterey, California, USA, FDG 10, New York, NY, USA: ACM. Wiggins, G. A A preliminary framework for description, analysis and comparison of creative systems. Knowledgebased Systems 19(7): Yannakakis, G. N.; Liapis, A.; and Alexopoulos, C Mixed-initiative co-creativity. In Proceedings of the 9 th Conference on the Foundations of Digital Games. April Ft. Lauderdale, Florida, USA. CC-2017 Anna Kantosalo 24/11/

Modes for Creative Human-Computer Collaboration: Alternating and Task-Divided Co-Creativity

Modes for Creative Human-Computer Collaboration: Alternating and Task-Divided Co-Creativity Anna Kantosalo and Hannu Toivonen Department of Computer Science and Helsinki Institute for Information Technology