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Creative Software for the Creative Industries Dr. Simon Colton Department of Computing Imperial College, London.

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Presentation on theme: "Creative Software for the Creative Industries Dr. Simon Colton Department of Computing Imperial College, London."— Presentation transcript:

1 Creative Software for the Creative Industries Dr. Simon Colton Department of Computing Imperial College, London

2 Increasing Creativity in a Design/Advertising Firm Hire a new employee Buy some fancy software Send staff on a tree-hugging course Fundamentally Different

3 Design studios, fashion houses and advertising agencies hire creative people. Their employees have certain skills which enable them to carry out their duties. These skills include the ability to innovate and create – the last thing employers in the creative industries want is employees that do exactly as they are told to. Design studios, fashion houses and advertising agencies buy uncreative software. Their programs have certain skills which enable them to carry out their duties. These skills very rarely include an ability to innovate and create – computer users in the creative industries expect their software to do exactly what it is told to.

4 Using Software to Enhance Creativity Employ software to increase the skill base of the user  Scope for creativity is higher Employ software to increase the efficiency of the user  Evaluate more design solutions Employ software to act creatively independently of the user  Surely not? But this is why you hire someone new…

5 A New Outlook on Software Usage The “How Would You Have Done That” Button  Provides alternative solutions to design tasks  That require creativity in the user Alternatives are chosen so that  The user will appreciate them  The user may not have thought of trying them Software acts as a creative partner  Not just as a tool, but also for inspiration

6 Not to be Confused With Adaptive software  Improves with usage Using macros in Photoshop, etc.  User still makes the choices Software makes decisions only which follow from the user’s choices Software is hardly likely to surprise or positively affect the approach to design

7 Tony Blair A man on a mission? Tony Blair A man on a mission “Well, how would you have done that?” A design student produces this, and asks…

8 Project Proposal Work on visual design tools  Production of artworks, posters, flyers,  Desktop publishing, web pages, … First half of project  Build and assess prototypes  Design abilities & creative abilities Second half of the project  Apply technology to existing packages  Such as Photoshop, etc.

9 Prototypes First axis of development  Graphics ability Ability to produce:  Abstract art, photomontages, posters, multi- media web pages Via implementation of:  Bitmap transformations, layers, text, HTML objects, web output Prototypes to be built from the ThreeCreate program, described later

10 Prototypes Second axis of development  Creative ability Ability to take responsibility  Learn user’s preferences, redesign documents, assess aesthetics Via implementation of techniques from:  Human-computer interfaces, machine learning, Artificial Intelligence search

11 Assessment For early prototypes  Tests with arts and design students For later prototypes  Tests with people in the creative industries Need to evaluate:  Amount and ease of usage, respect/trust in the program, perceived value of products Later prototypes improved  In line with good and bad observations

12 HCI Aspects User requirements studies Harvest every piece of information  How user chooses materials  How user transforms materials  How user places materials  How user assesses products & service The “How Would You?” Button  Non-intrusive interface  Record and playback  Entire document re-engineering  Parameters for trust, innovation, etc.

13 Machine Learning Aspects Learn rules about choice of materials  Image analysis, e.g., colour histograms  Neural networks for feature recognition Learn rules about how user works  Inductive Logic Programming (ILP) Learn rules about user aesthetics  ILP, Neural nets for image analysis

14 AI Search Aspects Define search space over possible documents and sub-documents Constrain using information from  Pre-programmed best practice  Rules about the user  Rules about other users Constructively break the rules  Appeal to aesthetic considerations, not observed practice Search techniques  GOFAI, Evolutionary approaches

15 The ThreeCreate Program

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17 Line Drawings

18 Montages

19 Paintings

20 Some More Inspiration Michaelangelo’s big break Vygotskyian tools  Tools shape the design process  Radical new tools from the computer Have you ever used the wrong Photoshop filter, and kept the image?  Increase serendipity

21 Actively Seeking… Input from the visual design community  In academia and at large Potential partner  At the investigator level?  At the consultant level? Firms in the creative industries  Design, advertising, fashion, games, architecture, web designers


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