Usable intelligent interactive systems: CHI 2009 special interest group meeting

ABSTRACT

The AI and HCI communities have often been characterized as having opposing views of how humans and computers should interact" observes Winograd in Shifting Viewpoints. It is time to narrow this gap. What was once considered the forefront of artificial intelligence (AI) research can now be found in commercial products. While some have failed, others, such as face detection in digital cameras or product recommendation systems, have become so mainstream they are no longer thought of as artificial intelligence. This special interest group provides a forum to examine the apparent gap between HCI and AI communities, to explore how intelligent technologies can enable novel interaction with computation, and to investigate the challenges associated with understanding human abilities, limitations, and preferences in order to drive the design of intelligent interactive systems.

REFERENCES

• 1: Benyon, D. Adaptive systems: A solution to usability problems. User Modeling and User-Adapted Interaction, Vol. 3, No. 1. (March 1993), 65--87.
• 2: Cesta, A., and Pecora, F. Integrating intelligent systems for elder care in RoboCare. In W. C. Mann and A. Helal (Eds): Promoting Independence for Older Persons with Disabilities, IOS Press. (2006), 65--73.
• 3: Leah Findlater , Joanna McGrenere, Impact of screen size on performance, awareness, and user satisfaction with adaptive graphical user interfaces, Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, April 05-10, 2008, Florence, Italy [doi>10.1145/1357054.1357249]
• 4: Krzysztof Z. Gajos , Katherine Everitt , Desney S. Tan , Mary Czerwinski , Daniel S. Weld, Predictability and accuracy in adaptive user interfaces, Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, April 05-10, 2008, Florence, Italy [doi>10.1145/1357054.1357252]
• 5: Jonathan Grudin, Turing maturing: the separation of artificial intelligence and human-computer interaction, interactions, v.13 n.5, September + October 2006 [doi>10.1145/1151314.1151346]
• 6: Greg Linden , Brent Smith , Jeremy York, Amazon.com Recommendations: Item-to-Item Collaborative Filtering, IEEE Internet Computing, v.7 n.1, p.76-80, January 2003 [doi>10.1109/MIC.2003.1167344]
• 7: Greg Little , Tessa A. Lau , Allen Cypher , James Lin , Eben M. Haber , Eser Kandogan, Koala: capture, share, automate, personalize business processes on the web, Proceedings of the SIGCHI conference on Human factors in computing systems, April 28-May 03, 2007, San Jose, California, USA [doi>10.1145/1240624.1240767]
• 8: Ben Shneiderman, Looking for the bright side of user interface agents, interactions, v.2 n.1, p.13-15, Jan. 1995 [doi>10.1145/208143.208150]
• 9: Robert R. Trippi , Efraim Turban, Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real World Performance, McGraw-Hill, Inc., New York, NY, 1992
• 10: Terry Winograd, Shifting viewpoints: Artificial intelligence and human--computer interaction, Artificial Intelligence, v.170 n.18, p.1256-1258, December, 2006 [doi>10.1016/j.artint.2006.10.011]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Theory and methods

General Terms:
Design, Human Factors, Theory

Keywords:
artificial intelligence, human computer interaction