Cognitive systems engineering: new wine in new bottles
International Journal of Man-Machine Studies
International Journal of Man-Machine Studies - Knowledge acquisition for knowledge-based systems. Part 2
Mapping cognitive demands in complex problem-solving worlds
International Journal of Man-Machine Studies - Knowledge acquisition for knowledge-based systems. Part 2
Plans and situated actions: the problem of human-machine communication
Plans and situated actions: the problem of human-machine communication
The psychology of expertise: cognitive research and empirical AI
The psychology of expertise: cognitive research and empirical AI
Knowledge acquisition as modeling
Knowledge acquisition as modeling
The knowledge level reinterpreted: modeling socio-technical systems
Knowledge acquisition as modeling
Cognitive Work Analysis: Towards Safe, Productive, and Healthy Computer-Based Work
Cognitive Work Analysis: Towards Safe, Productive, and Healthy Computer-Based Work
Toward a Theory of Complex and Cognitive Systems
IEEE Intelligent Systems
Work-arounds, Make-work, and Kludges
IEEE Intelligent Systems
Map-Mediated geocollaborative crisis management
ISI'05 Proceedings of the 2005 IEEE international conference on Intelligence and Security Informatics
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The widespread introduction of the personal computer, beginning about 1970, helped spawn the field of inquiry called cognitive engineering, which concerns itself with such things as interface design and user friendliness. Since then, this field has taught us many important things, including two major lessons. First, the road to user-hostile systems is paved with designers' user-centered intentions. Even smart, clever, well-intentioned people can build fragile, hostile devices that force the human to adapt and build local kludges and workarounds. Worse still, even if you are aware of this trap, you will still fall into it. Second, technology developers must strive to build truly human-centered systems. Machines should adapt to people, not the other way around. Machines should empower people. The process of designing machines should leverage what we know about human cognitive, perceptual, and collaborative skills.