NASA SISM Intelligent Systems Project Human-Centered Computing Objectives

HSM

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MI

Technical Commitment

IS/HCC research tasks are categorized as milestone-directed, strategic supporting research, or mission infusion. Strategic supporting research is awarded through competitive mechanisms. Milestone-directed tasks are designed to ensure that the Strategic supporting research results are integrated into the milestone deliverables for the project. Mission infusion tasks ensure that maturing technologies migrate into solutions for NASA needs, as opportunities arise.   The majority of HCC-funded work will be at technology readiness levels 1 to 3, with some tasks being developed to levels 4 to 5 in partnership with other funding programs. When a technology matures to Level 6 it will flow out of the IS Project and into the specific NASA Enterprises and industry. The IS/HCC subproject supports CICT Program Plan Objective 1 -- Goal-Directed Systems, which says in part: "Develop and demonstrate human-centered computing technologies that optimize the combined performance of human experts and the supporting information system." In particular: Milestone 9.1: The IS Project will demonstrate in a Mission Operations Facility or similar testbed, by May 2005, the use of agent-based integrated tools for routine operations, as well as anticipated and unanticipated off-nominal operations. Key technologies include collaborative tools, distributed software agents, and multimodal user interfaces.

Human-System Modeling

The fundamental challenge for HCC is to be able to model realistically complex human-computer systems. Models useful for design, simulation, and team coordination must include people, objects, activities, and many types of constraints. System-level models aid understanding of joint activities, dynamic interactions, and plan modifications. A new class of system-level models -- integrated with models of life-support systems and software -- will enable design-phase analysis of human performance. These will be extensively formalized and simulated in computer programs as part of a design and test process. A model of human behaviors is also needed, so that system simulations can make valid assumptions about loads placed by human activities. (System simulations have often used overly simple models of how people use an interface.) Sophisticated human-system models can answer key design questions about facilities design, automation design and testing, science protocols, work scheduling, communication and coordination, and team training. PACING RESEARCH CHALLENGES: Integrating human models with other engineering models. Formal analyses of standard operating procedures. Reducing the costs of model development, verification, validation, and maintenance. Enhancing the usability of modeling frameworks. Developing model-based command-and-control and training systems. Modeling of multitasking and error vulnerability.

Decision Systems

Computers have become an effective means for communicating with people and machines. The HCC subproject seeks to harness networking and communication technology to improve knowledge sharing and reuse. Knowledge becomes more usable when mediating representations are tailored to specific groups of users. NASA will need new adaptive, dynamic representations for disseminating knowledge to the science community, and to help engineers use lessons learned from prior missions. These representations and tools can also support novel approaches to education and outreach. HCC capabilities include software tools for intelligently acquiring, representing, managing, sharing, and interacting with scarce or valuable knowledge. (This strongly complements IS Intelligent Data Understanding research.) NASA enterprises can use these technologies to improve the management of design data, mission science data, modeling and simulation data, and technical documents. Computers must become active assistants in enterprise-wide organization learning and institutional memory. Decision Systems applications range from "best practice" enhancements of major activities -- such as managing launch services -- to making specialized knowledge of hazardous material handling available anywhere, anytime. Innovative, automated approaches to acquiring, preserving, and reusing expertise could reduce the knowledge loss as engineers depart or retire from NASA. Representative technologies for enhanced knowledge modeling and sharing include: representation, indexing and management of knowledge; distributed agent architectures for information sharing; knowledge management for mobile computing; collaborative access to remote scientific instruments; just-in-time training systems research; next-generation browsers for inter/intranets; and collaboration tools for scientists and engineers. PACING RESEARCH CHALLENGES: Understanding the nature, modeling, and sharing of expertise. Mediating representations for communication and understanding. Software tools for synchronous and asynchronous collaboration. Engineering and mission design knowledge capture. Institutional knowledge capture, modeling, management, maintenance, and delivery.

Multimodal Interfaces

NASA's missions will require dramatic advances in the functional bandwidth, robustness, and reliability of operator-system interfaces. Humans and computers should form cooperative, efficient, mixed-initiative systems, without forcing humans to adapt to the machines. Multimodal interface research aims for advanced technologies and design methodologies that meet NASA's specific requirements. These technologies include speech and natural language interfaces, multimedia systems, adaptive and intelligent interfaces and displays, ubiquitous computing, and mobile and wearable computers. Time-consuming and expensive human-in-the-loop testing is often infeasible for NASA missions. Instead, reliable HCC design can be based on models of attention, memory, conceptual structure, decision-making, learning, and higher-level perception. Rigorous simulation-based testing can then validate safety in advance. PACING RESEARCH CHALLENGES: Architectures for information management in multimodal interfaces. Formal models of task-relevant content. Tools, methods, and metrics for intelligent interfaces. Models of collaboration between humans and other intelligent agents. Integration of cognitive analysis into interface design. Operator interfaces to portable and wearable computational systems.

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