Technical Thrust: Enhancing Human Information Interaction and Decision Making
|Vision:||Apply computational power to support/augment cognitive skills, bolstering limited cognitive resources|
Information analysts and decision makers are confronted each day with high demands for rapid, accurate assessments that require discovery and marshaling of evidence, integration, and synthesis of data from disparate sources, interpreting and evaluating data and information that are constantly changing, and making recommendations or predictions in the face of inconsistent and incomplete data. While computational capabilities and the volume and complexity of information continue to grow rapidly, human cognitive abilities—memory, attention, sensory bandwidth, comprehension, visualization abilities—remain static. Therefore, there is a recognized need to develop technology-based solutions to reduce the workload and improve the throughput and quality of information analysis products.
The goals of research in this area are to develop joint cognitive systems—i.e., human-computer collaborative systems—that yield superior performance to either the human or the computer acting independently. This research includes:
- Performance aids/tools and knowledge-based systems
- Human performance enhancement through automated support that targets specific cognitive limitations or biases.
Human-Information Interaction refers to the study of how humans recognize process, remember, synthesize, visualize, and comprehend information. More than human-computer interaction, this field of research recognizes the ever-changing nature of information analysis problems that require smarter, more adaptive systems that augment the human's cognitive skills to enhance the performance of the human-computer system.
Research challenges are to develop system designs and methods that leverage new understanding about characteristic limitations in cognition. Among the activities being conducted by PNNL in support of this growing research area are:
- Cognitive modeling, intelligent interfaces
- Human-computer collaboration/agent-based systems
- Multimodal interaction technologies
- Human-System Effectiveness Evaluation
- Support for data analysis/discovery
- Requirements and design of visualization concepts and interaction techniques.
Cognitive systems draw from neuroscience, cognitive science, biology and computing technology, to aid in human decision making and predictive systems science/technology. While traditional computing technologies are quantitative in nature, cognitive systems exploit the tolerance for imprecision, uncertainty and partial truth, found in biological systems to achieve tractability and robustness in modeling and decisions involving
- Complex systems
- Emergent systems
- Systems requiring adaptation