Industrial interest in AI and HCI can be measured in terms of their use in industrial operations and the extent of external (usually government) funding of industrial programs.
AI practitioners and users would concur that AI has an apparently solid future in academia and a bright, expanding future in applications. Today AI is pervasive in academic institutions, although its applications are primarily in industry and government. Well-known and widespread examples of AI applications include the following: expert systems, multisystem analysis, natural language processing, pattern recognition, robotic control, and computer vision.
HCI is rapidly acquiring all of the attributes of a scientific specialty area of computer science and, according to many experts, will shortly be perceived as such. The hardware resource base for HCI is shared fairly equally between academia and industry.
The skill base for AI and HCI is currently shared fairly equally between academia and industry. Government is primarily an HCI customer rather than a research source. The diversity of the required skill base for AI and HCI makes it difficult for a single research organization to sustain the minimum skill requirements. One attractive option is for NRL to form long-term arrangements with other research groups to pool skill bases in order to meet programmatic needs. This pooling is a cost-effective means for obtaining more current skills than are often available in a government laboratory with a stable professional population and a low attrition rate. Fortunately, the growing success of multimedia networking has essentially negated any justification for "owning" all needed skills at one facility. NRL is encouraged to enter into such strategic alliances via multimedia networking to maintain the necessary diversity in its AI and HCI skill base. It is further encouraged to establish joint projects in as many research or application areas as is feasible. However, the laboratory is cautioned that cooperative networking programs need to be explicitly defined, with formal, agreed-on objectives.
The panel made a number of observations and reached a number of general recommendations regarding AI and HCI: