Defense Advanced Research Projects AgencyTagged Content List

Artificial Intelligence and Human-Computer Symbiosis Technologies

Technology to facilitate more intuitive interactions between humans and machines

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Dramatic success in machine learning has led to a torrent of Artificial Intelligence (AI) applications. Continued advances promise to produce autonomous systems that will perceive, learn, decide, and act on their own. However, the effectiveness of these systems is limited by the machine’s current inability to explain their decisions and actions to human users (Figure 1). The Department of Defense (DoD) is facing challenges that demand more intelligent, autonomous, and symbiotic systems. Explainable AI—especially explainable machine learning—will be essential if future warfighters are to understand, appropriately trust, and effectively manage an emerging generation of artificially intelligent machine partners.
The goal of the Fundamental Design (FUN Design) program is to determine whether we can develop or discover a new set of building blocks to describe conceptual designs. The design building blocks will capture the components’ underlying physics allowing a family of nonintuitive solutions to be generated.
Machine learning has shown remarkable success across many application areas in recent years, leveraging advances in computing power and the availability of large sets of training data. It provides a tremendous opportunity to deploy data-driven systems in more complex and interactive tasks including personalized autonomy, agile robotics, self-driving vehicles, and smart cities. Despite dramatic progress, the machine learning community still lacks an understanding of the trade-offs and mathematical limitations of related technologies for a given domain, problem, or dataset.
In supervised machine learning (ML), the ML system learns by example to recognize things, such as objects in images or speech. Humans provide these examples to ML systems during their training in the form of labeled data. With enough labeled data, we can generally build accurate pattern recognition models.
| AI | Algorithms | Data |
Artificial intelligence (AI) and machine learning (ML) systems have advanced significantly in recent years. Despite a wide range of impressive results, current AI is not intelligent in the biological sense. These systems are limited to performing only those tasks for which they have been specifically programmed and trained, and are inherently subject to safety hazards when encountering situations outside them.