Defense Advanced Research Projects AgencyTagged Content List

Artificial Intelligence and Human-Computer Symbiosis Technologies

Technology to facilitate more intuitive interactions between humans and machines

Showing 9 results for AI + Trust RSS
A key ingredient in effective teams – whether athletic, business, or military – is trust, which is based in part on mutual understanding of team members’ competence to fulfill assigned roles. When it comes to forming effective teams of humans and autonomous systems, humans need timely and accurate insights about their machine partners’ skills, experience, and reliability to trust them in dynamic environments. At present, autonomous systems cannot provide real-time feedback when changing conditions such as weather or lighting cause their competency to fluctuate. The machines’ lack of awareness of their own competence and their inability to communicate it to their human partners reduces trust and undermines team effectiveness.
Today, machine learning (ML) is coming into its own, ready to serve mankind in a diverse array of applications – from highly efficient manufacturing, medicine and massive information analysis to self-driving transportation, and beyond. However, if misapplied, misused or subverted, ML holds the potential for great harm – this is the double-edged sword of machine learning.
March 14, 2019, 9:00 AM ET,
DARPA Conference Center
The Information Innovation Office is holding a Proposers Day meeting to provide information to potential proposers on the objectives of the new Artificial Social Intelligence for Successful Teams (ASIST) program. ASIST will explore human-machine teaming and machine social intelligence in a teaming context. DARPA envisions computer-based agents that observe their surroundings; build and maintain rich representations of the environment, team, and individuals; infer teammates’ goals (non-verbal behavior); predict teammates’ actions; and assist teams by planning interventions and executing them at appropriate times. During demonstrations in a virtual testbed, ASIST agents will operate in increasingly complex environments and will have to adapt to challenges such as a change in strategy.
February 20, 2019,
The Defense Advanced Research Projects Agency (DARPA) Defense Sciences Office (DSO) is sponsoring a Proposers Day webcast to provide information to potential proposers on the objectives of an anticipated Broad Agency Announcement (BAA) for the Competency-Aware Machine Learning (CAML) program. The Proposers Day will be held via prerecorded webcast on February 20, 2019 at 11:00 AM EST and will repost at 3:00 PM EST. Advance registration is required for viewing the webcast.
In order to transform machine learning systems from tools into partners, users need to trust their machine counterpart. One component to building a trusted relationship is knowledge of a partner’s competence (an accurate insight into a partner’s skills, experience, and reliability in dynamic environments). While state-of-the-art machine learning systems can perform well when their behaviors are applied in contexts similar to their learning experiences, they are unable to communicate their task strategies, the completeness of their training relative to a given task, the factors that may influence their actions, or their likelihood to succeed under specific conditions.