Flexibility and Resilience

Some participants commented that improved human-machine collaboration will require improved flexibility and resilience. For example, Hoffman observed that human-machine interfaces would be improved by engineering for resilience, that is, designed for unanticipated tasks. Such flexibility is particularly important, Jean Scholtz added, as the tasks people do today will not be identical to those being done tomorrow or in five or ten years. Humans can rapidly adapt and apply their capabilities to new situations, so how can this flexibility and learning be applied to robots without significant programming?

Frank Dignum suggested that lessons may be learned from human adaptability—for example, the adaptation of human language to widespread adoption of text messaging. Rather than wait for convergence in, for example, natural language between humans and robots, he proposed a deeper examination into situations in which humans but not robots are able to adapt.

This resilience, Neerincx noted, will require breakthroughs in context-driven adaptive autonomy. Both Hoffman and Sidner commented that such high levels of complex autonomy would first depend on significant breakthroughs in commonsense knowledge and practical manipulation tasks.

Modeling

Another common challenge discussed was the potential benefit of improved human, machine, and shared human-machine models. Goodrich spoke to the difficulties of developing such shared models by describing human and machine dynamic asymmetries in experience, understanding, goals, and capabilities.

Although some participants emphasized the need to provide robots with better models of humans, Scheutz noted the challenges of building correct models of robots for humans. Human models of robots, he said, need to be compatible with the ways humans will interact with them. For example, if a robot does not have good natural language or good visual sensing capabilities, perhaps anthropomorphized robot mouths or eyes will mislead humans to overestimate the robot’s capabilities. While highly realistic Geminoid robots exist, Holly Yanco added that the “uncanny valley” factor should also be taken into consideration.

According to Dignum, new social reality models may allow machines to do things “with” humans, and not just “for” humans in a limited role. Many of the workshop participants remarked that it would help for humans to develop social understanding and acceptance of such sophisticated machine capabilities in order for this level of collaboration to occur.



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