We live in a world in which we are surrounded by technologies designed to meet our every need and whim; we have sent probes beyond the farthest reaches of our solar system, and we have selfie-taking machines exploring celestial neighbors and conducting revolutionary experiments that alter our understanding of the universe, a National Institute for Standards and Technology research scientist wrote.
Meanwhile, media, communications, retail, investment and banking industries are clamoring to cater to our personal preferences for service. Artificial intelligence is the underlying technology that enables the wonders we now take for granted, and promises more innovations into the future.
“AI enables the way we drive, entertain ourselves, read the news and make dinner. We can even carry out complex social relationships through online video games without ever having to physically meet another human being,” Jeremy Marvel wrote.
The world’s stockpile of many centuries of knowledge can be accessed in mere seconds on computers we carry in our pockets. It’s not a stretch to say we are living in a future predicted in popular movies and books.
Still, we want more.
“Robots are becoming increasingly prevalent in the manufacturing, medical and service fields. Robots are purposefully designed to work around and with people. Robots are even marketed as being ‘collaborative’ in that they are supposedly safer and easier to use than ever. In every case, robots are custom-tailored for their users’ needs. Such trends imply robotics are becoming consumer products,” wrote Marvel.
Revolutionary and sociable robots are being sold in an eager and enthusiastic market. However, robots are falling short of consumer expectations for companionable multipurpose devices designed to take the drudgery out of household chores and daily life.
This is because all robots are purpose-built, principally because there is a trade-off between simplicity and functionality. To be usable and useful, the interfaces connecting people and machines must carefully negotiate a path that is either “too complex” or “too simple,” Marvel explained.
The real challenge lies in developing the right interface mechanism for expressing a user’s desired actions. The purpose of the interface is to facilitate communication and drive interaction between a human and machine. The challenge, however, is in balancing usability for a broad spectrum of users while simultaneously providing useful products that can also satisfy an individual user. The right mix of comfort and functionality often requires a lot of trial and error, especially if the ultimate application of the machine is unknown, Marvel explained.
“It’s the task and the utility of a given robot that allows it to be custom-designed for the end-user. Specific tasks get specific robots that are built to be user-friendly. General tasks get … something else. When the task is unknown or ill-defined, the manufacturer must anticipate all possible — or at least all supported — applications and design around that,” Marvel wrote.
When things start to go wrong between the user and machine, it can be extremely difficult to diagnose the problem, and it’s the interface’s job to assess the situation and formulate a solution for the robot. A good interface can enhance a user’s experience, while a bad interface can render a machine completely unusable, Marvel wrote. “Thus, the interface drives the experience. Similarly, the means by which humans interact with machines dictates their utility. By changing the interface, one can effectively change how a given robot is used … or if it’s used.”
An interface that can efficiently adapt to a user or a task is theoretically more useful for that task than an interface that attempts to accommodate all possible tasks or behaviors. To be able to accomplish this, however, the robot needs to be aware of its environment and the user.
“While we have some basic tenets to help us differentiate good graphical interfaces from bad ones, there are no metrics by which vendors can measure the effectiveness and efficiency of the interaction between people and robots before the robots are sold and used. Nor are there any standardized means by which we can measure how much a given interface or interaction will be better than another. Currently, the best metrics for measuring the effectiveness of human-machine interactions are through subjective, qualitative, user-volunteered reports. There are few objective, quantitative measures by which a given interaction can be assessed,” Marvel wrote.
If such quantitative metrics existed, however, a robot could adjust its behaviors to match the user and the application, working in a collaborative manner to enable the efficient completion of a task, Marvel explained. “Similarly, if such adjustments are perceived by the people working with the robot to be both intentional and appropriate, then their confidence in the performance of the robot is strengthened and they can, in turn, respond accordingly. This mutual situational awareness is critical for effective teaming, regardless if it’s on the factory floor or in your kitchen at home. If the interaction breaks down, so too does the team’s performance,” he wrote.
This is the basis for a new research project at NIST, the Performance of Human-Robot Interaction, which seeks to establish test methods and metrics for assessing and assuring the effective teaming of humans and machines, Marvel wrote. These metrics and test methods will enable the benchmarking and advancement of technology to a baseline of maintaining trust in the capabilities of the robot. Part of the project’s efforts includes reaching out to the world’s experts in human-robot interaction to develop a standardized measurement methodology.
“In the recent workshop, Test Methods and Metrics for Effective HRI in Collaborative Human-Robot Teams, NIST researchers and world experts established both the need and means by which human-robot interaction can be objectively measured and replicated. These needs take into account both applications and intercultural issues that drive the user experience and mechanisms for interaction. Ultimately, this workshop kick-started a concerted effort to advance collaborative robot technologies into the future,” Marvel wrote.
Edited from the article, “The Cybernetic Revolution: The Influence of Metrology on the User Experience in Human-Robot Interaction,” by Jeremy Marvel, a research scientist and project leader in NIST’s Intelligent Systems Division. Marvel has over 15 years of research experience in robotics and artificial intelligence.