Human$-$Machine Teaming

This activity is important because managers should understand the feelings and thoughts of team members as they work together. Team member feelings can be important even when working with artificial intelligence $($AI$).$ The ability to identify successful strategies to encourage effective team states will improve team productivity and satisfaction.

The goal of this activity is for you to learn about team states and AI developments that make computers act as team members, also called human$-$machine teaming $($HMT$).$

Read the case and answer the questions that follow.

You may describe a good team member as being skilled in communication, collaboration, adaptability, and innovativeness, but what about a team member with artificial intelligence $($AI$)?$ Human$-$machine teaming $($HMT$)$ is increasingly popular in complex types of work, and the AI counterparts are surprisingly human.

More advanced robots have subtle movements that mirror human interaction versus jolts and loud noises. They also can interpret conversational speech and gestures. These characteristics make AI team members fit into the natural flow of work better. AI also has the decision$-$making ability that leads people to expect human qualities. Many can converse, give empathetic responses, and use appropriate social skills.

AI machines can be programmed with the history of a project and past decisions, able to integrate that information into future decisions. They also learn as they work alongside a human and can anticipate next steps. In this way, AI teammates know how the team approaches the problem and what drove past decisions, creating a more natural flow of work.

HMT can be used in various industries such as air travel, law, health care, and defense. The Army Research Lab reports that it uses HMTs in autonomous vehicles that can maneuver in highly volatile and dangerous situations. When facing enemy threats, the soldiers can focus on their mission because they do not have to operate the vehicle or make sudden adjustments that would divert their attention.

HMTs can also be found in unexpected industries, according to Workflow magazine. For example, home caregiver bots can work in partnership with doctors to manage medication and monitor elderly patients on a daily basis, even assisting in diagnosing and detecting subtle problems. AI can provide legal representation and advice, working alongside paralegals and lawyers to perform routine tasks. AI can even settle simple legal cases.

In the best scenario, AI and humans have compatible skills. Cross$-$training is one effective way to build teammate relationships versus one$-$way command relationships in an HMT$.$ MIT researchers found that when the AI and employee trained together and switched tasks in order to better understand how the work was performed, the employee was better able to anticipate the computer$$s reactions. This resulted in higher productivity.