Management in the Feeling Economy: Tips for Fostering Human-Machine Collaboration

As Artificial Intelligence (AI) continues to advance and handle more complex analytical and cognitive tasks, humans throughout the workforce will be increasingly valued for their dexterity with emotional issues, intuition, empathy, and people skills. In businesses and organizations of all kinds, AI will no longer be seen as subservient to humans—or as a threat to their job security. Instead, AI will be seen as an equal member of the team, working with humans to get work done. Collaborating and complementing one another, humans and machines will each do what they do best, based on the respective nature of their intelligences. Yet for human-AI collaboration to become widely embraced and implemented, management will have to change.

Seamless collaboration between AI and HI—that is, human intelligence—is a hallmark of the emerging Feeling Economy. In the very near future, thinking AI will evolve to handle more of the traditional “brain” work, while human workers in far-flung fields—manufacturing, retail, healthcare, hospitality, and more—will need to focus on developing their natural capacity for feeling. Beyond standardization of products and personalization of services, the major consumer benefit of the Feeling Economy is relationization: personalized relationships.

AI-HI collaboration can be achieved at different intelligence levels and at different networking levels for remarkable gains in relationization. However, such AI-HI collaboration can sometimes go bad. For example, we can design machines with the goal to “augment” humans, but the self-learning path may not follow suit. We can use data in a way that follows consumers’ privacy wishes, but the networking environment may not always be under control (try to think of Facebook’s many data breach and leakage problems). Thus, we need to have a better understanding about how to manage these collaborations, to move the outcomes in the positive direction.

Towards that goal, we propose major priorities for managers: 

Think of AI and employees as teammates, not adversaries. In the Feeling Economy, nearly every workplace is bound to be one where AI and HI collaborate, rather than either AI or HI dominating individually. Therefore, managers should shift their thinking from whether AI replaces or augments employees to AI-HI collaboration. In specific jobs from customer service agent to physician, typically AI will assume an increasing number of the thinking tasks, and human employees will spend more of their time on feeling tasks and interactions with others.

Be feeling intelligent. Managers need to focus more on the feeling and empathetic nature of business, and be more attuned to the emotional needs of employees and consumers to get (and keep) business. Just as mechanical AI automated mechanical tasks and created opportunities for thinking companies (e.g., Microsoft), thinking AI is automating more and more thinking tasks and creates new opportunities for feeling companies (e.g., Facebook). Managers thus need to be more feeling intelligent.

Understand emotional needs. In the Feeling Economy, consumers will focus more on their feelings. Consumers, especially young consumers, are already accustomed to anywhere-anytime interaction through computers and smart phones on social media. This shift toward constant interaction results in greater reliance on feeling and social interaction for buying decisions. For example, we have witnessed the unprecedented use of emotional shorthand, such as emoji, on AI-facilitated social interactions. When consumers increasingly deemphasize thinking and emphasize feeling, the need to better understand emotions and their power becomes more important.

Skill for feeling intelligence. As AI becomes more capable of thinking, managers and employees all need to improve their feeling intelligence skills, especially empathy. This can be achieved by re-skilling (if they are very unskilled with respect to people skills and social skills to begin with), up-skilling (to improve their people and social skills), or cross-skilling (if they are the thinking type by nature). This skill-building applies to consumers as well. We have seen too many instances in social media in which some consumers do not have good people and social skills (e.g., cyberbullying, cruel Twitter tweets) that hurt other consumers, intentionally or unintentionally.

Written by Ming-Hui Huang and Roland T. Rust.