Reflections from Maryland
“Under the right conditions Artificial intelligence (AI) could prompt a seismic shift that reverberates throughout the entire economy. But good decisions will have to be made,” writes Jan Oskar Bolin, from his research stay at the University of Maryland.
As part of my PhD at NHH, a six-month research stay at the University of Maryland, has been included. Consequently, I had the opportunity to audit a PhD-level course on Strategic Marketing by Professor Roland Rust at Smith school of Business.
Rust is the co-author of the book “Feeling Economy: How artificial intelligence is creating the new era of empathy” (2021). In the book Rust and Huang argue that manufacturing technology (e.g., industrial robots) is the pillar of the physical economy, information technology (e.g., mechanical AI) is the driving force of the thinking economy, and AI (cognitive technology) is the backbone of the feeling economy.
Good decisions matter
A key takeaway from the seminar is that artificial intelligence, under the right conditions, could prompt a seismic shift that reverberates throughout the entire economy. Yet, it does not have to be so. To make the most out of AI, good decisions will have to be made.
One of our discussions centered around an unpublished working paper by Ming-Hui Huang and Roland Rust which details empirical evidence on the feeling economy. They demonstrate that investments in artificial intelligence by no means is a panacea for the various shortcomings of human intelligence.
Instead, they find evidence indicating the existence of an intelligence complementarity mechanism which operates at the individual level, and an intelligence congruence mechanism which operates at the macro level.
Individual and societal levels
At the individual level, artificial intelligence is the most effectual when it complements the individual worker’s intelligence. Feeling-advantaged females, for example, stand to benefit from investments in analytical AI. Conversely, bullheaded—often male—workers could learn a thing or two from the compassion embodied by feeling AI.
At the societal level, artificial intelligence produces the best outcomes when it is congruent with the dominant intelligence in the economy. For example, recently industrialized developing economies may benefit more from investments in mechanical rather than feeling or thinking AI.
Although promising, this technology presents politicians, managers, and workers with tough choices.
Do politicians in industrializing nations lay the groundwork for long-term benefit by readying the nation for the coming feeling economy, or do they seek to take advantage of currently complementary investments in mechanical AI?
How can managers make the most out of this opportunity to reimagine the nature of work by not necessarily replacing but freeing up human intelligence?
Should workers protect themselves by investing in their strengths or should they rather focus on empathic skills which are still more difficult to emulate?
A sense of optimism
I look at these questions with a sense of optimism. There will never be a catch-all approach towards adoption of new technologies, including artificial intelligence. Yet, with sensible stewardship, companies and even countries can make tough, but ultimately rewarding, choices concerning the adoption of artificial intelligence.
As researchers in the Digital Innovation for sustainable Growth (DIG) research center, I believe our research can offer valuable guidance on this process. Specifically in services where high tech can be better balanced with high touch – empathy and feelings – to create more value for customers.
One area to expect more high touch is in online shopping where the (positive) emotional experience of shopping can be brought back into the equation through advancements within metaverse technology.
Differential pricing vs. consumers’ desire for fairness
As for my own research, personalization and algorithmic pricing stand out as emerging applications of artificial intelligence. As (moderately) youthful people, most of us cling on to the notion of pricing as an impersonal phenomenon.
But it was not always so, and the standardization brought about by the industrial revolution is now being scaled back. For the remainder of my exchange, I will continue to explore how to capitalize on the promise of differential pricing without upsetting consumers’ desire for fairness and displays of empathy.