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2021 | Book

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The Feeling Economy

How Artificial Intelligence Is Creating the Era of Empathy

Authors: Roland T. Rust, Ming-Hui Huang

Publisher: Springer International Publishing

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

As machines are trained to “think,” many tasks that previously required human intelligence are becoming automated through artificial intelligence. However, it is more difficult to automate emotional intelligence, and this is where the human worker’s competitive advantage over machines currently lies. This book explores the impact of AI on everyday life, looking into workers’ adaptation to these changes, the ways in which managers can change the nature of jobs in light of AI developments, and the potential for humans and AI to continue working together.

The book argues that AI is rapidly assuming a larger share of thinking tasks, leaving human intelligence to focus on feeling. The result is the “Feeling Economy,” in which both employees and consumers emphasize feeling to an unprecedented extent, with thinking tasks largely delegated to AI. The book shows both theoretical and empirical evidence that this shift is well underway. Further, it explores the effect of the Feeling Economy on our everyday lives in the areas such as shopping, politics, and education. Specifically, it argues that in this new economy, through empathy and people skills, women may gain an unprecedented degree of power and influence.

This book will appeal to readers across disciplines interested in understanding the impact of AI on business and our daily lives. It represents a bold, potentially controversial attempt to gauge the direction in which society is heading.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
Artificial Intelligence (AI) is advancing rapidly, and transforming all aspects of daily life, and particularly business. AI is advancing in a predictable and systematic way, from mechanical intelligence, to thinking intelligence, to feeling intelligence (in order of difficulty for AI. With AI increasingly taking on thinking tasks, humans are finding that our differential advantage lies in feeling intelligence. The result is a “Feeling Economy,” in which humans focus less on thinking and more on feeling, emotional intelligence, and empathy. These changes will be profound, and are already underway.
Roland T. Rust, Ming-Hui Huang
Chapter 2. The Physical Economy
Abstract
The Physical Economy was the economy that existed before the revolution in information and communication technologies. Roughly speaking, this is the economy of the nineteenth century and before, in most developed countries. Industries like farming, mining, and labor-intensive manufacturing dominated this period. Nostalgic politicians often promise to save or recover the jobs of farmers, coal miners, and other physically oriented workers, but those promises are futile. The Physical Economy has been in decline for more than 100 years, and we are not going back.
Roland T. Rust, Ming-Hui Huang
Chapter 3. The Thinking Economy
Abstract
Most developed countries are now in the last years of the Thinking Economy. As physical labor became automated, human physical labor became devalued. This created a Thinking Economy, in which the most valued human skill was thinking. We still mostly live in the Thinking Economy, but there are starting to be cracks. AI is beginning to make impressive inroads in thinking, which is now threatening the economic value of human thinking. Thinking AI can be usefully categorized into analytical thinking and intuitive thinking. Modern machine learning is making rapid advances in analytical thinking, but has much more trouble with intuitive thinking, which may require a different approach. This means the last human bastion of dominance in the Thinking Economy is intuitive thinking and common sense.
Roland T. Rust, Ming-Hui Huang
Chapter 4. The Feeling Economy
Abstract
As AI assumes an increasing number of thinking tasks, eventually including even intuitive thinking tasks, humans will find that their highest and best use involves emotion, empathy, and interpersonal relationships. At that point, we will be in a Feeling Economy, in which AI specializes in thinking, and humans specialize in feeling. We are not entirely there yet, but the trend is already clear, and supported by empirical data. We project, based on the current rate of change, that feeling tasks should be more important than thinking tasks for human workers by the year 2036.
Roland T. Rust, Ming-Hui Huang
Chapter 5. The Age of Emoji
Abstract
As the Feeling Economy emerges, and AI assumes more thinking tasks, people are increasingly focusing on emotion. One notable way this trend is manifested is the increasing use of emoticons (typographical tricks that resemble pictures) and emoji (plug-in graphics that are actual pictures). Such emotional communication has become ubiquitous on social media and the Internet. Those technologies have deconstructed time, physical distance, and emotional distance, making emotional connection possible even when people are far apart, and even when their communication is separated in time. This greater access to emotional communication makes emotional intelligence more important than ever. We even see the emotionalization of the creative arts, such as music, as AI becomes more involved in artistic production.
Roland T. Rust, Ming-Hui Huang
Chapter 6. Jobs That Feel
Abstract
: Jobs are changing, as AI assumes more thinking tasks. With thinking no longer an area of human dominance, human workers are being driven to increase the feeling and interpersonal content of what they do. From the viewpoint of AI intelligence, those jobs are “upgraded” to focus on the tasks that are more difficult for AI. Empirical research shows that the importance of feeling tasks is increasing for human workers, and that feeling-related jobs are increasing the fastest in terms of pay.
Roland T. Rust, Ming-Hui Huang
Chapter 7. The Era of Women
Abstract
As the Feeling Economy emerges from the development of AI, one group of people seems uniquely positioned to benefit. We may be beginning to experience the era of women. The history of automation and AI turns out to involve a steady decline in the status and importance of men, along with a steady increase in the status and importance of women. The Physical Economy was dominated by men, with their larger size and bigger muscles. As physical tasks were automated, the Thinking Economy emerged, which was a much more favorable environment for women. Throughout the Thinking Economy, signs of women’s progress have been accelerating, reflected by such things as women’s right to vote, a proposed Equal Rights Amendment and Title IX in the United States, and increasing participation by women in the military, sports, business, academia, and politics. This progress is sure to accelerate further, as women assume unprecedented status and importance in the Feeling Economy.
Roland T. Rust, Ming-Hui Huang
Chapter 8. Politics That Feel
Abstract
As people increasingly delegate their thinking tasks to AI based in the Internet and accessible by smartphones and digital assistants, their thinking abilities atrophy. This means that the best way to reach people is now through their emotions. As a result, as the electorate becomes more feeling-oriented, political campaigns and political candidates are also becoming more feeling-oriented. This explains the rise of so many populist politicians around the world, as well as the rise (and predicted fall) of US President Donald Trump.
Roland T. Rust, Ming-Hui Huang
Chapter 9. How Education Must Change
Abstract
The current educational system is designed to produce Thinking Economy workers. That has not always been true, and it will soon not be true again. The Physical Economy emphasized very different skills. When the Physical Economy was superseded by the Thinking Economy, the educational system was forced to adapt. A similar adaptation is required today, as the Feeling Economy begins to overtake the Thinking Economy. Skills that are highly prized today may soon be worth much less, which suggests the need for a revolution in education. In the Feeling Economy, the most prized skills are likely to be empathy, emotional intelligence, communication, and interpersonal relationships. This will require a different kind of education. Many of today’s Thinking Economy workers will be faced with a massive dislocation, as the skills they need to compete change to Feeling Economy skills. This suggests a heightened need for retraining and continuing education.
Roland T. Rust, Ming-Hui Huang
Chapter 10. AI for Consumers
Abstract
Many people think of AI as a tool that businesses employ, and of course business actually is applying AI very widely. However, consumers also use AI, and it is having a profound impact on how regular people live their lives. What’s more, AI is changing people’s very nature in a systematic way. Consumers in an AI-dominant world are very different from the consumers of previous generations. We consider such things as the impact of the smartphone (“AI in a pocket”) and how it allows consumers to focus more on feeling and interpersonal relationships.
Roland T. Rust, Ming-Hui Huang
Chapter 11. Management in the Feeling Economy
Abstract
As we move from the Thinking Economy to the Feeling Economy, management will have to change. The key to this new era is that AI will no longer be seen as subservient to humans. Instead, humans and AI will be teammates that collaborate to get work done. AI will be seen as an equal member of the team, and will increasingly assume more of the team’s thinking tasks. This teamwork will be more collaboration than augmentation, with AI increasingly seen as an equal member of the team.
Roland T. Rust, Ming-Hui Huang
Chapter 12. Moral, Ethical, and Governance Implications
Abstract
As the Feeling Economy emerges, there are likely to be quite a few new issues that will arise, that will challenge us morally and ethically, and will create new demands with respect to governance. Although the Feeling Economy will create new opportunities, it will also cause serious job dislocations. Related to this is the threat of increasing income and wealth inequality. The rise of Thinking AI may also result in unintended consequences that arise from our imperfect understanding of how to manage AI. One such consequence is the possibility of bias and discrimination resulting even from totally rational algorithms. Also under threat will be our privacy. New technologies are almost always used for war, also, which is likely to form the basis for a new arms race. There is also the possibility that AI can go rogue, in ways unanticipated. There is also the concern that AI may cause harm, leading to the issue of how to manage the liability arising from damages arising from the use of AI. Finally, there is the possibility of “robot rights,” which is likely to become an issue as AI becomes more intelligent.
Roland T. Rust, Ming-Hui Huang
Chapter 13. Artificial Creativity
Abstract
Can AI really be creative? Creativity has long been considered a capability unique to humans. True creativity requires intuitive intelligence at minimum, and usually also Feeling Intelligence for creation of works of art that evoke a strong emotional response. Although research on intuitive AI is progressing, this intelligence level currently represents a bottleneck for computer scientists. Nevertheless, we are seeing more and more music and art created by machines. We conclude that AI is already well-entrenched in the creative process, usually as an aid to human creators. Truly autonomous AI creativity is in its nascent stage, but numerous examples already exist
Roland T. Rust, Ming-Hui Huang
Chapter 14. AI for Feeling
Abstract
AI intelligence does not stop at thinking. Many tech companies are competing to develop feeling AI. Feeling AI is AI that has the capabilities to (1) recognize, (2) simulate, and (3) react appropriately to emotions. The current feeling AI is more mature for recognizing emotions than for simulating and responding to emotions appropriately. This is because recognizing emotions involves simple extensions of machine learning, such as data mining and text mining, with the difference being that it is emotional data that are analyzed. Examples include affective state detection (used for detecting driver’s driving conditions), classification or prediction of affective state, visualization for affective data, and biometric and behavioral sensors (e.g., eye tracking, heart rate, keystroke, and mouse tracking). Responding appropriately to emotions, such as human–computer interaction (HCI) and conversational AI, requires more human-like capabilities that are currently challenging for machines.
Roland T. Rust, Ming-Hui Huang
Chapter 15. Beyond the Feeling Economy
Abstract
If feeling AI gets good enough, it may become even better than humans on that dimension. At that point, AI would dominate HI with respect to all three intelligences—mechanical, thinking, and feeling. That point is known in the literature as the “singularity,” and it would take us beyond the Feeling Economy. The implications of the singularity would be profound. There are a number of implications that follow logically from our multi-intelligence view of AI. For example, the singularity may result in inequality of wealth and income that makes today’s situation seem benign. Even more concerning, we may find that humans do not have the control over AI that they think they do. Ultimately, AI may see itself as existing to serve itself, rather than the human race. Authors, philosophers, and other intellectuals are divided about whether the singularity will ultimately be good or bad for humans. One scenario has AI doing all the work, while humans enjoy lives of leisure. Another favorable scenario has AI augmenting and transforming humans, with the result that our powers are expanded. On the other hand, there are doomsday scenarios in which the human race is effectively replaced by AI, which may then be thought of as the next stage of human evolution and development.
Roland T. Rust, Ming-Hui Huang
Chapter 16. Conclusions
Abstract
The main thesis of this book is that, as AI assumes more thinking tasks, humans will emphasize feeling. Just as many people’s lives were transformed in the 1900s by the industrial revolution and automation, people’s lives are now again being transformed. The transformation in the last century was from physical and mechanical tasks to thinking tasks. In the twenty-first century, the transformation is from thinking tasks to feeling tasks. The transformation to the Feeling Economy, already well underway, will cause profound changes in everyone’s lives.
Roland T. Rust, Ming-Hui Huang
Backmatter
Metadata
Title
The Feeling Economy
Authors
Roland T. Rust
Ming-Hui Huang
Copyright Year
2021
Electronic ISBN
978-3-030-52977-2
Print ISBN
978-3-030-52976-5
DOI
https://doi.org/10.1007/978-3-030-52977-2