What Comes After the Knowledge Economy?

Earlier this year, Elon Musk sparked controversy with his prediction that we will have AI smarter than human beings by 2026. While the accuracy of this statement is widely debated, it’s undeniable that AI has already surpassed human performance on several benchmarks and is increasingly capable of automating operations that once required human knowledge. AI systems can now perform complex tasks in fields like data analysis, customer service, and even medical diagnostics.

This rapid advancement has understandably fueled widespread concern about AI's impact on jobs and the broader economy. According to Pew Research, 52% of Americans report feeling more concerned than excited about AI, a notable increase from 38% in 2022. It’s not surprising that the future of AI is a polarized topic among experts, ranging from optimists who believe it will give humanity freedom like we have never seen, to doomsayers who truly fear extinction.

Whatever the debates, everyone agrees that AI is poised to automate a significant portion of knowledge work. Therefore, it’s crucial to explore how it will reshape jobs and the fundamentals of our economy.

Understanding the Knowledge Economy

We currently operate in a Knowledge Economy, which Stanford researchers define as “production and services based on knowledge-intensive activities that contribute to an accelerated pace of technical and scientific advance, as well as rapid obsolescence.” The key component of a knowledge economy is a greater reliance on intellectual capabilities or “intellectual capital” than on physical inputs or natural resources. Think: doctors, marketers, engineers, lawyers, researchers, science communicators, you name it.

In simple terms, we got to this point through innovation – for millennia, human society was dominated by an Agricultural Economy, which was characterized by manual labor and the use of natural resources to produce food and raw materials. While most ag workers and farm owners were extremely knowledgeable about their land, crops, and best practices in keeping the world fed, a successful agriculture economy relied heavily on the sweat and labor of humans and animals. The advent of the Industrial Revolution in the late 18th century marked a dramatic shift to an Industrial Economy. This period saw the rise of factories, mass production, and significant technological advancements, which transformed how goods were produced and fundamentally changed societal structures. Physical labor was still absolutely necessary (hello, Upton Sinclair). The Information Age in the late 20th century transitioned us from a labor-based industrial economy to a knowledge-based one.

And today, we are at the beginning of a new economic era. Britannica defines an economy as “the process or system by which goods and services are produced, sold, and bought in a country.” AI is infiltrating the knowledge economy – Asana’s State of AI at Work 2023 report found that 29% of employees say their work tasks are replaceable by AI.

That percentage will continue to increase, as global spending on AI-centric systems skyrocket, reaching $154 billion in 2023. The market is projected to grow more than thirteenfold in the next seven years. Unlike previous waves of automation, which primarily created tools proficient at handling repetitive tasks, AI can now address highly non-routine tasks that were once the domain of highly skilled workers. It’s infiltrating all industries, as AI’s ability to process vast amounts of data and perform sophisticated analyses means it can take on tasks ranging from legal document review to medical image interpretation.

On the surface, this is understandably scary for workers who have grown up believing that their education, experience, and skills would keep them employable until retirement. Right now, the future of our workforce is uncertain. While AI is likely to automate routine, repetitive tasks, it will also create new opportunities that require uniquely human skills. Imagine all that time invoicing time freed up for finance and ops teams to engage in more creative, strategic, and empathetic work.

“Information and accumulated knowledge have become a commodity. What may be missing is the wisdom of what to use and when.” Gregory Stebbins, Ed.D.

A New Economic Era

The future is never certain, but many experts (perhaps optimists) have proposed we are entering a human-centric economy or “wisdom economy” in the age of AI, meaning humanity's wisdom will become capital.

The term “wisdom economy” was first seen in Earl Cook's 1982 paper on "the Consumer as Creator.” In a wisdom economy, value is derived from the application of collective and individual wisdom to solve complex problems, innovate, and create sustainable practices. The term "wisdom economy" refers to an economic system where the focus shifts from merely accumulating and applying knowledge and information to applying wisdom, which involves deep understanding, ethical considerations, and long-term thinking.

As AI infiltrates our everyday life, it blurs the line between what is human and what is machine. Already, humans naturally prefer humans. In a 2023 survey, Storyblok found that a majority of consumers expressed disinterest in AI recommendations. Specifically, 85% of the 1,000 respondents did not want AI to assist them in making purchasing decisions. Furthermore, 60% stated they would not buy a product if they knew it was recommended by AI. In another survey by Nexcess, respondents could identify the AI-generated content nearly 55% percent of the time. It was easy, of course, when Will Smith eating spaghetti was the height of AI’s powers. As of July 2024, AI has already come for User Generated Content creators and television commercials. Many consumers cannot clock the AI content. AI is already testing what it is to be human.

In short, we desire the wisdom to decipher what is real and what is machine, which will become more and more complicated over time. In 2014, Dov Seidman discussed the concept of a human economy in the Harvard Business Review article “From the Knowledge Economy to the Human Economy.” “In the human economy,” he writes, “the most valuable workers will be hired hearts.”

After years of conditioning our brains, how do we prepare our hearts to be hired? Jobs in this economy are those that require high degrees of human interaction and emotional intelligence. For example, hospice workers provide compassionate care and support to patients and their families during end-of-life stages—a role that AI cannot replicate. Teachers and educators need to engage, inspire, and adapt to the unique needs of each student. Social service jobs involve direct interaction with the community, addressing social issues, and providing support services. In healthcare, AI supports professionals by handling data-intensive tasks, allowing them to focus on patient care. This balance showcases the potential harmony between human wisdom and technology.

Eliza Kosoy, a researcher at MIT’s Center for Brains, Minds, and Machines, believes that “with enough data and the correct machine learning algorithms, machines can make life more enjoyable for humans.” While this may hold true, numerous contingencies currently hinder the transition to a human-centric economy in this new age of AI.

Ethical Considerations

For AI systems to benefit society, they must be designed and used ethically, ensuring transparency, fairness, and accountability. Global concern has spurred both private and public institutions to develop best practices for creating and using AI ethically, urging researchers and engineers to consider unintended consequences and future challenges. For instance, unintentional biases in decision-making algorithms pose significant challenges. An example: A 2021 study conducted by the World Economic Forum reported that women comprised just 29 percent of the workforce in science, technology, engineering, and math (STEM) fields. We know that representation changes industries and world views. A lack of diversity will likely exacerbate biases in AI development.

Additionally, Big Tech's dominance in the AI space raises concerns about equitable development and deployment. In MIT’s Download, Rhiannon Williamns highlights the dependency on Big Tech for AI development: “With vanishingly few exceptions, every startup, new entrant, and AI research lab is dependent on [Big Tech].” In today's world, almost everyone working on AI relies on companies like Microsoft, Amazon, and Google. These giants offer the computing muscle to train the systems, and the vast customer pool to launch and sell them.

Equitable Access and Political Leadership

Effective utilization of technology requires specialized skills and resources. However, disparities in access to these resources present significant barriers. According to Broadband Now, in 2021, 42 million Americans lacked access to the internet, limiting their ability to engage with new technologies. Furthermore, the McKinsey Global Institute projects that automation could necessitate occupational changes for up to 375 million workers worldwide by 2030, underscoring the need for widespread retraining and education initiatives. To reduce the technology sector’s impact on income inequality, proactive steps by policymakers are crucial.

The U.S. leads the AI market, but ethical concerns need addressing to ensure AI benefits society. The Senate AI Gang recently released a roadmap on how the country will address AI, which critics labeled “pathetic” due to its vagueness in addressing major risks. Many felt the roadmap emphasized investment and acceleration while offering minimal guidance on regulation and accountability. Effective political leadership is essential to balance innovation with societal protection.

Public Confidence and the Future of the Wisdom Economy

AI's complexity and the fear of the unknown create significant apprehension among employees and the public. The Stanford AI Index Report revealed that only 37% of respondents believe AI will improve their jobs, and 34% anticipate AI will boost the economy. Additionally, 52% express nervousness toward AI products and services. For successful AI adoption, companies must approach it inclusively, ensuring that everyone is on board.

While uncertainty remains, and many fear that AI will threaten various professions and aspects of human life, it cannot replicate the unique intelligence and emotional depth inherent to humans. Dov Seidman’s prescient HBR article didn’t predict that AI was necessarily going to crash the global workforce, but he did predict that in the face of instability “companies that succeed best will be those that focus on the humanity of work and capitalize on what humans can uniquely do.”

As we approach the next election cycle, it’s clear that candidates will need to address key issues related to AI and its impact on society. Embracing a wisdom economy, where human qualities complement technological advancements, is essential for a future where both AI and humanity can thrive.

“Certainly, machines will continue to get better at many things that humans have traditionally done in businesses, but machines will never be the source of enduring advantage. The companies that succeed best will those that focus on the humanity of work, and capitalize on what humans can uniquely do.” Dov Seidman

Further Reading

AI Taking Over Jobs: What to Know About the Future of Jobs

• AI is set to replace a range of jobs that impact industries ranging from healthcare to agriculture and the industrial sector. Workers in these fields can anticipate significant disruptions in hiring due to the advancement of AI technologies. Simultaneously this shift will also create increased demand for workers in other sectors, driven by the new opportunities and roles that AI is expected to generate.

Deploying AI For Profit Or Humanity: Why Not Both?

• David Rothschilds argues for a balanced approach to AI innovation, emphasizing that AI can enhance both profitability and human connection. Rothschild, inspired by his early experiences with technology, believes AI's true potential lies in augmenting human capabilities. He highlights AI's role in healthcare to illustrate how it can handle routine tasks, freeing professionals to focus on empathy and deeper engagement, ultimately suggesting that AI can align with humanity's broader purpose and well-being.

For Success with AI, Bring Everyone On Board

• An exploration of why leaders hesitate to involve rank-and-file employees in AI projects, how to model inclusive behavior, and what steps organizations should take to develop inclusive AI practices. These practices can enhance long-term performance and ensure employees remain happy, productive, and engaged.

Why can’t anyone agree on how dangerous AI will be?

• This is a debate among experts and superforecasters about the existential risks posed by AI. While experts express higher concern, superforecasters are more optimistic. A study by the Forecasting Research Institute found that discussions and exposure to opposing views did little to change their initial positions.