Interview with Karen Linkletter at the 16th Global Peter Drucker Forum 2024  Video Interview

Nowhere is management theory demanded more than in managing the knowledge worker, and yet nowhere is management theory more inadequate in addressing a field’s issues than in knowledge work. This is the point Peter Drucker posited in his work Management Challenges for the 21st Century (1991), and to resolve it he came up with six factors that determine the productivity of the management worker. Among these, his final point that management workers “must be treated as an ‘asset’ rather than a ‘cost’” by any given organization is an important concept1. While it only gradually emerged within management theory over the century, it is crucial for any employer and any government to understand and apply if they are to retain a competitive advantage going into the future. Historically, management theory has been about improving the output of the worker through banal efficiency: how to increase the production of steel per head, how to increase the production of cars per hour, how to minimize deficient products, etc. In all these considerations, the worker is a disposable resource. When he is hired, he is set to a particular task that is typically repetitive and thus easily taught, and when he is not needed because of shortcomings in his work, company difficulties, or automation, he is laid off. Referred to as “dumb oxen”, workers were seen in management theory as machines to have productivity squeezed out of. The shift from a majority manufacturing to service-based economy during the first half of the twentieth century changed this dynamic to some extent. The American postwar economic boom introduced the office worker as a common source of employment. This trend continued throughout the conglomerate era of the 1960s and was helped by the decline of the American manufacturing industry in the 1970s. Now in a stage dominated by service and knowledge work, the American economy must approach management differently. The aforementioned cost-asset shift is a demonstration of why this is so, as Drucker’s emphasis on the knowledge worker’s autonomy means that they wield control, not only within their job but over who they should work for as well. This in addition to the high-capital nature of knowledge workers means that the old management theory approach to labor as disposable will backfire catastrophically for any company that tries it with their knowledge workers. It is also important to remember the demographic trends of the United States, and more so the world, in considering why the cost-asset shift is vital. For all of human history until some fifty years ago, population was considered to be in tandem with economic power, given larger populations yielded larger labor forces and consumer markets. Economic growth was thus also correlated with population growth, demonstrated by the historic development of Europe and the United States and the more recent examples of the developing world. Consequently, the worldwide decline in fertility rates, and the decline in population numbers in some developed countries, signals economic decline for the future. In the labor market, smaller populations mean fewer jobs that produce for and service fewer people. Although the knowledge worker has grown in proportion to the total labor market, these demographic declines will affect knowledge workers as well, meaning employers will have a vested interest in retaining their high-capital labor. To enforce this, the cost-asset shift will have to come into play. The wants and needs of the knowledge worker pose a unique challenge in the field of management. Autonomy, for the first time, can be regarded as a significant factor affecting all other aspects of this labor base. What good does a large salary provide a knowledge worker if they don’t feel that they are welcome at an institution? How would they perceive that their work is not being directed towards productive pursuits at their corporation, especially given the brain work and dedication given to it? Of course, the fruits of one’s labor has been a contentious issue in management ever since compensation and workers’ rights became a universal constant with the Industrial Revolution, but this is augmented by the knowledge worker’s particular method of generating value. Given that Drucker poses their largest asset and source of value as their own mind, they will intrinsically have a special attachment to their work almost as their brainchild. Incentivizing the knowledge worker is also only one part of this picture. Per Drucker, the knowledge worker’s labor does not follow the linear relationship between quantity invested and returned. The elaborate nature of knowledge work makes it heavily dependent upon synergy: the right combination of talent can grow an organization by leaps and bounds, while virtually incompatible teams or partnerships can render all potential talent useless. And the human capital cost of the knowledge worker, both in their parents and the state educating them and in cost to their employers, is astronomical compared to all previous kinds of labor. In conclusion, the needs and wants of the knowledge worker must be met adequately, especially in the field of management. Management must almost undergo a revolution to adapt to this novel challenge, for the knowledge worker is the future of economic productivity in the developed world. Those employers that successfully accommodate the demands of this class of talent will eventually reign over those that do not accept that this is the direction economic productivity is headed.  References Drucker, P. F. (1991) Management Challenges for the 21st Century. Harper Business.

What is wisdom? The dictionary says it is knowledge of what is true and right coupled with just judgment as to action. Jennifer Rowley reports that it is the “ability to act critically or practically in a given situation. It is based on ethical judgment related to an individual's belief system.” (Rowley 2006 p. 255). So, wisdom seems to be about deciding on or doing an action based on moral or ethical belief in helping other people. This clearly describes Peter Drucker and his often prescient ideas For the 100 th anniversary of Peter Drucker’s birth, Harvard Business Review dedicated its November 2009 magazine to Drucker. In one of the articles about Drucker by Rosabeth Moss Kanter (2009 p. 1), What Would Peter Say? Kanter posits that, Heeding Peter Drucker's wisdom might have helped us avoid—and will help us solve numerous challenges, from restoring trust in business to tackling climate change. He issued early warnings about excessive executive pay, the auto industry’s failure to adapt and innovate, competitive threats from emerging markets, and the perils of neglecting nonprofit organizations and other agents of societal reform. Meynhardt (2010) calls Drucker a towering figure in Twentieth Century management. He says no other writer has had such an impact. He is well-known to practitioners and scholars for his practical wisdom and common sense approach to management as a liberal art. Drucker believed that there is no how-to solution for management practice and education. Doing more of “this” and less of “that” and vice versa is not how Drucker suggests managers do their work. Rather, Drucker relies more on morality and the virtue of practical wisdom to solve problems related to organizations. The virtue that Drucker talks about cannot be taught. It must be experienced and self-developed over time. A good example of this is Drucker’s Management by Objectives (MBO). Drucker does not give technical advice on how to initiate MBO. Rather he wisdomizes his moral convictions that integrating personal needs for autonomy with the quest of submitting one’s efforts to a higher principle (helping people) ensures performance by converting objective needs into personal goals. (Meynhardt, 2010). Peter Drucker published thirty-eight articles in the Harvard Business Review (HBR) and seven times won the McKinsey Award presented annually to the author of the best article published during the previous year in HBR. No other person has won as many McKinsey awards as Drucker The former editor-in-chief of Harvard Business Review, Thomas A. Stewart, quotes Peter Drucker; “The few of us who talked of management forty years ago were considered more or less deranged.” Stewart says that this was essentially correct. Harvard Business Review's very mission is to improve management practice. Stewart says this mission is inconceivable without Drucker’s work. Drucker’s work in management planted ideas that are as fruitful today as they ever were. Stewart posits that each year, managers discover extraordinary and immediate relevance in articles and books that were written before they were born or even before their parents were born. Stewart (2016) tries to answer the questions: Why does Drucker’s work endure? and Why is Drucker still relevant? First, was Drucker’s talent for asking the right questions. He had an instinct for being able to not let the urgent drive out the important, for seeing the trees, not just the forest. This allowed him to calmly ask pertinent questions that encouraged clients to find the proper course to take. Secondly, Drucker was able to see whole organizations. Instead of focusing on small particular problems. Ducker had the ability to find the overarching problem as well. Stewart uses Drucker’s 1994 HBR article, The Theory of the Business to make this point. Many people were trying to analyze the problems of IBM and General Motors by looking for root causes and trying to fix the blame. Drucker, on the other hand, argued correctly that the theories and assumptions on which they had managed successfully for many years were outdated. This article is as relevant today as it was in 1994 because Drucker took the “big picture view.” And no one else has ever been so skillful at describing it. Thirdly, starting in 1934, Drucker spent two years at General Motors with the legendary Alfred P. Sloan, immersed in the workings of the automaker and learning the business from within. This allowed him to talk with authority, but he has always stayed “street smart and wise.” This mentoring helped give Drucker the gift of being able to reason inductively and deductively. He could infer a new principle or a theory from a set of data or being confronted with a particular problem; he could find the right principle to apply to solve it. Drucker’s first article published in HBR, Management Must Manage, challenged managers to learn their profession not in terms of prerogatives but in terms of their responsibilities, to assume the burden of leadership rather than the mantle of privilege. Many in the management/leadership field probably found Drucker to be “deranged,” but in 2024, this is important advice for leader (Stewart 2006). Just a few more of Drucker’s ideas that seemed well outside the mainstream when he proposed them but are standard practice today include: Managing Oneself, Privatization, Decentralization, Knowledge Workers, Management by Objectives, Charismatic Leadership Being Overrated, CEO Outsize Pay Packages, and Enthusiasm of the Work of the Salvation Army (Rees, 2014). Clearly, Drucker remains relevant! References: Kanter, R. 2009. What would Peter say? Harvard Business Review. November, 2009. Meynhardt, T. 2010. The practical wisdom of Peter Drucker: Roots in the Christian tradition. Journal of Management Development Vol. 29. No. 7/8. Rees, M. 2014 The wisdom of Peter Drucker. Wall Street Journal. Dec. 12, 2014. Rowley, J. 2006. Where is the knowledge that we have lost in knowledge? Journal of Documentation. Vol. 62, Iss. 2. 251-270. Stewart, T. 2006. Classic Drucker. Editor Thomas A. Stewart. Harvard Business School Publishing Corporation.

A specter is haunting the world – though this time, the dynamics of labor have shifted to the point where this specter cannot resemble a communist force. If Drucker’s works have been any indication, the rise of the knowledge worker is a first in the history of human productivity. This first has, among many other things, overturned the traditional labor hierarchies that have existed since the rise of agriculture. For much of history, societal hierarchies and their subsequent conflicts have been demarcated by the fine line between ruler and ruled – master and slave, lord and serf, bourgeois and proletariat, and so on. The commonality between each of these relationships has been that authority and autonomy has been largely allocated to one side – the ruling – and that the literal toil of labor has been the leverage of the other – the ruled. The rulers instructed the ruled on where to direct their labor, while the ruled prevented their rulers from siphoning too much of their earnings. Such a delicate balance, established in the first agrarian civilizations, was often upset, as shown by history’s account of countless peasant revolts and eradicated kingdoms. In his 1966 essay “The First Technological Revolution and its Consequences”, Drucker established that currently recognizable human lifestyles trace much of their origins back to this first agrarian revolution in affairs. This includes the aforementioned labor hierarchy, which has dictated government policy even into the industrial age. Even through the various industrial revolutions, the evolution of labor only affected the organization of workers, with unions and labor groups giving mass labor a platform to negotiate less violently against their employers. The base demands of labor – better wages, better working conditions – as well as the demands of their employers – more output per head, more efficiency – still belonged to the old ruler-ruled hierarchy, despite the emergence of supposedly modern fixtures of economy like the union. The rise of the knowledge worker threatens to upend this paradigm. Drucker laid out some basic facts about the knowledge worker that are relevant to dealing with this revolution. First, the knowledge worker is far more autonomous than any other kind of worker in history. Management of labor has depended on power resting largely with authority. Autonomy of the worker significantly shrinks the need for this hierarchy. Second, the knowledge worker’s output is augmented by information technology. Drucker identified this as the computer in his time, but artificial intelligence fits this role as well. In previous times, any labor-altering advancements in technology only created more jobs through economic expansion. The Luddites’ archnemesis, the textile machines dominating Britain and the United States in the early nineteenth century, created a plethora of employment through an explosion of demand for consumer goods. The assembly line that threatened the monopoly of high-cost artisans generated jobs for countless factory workers. All these phenomena were driven by the mechanization of work – repetitive work, that is. Even the replacement of the artisan was the simplification of each step of their work into a repetitive task that any unskilled laborer could replicate. However, all these technologies simply made existing manual labor more efficient by subdividing it - an early application of management theory, but one that still required mass labor regardless. The development of the computer and AI poses a distinct form of technological automation, in tandem with the rise of the knowledge worker. For the first time, true automation has become a reality. Drucker noted that the computer, and now AI, can dictate and execute decisions that before would have required a human to do. Pairing this with the autonomy of the knowledge worker, we witness the creation of a system that foregoes the historic one-way direction of command for a more reciprocative structure where workers contribute as much feedback to their institutions as their bosses and the only defining difference in authority between either is the extended foresight required to direct the entire company forward. The United States is in a mixed position to deal with this shift in hierarchy. Historically, it has prescribed all its citizens to be equal and free, however different reality may have been. Individual liberty has been baked into the country’s persona beginning with the Founding Fathers and spanning the defining moments of American history, from the Civil War to the Frontier Thesis of 1890 to the civil rights movement of the 1960s. Thus, the American psyche is better adjusted to welcome the knowledge worker; the view that an American peasant never existed doesn’t exist for nothing. However, other contradictions, such as the centuries-long establishment of slavery and the historic disenfranchisement of particular groups within the United States, will contribute to friction in the transition. If not for being at direct odds with the loosening of hierarchy, these facts will at the very least create tension for the many facets of American society left behind in the deepening dependency on knowledge workers, as has recently been observed with the rise of populism on both wings of the American political spectrum. Drucker was receptive to such potential reverberations, evidenced by his concerns expressed in his work “The New Productivity Challenge” (1991). He acknowledged that however much of a role knowledge and higher service work would contribute to the American economy, the majority of the population would inevitably be outside this ecosystem, especially given the lack of concentrated education and training available to them. In that particular work he proposed that increases in productivity were crucial in maintaining the economic prosperity to generate the social stability that had prevented the oft-violent revolutions of the past. In consideration of the aforementioned hierarchical shift brought to light, the relationships between employer and employee within management theory are also important in defusing any grievances the denied populace has towards their exclusion from high-concentration work. Although service work has progressed in “employee feedback” since the mid 20th century, dissent among lower-paid service workers has risen, leading to unionization conflicts like those at Amazon and Starbucks as well as large waves of “quiet quitting” that came right after the Covid-19 pandemic. Given the prevalence of phenomena like these, management theory should heed Drucker’s warnings in advance and evaluate existing practices in employer-employee hierarchies, not only in the knowledge-worker field but in the wider service worker field as well. For if neglected, this issue shall likely boil over and erupt just as the Revolutions of 1848 manifested the specter of the labor crises sweeping Europe. As the modern maxim goes, institutions must truly adapt to having their employees “be their own boss” more than before, for the benefit of employer, employee, society, and the economy.  References Drucker, P. F. (1966) The First Technological Revolution and its Consequences. Johns Hopkins University Press. Drucker, P.F. (1991) The New Productivity Challenge. Harvard Business Review.

Nowhere is management theory demanded more than in managing the knowledge worker, and yet nowhere is management theory more inadequate in addressing a field’s issues than in knowledge work. This is the point Peter Drucker posited in his work Management Challenges for the 21st Century (1991), and to resolve it he came up with six factors that determine the productivity of the management worker. Among these, his final point that management workers “must be treated as an ‘asset’ rather than a ‘cost’” by any given organization is an important concept 1 . While it only gradually emerged within management theory over the century, it is crucial for any employer and any government to understand and apply if they are to retain a competitive advantage going into the future. Historically, management theory has been about improving the output of the worker through banal efficiency: how to increase the production of steel per head, how to increase the production of cars per hour, how to minimize deficient products, etc. In all these considerations, the worker is a disposable resource. When he is hired, he is set to a particular task that is typically repetitive and thus easily taught, and when he is not needed because of shortcomings in his work, company difficulties, or automation, he is laid off. Referred to as “dumb oxen”, workers were seen in management theory as machines to have productivity squeezed out of. The shift from a majority manufacturing to service-based economy during the first half of the twentieth century changed this dynamic to some extent. The American postwar economic boom introduced the office worker as a common source of employment. This trend continued throughout the conglomerate era of the 1960s and was helped by the decline of the American manufacturing industry in the 1970s. Now in a stage dominated by service and knowledge work, the American economy must approach management differently. The aforementioned cost-asset shift is a demonstration of why this is so, as Drucker’s emphasis on the knowledge worker’s autonomy means that they wield control, not only within their job but over who they should work for as well. This in addition to the high-capital nature of knowledge workers means that the old management theory approach to labor as disposable will backfire catastrophically for any company that tries it with their knowledge workers. It is also important to remember the demographic trends of the United States, and more so the world, in considering why the cost-asset shift is vital. For all of human history until some fifty years ago, population was considered to be in tandem with economic power, given larger populations yielded larger labor forces and consumer markets. Economic growth was thus also correlated with population growth, demonstrated by the historic development of Europe and the United States and the more recent examples of the developing world. Consequently, the worldwide decline in fertility rates, and the decline in population numbers in some developed countries, signals economic decline for the future. In the labor market, smaller populations mean fewer jobs that produce for and service fewer people. Although the knowledge worker has grown in proportion to the total labor market, these demographic declines will affect knowledge workers as well, meaning employers will have a vested interest in retaining their high-capital labor. To enforce this, the cost-asset shift will have to come into play. The wants and needs of the knowledge worker pose a unique challenge in the field of management. Autonomy, for the first time, can be regarded as a significant factor affecting all other aspects of this labor base. What good does a large salary provide a knowledge worker if they don’t feel that they are welcome at an institution? How would they perceive that their work is not being directed towards productive pursuits at their corporation, especially given the brain work and dedication given to it? Of course, the fruits of one’s labor has been a contentious issue in management ever since compensation and workers’ rights became a universal constant with the Industrial Revolution, but this is augmented by the knowledge worker’s particular method of generating value. Given that Drucker poses their largest asset and source of value as their own mind, they will intrinsically have a special attachment to their work almost as their brainchild. Incentivizing the knowledge worker is also only one part of this picture. Per Drucker, the knowledge worker’s labor does not follow the linear relationship between quantity invested and returned. The elaborate nature of knowledge work makes it heavily dependent upon synergy: the right combination of talent can grow an organization by leaps and bounds, while virtually incompatible teams or partnerships can render all potential talent useless. And the human capital cost of the knowledge worker, both in their parents and the state educating them and in cost to their employers, is astronomical compared to all previous kinds of labor. In conclusion, the needs and wants of the knowledge worker must be met adequately, especially in the field of management. Management must almost undergo a revolution to adapt to this novel challenge, for the knowledge worker is the future of economic productivity in the developed world. Those employers that successfully accommodate the demands of this class of talent will eventually reign over those that do not accept that this is the direction economic productivity is headed.  References Drucker, P. F. (1991) Management Challenges for the 21st Century. Harper Business.

Peter Drucker wrote extensively on the computer as both the symbol and the tool of the digital revolution. His contexts, however, emphasized its effects on the economy and workforce rather than on society and populations as a whole. In fact, there is a two-way relationship between the introduction of the computer as a standard tool of industry and the effects of demographic shifts on the importance of quality over quantity. In tandem with the knowledge worker, the computer is the driving force of the future, whether in terms of society or economics. Drucker’s reasoning for emphasizing the computer was a result of this shift in human lifestyles. If families are to have fewer children and if societies are to decline in populations as a result, the computer, or at least the iteration of technology it symbolizes, is the perfect tool to preserve economic growth and stability in the face of this predicament. Moreover, the shift is not one-way. The reason rearing children has become far more of an expense is also itself due to the nature of the economies these children will be entering upon maturity, especially in the most developed nations. Rather than menial farm or industrial work like before, these children are being prepared for service work, office work, “white-collar” work that involves increasing proportions of brainpower. This is observable in the development of the United States over the past century. Beginning with the 1920 census, which recorded the outright transition from a rural-majority to urban-majority America, the nation’s psyche became enraptured with the trappings of an industrial-service society from the rise of consumerism and credit to the automotive assembly lines of Ford and GM that employed much of the now-prospering working class6. It is not merely a coincidence that Taylorism reached its apex in the American mind around this time, as this was the first era where scientific principles could be developed and widely applied to entire industries to accentuate efficiency. While not applicable to artisans and craftsmen of the past, whose guilds and exclusivity hampered productivity and output, scientific approaches to management were finally able to be applied to a working base whose labor itself was based on scientifically derived outputs. However, most production around this time still focused on mostly menial toil and was linearly proportioned with growth in the human base that made it possible. An assembly line worker could be trained to maximize the number of wheels he could fix to a chassis per hour, but he couldn’t be trained to design new cars or to identify points of improvement in existing ones. As such, for the factory owners of this time, the fixture for economic growth rested upon hiring more workers to speed up the process. As time passed, however, the American economy gradually shifted towards being composed of service jobs, with this transition having been solidified in the public mind with the flight of the automotive industry from the now-labeled Rust Belt to East Asia, particularly Japan, in the 1980s. This weakened the relationship between population and economic growth, but the new service jobs as well as the remaining manufacturing jobs still retained a semblance or more of training and outright repetition. Even at the peak of the American conglomerate phenomenon in the late 1960s, taking Boeing’s dominance in the aerospace industry in Southern California for example, most employees were still assemblers, engineers, and office workers who were hired and designated to do a specific task within their company. At this point, the only people who were delegated the task of independent and spontaneous decision making were management, a growing yet still small segment of the workforce. The employment landscape now has been radically altered. Drucker already predicted it in his time, but the rise of the knowledge worker has marked a departure from all other previous forms of labor. For practically the first time in history, a significant and growing proportion of the workforce is both autonomous and a common asset in their own right. Unlike the artisans of the agrarian age who required wealthy patrons for their services to be of use and unlike the scientists of the industrial age who required direction from laboratories for their research, the knowledge worker is able to utilize both traits in such a manner and on such a scale that they have already began shifting the patterns of the American workforce, and to that extent American social life. During the Covid-19 pandemic, the widespread emergence of remote workers was in significant part due to the proliferation of knowledge workers in the nation’s service-based economy, and the continuation of this trend even after all pandemic precautions had subsided has given the corporate employee far greater leverage in employment than before. Much of this has only become a reality in due part to the computer. As well as performing the office grunt work that Drucker had observed in the 20th century, the computer has now also taken on the role of a presence augmenter, hastening communication far past what telephone or fax could ever have done with email and video calls. Looking past the immediate implications of the computer itself on society, the subsequent shifts in workforce patterns can be argued to have as much if not more of a dramatic impact on societal constructs. Given a newfound leverage over their employment, knowledge workers have the ability to individually bargain with their employers over matters like payment incentives to the extent that only a union was capable of before. Their advent also collides with the concept of unions, which have traditionally relied on member numbers and a grasp over the “human toil” of companies that is now increasingly being replaced with machinery. The aspect of human quantity is now especially important given current demographic trends. The developing world can no longer expect the benefit of increasing populations nor the agrarian settings to stimulate such effects in the long term. Given that economic development has nearly ubiquitously been linked with simple growth in things like population, these trends will initiate steep declines in the prosperity of countries with shrinking populations. It is in this context that the value-concentrated knowledge worker will begin to play a primary role, as their autonomous nature renders them independent of the quantity-growth economic relationship. This combined with the fact that their value lies with their mind, a nearly infinite source of ideation, will mean that their presence within the workforce will likely become the new economic driver of a country, even without growth in terms of quantity. Coming back to the computer, it is the very augmenter of productivity that separates the quantity-based output of yesteryear from the concentrated production that will dominate the future. However, its functions are limited to simple automation without its counterpart in the Digital Revolution: the knowledge worker. The synergy between the two is something governments and corporations alike must quickly understand if they are to retain their competitive edge, and it will be the subject of discussion in works succeeding this one.  Drucker, Peter. (1942) The Future of Industrial Society (1942)

Welcome to the last installment of this blog series, where we bring knowledge, wisdom, and technology together. How can human wisdom and technology, specifically AI, collaborate to redefine knowledge, knowledge work, and a knowledge society? As we saw in the first installment, the nature of knowledge has long been a topic of discussion. Peter Drucker was concerned with the relationship between knowledge and power, and the changing nature of knowledge, particularly related to technology. In his twentieth century era, new technology in the form of atomic weapons unleashed knowledge that contained the power to destroy humankind. With this kind of technological knowledge came enormous responsibility. Technological advances related to computing in Drucker’s time carried with them fears of economic and social turmoil. Would automation of manufacturing processes and the introduction of the computer to knowledge work result in the elimination of jobs and a massive restructuring of the economy? In Drucker’s view, automation was part of a larger process of seeing production as a whole rather than a series of small parts. The new technology would cause disruption, but this was part of the long history of technological advancement in societies. The computer itself was an order taker, a human creation that was an instrument for efficiency and more productive use of knowledge work. Today, we still wrestle with the same questions of knowledge and power and the potential for social disruption due to technological advancement. New knowledge still wields enormous power – now to influence emotions, attitudes, and beliefs, undermining the very nature of truth and trust in institutions. Rather than the physical destruction of nuclear weapons, deep fakes, data breeches, and financial scams using AI and targeted algorithms can call into question the essence of reality. Can we trust our own ears and eyes, much less the dominant institutions of society? Drucker’s order-taking computer, the “moron” of his writing, is now capable of generating material, not just computing. Generative AI is rapidly producing increasingly sophisticated texts, images, and music as it refines its use of available information and its relationship with the user. As was discussed in previous installments, effective use of knowledge, or conversion of information into useful knowledge, involves wisdom and judgment. Here is where the differentiation between generative AI and human beings lies, and how we can better understand ways in which people and technology can collaborate effectively. Drucker often remarked that the key to effective problem solving was asking the right question, in essence, framing the problem itself. This was more important than finding the “right” answer; finding the” right” answer to the “wrong” question results in wasted time (and perhaps even more problems than the one you tried to solve). Simply put, AI is not designed for this function. In its most basic form, AI responds to information with a limited menu of options (chatbots for customer service, for example). In its more sophisticated iterations, it is designed to fulfill goals that are predetermined by humans. If we delegate a decision to an algorithm, there are parameters that have been set by humans. Algorithms are designed to execute; even more sophisticated tools, such as ChatGPT, require human instruction. They are designed to solve problems. They are not designed to decide which questions to ask to solve the problem (although one function they can serve is to help guide people in figuring out possible questions to ask). In this sense, even today’s AI reflects Drucker’s view of computers as order-takers. In our discussion of wisdom, we acknowledged the human problems of misinformation, narrow focus, filtering flaws, and bias as barriers to good judgment. If we are to partner with technology in the form of AI, we need to be even more cognizant of our own flaws as human beings. We are the ones driving the technology and its use. How does the delegation of decision making to algorithms perpetuate the flaws that already exist in our own judgment? What are the consequences? At what point does the decision to delegate knowledge work to a machine that has no wisdom create more social problems than it generates benefits? These are the questions we need to be asking. This requires higher order thinking that, dare I say, Drucker proposed in his concept of Management as a Liberal Art. With his pillars of knowledge, self-knowledge, wisdom and leadership, Drucker gave us valuable tools and lessons for navigating our new world of knowledge work. So, how can we effectively collaborate with AI to create an effective knowledge society for tomorrow? · Understand the limitations of technology: AI will reflect the quality of the information it uses. To use a tired phrase, “garbage in, garbage out.” Algorithms are also susceptible to the cultures, biases, and limitations of human beings that create them. Technology is a human creation. It is not something outside of us. Drucker told us this beginning in the 1950s! · Understand the limitations of human beings: People will use technology to do work if they don’t want to do it. Students will use ChatGPT to write papers. People will use deep fakes and other techniques to advance their causes. This does not mean the technology is bad. It just means we need to learn how to regulate and monitor its use. Drucker used the concept of Federalism to discuss the need for guardrails and checks/balances. Our global society is having these conversations about AI now. · Know how to leverage wisdom and judgment: Leaders need, more than ever, to emphasize skills that used to be referred to as “soft.” In a world awash with data and technology, we are increasingly in need of people well-versed in emotional intelligence, the ability to discern and make judgments in times of rapid change, and who can connect honestly with their team members. As we make decisions about delegating decisions to non-humans, the need for human connection will only increase. Our new knowledge society needs people who understand people, not just technology and data. But it also needs people who can use their wisdom and judgment to know when to rely on technology. In the words of Scott Hartley, we need both the “Fuzzy” and the “Techie.”  Rather than seeing AI as a threat to our humanity, as competition to knowledge work, we should see it as a development that allows us to think deeply about our role as human beings in our new knowledge society. In her book, In AI We Trust, Helga Nowotny, Professor Emerita of Science and Technology Studies at ETH Zurich, argues for the importance of “cathedral thinking,” the ability to appreciate the value of shared, inherited practices that are constantly being reevaluated and realigned. It includes the kind of interdisciplinary, critical thinking I discussed in the previous installment, but it also involves connecting the past with both the present and the future. In Nowotny’s words: “Wisdom consists in linking the past with the future, advising what to do in the present. It is about rendering knowledge retrievable for questions that have not yet been asked” (Nowotny, 2021). I think Nowotny makes a clear case for the relevance of Drucker’s work today. We may be frightened by new knowledge and technology, the power it has, its impact on our lives. But this is the reaction of people who are ill-equipped for facing the reality of change, change which bears the possibility of not just disruption but also opportunity. As Drucker wrote almost 100 years ago, humans have survived technological change as part of the natural order of things. The key to understanding today’s technological change is to see it as a matter of collaboration, not competition. This is the trajectory of our new knowledge society: where human wisdom and judgment augment the power of AI. AI can help us understand our own limitations and flaws, which can, in turn, make us better as people. Agrawal, A., Gans, J., Goldfarb, A. (2023). How large language models reflect human judgment. Harvard Business Review, June 12. Drucker, P.F. (1967). The manager and the moron. McKinsey Quarterly, 1 December. In Drucker, P.F. (1970). Technology, Management and Society. New York: Harper & Row. Hartley, S. (2017). The fuzzy and the techie: Why the liberal arts will rule the digital world. Houghton Mifflin. Jarrahi, M.H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61 (4). Moser, C., den Hond, F., Lindebaum, D. (2002). What humans lose when we let AI decide. MIT Sloan Management Review, 63 (3), 11-15. Nowotny, H. (2021). In AI we trust: Power, illusion, and control of predictive algorithms. Polity Press.

When is a resource especially useful? The answer often varies based on the technological advancement of the society in question. Human capital is especially susceptible to this variable, as it is only as useful as its carrier’s tools are. In this Fourth Industrial Revolution, the knowledge worker’s debut is the consequent shift of human capital owing to information technologies such as the computer and artificial intelligence. Just how monumental this shift may be is to be analyzed. Historically speaking, few resources aside from hard currency like bullion and necessities like water have maintained a constant degree of usefulness. Clearly, an abundance of fossil fuels offers a different meaning to a hunter-gatherer tribe and an industrialized nation just as a plentiful supply of spices means different things to a medieval European kingdom and any country today. More often than not, though, these differences in meaning can be attributed to differences in technology. A hunter-gatherer society has no means and no purpose to exploit fossil fuel technology, while any industrial nation will demand (at least for now) a constant supply of non-organic energy due to lighting systems that require the energy from fuels. Even the disparity in significance of spices can be attributed to technology, however indirectly. The medieval European kingdom was at the mercy of the Italian merchants, Ottoman sultans, and Indian planters to attain expensive spices, especially without any technologies in the fields of preservatives, cultivation, or transport. By contrast, today’s globalized trading network, mixed with extensive advancements in preservatives and wider spice cultivation have reduced salt and pepper from the most expensive commodity on a continent to a kitchen counter constant. Typically, changes in the usefulness of resources go in tandem with shifts in the technologies that put them to use. The introduction of steam power in the Industrial Revolution, for example, necessitated the use of coal and other fossil fuels. Great Britain’s vast underground coal reserves, thus, suddenly became a valuable asset to the country in propelling it to industrial powerhouse. These shifts can also go the other direction. With the rise of oil- and diesel-powered combustion machines in the 20th century, those same coal reserves declined in significance, reducing Britain’s industrial advantage. Human capital is not exempt from these shifts in usefulness. Engineers became of great use whenever the technologies to develop siege weapons (as well as the capital and organization to build them) became available to states; Roman and Chinese armies of antiquity employed great numbers of siege engineers. Similarly, architects were commissioned whenever the means of building elaborate structures became available; the Renaissance abounds with examples of this. Thus, the Fourth Industrial Revolution (or more aptly the Digital Revolution) will enact unique shifts in the usefulness of workers and resources alike, thanks to the nature of the technology involved: the computer. Though Drucker passed away in 2005, he foresaw the rise of artificial intelligence within his predictions about the computer in “What the Computer Will be Telling You” (date unknown), calling out its potential to analyze data akin to what artificial intelligence does nowadays. This brings meaningful shifts for all levels of human labor. The combination of computing with robotic technology and affordability has made it possible for unskilled labor to be replaced en masse, reducing the use for unskilled labor. Even lower-level white collar jobs like clerks and accountants face stiff competition given their work is repetitive at a digital level and liable to be replaced by artificial intelligence. The one field of employment that is expanded as a result of these technologies is the knowledge worker. Partially born from the growth of computing technology, partially an existing beneficiary of said technology, the knowledge worker performs their work on the premise that the grunt work of crunching numbers and calculating growth metrics can be easily done by the tools at their disposal. In an economy where physical production is a linear metric of economic performance, the knowledge worker has limited use. In such an economy that furthermore relies on a chain of human calculators and analog communication, the knowledge worker is extremely limited in capability and is thus not a significant factor in economic output. Hence why the knowledge worker has only risen to prominence within postindustrial economies. Thus, the American economy is especially susceptible to shifts in usefulness as one of the most postindustrial economies on the planet. This has significant consequences for its future economic prospects. For one, it was able to reach its status as a global powerhouse due to the growth of its giant manufacturing base, which took place between the Civil War and World War II. Its further investment in STEM education, priority on innovation, and corporate dominance during the Cold War allowed it to keep its top position throughout the 20th century. However, the Fourth Industrial Revolution has introduced some subtle changes to the economic calculus that necessitate reform of the current system. For one, even though the American economy is already heavily service-based, the automation of tasks at the lower level combined with the augmentation of capabilities in the office means the labor shift is geared towards prioritizing higher educated workers as primary human factors of economic output. Given much of the service sector is not necessarily aligned with knowledge work, the usefulness of the service sector in general is skewed upwards in terms of human capital. For another, the productivity of the knowledge worker rests with both production and mentality. Drucker stressed the autonomy of the knowledge worker as one of their defining characteristics, made possible by the powers of computing and AI. Because the complex calculations are automated by these technologies, that leaves the decision-making up to the human. Of course, the knowledge worker must still be trained in the technical skills required to use the tools at their disposal. However, the decision-making facilities of the knowledge worker, including foresight and rationality, matter greatly if they are to efficiently perform their job. The future competitiveness of the American economy, and by extension many other economies, is dependent upon this. In its manufacturing heyday, the United States was the world’s superpower due to its towering advantage in scale over its European counterparts and the absolute lack of industrialization elsewhere in the world. During the Cold War, the United States once again strode the world economically due to sheer scale, concentration of capital, and worker efficiency. Now, however, economic disparities in the world have narrowed. After rapid industrial development in the twentieth century, East Asia has caught up to America in terms of economic development and has even surpassed it in certain fields like semiconductors. Developing nations, most notably the BRICS countries, have become manufacturing leaders. China in particular has bridged being both the “world’s factory” and a center of highly educated talent. What this all means is that the United States cannot rely on simple scale and the virtue of being the earliest as it did in the past. The combination of knowledge workers requiring extensive high-quality rearing and the dilapidated nature of American institutions like education and infrastructure puts the country at risk of losing its economic edge in the world. However, the American economy is not consequently destined to decay. Its national culture of pursuing individual advancement and success is well-fitted for the world of the knowledge worker. It already possesses a well-educated population that has been used to living in a developed economy for a century. It holds the largest concentration of financial capital in the world. While this by no means encourages complacency, it simply means the country must pursue a different utilization of its resources in order to keep its current economic position in the world. It cannot compete in human numbers, for India and China boast populations far larger and countries like Indonesia and Nigeria are quickly catching up. It cannot compete in manufacturing, as Brazil and China are now the biggest producers of the commodities that America dominated over a century ago. Even in higher-tech industries like semiconductor chips, countries like South Korea and Taiwan have demonstrated that small populations can easily and quickly trounce less-prepared competitors many times their sizes, as the United States has learned of late. So ultimately, the United States ought to perceive that through the synergy of its relative strengths in all the aforementioned fields with investment into cultivating a robust knowledge worker base, it will be best positioned to retain its premier status as a global economic leader. In conclusion, the American economy will have difficulties adjusting to this new reality in spite of its current advantages in education and economic maturity. What matters most - not only for the United States but for the other economies of the world - is that with the Fourth Industrial Revolution, the usefulness of labor will play a defining role in each country’s economic standings. Those that grasp this concept will prosper, while those that neglect it will fall behind. The use of the knowledge worker, and subsequently the highest level of human capital, will become top priority. References Drucker, P. F. (1995) “What the Computer will be Telling You” – in People and Performance (Routledge)