Management as a Liberal Art Research Institute

Human/Technology Collaboration: Tomorrow's Knowledge Society

Karen Linkletter Ph.D.

PUBLISHED:

October 7, 2024

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.


By Karen Linkletter Ph.D. November 19, 2024
Interview with Karen Linkletter at the 16th Global Peter Drucker Forum 2024  Video Interview
By Ryan Lee November 7, 2024
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.
By Michael Cortrite Ph.D. November 7, 2024
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.
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