After 200 years of trying to turn workers into interchangeable parts, we are now expecting them to rise to the challenge of being knowledge workers. More than 30 years ago, Peter Drucker coined the phrase knowledge worker. Today you can hardly open the latest business magazine or book without encountering phrases such as intellectual capital, learning organization and knowledge economy. Data, information and knowledge are not the same things, though you wouldnt know this by how people, even those in the information technology industry, sometimes confuse the terms. Webster’s defines knowledge as “a clear and certain perception of something; the act, fact or state of knowing; understanding.” Knowledge workers spend most of their time interpreting and communicating information using words and symbols rather than acting physically on materials such as brick, stone or wood. This shift from physical toward intellectual labor represents what Shoshana Zuboff in her book In the Age of the Smart Machine calls the informating of work. CIOs and their organizations are very interested lately in finding ways to recognize, collect, share (and dare I say reward) expertise among their workers through techniques such as social networking and knowledge-sourcing. Ironically, the obstacle they often face in this age of information overload is uncovering hidden (that is, tacit) knowledge and presenting it in a coherent fashion. Having spent huge sums of money on computing power to help them streamline processes and create repositories of data, many organizations want to believe they can apply information technology as a simple short-cut to knowledge management. One organization, which pioneered the use of nuclear power in the U.S. Navy, asked me about developing a simple IT solution to capture the expertise of its retiring engineers. What I offered them was a labor-intensive, time-consuming process of interviewing engineering personnel in their respective areas of expertise, documenting their responses (i.e., making the tacit explicit) and organizing the results logically in some sort of knowledge-base. That organization’s request points to an underlying fallacy. Knowledge does not exist like vast reserves of oil, waiting to be extracted. It does not reside in peoples heads waiting to be downloaded or “jacked into” (films like The Matrix to the contrary). Knowledge is subjective, idiosyncratic and dynamic. It is formed in the interaction among people, where it is shaped by language, thought and perception. It builds on what individuals and cultures have learned and transmitted across time and distance through face-to-face communication and books, and now through electronic means such as e-mail and the Web. However, even as companies and other organizations face an increasing need to leverage their knowledge assets and compete in the global knowledge economy, they face a shortage of workers with the competencies to function effectively in it. The success of factory automation in the nineteenth and early twentieth centuries was based on reducing tasks, and the expertise and skill required to perform them, to the lowest common denominator. Frederick Taylor developed his gospel of scientific management in the early 1900s. Henry Ford was Taylorism’s main prophet, using it to refine and perfect his assembly-line process of auto manufacturing. Applied across a variety of industries, this approach enabled production of a large quantity of cheap, mass-produced goods using a readily-available labor pool that possessed a minimum of education. Its disadvantages included de-skilling, lack of understanding and lack of independent thinking among workers. These weren’t critical drawbacks in the early and even later industrial economy. Public education evolved during the nineteenth century to assimilate new immigrants and workers into society and give them the minimum skills to do the work required of them. The majority of men and women who labored in the factories werent valued for being literate, articulating ideas clearly, solving problems or being innovative. They were valued and rewarded for performing repetitious tasks quickly, consistently and accurately. The knowledge economy requires a predominance of employees who can think critically, recognize and solve problems creatively and work with others cooperatively. But the legacy of our educational system and factory automation has prepared us for an old way of thinking and acting, and an older type of work. The ghost of Taylorism persists in organizations that continue to use information technology merely as a tool to reduce the training and level of education required of their workers to the lowest common denominator. Workplace automation can still reduce costs and improve efficiency, but has reached a point of diminishing returns, as was pointed out in a recent blog post by Christopher Koch on this site. It is being superseded by supply-chain economics and just-in-time manufacturing, which require a high degree of skill and responsiveness by workers. Schools and our mass culture reinforce the notion that all problems can be solved merely by applying the proper technology. One recent newspaper article stated that the secret to helping children do well in school lies in buying them the right PDAs, laptops and electronic spell-checkers. Anyone who has sat on a crowded bus, at a business meeting or in a classroom will notice that people sometimes seem disturbingly more adept at interacting with their iPod or cell phone than with human beings. But proficiency in using the tools that technology provides is no guarantee that these tools will be used intelligently and ethically. From the tragic loss of life in Bhopal, India, more than 20 years ago to the recent debacle surrounding Hurricane Katrina, we can see that many problems in our modern world are caused or exacerbated by human beings who fail to think and communicate, relate to others or respond mindfully to changing circumstances. Technology pundits, business executives and educators preach the promise of workflow automation, intelligent systems and computer-based learning. But businesses and society still rely on human beings to define and respond to needs, recognize risks and opportunities and be motivated to find creative solutions to problems. As we talk of building intelligence into computing systems, we also need to make sure the people who design and use them are intelligent and capable. The late Neil Postman suggested that the main challenge facing us in this era of easy access to information and proliferation of online content is not so much finding answers, but asking the right questions. Government, businesses and schools must cooperate to ensure a workforce with the requisite skills to participate and help companies compete in the global knowledge economy. In Pittsburgh and Southwestern Pennsylvania, where I live, the Allegheny Conference on Community Development, a 10-county consortium of local government, business and community leaders, has instituted a number of workforce development initiatives. These include Proficiency by 10, a program that aims to ensure that by 2010 children in the region achieve reading, writing and math proficiency by the time they are 10 years old. Several years ago I participated as a business representative on an IT workforce education board sponsored by Catalyst Connection of Southwestern Pennsylvania. We provided input to local educators on the skills employers look for in students leaving high school and college and entering the workforce. For a final example, PNC, a financial service company where I have worked, instituted its Grow Up Great program across all its regional markets to help ensure that children from birth to age five develop the necessary skills for a healthy start in life. Collaborative efforts such as these give substance to the rhetoric about leaving no child behind. But these examples are just a start. We must create a culture that truly values learning and treats children as more than miniature consumers. Such a culture will encourage mastery, competence and a thoughtful approach to problem solving and the sharing of ideas. It will recognize and reward the experience and expertise of its workers and not treat them as disposable commodities. It will support parents, caregivers and schools in meeting their responsibility to raise engaged, mindful human beings who are accountable for their choices and prepared to be successful in their work and in life. Charles Lanigan teaches and consults on workflow and collaborative computing. He holds a master’s degree in instructional design and technology with a focus on literacy, critical thinking and computer-mediated work. He has taught at the Katz Business School Center for Executive Education, Carnegie Mellon University and Penn State Outreach, and made presentations on collaboration and knowledge-sharing to the Pittsburgh chapter of the Project Management Institute, the Pittsburgh Technology Council and the Pennsylvania Technical Assistance Program (PENNTAP). In addition to his work and teaching, he serves on the economics committee of the Pittsburgh Urban Magnet Project (PUMP) and also as board president of STC WorkQuest. He is currently working on a book about collaboration and knowledge-sharing in the workplace. Please e-mail him at waysofknowing@comcast.net, or visit his website at waysofknowing.home.comcast.net. Related content feature Mastercard preps for the post-quantum cybersecurity threat A cryptographically relevant quantum computer will put everyday online transactions at risk. Mastercard is preparing for such an eventuality — today. By Poornima Apte Sep 22, 2023 6 mins CIO 100 CIO 100 CIO 100 feature 9 famous analytics and AI disasters Insights from data and machine learning algorithms can be invaluable, but mistakes can cost you reputation, revenue, or even lives. These high-profile analytics and AI blunders illustrate what can go wrong. 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