This paper explores ethical and philosophical dimensions of knowledge management.   In particular, it raises the questions of whether knowledge management, as a set of computer information technologies and practices, threatens to devalue the role of individuals as experts and “knowledge workers” within organizations and whether it risks exploiting these experts by converting their work into intangible assets or intellectual property/capital.    These questions arose for traditional information technologies during the seventies and eighties in the form of a debate about deskilling and unemployment on the one hand, and the role of knowledge and capital in relation to autonomy and control within the corporation on the other.  

Knowledge management is an emerging area of research in the fields of computer science/information technology and business management, as well as the social sciences.   It is concerned with managing the creation, capture, distribution, application, and retention of knowledge produced or acquired within or by the firm through its internal operations and external relations with suppliers, clients and other parties.   KM objectives have fueled the development of a market for computer technologies designed to capture and manage knowledge and organizations have sought to develop new business practices conducive to the capture and production of knowledge.

Knowledge management differs from traditional information management in its attempt to transfer to information systems aspects or products of human cognition knowledge and to create computer applications that support or enhance knowledge based work.   Information structures in knowledge management applications are meant to represent knowledge or integrate information tightly with knowledge based activities.   Traditional information management by contrast has been concerned to store and process data that represent basic facts that are atomistically structured and typically used in routine business processes where contributions of expertise and professional knowledge are not necessary.    

The distinction between knowledge management and traditional information management, preliminary and vague as it, is one of degree.   Also, it may seem to admit of counter examples.   For example, traditional information systems have been critical in the sciences.   Scientists, engineers, medical professionals, and other experts depend upon and have advanced the scope of their knowledge based activities using traditional data processing systems.   However, the manner in which they do so is different from what knowledge management at least intends.   Information systems collect data, which from an epistemic perspective, corresponds to observational information.   Since experimentation and calculation are critical to scientific and professional activity, information systems clearly can and do support knowledge work.   The aspiration, however, of knowledge management applications, extends beyond this.   It attempts to represent and utilize aspects of cognition involved in the theorizing and interpretation of observational information.   Further, it does so in a corporate context in relation to all aspects of corporate work. Hence, it raises profound questions for knowledge based work as it seeks to go beyond providing richer data to experts, but rather seeks to provide expertise to experts and non-experts.   Whether the phrase “knowledge management” continues to be an organizing concept of certain technologies now and in the future, the trend to move beyond data and information processing to capture, simulate, or supplement expertise should be expected to continue and intensify, whatever its name or guise.

Despite its profound implications for the character of work, the ethical outlook for knowledge management has been positive.   In fact, knowledge management has thus been seen as a countervailing technical development in relation to traditional information technologies which, as mentioned above, were thought to have the effect of automating and deskilling work.    The introduction of computer systems into the workforce in the 1970s brought fears that skilled, high paying jobs would be lost to computerized manufacturing systems or would be degraded to low skill, low paying jobs monitoring systems that would now do most of the routine work.   Small numbers of employees might see an enhancement of their work status as they would be needed to handle non-routine work, but the majority of workers would face underemployment or unemployment as automation permeated their workspaces.

In contrast to traditional information systems, knowledge management technologies have been seen as supporting and in part constituting a positive trend in work that replaces manual, skilled labor, with abstract, cognitively rich “knowledge work.”    Knowledge management technologies are viewed as an outgrowth of and related to concepts such as the knowledge society and knowledge worker. (Drucker, 1967, 1988) They are thought to hold out the promise of promoting such values as autonomy for workers and the development of their rational faculties. (Bowie, 1999) Instead of automating and reutilizing work, which displaces and deskills workers, they are seen as fostering creativity and continuous learning, as well as rich and meaningful work.   From a technological perspective, which is the focus of this paper, knowledge management applications are viewed as having the opposite effect of earlier technologies.  

This optimistic picture has been challenged, however, by critics of knowledge management. For example, Steve Fuller, in his book Knowledge Management Foundations, argues that the KM movement aims to convert tacit, human knowledge into explicit, transferable intellectual property.   The main technologies of knowledge, in his view, are expert systems and knowledge bases.   Expert systems, by their very nature, automate human work, in particular, the work of providing expert advice to clients.   They also transfer the intellectual ability to give expert answers to a computer information system that can be owned by a corporation.  The result of developing and implementing expert systems and knowledge management technologies on a large scale will ultimately be a deskilling of many knowledge workers and a conversion of knowledge to intellectual capital.   As knowledge workers are the owners of their knowledge and their knowledge is their source of power, knowledge management threatens to restore the power of capital over knowledge after a very brief set back in which individuals were thought to be in the ascendancy.

This paper will examine knowledge management technologies in light of these criticisms.   I will first discuss the nature of knowledge management in relation to traditional information management.   I will develop and review what I see as the important ethical criticisms of knowledge management technologies.   I will then argue that these criticisms apply more strongly to certain models of knowledge management objectives and technology than to others.   Specifically, I will argue that an expert/client model of knowledge management objectives, coupled with expert systems and knowledge bases may be problematic.   However, an alternative model, the expert/expert model, coupled with the same and other technologies, knowledge bases, content repositories, collaboration, etc., does not raise the same problems and may have positive effects on knowledge workers and knowledge work.    I will also connect the different models of knowledge management objectives with corresponding models of research.   The expert/client model, I will argue, corresponds with a psychological/artificial intelligence approach to knowledge management.   The expert/expert model, by contrast, corresponds to a social epistemological approach.   The paper will conclude by endorsing the expert/client, social approach to knowledge management.

Selected References

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