AI ethics and its impact on knowledge management
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OPINION PAPER
AI ethics and its impact on knowledge management Anthony J. Rhem1 Received: 12 September 2020 / Accepted: 17 September 2020 © Springer Nature Switzerland AG 2020
1 Introduction The focus of knowledge management (KM) is to enable people and organizations to collaborate, share, create and use knowledge. Understanding this KM is leveraged to improve performance, increase innovation and grow the knowledge base of both people and the organization. Knowledge must be Dynamic, Accurate and Personal to be applied in the decision-making process. Artificial Intelligence (AI) through machine learning allows machines to acquire, process and use knowledge to perform tasks and to unlock knowledge that can be delivered to people to improve the decisionmaking process. AI plays an important part to delivering knowledge in a digitized organization by elevating how the delivery of knowledge occurs to the people who need it. AI is used to scale the volume and effectiveness of knowledge distribution. It is imperative that when AI is applied to deliver knowledge for people to make decisions; including when AI is used to make decisions without human involvement; that the knowledge is without bias and the decisions made with the knowledge are ethical.
1.1 Incorporating artificial intelligence (AI) AI provides the mechanisms to enable machines to learn. Incorporating AI in the delivery of knowledge will facilitate fast, efficient and accurate decision making. AI provides the capabilities to expand, use, and create knowledge in ways we have not yet imagined. AI systems which use machine learning, can detect patterns in enormous volumes of data and model complex, interdependent systems to generate outcomes that improve the efficiency of decision making, The use of AI (machine learning) in delivering knowledge is based on the data that is used to train the machine learning
* Anthony J. Rhem [email protected] 1
A. J. Rhem and Associates, Inc., 205 North Michigan Ave., Suite 810, Chicago, IL 60601, USA
algorithms. We must keep in mind that when it comes to AI, we need both responsible use and responsible design.
2 Delivery of knowledge Knowledge Management (KM) in organizations is based on an understanding of knowledge creation, knowledge transfer, knowledge use, knowledge flows, and knowledge governance. In implementation, KM is an effort to benefit from the knowledge that resides in an organization using it to achieve the organization’s mission and the activities of its users. The transfer of tacit or implicit knowledge to explicit and accessible formats, the connection of tacit to explicit knowledge (which is connecting your organization’s experts to explicit knowledge), and the understanding of social network analysis within the organization contributes to the effective distribution and use of knowledge. It is important to not only understand what knowledge management means for the organization, but also understand the nature of the organization’s knowledge itself. AI effect on KM is to provide the delivery of knowl
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