Special Topics
April 21, 2021 — 9:15

Author: admin | Category: | Comments: Off

Content Ethics

Content ethics denotes the specification and operationalization of digital ethics for the context of managing unstructured digital content and business processes with technologies normally designated under the umbrella term “ecm” (enterprise content management).

This section will contain links to a series of articles written on content ethics that together and in their rough ordering will constitute a handbook. This project will be carried out in 2021 and may continue into 2022, so please check periodically for new articles.

Click here to view/download the introductory piece on Content Ethics.

Click here to view/download piece on stakeholder ethics in ecm.

Click here to view/download piece on ecm and data privacy.

Click here to view/download piece on RPA and ethical change management.

Business Analysis and Data Ethics

As noted above, data ethics is increasingly a concern for organizations and regulators. A technology related professional role that has the protentional to make a significant contribution to data ethics initiatives and programs is business analysis.  Business analysis is a field dedicated to “enabling change in an enterprise by defining needs and recommending solutions that deliver value to stakeholders.” (IIBA Core Standard) Analysts identify requirements and design solutions. Data ethics projects often have a design dimension (e.g., privacy by design).

Business analysts should be key players for organizations undertaking data ethics initiatives. Their core competencies in analytical thinking, business and technical knowledge, interpersonal skills are precisely the abilities needed to drive the sort of change needed by end user organizations, or technology developers or integrators. As the EC High-Level Group on AI states (Draft Ethical Guidelines for Trustworthy AI), trustworthy AI requires “. . . a continuous process of identifying requirements, evaluating solutions and ensuring improved outcomes throughout the entire lifecycle of the AI system.” Such a process is at the heart of BA work.

The key for business analysts is to add to their stock of business knowledge the requisite ethical knowledge, consisting of the principles and concepts that make up data ethics. Business analysts are subject matter experts and trusted advisors in their domains who employ a robust skill set to enable and sustain change. Adding data ethics to their knowledge base will enable them to take on a strategic role within their organizations as the latter engage in digital transformation within a context of ethical risk.

Read Article – Business Analysis and Data Ethics-White Paper-Mooradian-2019

Knowledge Management

Knowledge management is an area of research in the fields of computer science/information technology, business management, and 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.

In the early 2000s, knowledge management (KM) achieved buzzword status, finding its way into the marketing materials of a large number of software providers. Today, some of the buzz has subsided, but the aims and objectives of KM are still part of many software development initiatives, sometimes embedded implicitly in programs and projects, sometimes explicitly. Position titles also continue to reflect an ongoing interest in KM, even if chief knowledge officer positions have not proliferated.

Whether KM lives on with fanfare or works quietly in the background, KM objectives will be realized to various degrees in the future. Since KM will have an impact on the working lives of many people, particularly “knowledge workers” as they are often called, it is important to explore the ethical implications of KM. Is KM a threat to the financial and intellectual well being of knowledge workers, or will it enrich them intellectually and financially? For some, KM promises to carry on the process of deskilling and devaluing workers by offloading thought and judgment and converting human knowledge into machine based intellectual property. For others KM provides an opportunity to accelerate learning, forester collaboration, and enhance the stature of knowledge workers. This issue will be explored here.