Accenture - Universal principles for data ethics
Nov 03, 2021
[Graph Issues]
Summary
This corporate report is addressed to institutions and companies intending to develop a code of ethics. It offers general guidelines; "Rather than attempt to deliver dozens of industry-specific codes, this framework approach lets organizations incorporate their industry knowledge and domain expertise in developing a code of ethics for their industry, ecosystem, or organization" (Accenture, 2016:5).The highest priority, according to the principles, is "the person behind the data". Accordingly, practitioners need to be aware of the harm the data could cause, both directly, and through the "downstream use" of data. The principles also acknowledge that data is not neutral. "There is no such thing as raw data." They seek to limit data collection to the specific purpose, and to foster transparency and accountability. It also asserts "practitioners should accurately represent their qualifications (and limits to their expertise)," and defines a need for ethics review.
Content
- Course Outline
- Course Newsletter
- Activity Centre
- -1. Getting Ready
- 1. Introduction
- 2. Applications of Learning Analytics
- 3. Ethical Issues in Learning Analytics
- 4. Ethical Codes
- 5. Approaches to Ethics
- 6. The Duty of Care
- 7. The Decisions We Make
- 8. Ethical Practices in Learning Analytics
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