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This article gives an overview of professional ethics as applied to computer programming and software development, in particular the ethical guidelines that developers are expected to follow and apply when writing programming code (also called source code), and when they are part of a programmer-customer or employee-employer relationship.
Computer ethics is a part of practical philosophy concerned with how computing professionals should make decisions regarding professional and social conduct. [1]Margaret Anne Pierce, a professor in the Department of Mathematics and Computers at Georgia Southern University has categorized the ethical decisions related to computer technology and usage into three primary influences: [2]
Research integrity or scientific integrity is an aspect of research ethics that deals with best practice or rules of professional practice of scientists. First introduced in the 19th century by Charles Babbage , the concept of research integrity came to the fore in the late 1970s.
Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of professional scientific research. It is violation of scientific integrity: violation of the scientific method and of research ethics in science, including in the design, conduct, and reporting of research.
Medical ethics is an applied branch of ethics which analyzes the practice of clinical medicine and related scientific research. [20] Medical ethics is based on a set of values that professionals can refer to in the case of any confusion or conflict. These values include the respect for autonomy, non-maleficence, beneficence, and justice. [21]
A code of practice is adopted by a profession (or by a governmental or non-governmental organization) to regulate that profession. A code of practice may be styled as a code of professional responsibility, which will discuss difficult issues and difficult decisions that will often need to be made, and then provide a clear account of what behavior is considered "ethical" or "correct" or "right ...
In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false. [1] Type I error: an innocent person may be convicted. Type II error: a guilty person may be not convicted.
Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of professional scientific research. A Lancet review on Handling of Scientific Misconduct in Scandinavian countries gave examples of policy definitions. In Denmark, scientific misconduct is defined as "intention[al ...