Data ethics is concerned with ethical questions, considerations, and debates around data, including the collection, management, analysis, interpretation, sharing, and use (and misuse) of data, and the impact of data on individuals and the society.
Important laws regarding data privacy and confidentiality in the United States:
Data Science Ethics (Coursera)
A free online course offered by the University of Michigan on Coursera. What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches? This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten." This course will help you answer questions such as who owns data, how do we value privacy, how to receive informed consent and what it means to be fair.
Length: 4 weeks (self-paced).
Ethics and Law in Data Analytics (LinkedIn Learning)
An online course on LinkedIn Learning with transcripts, exercise files, and self-assessment quizzes. With big data analytics and artificial intelligence (AI), corporations, governments, and individuals have access to powerful tools that can have real-world outcomes. Data professionals today need both the frameworks and the methods in their job to achieve optimal results while being good stewards of their critical role in society today. This course—part of the Microsoft Professional Program offerings—explores the ethical and legal frameworks applicable to the data profession. Learn how these frameworks apply to practical problems posed by work in big data and data science, and investigate applied data methods for ethical and legal work in analytics and AI.
Length: 3 hours, 40 minutes. (Free access with Bucknell login.)
Understanding Intellectual Property (LinkedIn Learning)
An online course on LinkedIn Learning with transcripts, exercise files, and self-assessment quizzes. Provides a high-level overview of intellectual property (IP), including topics such as patents, trademarks, and other protections. Learn the answer to common IP questions and discover an attorney's perspective on how you can best safeguard your ideas, and avoid infringing others' rights.
Length: 1 hour, 30 minutes. (Free access with Bucknell login.)
Understanding Copyright: A Deeper Dive (LinkedIn Learning)
An online course on LinkedIn Learning with transcripts, exercise files, and self-assessment quizzes. The course provides a deeper dive into copyright—the mechanism for protecting intellectual property that resides in a tangible form: books, songs, software, product designs, etc. Explains what constitutes copyright infringement, and how to respond when someone has infringed upon your copyright or if you receive a demand letter or cease and desist from a third party. Covers licensing, public domain, and fair use, and reviews the process for searching for and filing copyrights.
Length: 1 hour, 12 minutes. (Free access with Bucknell login.)
AI Accountability Essential Training (LinkedIn Learning)
An online course on LinkedIn Learning with transcripts, exercise files, and self-assessment quizzes. Artificial intelligence (AI) offers businesses the potential for a dramatic increase in functionality and profitability, but it can also spark an array of complex ethical, legal, and social challenges. This nontechnical, conceptually-oriented course explores the ethical issues posed by AI, including competing concepts of fairness and moral reasoning, as well as social concerns and safety challenges for AI, such as potential life-and-death scenarios in autonomous driving; and it concludes with recommendations on how to reap the potential of AI in an ethical and trustworthy manner.
Length: 2 hours, 20 minutes. (Free access with Bucknell login.)