Sections offered SPRING 2022:
#32188 |
YOUNEI SOE |
MW 9:25 AM–10:40 AM
|
HU 217 |
CLASS NOTES: IUB GenEd S&H credit; COLL (CASE) S&H Breadth of Inquiry credit
Class meets In Person. For more information visit https://covid.iu.edu/learning-modes/index.html
This course was featured in the Indiana University Journal of Undergraduate Research: Learning what the buzzwords mean: Big data and AI in the Hutton Honors College
Every day, billions of people interact with information technologies on the internet and contribute to a world of valuable information. But the human brain simply cannot fathom the quantity of data generated daily. The term “big data” refers to data that is so large, fast, or complex that it’s difficult or impossible to process using traditional methods. We are living in a historic moment where big data and artificial intelligence are shaping many parts of society, and automated society is on the not-so-distant horizon. Therefore, we must make such technologies compatible with the core human values. In organizational settings, the focus on big data in society should look beyond the extraordinary volume of information in order to assess the value that organizations can extract from such data.
In this seminar-style, discussion-oriented course, students will learn to think and decide on their own in the likely future scenarios that involve data-related, potentially ethically challenging situations. With that goal in mind, this course introduces students to new social and ethical challenges arising from the use of data in various work contexts. The course also provides students with an understanding of the moral roles/rules and ethical dilemmas involved in the uses of big data. We will discuss various technical and societal approaches to tackling such challenges.
By the end of this course, students will understand the following:
• The role of big data in organizational decision-making
• How the integration of big data is changing the culture, structure, and work practices of
complex organizations
• Social, political, legal, and organizational impacts of big data
• How to develop mature stances regarding big data ethics