EconPapers    
Economics at your fingertips  
 

Ethics of Data Science and AI

Alex Coad ()

Chapter Chapter 6 in Data Science MBA, 2025, pp 75-89 from Springer

Abstract: Abstract This chapter discusses ethical aspects of data science and AI. On the one hand, digitalization has benefits, due to the potential for data to elucidate decision-making processes. On the other hand, there are serious ethical challenges posed by AI. The chapter covers topics such as AI bias, black box algorithms, privacy concerns, and the importance of ethical frameworks in AI development. The chapter also includes an example in R to demonstrate logistic regression on loan data, highlighting ethical issues in predictive modeling.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-981-95-2433-4_6

Ordering information: This item can be ordered from
http://www.springer.com/9789819524334

DOI: 10.1007/978-981-95-2433-4_6

Access Statistics for this chapter

More chapters in Springer Texts in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-07-27
Handle: RePEc:spr:sptchp:978-981-95-2433-4_6