Ethical Issues for Data Science, Machine Learning and Artificial Intelligence
Ethical Issues for Data Science, Machine Learning and Artificial Intelligence

Abstract: 

Doing the right thing has never been more important for people working in the areas of Data Science, Machine Learning and Artificial Intelligence. Data Ethics has been growing in importance recently and with recent global events has renewed the focus on the topic. This presentation will examine some of the main concepts involved in Data Ethics and will use a number of different case studies to illustrate the different challenges being encountered and how these can be address considering various legal aspects.

Bio: 

Brendan Tierney, Oracle GroundBreaker Ambassador and Oracle ACE Director, is an independent consultant (Oralytics) and lectures on data science, databases, and Big Data at the Technological University Dublin. He has over 27+ years experience working in the areas of data mining, data science, machine learning, big data, and data warehousing. Tierney has published five books,
97 Things about Ethics Everyone in Data Science Should Know, a best seller with MIT Press titled Data Science (Essentials Series), and three books with Oracle Press/McGraw-Hill (Predictive Analytics Using Oracle Data Miner, Oracle R Enterprise: Harnessing the Power of R in Oracle Database, and Real World SQL and PL/SQL: Advice from the Experts). 
Web and blog: www.oralytics.com
Twitter: @brendantierney

Open Data Science

 

 

 

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