Ethical Considerations for Data Science Research

You are here: Executive Education » Open Courses » Data Science

This Page

Ethical Considerations for Data Science Research - Course Details

Delve into the course contents and find out about the faculty members.

Single Course Price:

400.00 EUR (tax exempt)

Instructor:

Jessica Vitak, PhD (University of Maryland)

Video lecture:

Jessica Vitak, PhD (University of Maryland)

 

Course Dates:

To see all courses in the upcoming term click here.

Registration:

Book this course here!

In order to book the course with alumni conditions, please get in touch with Manon Pfeifer directly.

Course Description

Short Course Description
Networked technologies—including the internet of things (IoT), wearables, ubiquitous sensing, social sharing platforms, and other AI-driven systems—are generating a tremendous amount of data about individuals, companies, and societies. These technologies provide a range of new opportunities for data scientists and researchers to understand human behavior and develop new tools that benefit society.  At the same time, the ease with which data can be collected and analyzed raises a wide range of ethical questions about these technologies, their creators, and their users.

In recent years, we have seen numerous examples of research and technologies that are ethically problematic. For example, Facebook’s Cambridge Analytica scandal revealed researchers using problematic tactics to collect profile data from millions of Facebook users. In addition, algorithms and machine learning techniques have been revealed as systematically biased in how they evaluate resumes[1], recommend parole for prisoners[2], decide where police units should deploy[3], and identify people through facial recognition technology[4], just to name a few.

Therefore, it is critical that data scientists and others who will be working with big data can critically assess the potential risks and benefits of any end products, whether they are developing a search engine or a tool for detecting terrorists. This course will provide an overview of key ethical issues that arise when working with big data, and it will provide opportunities to review and reflect on past mistakes in this space.

Prerequisites
No prerequisites

Course objectives
By the end of the course, students will…

    Describe the history of research ethics and the goals of institutional review boards
    Describe the challenges data science and big data raise for protecting individuals’ rights and privacy
    Identify ethical issues in the study design, data collection, and data analysis process
    Detail best practices for conducting ethical research

Grading
Grading will be based on:

  • Participation in discussion during the weekly online meetings and contributions to weekly discussion forums demonstrating understanding of the required readings and video lectures (10% of grade)
  • Four open-book quizzes assessing comprehension of course material (20% of grade; 5% each)
  • Three online homework assignments reviewing specific aspects of the material covered (45% of grade; 15% each)
  • Final paper covering overarching themes of the class (25%).

ZFU Certification and Online Dispute Resolution

ZFU Certification

The Mannheim Master of Applied Data Science & Measurement program is certified according to the regulations of the ZFU (Staatliche Zentralstelle für Fernunterricht).

 

Online Dispute Resolution

Online dispute resolution according to Art. 14 Sect. 1 ODR-VO: The European Commission provides a platform for online dispute resolution (ODR). You can find more information under http://ec.europa.eu/consumers/odr/

MANNHEIM BUSINESS SCHOOL (MBS)

Located in the heart of the German and European economy, Mannheim Business School (MBS), the umbrella organization for management education at the University of Mannheim, is considered to be one of the leading institutions of its kind in Germany and is continuously ranked as Germany’s #1.

SOCIAL MEDIA NEWS WALL