Interested in the research and educational potential of big data but concerned about the ethics of using personal data for data science? Then join the AAAS for a panel discussion with leading academic, non-profit, and government experts on data ethics.

Date: Monday, May 14th, 2018

Time: 5:30pm (panel discussion), 6:30pm (networking)

Venue: AAAS HQ, Abelson-Haskins Room (1200 New York Ave NW, Washington, DC, 20005)

RSVP: EventBrite – free

 

Topic: Ethics of Using Personal Data in Data Science Research and Education

 

Natalie Evans Harris, MPA (Founder, Harris Data Consulting; Chief Operating Officer, BrightHive)

Simson Garfinkel, Ph.D. (Senior Computer Scientist for Confidentiality and Data Access, U.S. Census Bureau)

Jessica Vitak, Ph.D. (Assistant Professor & Director of the Center for the Advanced Study of Communities and Information, University of Maryland)

 

Affinity Groups for Big Data, Citizen Science, and DC Tech, AAAS S&T Policy Fellowships  

 

With the ubiquity of data and its use for research and education, an increasing number of questions are emerging around the ethical considerations of analyzing personal data. Federal and state agencies are having discussions centered around fairness, accountability, and transparency. From a consumer perspective, companies are considering how customer data can be monetized, while consumers are fighting for their privacy and many others are unaware of the implications of sharing their data. Privacy for single-source datasets, particularly those with Personally Identifiable Information (PII) has been explored through policies such as HIPAA (Health Insurance Portability and Accountability Act of 1996). Regulations focus on the removal of PII from individual datasets, with fewer restrictions placed on datasets from which PII fields have been removed. However, these rules are based upon the outmoded idea that removal of these fields protects individuals from re-identification. New privacy challenges are emerging, as the combining of datasets creates new threats by allowing for re-identification of individuals. Such losses in privacy represents huge ethical concerns, and creates challenges for data scientists trying to unlock insights from datasets, often with little awareness of the ethical implications of their actions.

 

In terms of data science education, it is critical to equip students with a strong ethics foundation in the context of using personal data, as well as to educate them about the potential pitfalls of using non-sensitive data that might be combined with PII data.

 

This panel, featuring speakers with experience from academia, nonprofits, and government, will focus on some of the ethical considerations in data science research and education.

 

Following the panel discussion, we will have some time to network with the panelists over light snacks.