Title: Data Is People: Ethics and Education for Data Science
Abstract: Big data has opened up new possibilities and transformed the ways we conduct research in nearly every discipline. However, ethical considerations and education for research has long focused on human subjects, governed in the U.S. by institutional review boards. Data science often falls through the cracks of these regulations, so it is even more imperative that we have strong ethical norms and guidelines. This starts with the reminder that though data scientists may not interact directly with people, the data collected and analyzed very often comes from people, which opens up important considerations around privacy, consent, and harm. Moreover, applications of data science research, particularly with respect to prediction, have the potential for large-scale societal impacts. In considering the broad landscape of technology ethics when it comes to uses and applications of big data, I will argue for a fundamental shift in how we teach ethics to future data scientists and researchers.
Abstract: Data science is a new discipline. As such, we have a greater opportunity than in many other fields to define what its culture should look like. In this talk, I discuss how open approaches to software, research, and education improve science, but also challenge the way in which we approach our work.
Bio: Dr. Stéfan van der Walt is a senior research data scientist at the Berkeley Institute for Data Science, the founder of scikit-image, and co-author of "Elegant SciPy: The Art of Scientific Python".
Stéfan has been developing scientific open-source software for more than fifteen years, focusing primarily on tools in the Python language. He is a director of NumFOCUS, and serves on the steering committees of NumPy, SciPy, and the Python Software Foundation's Scientific Working Group. Outside (and sometimes during) work, he is kept on his toes by two energetic toddlers, and he enjoys running in the great outdoors.
|Start menti.com code||End||Event|
|9:00 am||9:15 am||Opening Remarks|
|9:15 am 63 48 79 9||10:15 am||Keynote Speaker: Fiesler|
|10:15 am||10:45 am||Coffee Break|
|10:45 am 41 87 47 6||12:15 pm||Education Session Talks|
|12:15 pm||1:00 pm||Lunch Break|
|1:00 pm 74 73 30 5||2:00 pm||Keynote Speaker: van der Walt|
|2:00 pm 35 92 12 1||3:00 pm||Research Session Presentations and Discussion|
|3:00 pm||3:30 pm||Coffee Break or continued discussion|
|3:30 pm 96 06 04 0||4:30 pm||Industry Session Talks|
|4:30 pm||5:00 pm||A Discussion on Data Science at CU Denver and Closing Remarks|