Plenary Keynote Panel
Wednesday, August 7th, 4:00 pm – 6:00 pm (Tukatnu Ballroom, Level 3, Dena’ina Center)
The beneficiaries of advanced data science remain largely the key stakeholders in various industries. However, as we infuse data science into assisted and automated intelligence services, it will drive a major shift towards data science benefiting the consumers, a democratization of the technology. This panel debates what it would mean to democratize data science, how this might be done and the arguments for and against it.
- Moderator: Nitesh Chwala, University of Notre Dame
- Tina Eliasi-Rad, Northeastern
- Yu Zheng, JD.com
- Eric Sears, MacArthur Foundation
- Rediet Abebe, Cornell University
- Anil Jain, Michigan State
Issues to be covered include:
- What does democratization of data science mean? How might it be achieved?
- What are the tenets of fairness and transparency that must accompany this democratization?
- What (or how will these) applications will be most immediately and profoundly affected by democratization?
- Driverless cars
- What innovations do we anticipate on data sensing and gathering?
- Whose interests would be served by the democratization of data science and whose are served by its absence?
- How do we prepare ourselves for unanticipated risks?
- Do citizens have a right to share in the downstream benefits derived from data they generate?
- Do commercial interests have a right to benefit from data private citizens generate?
- What data ought to be public and what should remain private?
- Will it become a race to data ownership?
- Ethics, trust, and privacy issues
- What is our expectation of deep learning architectures? Is it a computational speed-up and scale challenge or what are the new algorithmic challenges that one may envision? What new learning paradigms await us?
- What will be the data science vs data trade-off? Where will the innovations come from?
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