Panel: a debate on data and algorithmic ethics

摘要: Recently, there has begun a movement towards Fairness, Accountability, and Transparency (FAT) in algorithmic decision making, data science more broadly. The database community not been significantly involved this movement, despite "owning" the models, languages, systems that produce (potentially biased) input to machine learning applications.What role should play movement? Do objectives of fairness, accountability transparency give rise core management issues can drive new research questions systems, or are these "soft topics" best left be managed with policy? Will emphasis on topics dilute our competency techniques technologies for data, it reinforce central technology stacks ranging from startups enterprise, local non-profits federal government? goal panel is debate questions, whet appetite important emerging area.