Professor Freire speaks to world’s leading data researchers about transparency and trust
Data-driven exploration has revolutionized science, industry, and government alike — a revolution enabled by an abundance of data coupled with cheap, widely available computing and storage resources, as Juliana Freire, a professor in the NYU Tandon Department of Computer Science and Engineering, explains. She cautions, however, that to extract actionable insight from data, complex computational processes are required that are not only hard to assemble but that can also behave (and break) in unforeseen ways. Thus, when results are derived, how can we be sure that they are trustworthy?
Freire, who also holds an appointment in the Courant Institute for Mathematical Science and is a faculty member at the NYU Center of Data Science, addressed that vital topic at the opening keynote address of the 2019 IEEE International Conference on Data Engineering (ICDE), held in Macau, to a rapt audience of more than 500 of the world’s leading data researchers, practitioners, and developers. In it, she presented recent research carried out at Tandon’s Visualization and Data Analytics (ViDA) Center on techniques and systems that empower domain experts to explore their own data, while supporting transparency and enabling them to build trust in the results they derive.
Just days later, on April 16, Freire gave another high-profile keynote, this one at the 2019 Women in Data Science Conference held in Copenhagen.
Given that life-altering decisions are now increasingly driven by data — who gets approved for a loan or granted parole, for example — erroneous conclusions can have serious consequences, and Freire’s work is helping support the correctness and efficacy of the process.