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Investigating Algorithms
Uber’s Surge Pricing May Not Lead to a Surge in Drivers | ProPublica
Lauren Kirchner and Surya Mattu report on research out of Northeastern University that challenges Uber’s claim that surge pricing helps passengers because it encourages more drivers to get on the road. Uber responded by saying the research was based on “extremely limited, public data” and they have seen surge pricing work for passengers in cities all over the world. The research was conducted through 43 newly created Uber accounts, which were used to hail cars over a four week period in San Francisco and Manhattan. Kirchner and ProPublica have reported on similar stories related to “algorithmic transparency” in the hope of shedding light on how the endless number of algorithms we use every day impacts our lives.
Practical Machine Learning
A Case Study In Practical Machine Learning | Postmates Engineering
Rick Fulton, Director of Engineering at Postmates, shares how his team applied “simple and accessible machine learning techniques” to tackle the challenges in providing their customers accurate estimated delivery times.
A Founding Father of AI Looks Back
Marvin Minsky Reflects on a Life in AI | MIT Technology Review
In 1951, Marvin Minsky built an artificial neural network from vacuum tubes that would come to be defined as “the first learning machine.” Eight years later he founded the Artificial Intelligence Laboratory at MIT, where he used early robots to attempt to model human perception and intelligence. Over the course of his career Minsky continued to try and build machines “capable of more than just computation,” and has created a legacy of “encouraging others to believe that intelligence can indeed be born in machines.” Will Knight recorded a recent visit to Minsky’s home, where the computing pioneer looked back on his early breakthroughs, and the state of AI research today.
The New Data Engineering Ecosystem
The New Data Engineering Ecosystem: Trends and Rising Stars | Insight
David Drummond and Ronak Nathani published an interactive map that provides an overview of trends, new technologies, and resources related to the current data engineering ecosystem.
Reimagining the News Story
The Future Of News Is Not An Article | New York Times Labs
Alexis Lloyd, the Creative Director of NYTLabs, suggests that news organizations need to let go of the old, temporal constraints related to print media, and should consider more innovative ways of thinking about the time scales of their reporting: “Information should accumulate upon itself; documents should have ways of reacting to new reporting or information; and we should consider the consumption behavior of our users as one that takes place at all cadences, not simply as a daily update.” The New York Times R&D Lab has created a project called Particles that starts by “identifying and annotating the potentially reusable pieces of information within an article as it is being written.” The project is part of an approach that will apply “computational techniques to augment journalists’ processes,” and has the potential to “transform the news reading experience.”
The Human Element
The Human Element of Data Science | Mode
Derek Steer, CEO of Mode Analytics, notes that the current dominant discussion in the Silicon Valley data science community is about how important the human element is throughout the data science process. Steer shares highlights from the first ever WrangleConf, hosted by Cloudera, where he says “nearly every speaker and panelist” talked about people, instead of topics focused on technology or tactics.
The Hippocratic Algorithm
Raw Data Podcast – Episode 3 | Worldview Stanford
Leslie Chang and Mike Osborne discuss how big data is transforming health and medicine. A wide range of guests join them to discuss genomics data, how wearable technologies may help cardiologists fight heart disease, how computational models can be used to study cancer biology, and the future role of the “human” doctor in providing what a computer cannot provide.
Each week we surface, summarize, and share the most interesting stories and biggest news from the world of data science. Have articles or podcasts that you think we should be covering in our Data Science Roundup? Send them to editor@rjmetrics.com.
