Applied Data Science & AI Round-Up: January 2018 Edition
by Tony Ojeda
For 2018, we are starting a new monthly round-up series on the DDL blog that highlights examples of data science and artificial intelligence being applied in different fields, industries, and domains. We’ve noticed that people who don’t work closely with data, or haven’t worked with data scientists, often have trouble envisioning how these methods and technologies are applicable to them and can impact the work they do. We hope this series will help further the conversation about how these technologies can be applied and spark some ideas for how you can apply them in your own business or domain.
Child abuse and neglect hotlines around the country screen millions of calls a year attempting to discern which cases are serious. Allegheny County in Pennsylvania is the first jurisdiction in the United States to use a predictive analytics algorithm when screening calls to their child abuse and neglect hotline to better help determine which families require intervention. The algorithm is capable of analyzing multiple databases and historical files in seconds, whereas it would have taken human employees hours to perform the same tasks.
In this in-depth interview with Forbes, current Walmart CIO Clay Johnson goes over his big priorities for the IT department this year, which includes developing a product model for IT to facilitate end-to-end ownership of different product areas created, as well as process automation, facilitated at least in part through artificial intelligence.
With more refugees in the world than ever before, this growing global crisis is often considered an overwhelming challenge. However, solutions are possible with the help of predictive analytics. By using migration data that is already being collected, experts can predict where refugees are most likely to head next so that countries can have time to react and prepare.
Fully tapping into the power of machine learning may require relying on results that are impossible to explain to the human mind. Modifying the technology to explain its conclusions in every case can lead to mistakes like failing to diagnose diseases, overlooking significant causes of climate change, or making an educational system that’s one-size fits all.
Historians and cryptographers have been attempting to decipher the Voynich manuscript since before WWII and all have failed until scientists at the University of Alberta enlisted the help of artificial intelligence.
That’s it for this month! If you come across some interesting articles that highlight the application of data science and AI to an industry or domain, let us know by tagging us on social or emailing us a link at firstname.lastname@example.org.
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