Stories

The IRE Resource Center is a major research library containing more than 27,000 investigative stories.

Most of our stories are not available for download but can be easily ordered by contacting the Resource Center directly at 573-882-3364 or rescntr@ire.org where a researcher can help you pinpoint what you need.

Search results for "algorithms" ...

  • Artificial Intelligence: The Robots Are Now Hiring

    Hiring is undergoing a profound revolution. Since skills have a shorter and shorter shelf life, companies are moving away from assessing candidates based on their resumes and skills, towards making hiring decisions based on people’s personalities.
  • Dangerous Doses

    For one story, “The hunt for dangerous doses,” investigative reporter Sam Roe led a collaboration with data scientists, pharmacologists and cellular researchers at Columbia University Medical Center in an attempt to discover potentially deadly combinations of prescription drugs. Intrigued by the novel data mining algorithms developed by Columbia scientist Nicholas Tatonetti, Roe proposed that the two team up to search for drug combinations that might cause a potentially fatal heart condition. Roe also recruited Dr. Ray Woosley, the leading authority on that condition and a former dean of the University of Arizona medical school, to the team. Over two years, as he orchestrated the project, Roe traveled to New York 12 times to meet with Tatonetti. They brainstormed, analyzed data and talked with Woosley via conference calls. Several of Tatonetti’s graduate students joined the team, as did Columbia cellular researchers whose work provided a critical layer of validation of the results.
  • Machine Bias

    With our Machine Bias series, we are investigating the algorithms that are increasingly making decisions about our lives, from what news or ads we see online to what sentences are meted out for crimes. Algorithms are often proprietary "black boxes," raising important questions about transparency and due process. By collecting and analyzing the output of these systems, we set out to reverse-engineer and make accountable some of the algorithms that were having the biggest impact on people’s lives. Our investigative methods included linear regression, statistical analysis, and the creation of our own software. Among the series’ findings were evidence of racial bias in risk assessment systems, and the preferential treatment of Amazon’s own products in its so-called open market.