Researchers are struggling to replicate AI studies

The problem: Science reports that from a sample of 400 papers at top AI conferences in recent years, only 6 percent of presenters shared code. Just a third shared data, and a little over half shared summaries of their algorithms known as pseudocode. Why it matters: Without access to that information, it's hard to reproduce a study's findings. That makes it all but impossible to benchmark newly developed tools against existing ones, causing difficulties in knowing which direction in which to push future research. How to solve it: Sometimes a lack of sharing may be understandable--say, if intellectual property is owned by a private firm.