I may be mixing my metaphors, here's NiemanLab:
Reuters’ new automation tool wants to help reporters spot the hidden stories in their data (but won’t take their jobs)
With Lynx Insights, Reuters wants to marry the data-crunching skills of machines with the editorial judgment of human reporters.HT to and headline from: Talking Biz News:
For the news industry, the promise — or perhaps threat — of automation is that technology will be able to handle more of the monotonous reporting, freeing up human reporters to do the enterprising, high-value work.
Reuters, however, sees another path: cybernetic reporters. At NICAR on Friday, Padraic Cassidy, Reuters’ editor of news production systems, took the wraps off Lynx Insights, a new in-house automation tool designed to augment reporting by surfacing trends, facts, and anomalies in data, which reporters can then use to accelerate the production of their existing stories or spot new ones.
While Reuters has experimented with automated reporting since at least 2015, Cassidy said that the process was not only expensive and time-consuming, but often resulted in articles that were transparently written by a machine. “After looking at those stories, we decided to be sensible about it and made it so that machines can do what they’re good at and marry that to what humans are good at, which is judgment, context, quotes, and insight,” he said.
Via Lynx Insights, which Cassidy said was “much more sane, less expensive, and quicker-to-market,” Reuters reporters can easily surface key data related to their stories. A markets reporter, could, for example, use the tool to quickly determine the total value of merger and acquisition deals for a given year, or analyze historical trends in commodities pricing. So far, Reuters has focused on markets data, but Cassidy said that over time Reuters will expand to other kinds of “low-hanging-fruit stories,” particularly in sports and corporate earnings numbers.
Reuters reporters have had a direct role in building Lynx Insights. Reuters’s Toronto-based data science team made a callout to reporters to determine what kind of data they’d be most interested in and what kinds of stories took them the most time to produce. Speed, of course, is a prime consideration with automation, which is why newswire companies have embraced the technology more readily than other news organizations....MORE
