Crosstown project turns citizens into squeaky wheels: “Crosstown joins a nationwide movement by government, universities and other institutions to make big data more useful to citizens and the news media,” writes Mark Jacob, focusing on core quality-of-life issues.
Medill spotlights local news collapse: As newsroom jobs disappear, writes Mark Jacob, some areas of the country are virtually uncovered by journalism and plagues all news consumers with more superficiality and mistakes.
“Which means there’s plenty to read and view, but it might not tell us very much,” he writes on the local news crisis as part of the Local News Initiative at Northwestern University’s Medill School of Journalism.
The Associated Press already uses an automated platform capable of producing up to 2,000 stories a second. This is especially handy when companies issue quarterly earnings, which can be drudgery for a human reporter who scans the reports for meaningful numbers and statistics.
The robotic journalist crunches those numbers in seconds and spits them out in readable form, not in Pulitzer Prize-winning style but adequate.
Robo-reporting is especially handy for business and sports stories heavy on numbers and scores.
Northwestern University was among the pioneers in using machine learning, or pattern recognition software, to assemble the basics of a news report. A 2009 student project created software to write a headline and story from a baseball game’s box score. Two NU professors in 2010 started a Chicago company, Narrative Science to find commercial uses for the technique.
Stories written by robots have a lot of potential for the news business, and a few issues that need to be hammered out. Like ethics.
Computers, for example, could become plagiarists.
“Just because the information you scrape off the Internet may be accurate, it doesn’t necessarily mean that you have the right to integrate it into the automated stories that you’re creating — at least without credit and permission,” said Tom Kent, Associated Press standards editor, in a Digital Journal article, which cited comments Kent made to the University of Wisconsin Center for Journalism Ethics.
“I think the most pressing ethical concern is teaching algorithms how to assess data and how to organize it for the human eye and the human mind,” said Kent. “If you’re creating a series of financial reports, you might program the algorithm to lead with earnings per share. You might program it to lead with total sales or lead with net income. But all of those decisions are subject — as any journalistic decision is — to criticism.”