SXSW 2018 Day 5 Session 2: The Humanoid Future of Journalism

Session page, including audio: https://schedule.sxsw.com/2018/events/PP80710

Robin Govik, COO MittMedia

Hanna Tuulonen, Göteborgin Sivukonntori

Hanna: Adaptation to automated (computer generated) journalism takes time.

Robin: We should not see automated journalism as scary – it’s not about computer journalism vs human journalism – it’s a collaborative environment.

What is automated journalism best at?  It’s not about creating a gripping survival story or covering a corruption scandal.  There’s room for automated journalism in weather reports, sports scores, and other similar types of topics.

Because of the revenue pressure on newspapers, the number of human journalists is going down, and we need a robot to pick up the slack.  AI can also help in investigative journalism, in analysis, searching and tracking of data which previously used to be handled manually by people.  Now the robot can manage the “dirty work” of sifting through tons of data and the human can focus putting all of the massive data in context as a coherent story.

AI can also personalize articles to the readers based on their interests, making the articles more compelling and improving reader loyalty.

Hanna: Finland and Sweden are pioneers in this domain.  Swedish people are less worried about AI displacing humans and leading to job loss because of the strong social safety net.

Robin: There are two kinds of news automation methods:

The first kind is software that generates and publishes stories directly on the site; mostly stories on sports.  Right now our newspaper publishes about 3000 AI-written articles a month.  The AI was initially used in one sport but expanded to other sports as well, due to the demand it generated.  This way one can cover a lot more teams and leagues than was possible previously, which appeals to local interest.

The second type is AI that creates short paragraphs that are sent to editors, who decide how to publish them.  These are frequently in areas like traffic reporting, weather, public transportation and so on.

Can this type of journalism generate money?  The key is relevant content.  We conducted data analysis to see what content converts users to paying users, and we can see what type of articles have high interest.

An AI can generate a richer experience than just a text story – it can get images from Google street view or from public domain image libraries, aggregate them into the story and create a richer experience.  For example, real estate reports generated by AI have been very successful.

Hanna: You can use AI to increase both quality and quantity:

• In quality, you can analyze data much more accurately, with fewer mistakes, when you use AI analytics.  This leads to better quality news reporting.
• In quantity, an AI can generate tens to hundreds of articles per second.  This leaves Journalists free to write stories they didn’t have time to previously on more interesting and complex topics.

Finnish journalists were asked how they felt about working with news robots, and answered that they loved it as it took away repetitive and boring jobs.  But this was their opinion _after_ working with the robots; before they had negative attitudes to them.  It only took about two weeks of working with the robots for them to change their view.

Robin: Two thirds of readers can’t tell that the story was written by a robot.  This allows making much wider and smaller sets of news reportable.

Hanna: Articles written partially or fully by machines score higher credibility with readers.  However, they frequently score lower on readability; you still need humans to write engaging stories.

A study that was done in south Korea showed that people felt journalists are corrupt, but algorithms are fair.

Robin: The humanoid future of journalism includes:

1. Personalization – this is much easier with robots, as it’s easy for them to generate multiple versions of a story, based on the preferences of the person reading it.  However, one thing to look out for is creating opinion bubbles, where people are only receiving news that reinforces their existing personal beliefs and points of view (as happens in social media).
2. Robot journalism + citizen journalism – an example of this is using robot journalism to report on a sports event, while using a service which sends messages to participants and possibly spectators to get quotes and pictures from them.  The combined result adds humanity to the story, but it does present a problem of curation of the provided input.
3. Dynamism – the ability to change formats of stories to support personalization.  For example, on the BBC an article can be rewritten every time it us loaded, which helps keep it up to date and personalized.
4. A new role for journalists – some journalists will focus on working with robots, finding data to feed them and working jointly on stories.  Others will continue the traditional and independent role they had (but now will be less encumbered with menial tasks).
5. Ethics and writing - Human journalists still excel in their ability to write and in soft domains such as ethics and emotions.  Robot journalism will help bring back quality of writing into focus.

So summing up:

The pros of robo-journalis

• Better journalism
• More content
• Increased quality

The cons:

• Bad data drives bad stories
• Potentially dull and spiritless writing
• May pivot news coverage to topics where there is plenty of data available.  Areas missing data sources lead to topics being under reported.