China’s state news agency, Xinhua, announced recently that it is building an AI platform for automated news production, combining multiple sources of data. This could potentially be the most comprehensive use of automation yet in newsrooms.
China's state news agency, Xinhua, announced
last month that it is integrating Artificial Intelligence into news production to
build a new kind of newsroom, in collaboration with the Alibaba Group.
Dubbed “Media Brain”, the platform was developed through a
joint venture between Xinhua News Agency and Alibaba Group. It is an open
platform where media agencies can apply to share and share their data resources.
It brings together cloud computing, the Internet of Things, Big Data and AI
technology, deploying them in the process of news production. Proposed
applications for the "Media Brain" encompass every stage of news
production, starting from finding leads, to news gathering, editing,
distribution and analysis of feedback. It intelligently identifies specific
scenarios and emergencies such as fires, explosions and traffic collisions, as
newsworthy. It will combine data from multiple sources near the scene of
the news, such as cameras, sensors, drones etc.
The platform’s capabilities include face verification from
videos and images. It can also be used to track copyright violation of all
forms of media.
Privacy concerns related to this platform were raised
in an article by the managing editor of China Money Network, which itself is
an AI-based platform tracking China’s private equity, venture capital and
For a while now, newsrooms around the world have been exploring
the use of AI for a range of purposes, from targeted personalised distribution
to content generation.
from the Reuters Institute for the Study of Journalism at the University of Oxford
on Journalism, Media, and Technology Trends and Predictions for 2018, highlights
several ways in which newsrooms are adopting AI. One of the most common applications
of AI is for improving content recommendations, by understanding individual
preferences, and personalising each edition in terms of ‘personalise each
edition in terms of format, time, and frequency’. AI driven paywalls can help in
identification of likely subscribers and based on previous behaviour serve them
an offer which is most likely to persuade them to subscribe. AI could also be
used to create more personalised advertisements or push e-commerce
recommendations based on previous interest shown.
It also talks about the potential for AI to aid journalists
with fact-checking, possibly even in real-time, during a live radio or TV
The use of AI is also being explored for automation of
workflows and boosting production efficiency. The report cites a project funded
by Google’s Digital News Initiative
to generate 30,000 stories per month for local outlets. It combines editorial expertise and automation,
leveraging of growing availability of open data. Once a journalist finds a
story using publicly available databases and write a story, multiple versions
are then created automatically for different local publications. Graphics,
video and pictures for the stories are automatically
Post has been using Heliograf, its in-house automated storytelling
technology to cover Washington, D.C.-area’s weekly high school football games.
In 2014, the Associated Press (AP) entered into a collaboration
Insights, to write earnings reports covering publicly traded companies using
algorithms, drawing on information from firms’ press releases, analyst reports
and stock performance. A subsequent collaboration between AP and researchers
from Stanford University and the University of Washington ‘found compelling
evidence that automated articles increase firms’ trading volume and liquidity’.
Chinese tech giant, Tencent, has also been working on using
AI for content generation in areas such as financial reporting and sports news,
along with understanding user preferences and making recommendations. In late
2015, South China Morning Post reported
that Tencent’s automated newswriting program, Dreamwriter, created a business
article on inflation, including analysts' comments, in less than a minute. More
recently, the executive director of Quartz, Zach Seward delivered a speech at a
conference in China organised by Tencent and it was turned into a news story by
a combination of AI-based speech to text software, automatic transcription, and
Automation is also being used for news detection, as seen
from the Reuters News Tracer, which tracks social media and highlights breaking
stories to reporters.
Such applications could increase breadth of coverage, help cover
local content and allow news organisations and journalists to direct limited
resources towards in-depth investigations. AI also has potential as an aid to reporters by enabling rapid analysis of vast troves of data and documents, such as the Panama papers.However, they have also raised
concerns that journalists’ jobs could among those expected to be lost to AI.
In this context, a 2017
study from the Reuters Institute for the Study of Journalism on the use of
automated journalism in European news agencies found that though most news
agencies are already using or actively exploring automation in news generation,
only two of the organisations surveyed were using algorithms to compare new
information to historical data, and provide interpretations, thereby adding
Automation is still not being used widely for more complex
reporting. The most popular areas for automation are finance and sport reporting.
Currently, there are also limitations with natural language generation ability.
The use of AI for detecting fake news is another important implication
of the technology for journalism. In
December 2016, Facebook’s director of AI, Yann LeCun said
(subscription required) that AI could be used to detect fake news. The MIT Tech
about start-up, AdVerif.ai,
which works with publishers, advertisers and networks who do not wish to be
associated with false or potentially offensive stories. Last year, a Fake News Challenge was launched through
a grassroots effort of over 100 volunteers and 71 teams from academia and
industry from around the world, to foster development of tools to help human
fact checkers identify hoaxes and deliberate misinformation in news stories. However,
it should be noted that this last challenge is still about assisting human fact
checkers. The efficacy of AI in filtering out fake news by itself remains to be
In conclusion, AI appears to be here to stay in newsrooms, supporting
journalists in their work and not replacing them, at least for the time being. A
large proportion of news consumption already happens through algorithm-driven recommendations
on social media platforms. Now algorithms are steadily entering into content
generation side as well. If used as an aid, it could improve creation and enhance
distribution of news. On the other hand, if it encourages owners to further
reduce limited human resources, before AI manages to reach the required level for
in-depth reporting, or gives governments greater control over what citizens see in the case of state-controlled outlets, AI could have an adverse impact. Then the quality and
extent of coverage (or lack of it) will also enter into the list of concerns
for public policymakers, as well as civil society.
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