INSUBCONTINENT EXCLUSIVE:
Koponen
Contributor
Jarno M
Koponen is working on intelligent systems and human-centered personalization
He currently is product lead at Yle, one of the leading media houses in the Nordics.
More posts by this contributor
AI on your
lock screen
The next AI is no AI
To put it mildly, news media has been on the sidelines in AI development
As a consequence, in the age of AI-powered personalized interfaces, the news organizations don&tanymore get to define what real news, or,
even more importantly, what truthful or trustworthy
Today, social media platforms, search engines and content aggregatorscontrol user flows to the media content and affect directly what kind
of news content is created
As a result, the future of news media isn&t anymore in its own hands
Caseclosed
The (Death) Valley of news digitalization
There a history: News media hasn&t been quick or innovative enough to become a change
maker in the digital world
Historically, news used to be the signal that attractedand guided people (and advertisers) in its own right
The internet and the exponential explosion of available information online changed that for good.
In the early internet, the portals
channeled people to the content in which they were interested
Remember Yahoo As the amount of information increased, the search engine(s)took over, changing the way people found relevant information and
As the mobile technologies and interfaces started to get more prominent, socialmedia with News Feed and tweets took over, changing again the
way people discovered media content, now emphasizing the role of our social networks.
Significantly, news media didn&t play an active role
in any of these key developments
Quite the opposite, it was late in utilizing the rise of the internet, search engines,content aggregators, mobile experience, social media
and other new digital solutions to its own benefit.
The ad business followed suit
First news organizations let Google handle searches on their websites and the upcoming search champion got a unique chance to index
With the rise of social media, news organizations, especially in the U.S., turned to Facebook and Twitter to break the news rather than
focusing on their ownbreaking news features
As a consequence, news media lost its core business to the rising giants of the new digital economy.
To put it very strongly, news media
hasn&t ever been fully digital in its approach to user experience, business logic or content creation
Think paywalls and e-newspapers forthe iPad! The internet and digitalization forced the news media to change, but the change was reactive,
not proactive.The old, partly obsolete, paradigms of contentcreation, audience understanding, user experience and content distribution still
actively affect the way news content is created and distributed today (and to be 110 percent clear —this is not about the storytelling and
the unbelievable creativity and hard work done by ingenious journalists all around the globe).
Due to these developments, today algorithmic
gatekeepers like Google and Facebook dominate the information flows and the ad business previously dominated by thenews media.Significantly,
personalization and the ad-driven business logic of today internet behemoths isn&t designed to let the news media flourish on itsown terms
ever again.
From observers to change makers
News media have been reporting the rise of the new algorithmic world order as an outside
And the reporting has been thorough, veracious and enlightening — thestories told by the news media have had a concrete effect on how
people perceive our continuously evolving digital realities.
However, as the information flows have moved into the algorithmic black boxes
controlled by the internet giants, it has become obvious that it very difficult or close toimpossible for an outside observer to understand
the dynamics that affect how or why a certain piece of information becomes newsworthy and widely spread.For themainstream news media, Trump
rise to the presidency came as a &surprise,& and this is but one example of the new dynamics of today digital reality.
And here a paradox
As the information moves closer to us, to the mobile lock screen and other surfaces that are available and accessible for us all the time,
its origins andbackground motives become more ambiguous than ever.
The current course won&t be changed by commenting on or
criticizing the actions of the ruling algorithmic platforms.
The social media combined with self-realizing feedback loops utilizing
the latest machine learning methods, simultaneously being vulnerable for malicious orunintended gaming, has led us to the world of
&alternative facts& and fake news.In this era of automated troll-hordes and algorithmic manipulation, the ideals of newsmedia sound vitally
important and relevant: Distribution of truthful and relevant information; nurturing the freedom of speech; giving the voice to the unheard;
widening and enriching people worldview; supportingdemocracy.
But,the driving values of news media won&t ever be fully realized in the
algorithmic reality if the news media itself isn&t actively developing solutions that shape thealgorithmic reality.
The current course won&t
be changed by commenting on or criticizing the actions of the ruling algorithmic platforms
#ChangeFacebook is not on the table for news media
NewAI-powered Google News is controlled and developed by Google, based on its company culture and values, and thus can&t be directly
affected by the news organizations.
After the rise of the internet and today algorithmic rule, we are again on the verge of a significant
Machine learning-powered AI solutions will have an increasinglysignificant impact on our digital and physical realities
This is again a time to affect the power balance, to affect the direction of digital development and to change the way we think when we
think about news — a timefor news media to transform from an outside observer into a change maker.
AI solutions for news media
If the news
media wants to affect how news content is created, developed, presented and delivered to us in the future, they need to take an active role
If news organizations want to understand the way data and information are constantly affected and manipulated in digital environments, they
needto start embracing the possibilities of machine learning.
But how can news media ever compete with today AI leaders
News organisations
have one thing that Google, Facebook and other big internet players don&t yet have: news organizations own the content creation process
andthus have a deep and detailed content understanding
By focusing on appropriate AI solutions, they can combine the data related to the content creation andcontent consumption in a unique and
powerful way.
News organizations need to use AI to augment you and me
And they need to augment journalists and the newsroom
What does this mean
Augment the user-citizen
Personalization has been around for a while, but has it ever been designed and developed in the
terms of news media itself The goal for news media is to combine greatcontent and personalized user experience to build a seamless and
meaningful news experience that is in line with journalistic principles and values.
For news, the upcoming real-time machine learning
methods, such as online learning, offer new possibilities to understand the user preferences in their real-lifecontext
These technologies provide new tools to break news and tell stories directly on your lock screen.
An intelligent notification system sending
personalized news notifications could be used to optimize content and content distribution on the fly by understanding theimpact of news
content in real time on the lock screens of people mobile devices
The system could personalize the way the content is presented, whether serving voice,video, photos, augmented reality material or
visualizations, based on users& preferences and context.
Significantly, machine learning can be utilized to create new forms of interaction
between people, journalists and the newsroom
Automatically moderated commenting is justone example already in use today
Think if it would be possible to build interactions directly on the lock screen that let the journalists better understand the way content
isconsumed, simultaneously capturing in real time the emotions conveyed by the story.
By opening up the algorithms and data usage through
data visualizations and in-depth articles, the news media could create a new, truly human-centered form ofpersonalization that lets the user
know how personalization is done and how it used to affect the news experience.
And let stop blaming algorithms when it comes to filter
Algorithms can be used to diversify your news experience
By understanding what you see, it alsopossible to understand what you haven&t seen before.By turning some of the personalization logic
upside down, news organizations could create a machine learning-powered recommendation engine that amplifies diversity.
Augment the
journalist
In the domain of abstracting and contextualizing new information and unpredictable (news) events, human intelligence is still
invincible.
The deep content understanding of journalists can be used to teach an AI-powered news assistant system that would become better
over time by learning directly from thejournalists using it, simultaneously taking into account the data that flows from the content
consumption.
A smart news assistant could point out what kinds of content are connected implicitly and explicitly, for example based on
their topic, tone of voice or other meta-data such as author or location.Such an intelligent news assistant could help the journalist
understand their content even better by showing which previous content isrelated to the now-trending topic or breaking news.The stories
could be anchored into a meaningful context faster and more accurately.
Innovation and digitalization doesn&t change the culture of
news media if it not brought into the very core of the news business.
AI solutions could be used to help journalists gather and
understand data and information faster and more thoroughly
An intelligent news assistant can remind thejournalist if there something important that should be covered next week or coming holiday
season, for example by recognizing trends in social media or search queries orhighlighting patterns in historic coverage
Simultaneously,AI solutions will become increasingly essential for fact-checking and in detecting content manipulation, e.g.recognizing
faked images and videos.
An automated content production system can create and annotate content automatically or semi-automatically, for
example by creating draft versions based on anaudio interview, that are then finished by human journalists.Such a system could be developed
further to create news compilations from different content pieces andformats (text, audio, video, image, visualization, AR experiences and
external annotations) or to create hyper-personalized atomized news content such as personalized notifications.
Thenews assistant also could
recommend which article should be published next using an editorial push notification, simultaneously suggesting the best time for sending
thepush notification to the end users
And as a reminder, even though Google Duplex is quite a feat, natural language processing (NLP) is far from solved.Human and machine
intelligence can be broughttogether in the very core of the content production and language understanding process
Augmenting the linguistic superpowers of journalists with AI solutionswould empower NLP research and development in new ways.
Augment the
newsroom
Innovation and digitalization doesn&t change the culture of news media if it not brought into the very core of the news business
concretely in the daily practices of thenewsroom and business development, such as audience understanding.
One could start thinking of the
news organization as a system and platform that provides different personalized mini-products to different people and segments of
people.Newsrooms could get deeper into relevant niche topics by utilizing automated or semi-automated content production
And the more topics covered and the deeper thereporting, the better the newsroom can produce personalized mini-products, such as
personalized notifications or content compilations, to different people and segments.
In a world where it increasingly hard to distinguish a
real thing from fake, building trust through self-reflection and transparency becomes more important than ever.AI solutions can be used to
create tools and practices that enable the news organization and newsroom to understand its own activities and their effects moreprecisely
than ever.At the same time, the same tools can be used to build trust by opening the newsroom and its activities to a wider
audience.
Concretely, AI solutions could detect and analyze possible hidden biases in the reporting and storytelling.For example, are some
groups of people over-presentedin certain topics or materials What has been the tone of voice or the angle related to challenging
multi-faceted topics or widely covered news Are most of the photosdepicting people with a certain ethnic background Are there important
topics or voices that are not presented in the reporting at all AI solutions also can be used to analyzeand understand what kind of content
works now and what has worked before, thus giving context-specific insights to create better content in the future.
AI solutions would help
reflect the reporting and storytelling and their effects more thoroughly, also giving new tools for decision-making, e.g
to determine whatshould be covered and why.
Also, such data and information could be visualized to make the impact of reporting and content
creation more tangible and accessible for the whole newsroom.Thus, theentire editorial and journalistic decision-making process can become
more open and transparent, affecting the principles of news organizations from the daily routines to thewider strategical thinking and
management.
Tomorrow news organizations will be part human and part machine
This transformation, augmenting human intelligence with machines, will be crucial for the future of newsmedia.To maintain their integrity
and trustworthiness, news organizations themselves need to able to define how their AI solutions are built and used
And the onlyway to fully realize this is for the news organizations to start building their own AI solutions.The sooner, the better — for
