A Reliable Technology: AI for News Media - Coffee with CIS - Latest News & Articles

A Reliable Technology: AI for News Media

To put it somewhat, news media was on the sidelines in AI development.

As a consequence, in the era of AI-powered customized vents, the information organizations do not anymore get to define what's real news, or, even more importantly, what is truthful or trustworthy. Nowadays, social networking programs, search engines, and content aggregators control user flows to the media articles and affects directly what kind of news material is made. Consequently, the near future of news media is not anymore in its hands. Case closed?

The (End) Valley of News Digitization

There's a history: News media hasn't been quick or innovative enough to turn into a change manufacturer in the electronic world. Historically, news used to be the signal that directed and attracted people (and advertisers) in its own right. The world wide web and the exponential explosion of available information on the web changed for good.

In the first internet, the portals steered visitors to the material in which they were interested. Recall Yahoo? Since the amount of data improved, the search engine(s) took over, altering the way individuals found pertinent info and information content online. As the mobile technologies and interfaces began to get more notable, social websites with News Feed and tweets took over, altering again the way that people found media articles, now emphasizing the function of our social networks.

Significantly, the news media didn't play an active role in at least one of these key developments. Quite the opposite, it had been late in utilizing the rise of the internet, search engines, content aggregators, mobile experience, social media and other new digital options to its benefit.

The advertising business followed suit. First news organizations let Google handle searches on their websites and the upcoming search champion got a special chance to index media content. With the rise of social media, news companies, especially in the U.S., switched to Facebook and Twitter to split the news rather than focusing on their very own breaking news attributes. As a consequence, news media dropped its core business into the rising giants of their new electronic market.

To put it very strongly, news media hasn't ever been completely digital in its approach to the consumer experience, business logic or material generation. Think paywalls and e-newspapers for your iPad! The internet and digitalization pushed the information media to shift, but the change was still reactive, not proactive. The older, partly obsolete, paradigms of content creation, audience understanding, user experience and content supply nevertheless actively affect the way news content is created and distributed today (and to be 110 percent obvious -- this isn't about the storytelling and the incredible imagination and hard work accomplished by ingenious journalists all around the globe).

Because of these improvements, the current algorithmic gatekeepers such as Google and Facebook dominate the data flows and the ad business previously dominated by the news media. Significantly, the ad-driven business logic of the online behemoths isn't designed to allow the news media to thrive on its own provisions again.

From Witnesses To Creators

News websites have been reporting on the rise of the new algorithmic world order within an outside observer. Along with the reporting was thorough, veracious and educational -- that the tales told from the news websites have experienced a concrete effect on how people perceive our constantly evolving electronic realities.

However, because the data flows have moved into the black boxes commanded by the internet giants, it is now evident that it's very hard or close to impossible for an external observer to comprehend the dynamics which influence how or why a specific piece of information gets newsworthy and widely spread. In spite of the mainstream news websites, Trump's rise to the presidency came as a"surprise," and that is but one example of the new dynamics of today's digital reality.

And here's a paradox. Since the information moves closer to us to the cellular lock display and other surfaces that are accessible and available for all of our time, its origins and desktop reasons become more pessimistic than ever before.

The present course won't be changed by commenting on or criticizing the activities of the judgment systems that are algorithmic.

The societal media along with self-realizing remarks loops utilizing the latest machine learning methods, concurrently being exposed to malicious or unintended gaming, has led us to the planet of"alternative facts" and fake news. In this era of automated troll-hordes and algorithmic manipulation, the significance of news media seem vitally important and relevant: Distribution of honest and relevant advice; nurturing the liberty of speech; giving the voice to the unheard; widening and enriching people's worldview; encouraging democracy.

However, the driving worth of news media won't ever be fully realized in the algorithmic reality if the press itself is not actively growing solutions that form the algorithmic truth.

The current course will not be changed by commenting on or criticizing the activities of the ruling systems that are algorithmic. #ChangeFacebook is not on the table for news media. New AI-powered Google News is regulated and made by Google, dependent on its company culture and values, and thus can not be directly influenced by the news organizations.

Following the rise of the web and now's algorithmic principle, we're again on the brink of a significant paradigm change. Machine learning-powered AI solutions will have an increasingly significant impact on our physical and digital realities. This is again a time to impact the energy balance, to influence the direction of electronic development and to change the way we think when we consider information -- a time for information media to transform from an external observer to a change maker.

Artificial Intelligence (AI) Solutions for News Media

In case the news media wants to influence the way that news content is created, developed, presented and delivered to people in the long run, they need to have an active role in AI development. If news organizations wish to understand the way data and information are constantly affected and manipulated in digital environments, they should start embracing the chances of machine learning.

However, how can news media compete with the current AI leaders?

News organizations have something that Google, Facebook, and other big internet players do not have: information organizations own the content production process and so possess a deep and comprehensive articles comprehension. By focusing on proper AI alternatives, they could combine the information linked to the content creation and content ingestion in a special and effective way.

News organizations need to use AI to fortify me and you. Plus they have to augment journalists and the newsroom. What exactly does this mean?

Expand the Users

Personalization has existed for a while, but has it ever been developed and designed at the terms of news media? The goal for news websites is to combine excellent content and personalized user experience to construct a seamless and purposeful news experience that's in accord with journalistic principles and values.

For news, the coming real-time machine learning approaches, like online learning, provide new possibilities to comprehend the consumer's tastes in their real-life circumstance. These technologies provide new tools to crack information and tell stories directly on your lock display.

A smart notification system sending customized information alerts can be used to maximize content and articles distribution on the fly by understanding the impact of news content in real time around the lock displays of most people's mobile devices. The system could personalize the way the content is presented, whether functioning video, voice, photographs, augmented reality material or visualizations, according to customers' preferences and context.

Significantly, machine learning can be utilized to produce new types of interaction between individuals, journalists and the newsroom. Automatically moderated commenting is just 1 example in use now. Think if it'd be possible to construct interactions right on the lock screen that let the journalists better understand the manner content is consumed, simultaneously capturing in real time that the feelings conveyed by the story.

By opening up the algorithms and data utilization through data visualizations and in-depth content, the news media can create a new, genuinely human-centered form of personalization which allows the consumer understand how personalization is done and how it's utilized to impact the news experience.

And let's stop attributing algorithms when it comes to filtering bubbles. Algorithms may be used to diversify your news experience. By knowing what you find, additionally, it is possible to understand exactly what you have not seen before. By turning a number of the personalization logic upside down, news organizations could create a system learning-powered recommendation engine that simplifies diversity.

Expand The Journalist

From the realm of abstracting and contextualizing new info and erratic (news) occasions, human intelligence is still invincible.

The profound content comprehension of journalists can be used to teach an AI-powered news helper system which will become better through the years by studying right from the journalists using it, concurrently taking into consideration the data that flows from the content intake.

A smart news helper could point out what sorts of content are connected implicitly and explicitly, such as based on their topic, the tone of voice or other meta-data like writer or place. This kind of intelligent news assistant could help the journalist know their articles even better by showing that previous content is linked to the now-trending topic or breaking news. The stories could be anchored into a meaningful context quicker and more accurately.

Innovation and digitalization don't alter the culture of information media if it isn't brought into the core of the news business.

AI solutions could be utilized to help journalists collect and understand data and data faster and more extensively. A smart news assistant can remind the journalist if there's something important that should be covered next week or coming holiday season, for example by recognizing tendencies in social networking or search questions or highlighting patterns in historic coverage. Simultaneously, AI solutions will become more and more vital to get fact-checking and in detecting content manipulation, and e.g. recognize falsified videos and images.

An automated content manufacturing system can produce and annotate content automatically or semi-automatically, such as by making draft versions based on a sound interview, that are then completed by human journalists. Such a system may be developed further to make news compilations from various content bits and formats (text, audio, video, image, visualization, AR encounters an external annotations) or to make hyper-personalized atomized news articles such as personalized notifications.

The information helper could also recommend which article ought to be published next using an editorial push telling, simultaneously indicating the best time for sending the drive notification to the users. And as a reminder, even though Google's Duplex is quite a feat, natural language processing (NLP) is far from resolved. Machine and human intelligence can be brought together in the very core of their content production and language understanding procedure. Augmenting the superpowers of journalists with AI solutions would empower NLP development and research in new ways.

Expand the Newsroom

Innovation and digitalization don't alter the culture of news media if it's not introduced into the core of the information industry concretely from the everyday practices of their newsroom and business development, such as viewers comprehension.

One could begin thinking of this news organization as a system and platform that offers distinct personalized mini-products to different people and sections of individuals. Newsrooms can get deeper into relevant niche topics by utilizing automated or semi-automated articles production. And the more topics covered along with the deeper the reporting, the better the newsroom can create personalized mini-products, such as personalized notifications or content compilations, to different people and sections.

In a world in which it's increasingly hard to distinguish a real thing from bogus, building confidence through self-reflection and transparency grows more important than ever. AI solutions may be employed to make tools and practices that enable the news business and newsroom to understand its activities and their impacts more precisely than ever before. At the same time, the exact tools can be employed to build trust by launching the newsroom and its activities to a broader audience.

Concretely, AI solutions can detect and analyze potential hidden biases from the coverage and storytelling. As an example, are some groups of individuals over-presented in some specific topics or materials? What's been the tone of voice or the angle related to hard multi-faceted themes or widely covered news? Are most of those photos depicting people having a certain ethnic background? Are there any significant issues or voices that are not presented from the reporting whatsoever? AI solutions can also be employed to examine and understand what kind of content works now and what's worked before, thus giving context-specific insights to produce better content in the future.

AI solutions might help reflect the reporting and storytelling and their effects more thoroughly, additionally giving new tools for decision-making, e.g. to determine what should be covered as well as why.

Also, such data and information may be visualized to create the impact of reporting and content production more concrete and available for the whole newsroom. Thus, the entire editorial and journalistic decision-making process can be open and transparent, impacting the fundamentals of news organizations from the daily routines to the broader strategical thinking and management.

Tomorrow's news organizations are going to be a part human and part machine. The transformation, boosting human intelligence using machines, will be critical to the future of information websites. To maintain their integrity and trustworthiness, news organizations themselves want to able to specify how their AI solutions are built and used. And the only way to fully realize that is really for those organizations to start building their own AI options. The sooner the better for us all.

Β