Jarno M.

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 A new hope: AI for news media AI on your lock screen New machine learning technologies, user interfaces and automated content creation techniques are going to expand the personalization of storytelling beyond algorithmically generated news feeds and content recommendation. The next wave will be software-generated narratives that are tailored to the tastes and sentiments of a consumer. Concretely, it means that your digital footprint, personal preferences and context unlockalternative features in the content itself, be it a news article, live video or a hit series on yourstreaming service. The title contains different experiences for different people. Netflix is experimenting with different episode orders for ‘Love, Death Robots& From smart recommendations to smarter content When you use Youtube, Facebook, Google, Amazon, Twitter, Netflix or Spotify, algorithms selectwhat gets recommended to you.

The current mainstream services and their user interfaces andrecommendation engines have been optimized to serve you content you might be interested in. Your data, other people data, content-related data and machine learning methods are used to match people and content, thus improving the relevance of content recommendations and efficiency of content distribution. However, so far the content experience itself has mostly been similar to everyone.

If the samenews article, live video or TV series episode gets recommended to you and me, we both readand watch the same thing, experiencing the same content. That about to change.

Soon we&ll be seeing new forms of smart content, in which user interface, machine learning technologies and content itself are combined in a seamless manner to create a personalized content experience. What is smart content Smart content means that content experience itself is affected by who is seeing, watching,reading or listening to content.

The content itself changes based on who you are. We are already seeing the first forerunners in this space.

TikTok whole content experience is driven by very short videos, audiovisual content sequences if you will, ordered and woven together by algorithms.

Every user sees a different, personalized, &whole& based on her viewing history and user profile. At the same time, Netflix has recently started testing new forms of interactive content (TV series episodes, e.g.

Black Mirror: Bandersnatch) in which user own choices affect directly the content experience, including dialogue and storyline.

And more is on its way.

With Love, Death Robots series, Netflix is experimenting with episode order within a series, serving the episodes in different order for different users. Netflix is pursuing more interactive content, including, maybe, a rom-com Some earlier predecessors of interactive audio-visual content include sports event streaming, in which the user can decide which particular stream she follows and how she interacts with the live content, for example rewinding the stream and spotting the key moments based on her own interest. Simultaneously, we&re seeing how machine learning technologies can be used to create photo-like images of imaginary people, creatures and places.

Current systems can recreate and alter entire videos, for example by changing the style, scenery, lighting, environment or central character face.

Additionally, AI solutions are able togenerate music in different genres. Now, imagine, that TikTok individual short videos would be automatically personalized by the effects chosen by an AI system, and thus the whole video would be customized for you.

Or thatthe choices in the Netflix interactive content affecting the plot twists, dialogue and evensoundtrack, were made automatically by algorithms based on your profile. Personalized smart content is coming to news as well.

Automated systems, using today state-of-the-art NLP technologies, can generate long pieces of concise, comprehensible and even inventive textual content at scale.

At present, media houses use automated content creation systems, or &robot journalists&, to create news material varying from complete articles to audio-visual clips and visualizations.

Through content atomization (breaking content into smallmodular chunks of information) and machine learning, content production can be increasedmassively to support smart content creation. Say that a news article you read or listen to is about a specific political topic that is unfamiliar toyou.

When comparing the same article with your friend, your version of the story might usedifferent concepts and offer a different angle than your friend who really deep into politics.

Abeginner smart content news experience would differ from the experience of a topicenthusiast. Content itself will become a software-like fluid and personalized experience, where your digitalfootprint and preferences affect not just how the content is recommended and served to you,but what the content actually contains. Automated storytelling How is it possible to create smart content that contains different experiences for differentpeople Content needs to be thought and treated as an iterative and configurable process rather than aready-made static whole that is finished when it has been published in the distribution pipeline. Importantly, the core building blocks of the content experience change: smart content consistsof atomized modular elements that can be modified, updated, remixed, replaced, omitted andactivated based on varying rules.

In addition, content modules that have been made in the past,can be reused if applicable.

Content is designed and developed more like a software. Currently a significant amount of human effort and computing resources are used to preparecontent for machine-powered content distribution and recommendation systems, varying fromsmart news apps to on-demand streaming services.

With smart content, the content creationand its preparation for publication and distribution channels wouldn&t be separate processes.Instead, metadata and other invisible features that describe and define the content are anintegral part of the content creation process from the very beginning. Turning Donald Glover into Jay Gatsby With smart content, the narrative or image itself becomes an integral part of an iterative feedback loop, in which the user actions, emotions and other signals as well as the visible and invisible features of the content itself affect the whole content consumption cycle from the content creation and recommendation to the content experience.

With smart content features, a news article or a movie activates different elements of the content for different people. It very likely that smart content for entertainment purposes will have different features andfunctions than news media content.

Moreover, people expect frictionless and effortless contentexperience and thus smart content experience differs from games.

Smart content doesn&tnecessarily require direct actions from the user.

If the person wants, the content personalizationhappens proactively and automatically, without explicit user interaction. Creating smart content requires both human curation and machine intelligence.

Humans focuson things that require creativity and deep analysis while AI systems generate, assemble anditerate the content that becomes dynamic and adaptive just like software. Sustainable smart content Smart content has different configurations and representations for different users, userinterfaces, devices, languages and environments.

The same piece of content contains elementsthat can be accessed through voice user interface or presented in augmented realityapplications.

Or the whole content expands into a fully immersive virtual reality experience. In the same way as with the personalized user interfaces and smart devices, smart content canbe used for good and bad.

It can be used to enlighten and empower, as well as to trick andmislead.

Thus it critical, that human-centered approach and sustainable values are built in thevery core of smart content creation.

Personalization needs to be transparent and the user needsto be able to choose if she wants the content to be personalized or not.

And of course, not allcontent will be smart in the same way, if at all. If used in a sustainable manner, smart content can break filter bubbles and echo chambers as itcan be used to make a wide variety of information more accessible for diverse audiences.Through personalization, challenging topics can be presented to people according to theirabilities and preferences, regardless of their background or level of education.

For example abeginner version of vaccination content or digital media literacy article uses gamificationelements, and the more experienced user gets directly a thorough fact-packed account of therecent developments and research results. Smart content is also aligned with the efforts against today information operations such asfake news and its different forms such as &deep fakes&(https://www.niemanlab.org/2018/11/how-the-wall-street-journal-is-preparing-its-journalists-to-detect-deepfakes).

If the content is like software, a legit software runs on your devices andinterfaces without a problem.

On the other hand, even the machine-generated realistic-lookingbut suspicious content, like deep fake, can be detected and filtered out based on its signatureand other machine readable qualities.

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Smart content is the ultimate combination of user experience design, AI technologies andstorytelling. News media should be among the first to start experimenting with smart content.

When the intelligentcontent starts eating the world, one should be creating ones own intelligent content. The first players that master the smart content, will be among tomorrow reigning digital giants.And that one of the main reasons why today tech titans are going seriously into the contentgame.

Smart content is coming.