Artificial Intelligence – (2016/17)

The research project focused on digital ecosystems as innovation cultures that pursued enhancements in user interface design combined with AI (i.e., machine learning) as a means to enhance consumer engagement as form of monetization. The researchers explored digital distribution and mergers/acquisitions across old and new media, new forms of ecommerce and their integration into existing digital platforms, new forms of content curation — human vs. algorithmic, and new forms of live video, including community-based liveness (e.g., Twitch) vs. social forms of liveness (e.g., Facebook). The research drew on examples from a variety of media and technology companies, including Loot Crate, Instagram, Time Warner/AT&T, and Twitch.

Innovative Infrastructures – AI and the New Rules of Media Content and Distribution by James Fleury

Digital-native companies from Silicon Valley continue to update the rules of the media industry. One of the major areas of ongoing disruption is content distribution, which affects multiple strands of the media sector, from film studios to television networks to telcos. In spite of a $7B+ record-breaking year at the 2016 box office, theatrical attendance has remained on a downtrend as consumer attention continues to disperse across mobile screens. The home, long the purview of cable providers and telcos, is currently governed by new digital technologies, supplied by GAFA (Google, Apple, Facebook, Amazon). Tech giants from Silicon Valley operate across the world through global distribution infrastructures (excluding China). YouTube, part of Google/Alphabet, is available in 89 countries, Netflix switched on the lights in over 130 countries at last year’s CES, and Amazon’s Prime video service announced its presence in 200 countries at the end of 2016. This ongoing expansion has put increasing pressure on domestic competitors in the media industry, which are focused on local pipelines with largely limited and time-based outlets in international territories. In this competitive environment, content is still king. Long-spanning franchises and compelling intellectual property continue to drive viewership across a growing field of platforms. To cement their presence in media, incumbents like Netflix and Amazon have thus increasingly scaled their investments in content and innovation, reaching $6B for 2017. Beyond content, the digital consumer experience has become an equally critical source of innovation. As content becomes ubiquitous, consumers increasingly look for seamless access and superior forms of presentation and interactivity. As the content surplus mounts, both sides increasingly channel their efforts into content navigation, which has become an integral part of the consumer experience. Streamlining access for consumers through advanced distribution mechanisms is one part of the equation. The other is fostering interactive touchpoints to maximize consumer attention and engagement with content. One of the key ways to accomplish this is through AI-based technologies. This paper analyzes these trends across the industry to develop a comprehensive overview of the media industry’s ongoing convergence with Silicon Valley.

Content Curation of Niche Subscription Services in the Age of the Platform by Heather Lea Birdsall and Monica Sandler

 This paper examines the growing niche marketplace for film, TV, and music streaming, along with the e-commerce retail market, focusing on outlets with monthly subscription services. In the film streaming arena, for example, October 2016 saw the launch of the new film lovers streaming app FilmStruck created by the Criterion Collection and Turner Classic Movies. However, established competitors like Mubi and Fandor have already sought to cover the cinephile market for several years. Can all of these platforms survive, and what are their strategies for doing so? Honing in on human curation as a central strategy, this paper studies these competing outlets and considers how they are trying to differentiate themselves by foregrounding human curation, as opposed to machine-learning based or “AI” algorithmic curation, which is often still at work behind the scenes, and visually expressed through UX/UI design. The paper looks at the use of content curation, as new platforms and players seek to enter, navigate, and dominate the digital economy. Expanding on this theme, the individual case studies more closely examine specific players in these spaces to more closely examine their unique approaches to curation and to further illuminate the role of and look to the future of curation in the platform landscape. The issue of platform competition, however, is not exclusive to niche platforms. Companies such as Apple, Facebook, Google, and Amazon are competing with each other over music and video streaming services. With such vast subscription systems in place, consolidation may be soon in the future, working similarly to a bundled cable subscription. One case study explores the business strategies of TV networks, many of which, like NBC and CBS, have sought to launch their own niche programming within subscription platforms. Bundled streaming services seem to be in the works within platforms like Hulu, Apple, and Google in order to compete with cable provider services like Sling TV that are already out on the market. This also extends further into the online retail community and retail subscription services, specifically subscription boxes, which showcase products that are sent to consumers on a recurring basis. In particular, niche subscription services for media- and fandom-related boxes have started to populate the market. Overall, this project explores how different digital industries are handling their competitive marketplaces by looking both at the industry and at the quality of the UX in terms of strategies of curation. The project further explores how human curation is used as a reaction against AI curation, combatting both its perceived and real shortcomings as a consumer-facing method of content presentation. However, it also looks to the complex ways in which these companies use human curation in tandem with AI curation. In the current digital landscape, while companies may tout human curation in their marketing media or UX design, it is difficult to find pure human curation without some aspect of AI backing it up. Human curation is sometimes just the skin over the AI.

The Development of Live Video Strategies by Daniel Zweifach and Michael Reinhart

Facebook, Snapchat, Google’s YouTube, Amazon, and Twitter have all introduced live video products and content partnerships. These developments highlight the turn towards live, real-time videos by social media networks. To this effect, Mark Zuckerberg has claimed the current moment as the “golden age for live video.” Zuckerberg’s pronouncement follows market data that suggests live video content increases user engagement with consumers watching longer and commenting more often, thereby making audiences potentially more valuable for marketers and advertising. Even as early as July 2015, companies such as Facebook have categorized video and live video separately as huge growth areas for their business revenue. Recent product updates have sought to accelerate these gains and improve monetization of live video and emphasize the overall strategy of social media companies to drive and maintain user engagement through the uses of artificial intelligence (AI) and machine-learning technology. The consequence of such strategies has been to emphasize the experience of “liveness” on social media platforms for consumers in order to limit user migration to other platforms. At present, there are two large problems that social media companies are looking to solve: content and its curation. Social networks have valued live content for its ability to facilitate (virtual) social interactions. This desire for content has found social networks seeking and forging new relationships with traditional television studios and companies. However, these technology companies do not aim to merely replicate live television. Their goal, indeed, is partly to produce a new experience in which traditional media is conjoined to the interactivity of the social network. As such, these platforms view live video as a segue into the augmented and virtual reality space. To this end, social media platforms have been using AI and their existing databases of users and creators to enhance the interactive experience of their networks and make it easier to monetize, which brings us directly to issue of curation as a connected problem to content within the development of live video. Improvements in machine learning will allow platforms like Facebook to automatically “index” live video — i.e., help them understand and sort what the content is — and promote certain videos to potentially interested users while flagging objectionable images. Expanding AI capabilities offers social media companies the ability to expand the reach of live video and address its current shortcomings and financial risks for the companies involved. This paper examines the overarching strategy and goals behind social networks’ live video offerings, specifically as they confront these problems of content and its curation to facilitate user engagement. It considers how brands and content fit into this equation and how the move towards live video offers potential points of contact for the development of social media as virtual reality interfaces.

The Expanding World of Social Media and Commerce by Lauren Boumaroun and Katherine Marpe

In the past decade, brands and retailers have learned the importance of an online presence, whether that is cultivating social media engagement, adopting influencer marketing strategies, or integrating ecommerce into their business models. However, in recent years, artificial intelligence, specifically machine learning, has made its way into the sales and marketing tactics of these brands as well. The growing use of artificial intelligence in social media marketing and e-commerce is a symptom of an evolving on-demand economy: the online marketplace created by recent developments in technology that provides consumers with immediate and efficient fulfillment of goods and service. The rapidly developing on-demand economy has given consumers a taste of a new type of buying experience, one that relies on flexibility, personalization, and responsiveness. The integration of artificial intelligence technology into the on-demand economy allows businesses to customize their approach to consumers by analyzing and predicting customer behavior and personalizing the shopping experience. Other examples include the integration of chatbots to guide customers through both the online and in-person shopping experiences, and visual search, offering shoppers similar products to an image they like or upload. This integration of AI strategies to enhance the buying experience grows out of the already established techniques of social media marketing used to manufacture authenticity and cultivate a personalized experience, building relationships and loyalty between brands and consumers. Although these changes are met with some skepticism, using machine learning to enhance the buying experience is a rapidly developing trend that adds to the larger ecosystem of the online retail experience. This study investigates this relationship between social media, branding, and ecommerce, exploring how brands are using artificial intelligence to turn social media users into direct consumers. Toward this, the paper focuses on two case studies, which investigate how brands integrate commerce into their own social media content and how brands have increased their involvement with social media influencers — both celebrity influencers as well as micro-influencers. The important takeaway from the case studies is that authenticity and personalization are key for both individuals and companies; the goal of social media marketing is to form real, personal connections with followers that inspires genuine and personalized engagement in the form of liking, commenting, and sharing. With advancements in machine learning, this authentic engagement is able to become more targeted and personalized to match brands to loyal consumers.


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