Artificial Intelligence in Cultural Production

Critical Perspectives on Digital Platforms

Dal Yong Jin

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000385717
• Edition: 1
• Topic: Languages & Linguistics
• Subtopic: Communication Studies
• Index: Languages & Linguistics

This book offers an in-depth academic discourse on the convergence of AI, digital platforms, and popular culture, in order to understand the ways in which the platform and cultural industries have reshaped and developed AI-driven algorithmic cultural production and consumption.

At a time of fundamental change for the media and cultural industries, driven by the emergence of big data, algorithms, and AI, the book examines how media ecology and popular culture are evolving to serve the needs of both media and cultural industries and consumers. The analysis documents global governments' rapid development of AI-relevant policies and identifies key policy issues; examines the ways in which cultural industries firms utilize AI and algorithms to advance the new forms of cultural production and distribution; investigates change in cultural consumption by analyzing the ways in which AI, algorithms, and digital platforms reshape people's consumption habits; and examines whether governments and corporations have advanced reliable public and corporate policies and ethical codes to secure socio-economic equality.

Offering a unique perspective on this timely and vital issue, this book will be of interest to scholars and students in media studies, communication studies, anthropology, globalization studies, sociology, cultural studies, Asian studies, and science and technology studies (STS).

1
Artificial intelligence in popular culture

Introduction

David (22) who lives in Vancouver, Canada, always checks cultural content on digital platforms, in particular his Apple iPhone. After watching a movie trailer of Morgan— created through artificial intelligence—a 2016 American sci-fi horror film on YouTube in March 2020, he immediately enjoyed the movie on Netflix. Right after, he also watched Kingdom—a Korean television series produced in 2019—on Netflix, partially due to social distancing regulation in the COVID-19 era.

Three major components that directly influence David’s cultural activities at this particular juncture are artificial intelligence (AI); digital platforms, including Netflix and smartphone; and popular culture. The interaction among these three seemingly not connected areas has been greatly increasing, a relatively new development, as AI has recently jumped into the realm of media and popular culture. Although AI is the latest comer in the cultural sphere, it has suddenly become one of the major forces transforming people’s cultural consumption habits, as well as the production of popular culture.

AI has been with us for many years, and the huge wave of AI breaks across several areas, such as robots, self-driving cars, Google Maps, Amazon, healthcare, and online education. In early 2020 when COVID-19, referring to an infectious disease starting in late fall or early winter 2019, was rampant globally, for example, the Canadian federal government signed a contract with BlueDot, a Toronto-based digital health firm to track the spread of the virus, the latest tool in the AI toolbox being deployed against the public health crisis. The federal government announced a CDN$1 billion COVID-19 response fund on March 11, 2020, with $275 million dedicated to research. A little less than $52 million has already been doled out to the 96 researchers and research teams across the country, and three of those projects are using AI (Chamandy, 2020).

Several information technology (IT) firms and universities have also developed not only online education tools but also advanced technological systems that subtract students’ participation and concentration on online education via AI technologies (Choi, J.H., 2020). Due to the rapid spread of the disease, universities in many countries, including the U.S., the U.K., Canada, and Korea, canceled in-class education and introduced online class systems. As the COVID-19 situation continues, and the new normal in the post-coronavirus era is evident, many universities and tech companies have continued to develop various forms of online education tools, mainly supported by AI. In other words, the rush to adopt new digital technologies during COVID-19-driven remote learning led educators at all levels, from elementary school to university, to use more tools powered by advanced AI (Rauf, 2020). As of late January 2021, many universities around the world still practice remote learning, which was started in March 2020, and therefore, AI-supported educational mechanisms have continued to deeply embed in people’s daily lives in the near future.

Meanwhile, AI is saturating in the realm of popular culture, in which humans have been traditionally primary actors. Many AIs now “act invisibly in the background of activities conducted on smartphones and computers; in search engine results, social media feeds, video games and targeted advertisements” (Dyer-Witheford et al., 2019, 2). As Elliott (2019, xx) points out, “The digital universe has a direct connection with AI.” Furthermore, today’s changes in the field of popular culture are far more encompassing in scope than AI alone as digital platforms; both social media platforms like YouTube and over-the-top (OTT) service platforms like Netflix also play a major role in the transformation process in conjunction with popular culture. Consequently, people around the globe live in a new cultural world of technological innovation that AI and digital platforms create and develop.

Since the mid-2010s, AI has been applied to quite diverse applications, including predictive text assistance in smartphones, the identification of objects and faces for photos, the interpretation of video material linked to self-driving cars, the evaluation of performances recorded as data, and many more—“a list which shows that the technology of machine learning is being used in multiple sectors and for a broad range of activities, some sensitive and others more playful” (Bunz, 2019, 264). The swelling use of AI in media and culture in tandem with digital platforms, however, came unplanned with a few exceptions, right after Korea hosted a Go match telecast live where Google DeepMind’s AlphaGo defeated Lee Sedol, one of the best Go players in the world, in 2016 (Figure 1.1).¹ The AlphaGo AI program triumphed in its final game against Lee to win the series 4–1, providing a landmark achievement for an AI program (Borowiec, 2016; Choi, W.W., 2016).

Figure 1.1 Go Match between AlphaGo and Lee Sedol in 2016 (SBS, 2016)

As evidenced in the Go match between AlphaGo and Lee Sedol, AI can easily beat humans in Go and chess. Watching AlphaGo’s victory over Lee put people, not only in Korea but also around the globe, into shock, as many global GO fans watched those five matches.² Everyone was suddenly talking about AI, and many global cultural and platform firms started to invest in this particular new technology. All this is in anticipation of the “Fourth Industrial Revolution,” which “proponents say differs from the third digital revolution in its emphasis on AI technology.³ Some speculate this could affect the digital economy as much as its shipping, automobile and electronics industries” (Volodzko, 2017). AI has seemed to become a core technology in the media and cultural industries in the age of the Fourth Industrial Revolution (Kim, K.H. et al., 2018).

Starting in the late 2010s when they saw the AlphaGo phenomenon, the global cultural industries, as in other industries, have rapidly transformed their industrial structures and the ways in which they produce cultural content. In both advanced economies, including the U.S., the U.K., Canada, and Japan, known as the Global North, and a few developing countries like China and Korea, namely, the Global South, AI, algorithms, and big data are reshaping all media-related industries, from platform to cultural sectors, as new digital technologies, including AI and digital platforms, are expected to provide opportunities for many ICT (information and communication technology) firms to create jobs and engender prosperity (McKelvey and Mac-Donald, 2019). These countries have already achieved substantial growth in their ICTs—internet and smartphones—and cultural industries. Mega media and cultural giants in these countries now focus on AI to further develop and produce new forms of popular culture, and therefore, the digital economy.

AI is becoming a ubiquitous part of our cultural lives, and the adoption of AI is indeed noticeable in media and cultural sectors like music, film, game, and webtoon, as well as journalism. As Caramiaux et al. (2019, 6) point out, “Creatives have always been in demand of new tools that they can use to enrich the way they work, making them early adopters of technological innovations. AI is not an exception.” AI seems to be suited to the particular requirements of the contemporary cultural industries that are shifting principal paradigms. In particular, AI is deeply associated with digital platforms, such as Google, Facebook, YouTube, Netflix, and smartphone technologies.

The paradigm shift in the realm of media and culture in tandem with AI has been controversial. Some admit that AI is a big part of the cultural sector, while others claim that it is only lip service. What is interesting, though, is that there has been a clear trend toward the adoption and actualization of AI in media and cultural production. As Gunkel (2012, 20) argues, in communication studies,

the operative paradigm—the framework that has defined what is considered normal science—situates technology as a tool or instrument of message exchange between human users. This particular understanding has been supported and codified by the dominant forms of communication theory…. Because this conceptualization has been accepted as normative, the computer and other forms of information technology have been accommodated to fit the dominant paradigm.

What he emphasized is that the computer has not effectively challenged longstanding assumptions about the role and function of technology in communication. For him, “The computer is not necessarily a new technology to be accommodated to the theories and practices of communication studies,” but the current situation has fundamentally changed (Gunkel, 2012, 20).

Now, it is certain that the computer and AI have actualized a paradigm shift in digital media and popular culture. The emphasis has switched to machine learning (ML), meaning a subset of AI, in communication and/or cultural studies. “With huge datasets available and cheaper hardware, machine learning has been gaining ground over conventional search and discovery applications. The future lies in machine learning and it is maturing at a faster pace and finding diverse applications” (Frankel, 2018, 10). As Benchmann (2019, 82) points out, data in ML processing becomes an issue not only in terms of the quality of data input itself but also its suitability for training the algorithms to recognize patterns and clusters. The more data and the more diversified training data people have, the better people’s algorithm potentially is at recognizing new data. Here the algorithm can only interpret data and predict patterns from the data that it has already seen from training data.

Many governments around the world have embraced the AI phenomenon. They firmly believe that AI can reshape the industry structure and is able to bring new energies to the digital economy. Governments have developed new supporting measures, both legal and financial, so that governments and corporations can work closely together to enhance the AI-driven digital economy. Governments, digital platform firms, and cultural corporations like broadcasting companies and music firms discuss a whole host of agendas surrounding the remarkable emergence of AI in general, as our contemporary society is “becoming increasingly visible and bullish on its own investments in AI” (Walch, 2019). The media landscape has been transformed so deeply that it is now unrecognizable. For many governments and corporations, how to utilize new digital technologies, in particular AI, for the growth of popular culture, and in general cultural production, becomes a key issue.

Cultural production can be explained from various perspectives, and it means “the making, circulation and reception of cultural forms and to cultural practices and processes in situ”; therefore, cultural production, sometimes, implies “processes whose outcomes or products are specialized and well defined” (Henderson, 2013, 3).⁴ In cultural production studies, it has also “addressed industrial contexts and professional routines to understand why films, television programs, and popular music genres are what they are” (3). However, in this book, cultural production refers to “the social processes involved in the generation and circulation of cultural forms, practices, values, and shared understandings” as well as “the work of the culture industry” (Oxford Reference, 2019). Cultural production is also “used as a shorthand term to refer to industrialized or semi-industrialized symbol making and circulation in modern societies” (Hesmondhalgh and Saha, 2013, 181). In other words, cultural production does not narrowly define the actual production of cultural content, but the overall process, including production, distribution, exhibition, and consumption of media content and popular culture and, recently, embedded in AI use.

Due to the significant role of digital platforms and their users who also participate in the process of cultural production and circulation, this book broadly includes the digital platform industry as well as the cultural industries as major parts of cultural production.

Digital platforms and cultural industries have transformed the production and distribution of cultural content, while people shift their consumption habits with the help of AI and digital platforms, differentiating the cultural sphere from the traditional norms that traditional media, including terrestrial broadcasting, have created. In the early 21st century, people, in particular global youth, equipped with new digital technologies enjoy popular culture and news on digital platforms instead of physically going to theaters or buying and possessing cultural materials.

On the one hand, recent data certainly proves the increasing use of AI in the ICT and cultural sectors, which asks us to contemplate the convergence of AI and platform/culture in the production of culture. According to Statistics Canada (2020), several different industries have invested and used AI technology. Among these, the information and cultural industry was the second highest in terms of AI usage at 25.5%, only behind the finance and insurance industry (32.2%), while the average usage of AI was recorded at 10.1% in 2017 (Table 1.1). This data includes only large companies who have more than 250 employees. The ranks are still similar when we include small businesses, although the percentage of AI usage slightly decreases. This certainly implies that IT, including digital platform and mobile sectors, and culture have already deeply integrated with AI technology, and we can expect that new media and cultural sectors will continue to use AI at the highest level in our contemporary capitalist society.

Table 1.1 AI usage by industry in Canada in 2017 (unit %)

Source: Statistics Canada (2020). Table 27-10-0367-01 Use of advanced or emerging technologies by industry and enterprise size.

On the other hand, AI has greatly transformed people’s consumption patterns in media and popular culture, as people enjoy media and cultural content on digital platforms, including social media platforms and OTT platforms (e.g., Netflix), rather than on traditional media like television channels and at theaters. People watch movies and listen to music recommended by AI and algorithms on Netflix and Spotify. As Frankel (2018, 10) argues, as user interfaces have advanced to

help TV viewers more easily find content amid an ever-expanding field of choices, the data science used to achieve true personalization in many cases has moved beyond the scope of human capab...