The news industry and journalism in China and Malaysia: Artificial Intelligence and its challenges in new media

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By Nik Suryani Megat Deraman & Yan Cong

Artificial intelligence (AI), first a concept developed by Turing, the founder of computer science theory, is a way of thinking that relies primarily on computers and algorithmic programs to implement ideas similar to those of the human brain.

In recent years, as people’s needs have become more and more difficult to meet, human society has pushed technology forward and AI technology has advanced at a rapid pace and is being used in a wide range of fields and industries. Artificial intelligence has the characteristics to mimic and extend human intelligence, and in this way technology becomes an extension of human capabilities.

In the traditional news model, journalists need to complete a series of work such as interviewing, selecting topics, writing, editing, distributing and collecting user feedback, etc. When AI technology becomes one of the important subjects of news production, it will not only free traditional journalists from basic labour and devote more energy to the production of in-depth news, but also promote the intelligent transformation of the news production process and the multi-faceted integration of the news industry structure, whose applications mainly include robotic writing, algorithmic recommendations and synthetic AI anchors, etc.

Artificial intelligence breaks the boundary between man and machine and has certain communication advantages in ensuring the authenticity of news, improving the efficiency of news production, cleaning up the news environment and protecting users’ information, and has an interdisciplinary impact on the field of journalism and communication.

The development and application of AI technology in China 

In 2017, the term artificial intelligence officially appeared in the national government work report. After years of development, domestic artificial intelligence has been used in security, finance, customer service, retail, healthcare, advertising and marketing, education, urban transportation, manufacturing, agriculture and other fields to achieve commercialization and scale effect.

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Journalism and communication

From the perspective of the structure of the news industry, both big data collection and AI generation technologies will break down the barriers between the original media organisations and realise the business opportunities of multi-party integration of resources within the media and cross-industry cooperation. In media operations, AI has led to a two-way interaction between capital and technology, and academics have continued to explore the development of the media industry in the context of AI, for example, Chinese scholars Li Huajun and Wang Kaiyue have explored the AI Internet of Things technology, a study on the model of reconstructing the relationship between human-computer media and subject-object relationship, and on the basis of this study, a new path of media transformation and development is explored.

In corporate applications, news media companies such as Tencent, Baidu and Phoenix have independently developed writing robots for use in the sports and financial news fields. From the perspective of news production, AI technology extends the spatio-temporal dimension of news gathering and improves the timeliness of material collection. 2017 earthquake in Jiuzhaigou, Sichuan, the Central Earthquake Network robot collected more than 10 data items such as snapshot parameters, topography of the epicentre, thermal population, surrounding villages and towns, and surrounding counties in just 25 seconds, and the automatically compiled and distributed articles were rich in content. China’s self-developed DJI drone’s filming was able to penetrate deeper into the danger zone, intelligently choose the route, calculate the surrounding environment and other intelligent ways, not only accurately collecting a larger range and more perspectives of information materials in the first time, but also extending the reach range of news coverage. Intelligent writing speeds up the efficiency of news production and reduces the error rate of manual reporting.

In the news production process, intelligent robots are not only able to quickly extract key information from information materials, but also to use big data networks to intelligently capture corresponding images. “It is able to capture and analyse a large amount of data, and its generated articles are fluent and fluent in natural human language. On 4 May 2017, Cover News launched its self-developed “Xiaofeng Robot”, which recognises users’ needs based on intent. In the future, Cover News may become the most user-friendly port, and the goal of the Xiaofeng bot is to become the most human-computer interactive information assistant. In addition, the addition of AI technology has also enhanced the presentation of news reports through 3D, VR, AR and other technologies to enhance the sense of presence and interactivity. In the academic world, Chinese scholars have also attempted to study and analyse the integration of AI technology and news media from various aspects.

Based on the current application of news writing robots, Wang Yunting proposes that AI needs to cater to the human trend of media evolution and gives reasonable suggestions from both the government and journalism practitioners.

After AI technology entered the field of news production, the traditional linear production model was gradually transformed into an interactive production model. In 2016, Baidu’s “DouSecretary” robot commentary was launched to synchronise live commentary of the Olympic basketball games, creating a personalised viewing experience, and this peer-to-peer live interactive and exclusive service overturned the traditional production model. The news censorship model is also more accurate and optimised, allowing not only the identification of “keywords” but also the identification of news opinions. The WeChat “Disinformation Assistant app” can compare individual transmissions with information in the database, send verified reports of misinformation to people who have mistakenly believed the rumours, and help screen the authenticity of their information. The combination of human and machine news production is becoming a new trend in China’s news communication industry, and in the 2019 National Day Parade live broadcast, drones took 360-degree shots and post-production intelligent editing to restore a panoramic view of the hot news, allowing the general public to “cloud participate” in the National Day Parade. Smart devices are no longer passive communication media, but have become the new coders, modifying and adjusting information symbols and content in response to the “intentions” of the transmitter and the needs of the recipient.

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Based on the general environment of China’s news media industry mentioned above, some new forms of digital media are also continuously tapping and developing the application of artificial intelligence technology, and various new media platforms are using algorithmic recommendations and digital news to develop and grow AI technology. It can not only structure and understand the input video, but also provide tags with frame-level accuracy. For a 2-minute video, it takes 4 hours to collect, edit and render the footage manually, but it can automatically generate the video and achieve the same effect within 30s. This makes it easier and more efficient for users to interact on social and new media platforms.

Journalism and AI New Media in Malaysia

Malaysiakini.com was the first Malaysian internet newspaper. Online since 20 November 1999, this news organization covers a wide range of languages. It wasn’t until the subsequent few years that alternative news outlets began actively offering web news. Today, practically every media outlet, whether state-run or privately owned, has its own website where its stories may be seen. As this example demonstrates, the rise of digital journalism will inevitably replace traditional print media. Internet first appeared in Malaysia in 1990, ushering in the country’s current age of hyperconnectivity. This also refers to the proliferation of new forms of digital media, which include everything from the widespread availability of low-cost internet access and user-friendly social media sites to the proliferation of devices like personal computers and cellphones. This fact has given consumers more options regarding where and how they may acquire their news.

Even though the Internet has expanded over most of the globe, its true significance lies in the hands of its users. Since the middle of the 1990s, when the majority of Malaysians got access to the Internet, the country’s new media environment has radically altered the news sector. Because of the Internet, the public sphere has grown and changed. Just like in other places, the Internet is increasingly serving a social purpose in Malaysia, providing a platform for the free exchange of ideas and the redistribution of power in an increasingly decentralized network. As more and more news outlets move their operations online, journalists need to acquire new talents to report and present information in real time and in an interactive style. Journalism and other forms of communication are experiencing a sea change as a result of the rise of new media.

Artificial Intelligence in the News Industry

Numerous experimental research, especially in scientific and technical domains, have shown that artificial intelligence has promising potential. In spite of the fact that it is difficult to predict how much it will cost to create and deploy an AI application without diving into the specifics of a certain project, most industry professionals are aware that the evolution of AI systems has led to cost savings in recent years. Competing with Silicon Valley firms is challenging because of the need for specific skills in artificial intelligence. To consolidate their dominance and stifle rivals, large IT firms are aggressively purchasing startups that are developing and implementing AI solutions. Competing for available talent is cited in a recent research as a key obstacle to the advancement of AI in the media. Due of lower compensation in compared to the IT sector, newsrooms face stiff competition in both attracting and keeping talented employees. The loss of talented journalists hinders the media industry’s ability to adapt to emerging technology. Despite the odds, news organizations everywhere are integrating AI technology into their reporting processes. Recent years have seen a rise in the mechanization of news articles in newsrooms. Some of these initiatives make use of machine learning methods, while the majority still depend on straightforward automation to fill in the details of preexisting story templates.

Though many of these fake news generators don’t use machine learning or NLP models. They know what has to be done and when it needs to be done in order to get their words out into the world, and they use this knowledge to organize and schedule their actions. Researchers have classified news bots into four distinct groups. Data sources that feed into news bots, the news bots themselves, the algorithms that determine how those inputs are transformed into outputs, and the news bots’ ultimate purpose or goal. The majority of data processing and interaction on digital media platforms in Brazil’s newsrooms is handled by Twitter bots powered by AI models like natural language processing, machine learning, and planning, scheduling, and optimization. In spite of its usefulness, bots have also been employed maliciously in recent events like the Brexit campaign and the 2016 US presidential election.

Photo Credit: TechRepublic

Journalist’s Perceptions about AI

Research on journalists’ attitudes about AI’s usage has lagged behind the field’s growing body of academic literature on the topic, despite a surge in such output over the last four years. We chose these studies because they attempted to address similar concerns to the ones we raise here. Experts were found to be dissatisfied with the writings generated by the program in a research conducted by Thurman et al. (2017), which surveyed 10 journalists. Despite this, sports writers believe AI will be a helpful tool for their profession, citing data processing to uncover interesting themes and faster content creation as two examples. Tez-López et al. (2018) conducted research on the perceptions of 366 Spanish journalists on the use of AI in the field. Where it is relevant to our work, we emphasize journalists’ understanding that AI’s use will provide higher output at reduced costs. However, the vast majority believe AI has potential in the dissemination of news while just 21.3% believe it has applications in content creation. The simplicity with which data may be processed is also remarkable; 30% of respondents highlighted this as a benefit.

The final reference is from a research conducted in four nations (the United States, the United Kingdom, Germany, and Spain) by Noain-Sánchez (2022), who spoke with journalists, media specialists, and academics concerning the use of AI. One of the many takeaways is the realization that AI may be useful to journalists and the media. The former because they are relieved of mundane work, and the latter because their operations become more efficient, allowing them to do more with fewer workers. The respondents agree that automated content creation and tailored distribution are two key areas where AI may be put to use. Concerning the future, the interviewees underline the need of human supervision of the material generated by the algorithms and the necessity for colleges that educate journalists to teach the concepts of artificial intelligence.

Disadvantages of AI

While AI technology is driving the development and transformation of the news media industry, it also poses certain pitfalls. While algorithmic recommendations have enabled personalisation and customisation, they also tend to create the problem of information cocoons and information silos. When users are caught in the information cocoon, they tend to habitually blame the media, but ignore the algorithmic recommendations themselves and their own selective exposure, thus making the news media easy to become the “bearer” of negative effects. While intelligent robots facilitate news production and free up manpower, they also add to the employment pressure of journalists to some extent. Since AI technology is nesting information in pre-set templates, robot writing tends to homogenise and pattern content. At the same time, robots do not have the subjective initiative of news editors and often lack the humanistic and emotional element in information gathering and dialogue writing.

Their writing does not allow for in-depth reporting and is not suitable for all topics. There is a risk that facial recognition technology will violate users’ privacy and portrait rights, and that “fast food” information will affect people’s ability to think independently and make their own choices. While artificial intelligence technology brings diverse news presentation, it also makes it more difficult for the news media to review the information. Unlike the previous text recognition, the news media’s gate-keeping difficulty will increase exponentially in the face of multi-dimensional news products such as video animation and virtual visuals. Undeniably, artificial intelligence technology, as an emerging technology, is an inevitable trend in this digital era, and it will inject new blood into journalism and enhance its core competitiveness. However, by focusing too much on the use of technology and neglecting the deep excavation of content and the adherence to values, mainstream media may fall into the dilemma of putting the cart before the horse and further lose their core competitiveness. Faced with the advantages and pitfalls of artificial intelligence in the field of journalism, we should continue to explore the issue of how to avoid harm and achieve the ideal state of “human-machine synergy”.

Photo Credit: TechRepublic

Integrity in Journalistic Development

In conclusion AI can be applied in the media. Machine learning, computer vision, and scheduling and optimization are more common in news than other areas. Several news cycle phases use machine learning. Our two-use situation was typical. First, there is interest in how to boost audience involvement through machine learning-based recommendation engines. The second employs machine learning to assist media organizations cater to their audiences’ preferences. Machine learning can predict subscription cancellations or create variable paywalls for each reader. Machine learning algorithms are used to strengthen news site business models and boost revenue. Automation dominates news planning, scheduling, and optimization. Despite the tight association between journalism and text, natural language processing models are used less commonly than scheduling, planning, and optimization models. We assume it’s because NLP models are hard to translate between languages. Automated journalism uses computer models to fill in story gaps. As they’re easy to install, news companies are more likely to adopt “dumb algorithms” that adapt but ultimately follow fundamental instructions.–THE MALAYA POST

The views and opinions expressed in this article are the author’s own and do not necessarily reflect those of the Malaya Post

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