In an era of rapid development of digital technologies, artificial intelligence, automation, algorithms, and datafication play a crucial role. These technologies are involved in social, cultural, economic and political spheres, such as social media-based interaction and information dissemination, giving rise to new industrial and financial models and roles in political elections through data analysis. Technology development has brought convenience and created opportunities but has also raised concerns and challenges. On the one hand, digital technology has dramatically improved efficiency and quality of life and opened up more possibilities in the marketplace. Yet, the opacity of the market, privacy concerns and deepening prejudices have led to social debates on the ethics and fairness of technology.
The discussion on the development and practical application of digital technologies can help to understand the technology’s current state and its potential impact, further analyze the advantages and disadvantages and explore the reasons behind them, including the problems faced. It is concluded that the implementation of the regulation is crucial in the field of digital technology, including overseeing the role of technology within the law, promoting the security and reliability of technology, promoting a democratic approach and preserving the development of fair and diverse digital markets, and ensuring the public interest.
Algorithm & Datafication
Algorithms and datafication are at the heart of modern technology. In internet platforms, algorithms are usually computer programs that automatically analyze, make decisions, and make intelligent recommendations based on user data (Sandvig et al., 2016). Andrejevic (2019) claims that the internet has a massive amount of culture, and users often gain great convenience due to the relevance of algorithmic content recommendations. Therefore algorithms are trendy among users. According to Lycett (2013), data is an effective tool for increasing innovation, competitiveness and productivity. The datafication of the internet refers to the process of transforming collected information into digital data, which is written into digital technology to personalize the experience for the user further, make accurate predictions for the user, and significantly improve the precision of advertising and marketing. Algorithms and datafication are closely linked; algorithms must analyze the data and find patterns before making inferences and decisions.
Figure 2: Facebook’ news feed (BBC News, 2019)
Facebook’s news feed algorithm provides users with a personalized list of updates. Facebook is a social media platform that sorts and recommends millions of possible news articles through an algorithm that uses data about users’ interests, social connections, historical behavior and other information to present highly personalized News content. Personalized recommendations produce news content highly relevant to users’ interests, thus saving them time and effort in finding news to read. The combined effect of algorithms and data is highly sought after by users because of the convenience it offers (Pasquale, 2015); For the platforms, the stickiness of users is also increasing, with constantly optimized algorithms increasing the time users spend on the platform and their loyalty to it; according to Pasquale (2015), user information is essentially the basis of the platform’s business economy. The precise placement of personalized advertising can lead to better advertising revenue. At the same time, Newman and Fletcher (2017) point to the phenomenon that, despite the vast amount of culture available on the internet, people’s perspectives are still limited to their sphere; While recommending content for users based more on their interests and historical behavior, Facebook’s news feed algorithm can also lead to users being caught in a filter bubble of information, limiting them to different views and information. Social media is more inclined to recommend polarized or controversial content (Andrejevic, 2019), further exacerbating information limitations and reinforcing the idea of having biased opinions; On the other hand, Pasquale (2015) indicates that internet companies collect user information while preventing users from controlling their data, thus generating many voices of discontent and that the lack of transparency and explanation from platforms to outsiders has led users to question them, such as concerns about data privacy and security risks.
Artificial Intelligence & Automation
Automation culture and artificial intelligence are among the most talked about technologies.
Artificial intelligence attempts to understand and build intelligent entities. — Crawford, 2021
AI is a computer technology based on algorithms, hardware and data, which takes large amounts of data into algorithms to find interdependent relationships between data, ultimately achieving the goal of making robots think, learn and be able to act like humans. Artificial intelligence can produce logical relationships based on old data and re-display the logical connections on the new data. The automated culture of the Internet is a form of cultural management that enables the production, presentation and consumption of content through digital technology, which means the computerized processing capabilities of the platform (Andrejevic, 2019). Automated culture is shown in content production, distribution and presentation, and operational management, where automation helps the platform be efficient. The Internet’s artificial intelligence technologies provide powerful support for automating culture. Automation of Internet content through artificial intelligence technology, For example, content generation through language processing capabilities or bot learning, automated ad delivery, management of social media platforms and so on.
Figure 3: Chat page of ChatGPT (Hoffman, 2023)
ChatGPT is a natural language processing model developed by OpenAI. The program has gained a great deal of social attention since its launch. Users enter a question on the platform and, after a short period, can get an automatic reply with text content, the conversation is continuous, thus giving the user the experience of feeling like they are talking to a human being. ChatGPT trains its models by collecting large-scale data, including and not limited to articles, news and social media content, to produce excellent natural language processing capabilities, which allows the model to learn the language’s evolving semantic meaning and contextual relevance to understand further and answer linguistic questions accurately. Compared to traditional bots, ChatGPT reduces the burden of human involvement and dramatically improves the efficiency of conversations. It is not perfect; ChatGPT has a robust data dependency, and it requires a large amount of data support to develop the model, resulting in a large number of human resources and time consumed during the data collection phase; also, the polysemy and complexity of the language can cause the program to misinterpret and thus respond incorrectly. Negative consequences follow, with Lund and Wang (2023) noting that ChatGPT can efficiently understand and interpret users’ requests, responding with near-natural human language responses. Highly realistic synthetic texts can be used for impersonation or deception, raising concerns about integrity; The Guardian reports that universities report a lot of writing done using ai software; and concerns have been raised about ai technology replacing humans to do their jobs, leading to employment difficulties.
Concerns & Social Issues
While the advancement of Internet technology has provided users with a number of advantages and benefits, it has also given rise to a number of worries and social challenges.
The well-known Clever Hans Effect describes how cues from bystanders can cause subtle changes in the thoughts and decisions of another party (Crawford, 2021). Pasquale (2015) contends that AI services serve the predominant interests at hand, which means that the content displayed on digital platforms is primarily one of advertising, marketing, and promotional methods that benefit the platform itself. Google, the biggest internet firm in the world, employs digital technologies to boost platform revenue. First off, a complicated algorithm used to order the search results determines that higher rankings have a higher chance of receiving clicks from users. For example, when users search for email through the Google search engine, Gmail will be ranked first, followed by Outlook, Yahoo Mail and others. From this point of view, the power is always concentrated in the hands of technical authority.
Figure 4: Gmail ranked first through Google search engine (Google, 2023)
The other concern is data privacy and online security. Pasquale (2015) argues that the algorithms of the Internet are an area of ignorance for users, who are unaware of the dissemination, use and consequences of information. In 2018, Google’s smart speaker – Google Home – was exposed for eavesdropping on users’ privacy and analyzing voice data without their authorisation, thus raising concerns about privacy breaches, with critics claiming that the move was a selfish act, ultimately aimed at darker motives of commerce and furthering the concentration of power and wealth, with law professor Glenn Reynolds (2015) notes that powerful behavior is gradually moving away from regulation and control, deepening concerns about privacy and security issues.
The main feature of the algorithm is personalization, the component is data-based and highly contextual (Just & Latzer, 2017), where the engine creates a unique universe of information for the user, limiting the user’s exposure to content information and restricting the user to a narrow range of sources, and Andrejevic (2019) notes that the user’s political leanings also change depending on the field of content to which they are exposed. From this perspective, the platform can also deepen radical ideas. Social media allows users to find common interests and gather to deepen their beliefs further. Google’s video platform – YouTube – will enable users to post videos about political issues such as democratic elections and march trailers, which can intensify conflicts when users gather on the platform and give them a sense of mainstreaming their views.
Digital technologies can perform several personal actions for social functions, leading to the loss of jobs. With the rapid development of the Internet, the widespread use of many digital-based technologies has impacted some traditional jobs. As Google’s search engine continues to be optimized and enhanced, some of the workforce of the traditional search engine optimization industry is being replaced. The artificial intelligence technology cited in Google’s search algorithm has dramatically improved the relevance of results, users are becoming more reliant on the search engine, and its influence is increasing (Pasquale, 2015), and traditional SEO methods are being gradually replaced; at the same time, some automated products and services are gradually replacing agent labor, such as voice recognition and language processing via Google, thus reducing the need for traditional customer service jobs, or the automation technology introduced in production and logistics, using machines to enable the transport of goods, leading to the disappearance of conventional manual logistics jobs.
Development Trends & Governance
While the development of digital technology has brought about a better experience for users, many problems have also emerged, and regulations and measures need to be taken to address the issues. Algorithms, datafication, artificial intelligence and digitisation are currently critical drivers in the digital sphere. They are leading the way for future developments with a high potential for application. The story of the internet, democratic elections, the creation of urban facilities and everyday shopping methods will all be reshaped with the involvement of digital technologies in the social and broad cultural experience.
The issues that arise are of equal concern, and regulatory measures must be taken to address the problems. As Crawford (2021) argues, digital technologies are inextricably linked to technology, social practices, institutions, infrastructure, politics and culture. In addition, the security and dependability of the technology are significantly improved under regulation, preventing potential technical vulnerabilities, system failures, and other issues, assisting the platform in growing and providing users with a better experience; finally, legal regulation ensures legality and compliance and protects user privacy, preventing misuse of data and other misconduct; moreover, digital technologies are a way of reinforcing technocratic power when they influence decision-making (Pasquale, 2015), and to avoid monopolistic and unfair competitive practices in the market, measures taken by the relevant authorities in response can promote innovation and the development of technological diversity and preserve the fair competitiveness of the digital technology market; lastly, regulation can also safeguard the public interest, such as reducing the spread of misinformation and identifying extremist views. Also, the involvement of digital technology may lead to the loss of some jobs; applying digital technology under regulation can put the public interest first and maintain a system of interests and values in line with society.
To sum up, digital technology will still be crucial in the future. It will affect many different areas much more broadly. Artificial intelligence and automation enable the automatic generation of content and automatic operation functions, increasing the efficiency of the work. The use of algorithms and data in internet platforms has helped users rely more and more on technology because it enables them to improve convenience by recommending content recommendations that are highly relevant to them based on a large amount of data. The advantages are undeniable, but a number of concerns have been raised; the main interest groups have gained as a result of the concentration of power brought about by the development and use of technology; Users are restricted to their line of sight in front of large volumes of information, limiting diversity. It also results in some jobs being replaced by technology, producing employment challenges. Concerns regarding data privacy and security are also raised. Regulation and governance are essential in this situation because they can protect user rights, advance technology, foster a better understanding of use, prevent the concentration of power, uphold free market competition, promote innovation and diversity, and simultaneously protect the public interest and the advancement of digital technology.
References
Andrejevic, M. (2019). Automated Culture. Automated Media. London: Routledge, pp. 44-72.
BBC News. (2019). Facebook’s news feed [Image]. BBC News. https://www.bbc.com/news/technology-47771922
Cooper, Z. (2019). Digital technology [Image]. Itpro. https://www.itpro.com/strategy/29899/three-reasons-why-digital-transformation-is-essential-for-business-growth
Crawford, K. (2021). The atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.
Google (2023). Gmail ranked first through Google search engine [Screenshot]. Google. https://www.google.com/search?q=gmail&rlz=1C5CHFA_enAU1049AU1049&oq=gmail&aqs=chrome..69i57j0i67i650j0i10i512j0i67i650l4j0i10i512l3.1054j0j15&sourceid=chrome&ie=UTF-8
Hoffman, D. (2023). Chat page of ChatGPT [Image]. The Jakarta Post. https://www.thejakartapost.com/business/2023/01/14/openai-creator-of-chatgpt-casts-spell-on-microsoft.html
Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: how may AI and GPT impact academia and libraries?. Library Hi Tech News.
Lycett, M. (2013). ‘Datafication’: making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381-386.
Newman, N., & Fletcher, R. (2017). Bias, bullshit and lies: Audience perspectives on low trust in the media. Available at SSRN 3173579.
Pasquale, F. (2015). The black box society: The secret algorithms that control money and information. Harvard University Press.
Sandvig, C., Hamilton, K., Karahalios, K., & Langbort, C. (2016). Automation, algorithms, and politics| when the algorithm itself is a racist: Diagnosing ethical harm in the basic components of software. International Journal of Communication, 10, 19.
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