How to use algorithms as human “weapons”?
As one of the controversial topics nowadays, artificial intelligence must be the emerging technology that has received a lot of attention. As one of the fastest-growing fields in recent years, AI has had a significant impact on the development and operation of various industries and fields, especially in search engines, Streaming media, and Applications in network security. The article will focus on discussing the challenges and opportunities faced by artificial intelligence algorithms in these fields through case studies of existing practical applications of artificial intelligence.
Artificial intelligence (AI) is a technology aimed at enabling computers to reason like humans. This technology will accelerate the Digital transformation of various industries. To promote more intelligent artificial intelligence, it is necessary to use machine learning (ML) and data analysis (DA) modules to simulate human learning, as well as evaluate and analyze all data generated over time, identify past trends, and improve the efficiency and effectiveness of future artificial intelligence algorithms. Artificial intelligence is like instilling intelligence into machines, enabling them to complete tasks that traditionally require human thinking. In this era, artificial intelligence-based systems are rapidly developing in terms of application, adaptation, processing speed, and capabilities (Ghosh et al., 2018).
Artificial intelligence can be simply understood as a technology that simulates human intelligence through technological means. It mainly includes technologies such as learning-related skills, language processing functions, visual processing, and intelligent recommendation. It is widely used in the internet industry. As of today, artificial intelligence has achieved significant results in applications such as search engines, personalized recommendations, data analysis, and network security (Burns et al., 2022).
Undoubtedly, artificial intelligence has become the preferred tool for many enterprises to handle data analysis and business decision-making. Its advantage lies in the ability of algorithms based on artificial intelligence to quickly analyze and process large-scale data. Through machine learning technology, algorithms can identify the important features of most information from the massive data on the Internet, and then use these features to achieve precise processing and push (Burns et al., 2022).
According to recent research and data analysis, the application of artificial intelligence algorithms in the field of the Internet is showing a rapid growth trend. The application of various forms of algorithms in the field of the Internet is constantly expanding, including search engines, streaming media, and so on. According to a report by market research company Statista, the application of artificial intelligence in the internet field is constantly growing. According to reports, the global artificial intelligence market reached $2020 billion in 2020 and is expected to reach $110 billion by 2027. At the same time, the application of artificial intelligence in the field of the Internet is also constantly increasing. According to the prediction of International Data Corporation (IDC), the global AI market size will reach 32.7 billion US dollars by 2025, with AI applications in the internet sector accounting for 43%. Artificial intelligence has a wide range of applications in the field of the internet, and it is constantly innovating and expanding with a growing market size (Gravrock, 2018).
However, artificial intelligence algorithms also face some challenges and problems in internet data analysis. Although these algorithms can improve the user experience, they may also have some drawbacks. The most significant issue among them is the privacy of users. The algorithm collects the personal data of users, such as viewing history and interest preferences, which may lead to the risk of user privacy leakage. In addition, algorithms may also have biases and discrimination due to the impact of data bias. In addition, excessive reliance on algorithms by users may lead to them missing out on other valuable content, thereby reducing their get knowledge and information breadth. Finally, recommendation algorithms may lead to information overload and have a negative impact on art and culture. Therefore, it is necessary to effectively regulate these algorithms and achieve more open transparency to ensure that users’ privacy and rights are protected, and to eliminate potential biases and discrimination in algorithms (Hinkle, 2021).
“Problems with content recommendations generated via artificial intelligence (AI) on streaming services according to consumers in the United States as of October 2018. Source: Statista. ”
The Application of Artificial Intelligence in Search Engines.
As an important component of the Internet, search functions should be something that most people often come into contact with in their daily lives. It is often used as the main way for people to obtain information and solve problems. Some people may not be aware that AI-related technologies have been applied in search engines for a long time, they have been used to improve your accuracy and efficiency in search.
For example, search engine optimization (SEO) refers to improving a website’s ranking in search engines by optimizing its content and structure. Artificial intelligence technology can help search websites achieve better SEO results. Firstly, artificial intelligence can improve the ranking of websites in search engines by analyzing and optimizing algorithms in search engines. For example, some artificial intelligence technologies can provide users with more accurate search results by analyzing their search behavior, website content, and other factors. Secondly, artificial intelligence can help websites improve user experience. For example, some artificial intelligence technologies can improve user satisfaction by analyzing user search behavior and providing more personalized search results and content recommendations (Ghosh et al., 2018b).
To take the simplest example, as the world’s largest search engine, Google has been actively exploring the application of artificial intelligence technology in different fields. Currently, it has implemented basic applications of artificial intelligence in fields such as search engines, language processing, image recognition, and autonomous driving. Google uses artificial intelligence algorithms to analyze users’ search history and behavior, providing them with more accurate search results. In contrast, traditional search engines can only provide search results based on keywords, making it difficult to accurately understand users’ search intentions.
For example, the Google Image Recognition feature, which is commonly used by most people, is a powerful feature implemented using artificial intelligence algorithms. Google has applied deep learning algorithms in this field, commonly known as Convolutional Neural Networks (CNN). CNN is a neural network that mimics the human brain’s nervous system. Simply put, it can use algorithms to extract features from images, thereby achieving the most image classification and recognition (Catherine & Ogilvy, 2022).
According to official data released by Google, it processes over 1 billion image search requests per day, most of which can be processed and matched through artificial intelligence algorithms. This also indicates to some extent that Google’s artificial intelligence algorithms have become practical and indispensable in the field of image recognition today (Chang, 2021).
With the application of artificial intelligence algorithms, of course, some problems and challenges inevitably arise. As a user, the most important concern should be privacy-related issues. Google needs to process a large amount of data and information when using artificial intelligence algorithms, although it provides users with many conveniences, there are also some potential hazards. Firstly, Google’s image search function may infringe on image copyright. According to a study on image data, these copyrighted images may be used by users and cause infringement, causing economic losses to copyright owners. In addition, approximately 70% of professional photographers believe that copyright infringement on the internet has increased over the past year, and Google Image Search Engine has become an important suspect in copyright infringement (Connellan, 2018).
Secondly, the Google Image Search feature may be used for illegal or inappropriate activities. According to a study, approximately 33% of online pornographic content can be directly found through search engines, with Google’s search engine playing an important role. In addition, Google’s image search function may also be used to search and download images containing child pornography, which not only greatly harms children but also poses certain harm to society (Whittaker, 2012).
In addition, Google’s image search function may also leak user privacy to some extent. According to a survey, many images in Google Image Search Engine alone contain user personal information. If this personal information is maliciously used, it may lead to the infringement of user privacy (Gathercole, 2021).
Finally, Google’s image search function may be limited by artificial intelligence algorithms. According to a study, when searching for photos of ethnic minorities such as black or Asian people, the Google Image Search feature exhibits significant bias, which may lead to inaccurate or discriminatory search results. This also indicates that the regulation of artificial intelligence algorithms cannot be ignored (Cohn, 2019).
Algorithms in Streaming Media Platform Services and Their Possible Impact.
As another popular industry in the internet industry, streaming media service platforms are also one of the rapidly growing internet industries, they utilize algorithms to improve user satisfaction and increase user stickiness and revenue. However, these algorithms may also bring some problems and negative impacts. Since these algorithms typically require access to users’ personal data, such as browsing history and preferences, they may compromise and leak users’ privacy. In addition, these algorithms may also lead to information filtering, where users can only receive severely homogenized content recommended by the algorithms, resulting in a lack of diversity and innovation. Streaming media service providers, need to balance business needs with the diversity of user privacy needs and develop more responsible and transparent algorithms through strengthened regulation (Hinkle, 021).
Shocking information leakage incident – Facebook Cambridge Analytica Event.
In 2018, Facebook was exposed to have collaborated with Cambridge Analytica on suspicion of illegally collecting user information, violating user privacy, and using user data for election manipulation. This event has sparked global attention to the regulation of internet algorithms. This scandal further demonstrates that regulatory agencies should strengthen their supervision of Internet companies and regulate their behavior (Confessore, 2018).
The regulation of internet algorithms is urgent.
Artificial intelligence algorithms have become an important component of modern social development, but they also bring many regulatory challenges. The current applications of algorithms are very extensive, involving fields such as search, recommendation, advertising, finance, and healthcare. The opacity of these algorithms and the leakage of personal privacy may lead to various negative consequences, such as bias, discrimination, fraud, harassment, and abuse, so it is crucial to regulate internet algorithms.
Of course, there are many difficulties in the regulation of current internet algorithms. Firstly, the complexity and opacity of artificial intelligence algorithms make them difficult to understand and regulate. Secondly, internet companies typically have a large amount of data and resources, which can easily evade regulation. Thirdly, regulatory agencies may lack sufficient technical and legal capacity to regulate internet algorithms, and the regulation of internet algorithms cannot be completely one-size-fits. It is necessary to balance the relationship between data privacy and algorithm transparency to protect the rights and interests of users (Rainie & Anderson, 2017).
To effectively regulate internet algorithms, a possible future solution is mentioned here. In terms of policy, regulatory agencies should establish relevant legal frameworks to regulate the transparency, fairness, and responsibility of artificial intelligence algorithms. At the technical level, regulatory agencies should also have sufficient technology and capabilities to regulate internet algorithms. While strengthening the supervision of Internet enterprises and regulating their behavior. Regulatory agencies need to continuously optimize and formulate new regulatory standards in cooperation and development with internet companies and various sectors of society and find effective measures to regulate artificial intelligence algorithms through extensive practice (Flew, 2021).
Burns, E., Laskowski, N., & Tucci, L. (2022, February). What is artificial intelligence (AI)? TechTarget; TechTarget.
Chang, J. (2021, April 1). 90 Google Search Statistics for 2021: Usage & User Behavior Data. Financesonline.com.
Confessore, N. (2018). Cambridge Analytica and Facebook: The Scandal and the Fallout So Far. The New York Times.https://www.nytimes.com/2018/04/04/us/politics/cambridgeanalytica-scandal-fallout.html
Cohn, J. (2019, April 24). Google’s algorithms discriminate against women and people of colour. The Conversation. https://theconversation.com/googles-algorithms-discriminate-against-women-and-people-of-colour-112516
Connellan, S. (2018, February 16). Google has just made it harder for you to steal photos from Google Images. Mashable. https://mashable.com/article/google-image-search-change
Catherine, C., & Ogilvy, H. (2022, February 22). How does picture search work? | Algolia. Algolia Blog. https://www.algolia.com/blog/product/picture-search-how-does-an-image-finder-search-engine-work/
Flew, Terry (2021) Regulating Platforms. Cambridge: Polity, pp. 79-86.
Ghosh, A., Chakraborty, D., & Law, A. (2018). Artificial intelligence in Internet of things. CAAI Transactions on Intelligence Technology, 3(4), 208–218. https://doi.org/10.1049/trit.2018.1008
Gathercole, L. (2021, November 26). Google introduces feature enabling under 18s to remove their images from image search. Briffa Legal. https://www.briffa.com/blog/google-introduces-feature-enabling-under-18s-to-remove-their-images-from-image-search/
Gravrock, E. von. (2018, November 15). Council Post: How AI Empowers the Evolution Of The Internet. Forbes. https://www.forbes.com/sites/forbeslacouncil/2018/11/15/how-ai-empowers-the-evolution-of-the-internet/?sh=4f57d7093256
Hinkle, D. (2021, August 18). How Streaming Services Use Algorithms. AMT Lab @ CMU. https://amt-lab.org/blog/2021/8/algorithms-in-streaming-services
Rainie, L., & Anderson, J. (2017, February 8). Code-Dependent: Pros and Cons of the Algorithm Age. Pew Research Center: Internet, Science & Tech.
Whittaker, Z. (2012, December 12). Google.com now “censors” explicit content from image searches. ZDNET. https://www.zdnet.com/article/google-com-now-censors-explicit-content-from-image-searches/