In this advanced digital era, internet users may be unaware of the extent of their online surveillance. For example, searching for hotels on Google can lead to related ads appearing on social media platforms like Facebook, Instagram, or TikTok.
This phenomenon is not coincidental but results from the collection of personal data aimed at targeted advertising.
This article aims to analyse the mechanisms of data collection, the functions of algorithms, the role of artificial intelligence (AI) in ad structuring, and the associated privacy implications, including long-term risks and measures that can be taken to protect user privacy.
User Data Collection
Each time a user browses a website or searches on Google, personal information is collected through technologies like “cookies” and “pixel tracking”.
Cookies are small files that store information about a user’s activity on a website, such as viewed products or visited pages. For example, if a user visits an e-commerce site, cookies will save information about the viewed products to display relevant ads on other websites.
Pixel tracking involves placing a small code on a website to track user actions even after they leave the site.
According to the article “Personalized Advertising Computational Techniques: A Systematic Literature Review, Findings, and a Design Framework” published by MDPI in 2021, these techniques enable advertising companies to gather personal information to form a more accurate digital profile of users, thereby enhancing the effectiveness of targeted advertising.
Reference: https://www.mdpi.com/2078-2489/12/11/480
The Role of Algorithms and AI Technology
Platforms like Facebook and Google utilise sophisticated algorithms and artificial intelligence (AI) to analyse the data collected from user activities. These algorithms build a digital profile that includes users’ interests, demographics, and purchasing behaviours.
Machine learning allows systems to identify patterns in user data and predict future preferences based on past behaviours.
For instance, if a user searches for hotels on Google, the algorithm identifies keywords and search patterns to display relevant hotel ads on social media through retargeting strategies.
The “Personalized Advertising Computational Techniques” article also identifies techniques and algorithms used to target ads to users based on their behavioural and demographic data.
Approaches such as machine learning, natural language processing, and big data analytics are among the most widely used to enhance ad relevance.
However, advertisers must consider ethical and privacy factors in implementing these techniques to avoid user rejection of personalised ads.
The capability of machine learning to analyse vast amounts of data makes ad targeting increasingly effective globally.
Privacy Implication
Although data-driven advertising offers significant advantages to advertisers, it raises serious concerns regarding user privacy.
Research by the Pew Research Center (2023) finds that Americans display high distrust towards social media company leaders. About 77% do not believe they would admit to mistakes regarding data misuse, and 71% doubt the government’s actions to enforce accountability. While 78% feel confident in making decisions about their personal information, the majority are sceptical about the impact of their actions, with only 20% confident that those holding their personal information will handle it responsibly.
The tension between individual confidence and concerns about stricter surveillance in protecting data privacy is evident. Therefore, companies need to be more transparent about how they use data and provide users with control over their information.
Increased user awareness regarding privacy is now driving calls for more data protection laws, as seen with the introduction of regulations like GDPR in Europe.
Reference: https://www.pewresearch.org/internet/2023/10/18/how-americans-view-data-privacy/
Long-term Implications of Data Collection
Concerns regarding data collection extend beyond advertising. The data gathered can be exploited by third parties for more malicious purposes, including identity theft and personal information fraud.
A study by McKinsey & Company in 2022 emphasises the importance of digital trust for businesses, showing that organisations perceived as trustworthy in protecting data and using AI responsibly tend to experience higher growth rates.
While users have confidence in digital privacy, many companies struggle to meet these expectations.
Leaders in digital trust adopt proactive risk reduction strategies and prioritise transparency, which helps enhance customer relationships and overall business performance.
Reference: https://www.mckinsey.com/capabilities/quantumblack/our-insights/why-digital-trust-truly-matters
Protecting User Privacy: Practical Steps
While it is challenging to fully avoid digital surveillance, there are several steps users can take to protect their privacy:
1. Use privacy-focused browsers like Brave or Firefox that automatically block ads and trackers.
2. Activate private browsing mode.
3. Install anti-tracking extensions like Privacy Badger.
4. Regularly delete cookies.
5. Block websites from tracking their activities.
By taking these measures, users can reduce their data exposure to advertising companies.
Commercial Benefits for Advertisers: A Balanced Perspective
Despite privacy concerns, there is also a commercial viewpoint to consider. Data-driven advertising allows advertisers to deliver more relevant messages to users, reducing irrelevant ad spam. Users may prefer to see ads that align with their interests rather than unrelated advertisements.
The Digital Media Trends report by Deloitte in 2023 finds that users are becoming increasingly connected and engaged with digital content. Surveys show they prefer personalised media experiences and are willing to pay for quality content. This report highlights the importance of innovation in media experiences to meet users’ evolving expectations.
With more relevant advertising, advertisers not only enhance campaign effectiveness but also reduce wasted cost per click.
Conclusion
In this digital era, the structuring of advertisements based on personal data and algorithms is an increasingly widespread phenomenon. While this technology helps advertisers deliver more relevant ads to users, it also raises significant concerns regarding privacy and ethics. Users need to be more aware of how their data is collected and utilised.
By taking specific measures to protect their privacy, users can ensure their safety in a digital world increasingly driven by algorithms and data collection. At the same time, understanding both the benefits and risks will enable us to face technological challenges more consciously.
This article emphasises the importance of balancing data usage for marketing purposes with individual privacy protection, which is an increasingly critical issue in contemporary society.
With greater awareness, society can evaluate whether the benefits brought by digital advertising technology outweigh the risks to individual privacy.
The author is the Editor-in-Chief of The Malaya Post and is currently pursuing a Doctor of Philosophy (PhD) in Media Management at Universiti Utara Malaysia.
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