APRIL 2 — Several years ago, I developed a chat application for a research project. Due to budget constraints, I turned the development into a bachelor students’ final year project and provided the students with little monetary compensation. To keep costs low in terms of time, money, and technical complexity, we only included the basic features necessary for the research.
However, during user testing, participants kept requesting additional features commonly found in “free” chat applications. Some even requested automatic translation of discussion posts, such as converting Malay and Chinese messages into English for non-Malay and non-Chinese speakers, e.g., expatriates in Malaysia.
But does “free” truly exist? Users may not pay money upfront, but that does not mean it comes at no cost. Someone is always footing the bill — whether it’s advertisers, paying subscribers, or users themselves, who unknowingly trade their personal data and time in exchange for these “free” services. Both personal data and time are difficult to quantify, but they are certainly not “free.”
Today’s powerful AI systems thrive on publicly available data, which has grown exponentially due to the Internet’s expansion into commercial and social spheres. The rise of social media has pushed vast amounts of personal data into the public domain, enabling AI to leverage the four Vs of big data: Volume (the sheer amount of data), Velocity (the speed at which data is generated and processed), Variety (the diverse sources and formats of data), and Veracity (the accuracy and reliability of the data). This, in turn, has created a fifth V — Value.
Simply put, today’s AI companies derive their value from the personal data that millions of individuals willingly provided in the past. This is essentially a massive global crowdsourcing project — not of money, but of information. Many may perceive their personal data as “free,” but that is only because they fail to see its value.
Simply put, today’s AI companies derive their value from the personal data that millions of individuals willingly provided in the past. This is essentially a massive global crowdsourcing project — not of money, but of information. — Picture from Pexels.com
Traditionally, collecting data from the public has been challenging. A clear example is the scepticism surrounding Malaysia’s PADU system, where the government sought to compile citizens’ personal data, facing resistance from the public. Researchers also often struggle to gather data from individuals.
Yet, when tech companies — including lesser-known entities — package data collection as entertaining social media activities, people readily hand over their personal information. For instance, photo-filter apps that modify images or turn them into artistic renditions are, in reality, data-harvesting tools in disguise.
People hesitate to share their data with governments due to concerns over surveillance. However, they tend to be less cautious about corporate surveillance. The 2018 Cambridge Analytica scandal, in which the company misused data from 50 million Facebook users for political purposes, served as a stark warning about surveillance capitalism—where corporate data collection can be exploited for political and ideological influence.
Today, we see a growing overlap between political and corporate power. US President Donald Trump’s administration aims to run the government like a business, while Elon Musk’s companies, which hold vast amounts of personal data, are now closely involved in shaping public policy through government efficiency initiatives. This convergence of political and corporate influence could escalate surveillance capitalism, leading to greater reliance on AI-generated content, recommendations, and even decision-making processes. In essence, it paves the way for the kind of societal control that authoritarian regimes have long pursued — only now, it is being done through commercial means rather than direct governmental coercion.
Perhaps it is time we reconsider the meaning of “free” and the hidden costs we continue to pay for it.
* Prof Dr Chiew Thiam Kian is from the Department of Software Engineering, Faculty of Computer Science and Information Technology, Universiti Malaya, and may be reached at [email protected]
** This is the personal opinion of the writer or publication and does not necessarily represent the views of Malay Mail.
