“Today, those who control the questions shape the answers and those who shape the answers control the world.” — Luciano Floridi (L., Floridi, The Politics of Uncertainty, Philosophy & Technology, volume 28, pages 1–4, (2015))
In the age of information, power no longer resides solely in who has the answers. It lies deeper—in who decides which questions get asked in the first place. From algorithms that prioritize some queries over others, to governments and platforms that filter what we can search, hear, or say, the architecture of inquiry is now a battleground of influence.
Floridi calls this dynamic the “politics of uncertainty”: a subtle yet profound shift where shaping the conditions of knowledge—what is known, unknown, and unknowable—becomes the primary mechanism of control.
It’s not just about misinformation. It’s about epistemic gatekeeping.
Understanding this new terrain means asking a different kind of question: Who decides what we’re allowed to wonder about?
The complex interplay between technology, society and control in the modern world is evident in issues such as prediction, power, uncertainty and information interception. Artificial intelligence is a discipline centred on prediction, utilising advanced algorithms and machine learning models to analyse data and forecast future events. This approach profoundly impacts crucial sectors such as finance, healthcare and climate science, where accurate prediction is essential for informed and strategic decision-making.
In this context, power is closely linked to the management of uncertainty.
In political and economic spheres, controlling or reducing uncertainty through privileged access to information provides a significant competitive advantage.
Large technology companies, for instance, gather vast quantities of data via user interactions and urban infrastructure. This vast accumulation of information enables them to analyse behaviour, predict trends and influence decisions on a large scale, thereby strengthening their position of power.
Similarly, intelligence agencies and secret services aim to reduce uncertainty by intercepting or accessing communications. Their aim is to protect national security and maintain strategic advantages by using the gathered information to prevent threats and plan precise actions. This highlights the importance of access to and analysis of information as key tools for exercising and controlling power in the contemporary era.
Information and the ability to predict are central to shaping current power structures. The intersection of advanced technology, data collection and predictive analysis has a profound influence on the evolution of society and the way power is acquired and maintained. Reflecting on these dynamics is crucial for understanding the potential impact of technology on our future, as well as considering the associated ethical implications. Data collection is an instrumental step in producing useful information. Raw data, collected from various sources, often has no immediate intrinsic meaning. It is only through collection and analysis that it is transformed into structured, understandable information that can provide a coherent picture of the reality we seek to understand. In essence, data collection forms the basis of the entire information process. The aim of this process is to convert fragmented and potentially chaotic data into information that can inform strategic decisions. Even the most seemingly insignificant piece of data can contribute to generating fundamental insights once it has been processed and placed in a broader context.
Modern society is undergoing a fundamental transformation as artificial intelligence creates unprecedented capabilities for prediction and control. This shift represents not merely technological advancement but a restructuring of power relations themselves, where the ability to anticipate and influence future behavior becomes the primary mechanism of social control. The convergence of AI prediction, mass data collection, and behavioral analysis is creating new forms of power that operate through uncertainty reduction rather than traditional coercion, fundamentally altering how societies function and how authority is exercised.
Artificial intelligence has evolved into what researchers call a “science of prediction” – a systematic approach to analyzing vast datasets to anticipate future events with remarkable accuracy. AI systems now handle 89% of global trading volume and demonstrate 93% accuracy in medical diagnostics, fundamentally changing how critical decisions are made across society. The technological foundation rests on three pillars: deep learning neural networks, ensemble methods, and real-time data processing.
The real power lies not in data collection itself but in the prexdictive capabilities this data enables.
The competitive advantages created by these information asymmetries are nearly insurmountable.
Companies with superior data access can predict and influence market conditions, creating self-reinforcing cycles of dominance.Network effects ensure that larger platforms become exponentially more valuable as they gather more data, creating winner-take-all dynamics that concentrate predictive power in the hands of a few major corporations.