Fwd: AI, Predictions, and The Future of Aviation
Chandana Liyanapatabendy
AI, Predictions, and The Future of Aviation
Airlines worldwide are embracing AI-driven workforce management systems.
by Dr. Ruwantissa Abeyratne
June 7, 2026
10 mins read
Skellefteå Airport [Niklas Jonasson/Unsplash]
“Artificial intelligence is likely to be either the best or worst thing to happen to humanity.” — Stephen Hawking
Commands in Disguise
Artificial Intelligence has become the defining technological phenomenon of our age, permeating every sector of human endeavor with promises of efficiency, precision, and predictive capability. Nowhere is this more evident than in the air transport and airport industries, where AI increasingly guides decisions affecting safety, security, passenger facilitation, revenue management, workforce planning, and operational resilience. Yet beneath the alluring promise of algorithmic certainty lies a deeper philosophical question: what happens when machines begin not merely to predict human behavior but to shape it? The writings of Professor of Philosophy at Oxford University, Carissa Véliz, particularly in Privacy Is Power, and Prophecy: Prediction, Power, and the Fight for Freedom from Ancient Oracles to AI offer a timely and compelling framework through which to examine this question. Her warning that “predictions are often commands in disguise” invites aviation policymakers, regulators, airlines, and airport operators to reconsider the ethical foundations upon which the industry’s digital future is being constructed.
Carissa Véliz’s two seminal works together offer a profound warning about the trajectory of technologically mediated societies. Although neither book is written specifically for aviation, both contain insights of exceptional relevance to the airline and airport industries, sectors that are increasingly dependent on artificial intelligence, predictive analytics, biometric identification, behavioral profiling, and algorithmic decision-making. Their significance for aviation lies not merely in the technological implications they identify but in the ethical and philosophical questions they raise concerning freedom, autonomy, accountability, and human dignity in a data-driven world.
The aviation industry has always been an industry of prediction. Long before artificial intelligence emerged as a commercial reality, airlines and airports relied upon forecasting models to predict passenger demand, fuel consumption, weather disruptions, maintenance schedules, route profitability, crew requirements, and airport capacity. Prediction, in this sense, has traditionally served operational efficiency and safety. What distinguishes the contemporary era, however, is that prediction has migrated from forecasting events to forecasting human beings.
Today, airlines seek to predict passenger behaviour. Airports seek to predict passenger movement. Governments seek to predict security risks. Marketing departments seek to predict purchasing decisions. Revenue management systems seek to predict willingness to pay. Loyalty programmes seek to predict customer retention. Human resource departments seek to predict employee performance and attrition. Artificial intelligence has become the nervous system of these predictive activities.
It is precisely at this point that Véliz’s warning becomes relevant.
Her central proposition that “predictions are often commands in disguise” challenges one of the foundational assumptions of contemporary aviation management: that predictive systems merely describe reality. Véliz argues that predictions are not passive observations. They actively shape outcomes. Once a prediction is made, institutions begin acting upon it, and those actions frequently transform the prediction into reality.
This phenomenon is increasingly visible throughout the air transport ecosystem.
Airlines and Airports’ Predictions
Consider airline revenue management systems. AI models predict which passengers are likely to pay premium fares, purchase ancillary services, or remain loyal to a carrier. The airline then structures its offers, incentives, and restrictions based upon these predictions. What begins as a forecast becomes a directive. The system effectively instructs the passenger how he or she should behave within the commercial architecture designed by the airline.
The same dynamic can be observed in airport security systems. Modern airports increasingly employ risk-based screening methodologies. Passengers are categorized according to predicted security risks derived from travel history, demographic characteristics, behavioral indicators, and digital footprints. Once categorized, travelers encounter different levels of scrutiny. The prediction influences treatment. The prediction becomes operational reality.
Véliz would argue that such systems reveal a subtle but profound shift. Individuals are no longer evaluated primarily according to their actions. They are evaluated according to statistical projections of what they might do. The distinction is critical. Traditional legal systems are founded upon accountability for conduct. Predictive systems increasingly assign consequences based upon probabilities.
This shift raises fundamental questions for aviation law and ethics.
The legal architecture of international civil aviation emerged from Enlightenment assumptions regarding human agency. The Chicago Convention of 1944, the Montreal Convention of 1999, and countless national aviation statutes implicitly assume that individuals possess autonomy and should be judged according to observable conduct. Predictive AI introduces a different paradigm. Human beings become probabilistic entities whose future actions can allegedly be anticipated, categorized, and managed.
Such a development challenges the philosophical foundations of justice itself.
The implications are perhaps most apparent in aviation security. Since the terrorist attacks of September 2001, governments and airports have increasingly embraced predictive intelligence systems. The objective is understandable and legitimate. Aviation security seeks to prevent catastrophic harm before it occurs. Yet Véliz’s analysis invites us to ask whether predictive security systems may gradually erode the distinction between suspicion and certainty.
When an algorithm identifies a traveler as potentially risky, what exactly has occurred? Has the passenger engaged in wrongful conduct? Or has a machine simply generated a statistical inference? The answer has profound ethical significance. If operational decisions are based primarily upon prediction rather than evidence, aviation risks moving toward a regime in which future possibilities become substitutes for present realities.
Challenges
The danger is not merely theoretical. History repeatedly demonstrates that predictive systems often inherit the biases embedded within their underlying data. Airports and airlines collect unprecedented volumes of personal information. Biometric identifiers, facial recognition records, travel histories, purchasing habits, social media activity, geolocation data, and behavioural patterns collectively form detailed digital profiles of individual travellers.
In Privacy Is Power, Véliz argues that such extensive data collection fundamentally alters the balance of power between institutions and individuals. The more information organizations possess, the greater their capacity to influence human behaviour. Privacy, therefore, is not simply a personal preference. It is a mechanism for preserving freedom.
Applied to aviation, this argument has extraordinary significance.
The contemporary passenger journey increasingly resembles a continuous process of data extraction. From the moment a reservation is made until baggage is collected at the destination, countless data points are generated and analyzed. Airlines know where passengers travel, what they purchase, how frequently they fly, whom they travel with, and often what they consume during their journeys. Airports monitor movement patterns, dwell times, retail preferences, and biometric identifiers.
The justification for these practices is generally efficiency. Better data enables better service. Yet Véliz reminds us that efficiency is not synonymous with ethics.
The ethical question is not merely whether data collection improves operational outcomes. The ethical question is whether individuals retain meaningful autonomy when subjected to pervasive surveillance.
This concern becomes particularly acute when predictive analytics are combined with behavioural influence mechanisms. Modern airlines increasingly employ personalized pricing, targeted marketing, and dynamic offers generated by AI systems. The objective is not simply to understand passengers but to shape their decisions.
A predictive model identifies a passenger likely to purchase lounge access. An offer is presented. Another model predicts a willingness to upgrade to business class. A targeted incentive appears. Another predicts vulnerability to scarcity messaging. The booking interface emphasizes limited availability.
From a commercial perspective, such practices represent sophisticated customer engagement. From Véliz’s perspective, they may constitute subtle forms of behavioural manipulation.
The distinction is important because autonomy depends upon the capacity to make decisions free from undue influence. If predictive systems continuously anticipate and shape choices, the boundary between persuasion and manipulation becomes increasingly difficult to identify.
The implications extend beyond passengers to aviation employees.
Airlines worldwide are embracing AI-driven workforce management systems. These technologies predict employee productivity, absenteeism, fatigue risks, training requirements, and retention probabilities. Flight crew scheduling increasingly relies upon predictive algorithms capable of analysing enormous quantities of operational data.
While such systems undoubtedly enhance efficiency, they also raise questions concerning professional dignity and organizational justice.
Suppose an AI system predicts that a pilot is likely to resign within two years. Management may unconsciously alter promotion decisions. Suppose another system predicts a higher probability of fatigue-related performance issues. Additional monitoring may follow. Suppose a predictive model identifies a flight attendant as unlikely to advance into leadership roles. Opportunities may diminish.
In each case, predictions risk becoming commands.
Individuals may find themselves constrained not by their demonstrated abilities but by algorithmic expectations regarding their future behaviour.
This dynamic evokes one of the most powerful themes in Véliz’s Prophecy. Throughout history, societies have sought certainty about the future. Ancient civilizations consulted oracles. Medieval kingdoms consulted astrologers. Modern organizations increasingly consult algorithms.
The technologies differ, but the psychological impulse remains remarkably similar.
Human beings are uncomfortable with uncertainty.
Airlines are especially uncomfortable with uncertainty. Their business models depend upon managing risk, optimizing resources, and minimizing unpredictability. AI appears to offer an unprecedented solution. Vast quantities of data can be transformed into forecasts that promise greater certainty.
Yet Véliz’s work suggests that the pursuit of certainty may itself become a threat.
The future derives its moral significance precisely because it remains open. Human creativity, innovation, and moral growth depend upon unpredictability. Every breakthrough in aviation history emerged because individuals defied expectations. The pioneers of flight, the architects of jet transportation, and the visionaries who transformed global mobility all succeeded because they transcended prevailing predictions.
An aviation industry governed excessively by predictive systems risks becoming less innovative precisely because it becomes more predictable.
The challenge is therefore not merely technical but civilizational.
How should airlines and airports employ AI without undermining the human freedom that makes progress possible?
Véliz’s answer would likely begin with privacy.
Privacy Aspects
Data minimization should become a central ethical principle within aviation AI governance. Organizations should collect only the information genuinely necessary to achieve legitimate operational objectives. The prevailing assumption that more data inevitably produces better outcomes deserves critical scrutiny.
The aviation sector has historically embraced a culture of safety based upon necessity and proportionality. Every safety measure must be justified by demonstrable risk reduction. A similar philosophy should govern data collection. Every category of personal information should be justified by demonstrable operational necessity.
Transparency is equally essential.
Passengers increasingly encounter algorithmic decisions without understanding their underlying logic. Whether determining pricing, security screening, service prioritization, or disruption management, AI systems often operate as opaque mechanisms. Ethical governance requires explainability. Individuals affected by algorithmic decisions should possess the ability to understand, challenge, and appeal those decisions.
This principle reflects not merely good governance but fundamental legal values.
The rule of law depends upon accountability. Accountability depends upon transparency. Transparency becomes impossible when critical decisions are delegated to inscrutable algorithmic systems.
The airport environment presents particularly significant challenges. Airports increasingly aspire to become “smart airports” in which artificial intelligence orchestrates passenger flows, security procedures, retail experiences, and operational processes. Facial recognition technologies promise frictionless travel. Behavioural analytics promise enhanced security. Predictive maintenance promises improved reliability.
These innovations undoubtedly offer substantial benefits. Yet Véliz would caution against allowing technological enthusiasm to eclipse ethical reflection.
A frictionless journey is not necessarily a free journey.
An airport capable of predicting every movement, monitoring every interaction, and influencing every decision may achieve remarkable efficiency while simultaneously diminishing individual autonomy.
This tension reflects a broader philosophical conflict between convenience and freedom.
Historically, societies have often surrendered liberty incrementally in exchange for perceived benefits. The digital age has accelerated this tendency. Consumers routinely exchange personal information for convenience without fully appreciating the long-term consequences.
Air transport is becoming one of the most data-intensive sectors of the global economy. Consequently, it occupies a critical position in the ethical debate concerning artificial intelligence.
The industry’s future will not be determined solely by technological capabilities. It will also be determined by ethical choices.
Will AI be used primarily to augment human decision-making or to replace it? Will predictive systems remain advisory tools or become authoritative mechanisms? Will passengers retain meaningful control over their personal information or become perpetual subjects of digital observation? Will aviation professionals continue to exercise judgment or become executors of algorithmic recommendations?
These questions lie at the heart of Véliz’s intellectual project.
Her work ultimately challenges the assumption that technological progress is inherently desirable. Progress must be evaluated according to its effects upon human flourishing. An AI system that increases efficiency while diminishing freedom may represent technical advancement but ethical regression.
The aviation community has historically understood the importance of balancing competing values. Safety must be balanced against efficiency. Security must be balanced against facilitation. Economic development must be balanced against environmental responsibility. The emergence of artificial intelligence introduces another balancing exercise: prediction must be balanced against freedom.
Perhaps the most enduring contribution of Véliz’s two books is their reminder that uncertainty is not a defect to be eliminated but a condition of human liberty. The future remains meaningful precisely because it is not fully knowable. Individuals remain responsible because they retain the capacity to choose differently. Societies remain democratic because citizens can challenge expectations and redefine possibilities.
For airlines and airports navigating the AI revolution, this insight is profoundly important. The objective should not be to construct systems that render human behaviour perfectly predictable. The objective should be to deploy technology in ways that enhance safety, efficiency, and service while preserving the unpredictability that constitutes human dignity itself.
When Véliz writes that predictions are often commands in disguise, she offers not merely a critique of artificial intelligence but a warning about power. Every prediction contains an implicit temptation: the temptation to treat possibility as destiny. For the air transport industry, whose future increasingly depends upon algorithmic systems, the ethical challenge is therefore clear. Artificial intelligence must remain a servant of human judgment rather than its substitute. The airline passenger must remain a citizen rather than a data point. The airport must remain a gateway to mobility rather than a laboratory of surveillance. And prediction, however sophisticated, must never be permitted to become fate. In that simple distinction between forecasting and commanding lies the future moral legitimacy of artificial intelligence in aviation.
My Take
As I reflect upon the implications of Véliz’s thesis for aviation, I am reminded that civil aviation has always succeeded when it placed the human being at the center of its endeavors. Aircraft, airports, navigation systems, and regulatory frameworks exist not as ends in themselves but as instruments serving humanity. Artificial intelligence should be viewed through the same lens. The objective of AI in aviation should not be to create perfectly predictable passengers, employees, or societies. Rather, it should be to enhance safety, efficiency, and service while preserving the essential qualities that distinguish human beings from algorithms: judgment, creativity, dignity, and freedom of choice. The temptation to substitute prediction for judgment must be resisted, particularly in matters affecting security, employment, and access to mobility.
There is also an urgent need for international aviation governance to embrace AI ethics as a core policy priority. Just as the international community developed common standards for safety, security, and environmental protection, so too should it pursue globally accepted principles governing transparency, accountability, explainability, and data minimization in aviation AI systems. Organizations such as ICAO are uniquely positioned to foster a normative framework that balances innovation with human rights. Without such safeguards, the aviation sector risks drifting toward a future where individuals are increasingly assessed not by their actions but by algorithmic forecasts of what they might do. Such a trajectory would represent a profound departure from the principles of fairness and justice that underpin modern legal systems.
Ultimately, the most valuable lesson emerging from Véliz’s work is that uncertainty is not the enemy of progress but one of the conditions of freedom. Aviation itself was born from the courage of individuals who refused to accept prevailing predictions about what was possible. The future of air transport should therefore not be dictated by algorithms that merely extrapolate from the past. It should be shaped by human imagination, moral responsibility, and a commitment to ensuring that technological advancement serves the enduring values of civilization. The challenge before us is not whether artificial intelligence can predict the future of aviation. It is whether humanity will retain the wisdom to ensure that such predictions never become commands, and that the freedom to choose a different future remains firmly in human hands.
Dr. Ruwantissa Abeyratne DCL, PhD, LL.M, LLB, FRAeS, FCILT
Senior Associate, Aviation Law and Policy
Aviation Strategies International
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