The Commodification of Behavior in the Age of AI

The commodification of human behavior defines the digital age, driven by artificial intelligence (AI) and an insatiable demand for behavioral data. Every online action—searches, clicks, purchases, or even brief pauses on a video—is turned into a monetizable data point. Tech corporations collect, analyze, and sell these behaviors, using sophisticated AI algorithms to predict, influence, and profit from our every move.

While compensating individuals for their data has gained traction, I believe such a solution fails to confront the far more pervasive and ethically troubling issue: turning human behavior itself into an economic asset.

As I explore AI’s ethical dimensions, it becomes clear that although research has examined AI ethics, surveillance capitalism, and data privacy, the commodification of behavior remains under-theorized and largely unchallenged in academia.

The core issue goes beyond ownership or privacy; it strikes at how AI systems manipulate and exploit human behavior for profit, often without individuals’ full awareness or consent.

These systems’ complexities—and their impact on personal autonomy, societal power dynamics, and marginalized communities—demand a far more rigorous and multidisciplinary investigation than current scholarship offers.

The Limits of Current Research

1. Overemphasis on Privacy and Data Ownership: Much of the discourse around AI ethics, especially after works like Shoshana Zuboff’s The Age of Surveillance Capitalism, has centered on data privacy and ownership. Zuboff’s work illuminates the vast power asymmetries between corporations and individuals, particularly in data exploitation. However, this focus often neglects the subtle ways AI commodifies behavior itself. Transforming behavior into data not only invades privacy but also erodes autonomy, as our actions are increasingly shaped by systems designed to keep us engaging, consuming, and producing more profitable data points.
2. Failure to Critically Engage with Behavioral Manipulation: A significant gap exists in research that examines how AI-driven systems manipulate behavior beyond traditional concerns of privacy and fairness. Scholars like Kate Crawford and Meredith Whittaker have highlighted AI’s social and environmental harms and advocated for greater transparency and regulation. Yet the conversation often stops short of interrogating how AI shapes human actions not merely for optimization but to align with corporate interests, often at the expense of individual autonomy and well‑being. Current research frequently lacks a robust critique of how AI systems distort behavior for financial gain under the guise of “better user experiences.”
3. Limited Interdisciplinary Engagement: While behavioral economics, psychology, and sociology each contribute to understanding how digital platforms influence behavior, much of the existing work remains confined within disciplinary silos. Economists explore incentives behind data collection; psychologists study cognitive effects of digital environments; ethicists focus on consent and autonomy. Rarely do these fields intersect to provide a comprehensive analysis of how behavior is commodified and monetized by AI systems. This fragmentation limits our ability to develop effective countermeasures or alternative frameworks.
4. Inadequate Attention to Power and Exploitation: One of the most profound concerns about AI’s commodification of behavior is how it reinforces structural inequalities and extends capitalist exploitation into new digital realms. Yet existing research often lacks a critical examination of these dynamics. Marginalized communities, already vulnerable to predatory data practices, are disproportionately affected by these systems. Scholars like Ruha Benjamin and Safiya Umoja Noble have exposed the racialized and gendered dimensions of algorithmic bias, but the commodification of behavior itself—particularly among marginalized populations—remains underexplored. This gap leaves blind spots in our understanding of how AI systems perpetuate exploitation, often under the guise of efficiency and personalization.

Engaged Principal Investigators and Current Efforts

Despite the need for more rigorous inquiry into behavior commodification, some engaged principal investigators (PIs) and research efforts are beginning to tackle these issues:

• Shoshana Zuboff (Harvard Business School) has provided foundational insights into surveillance capitalism. Her work primarily addresses data exploitation from a macroeconomic perspective, with less focus on the nuanced ways AI systems directly influence and commodify individual behaviors.
• Kate Crawford (AI Now Institute) has contributed significantly to the critical discourse on AI’s environmental and social impacts, advocating for deeper accountability and transparency. However, her work does not fully unpack the intricacies of behavior commodification at the micro‑level, particularly how AI systems manipulate user actions for profit.
• MacArthur grantee Ruha Benjamin (Princeton University) and Safiya Umoja Noble (UCLA) have engaged critically with the racialized and gendered dynamics of algorithmic bias, offering crucial insights into how AI systems exacerbate social inequalities. Their work opens new avenues for understanding how marginalized communities are disproportionately targeted by AI-driven commodification practices, but further research is needed to explore how behavior itself becomes a tool for exploitation in these contexts.

The Need for a New Research Direction

Addressing the commodification of behavior in AI systems requires moving beyond existing frameworks and engaging with the deeper ethical, social, and political dimensions of this phenomenon. This involves several critical steps:

1. Interdisciplinary Integration: A comprehensive understanding of behavior commodification demands collaboration across fields such as behavioral economics, AI ethics, psychology, sociology, and political economy. By bringing these disciplines into dialogue, researchers can develop a more nuanced picture of how AI systems manipulate behavior and commodify human actions, as well as the broader consequences for society.
2. Behavioral Manipulation and Autonomy: Focused research is needed to examine how AI-driven platforms influence human behavior in ways that are often invisible to users. This requires exploring how recommendation engines, predictive algorithms, and engagement-driven systems subtly nudge users toward actions that align with corporate profit motives, undermining autonomy and potentially causing psychological harm.
3. Power and Exploitation: Future research must interrogate how AI commodifies behavior to reinforce existing power structures and deepen social inequalities. It is crucial to explore how these systems disproportionately affect marginalized communities, commodifying their behaviors for profit while offering little in return. This demands a deep investigation into the exploitative dimensions of behavior commodification within global capitalism.
4. Regulatory and Ethical Frameworks: Developing regulatory frameworks that protect data privacy while addressing behavioral commodification is essential. These frameworks must emphasize transparency, algorithmic accountability, and the safeguarding of individual autonomy from AI’s exploitative tendencies. There should also be a push toward alternative models for AI development—ones that prioritize human dignity and ethical design over short-term profit.

The commodification of behavior by AI systems is one of the most ethically complex and socially impactful issues of our time. While current research has made strides in addressing data privacy and algorithmic bias, it has yet to fully engage with the deeper implications of behavior commodification.

The time is ripe for a critical exploration of how AI systems shape and monetize human actions, and what this means for autonomy, power, and equality in a rapidly digitizing world.

By advocating for a multidisciplinary approach, I hope to contribute to a shift in the way we understand and address these issues, challenging the power dynamics inherent in AI-driven commodification practices.

Expanding research beyond surface-level discussions of privacy and data ownership can help us develop frameworks that protect individual autonomy, resist exploitation, and promote more ethical uses of AI.