The Dismantled Mindset in the Age of Artificial Intelligence: Identity Fragmentation in Algorithmic Networks: A Mathematical Model, Simulation, and Empirical Research Agenda Felipe Castro Quiles, MBA Independent Researcher | felipe@castroquiles.com Working Paper, SSRN 5040267 / 5824582 | 2025 Abstract This paper extends the Dismantled Mindset Theory (Castro Quiles, 2024, 2025) into the domain of artificial intelligence and digital identity, arguing that algorithmic systems do not merely reflect existing power fragmentation; they actively accelerate it. Grounded in the theory's four foundational forces (greed, fear, influence, and responsibility) and its mathematical formalization of fragmentation dynamics in directed social networks, this paper situates the Dismantled Mindset construct within established research traditions in surveillance capitalism, filter bubble theory, algorithmic identity curation, and the psychology of oppression. We propose four causal mechanisms through which AI systems produce identity fragmentation, three falsifiable hypotheses linking algorithmic exposure to measurable psychological outcomes, and a research agenda for empirical validation. We further argue that the theory's normative commitment to collective empowerment, rooted in the author's lived experience across the Americas (from San Castro Quiles | Dismantled Mindset Theory | p. 1Juan to post-earthquake Haiti to the World Bank), provides a constructive dimension that critical AI scholarship has largely lacked. The path from thought leadership to scientific theory runs through measurement, peer scrutiny, and replication. This paper charts that path. Keywords: Dismantled Mindset Theory, identity fragmentation, algorithmic power, AI ethics, surveillance capitalism, collective empowerment, digital identity, social network dynamics, power redistribution 1. Introduction What if the very way we think about power, identity, and society is fundamentally flawed? What if our understanding of these concepts is not just misguided, but a trap, one built upon greed, fear, and manipulation, ultimately leading us to fracture our identities and limit our potential? These questions, posed at the opening of the Dismantled Mindset Theory (Castro Quiles, 2024), are not rhetorical. They describe a structural condition of contemporary digital life that has become measurable, propagating, and urgent. The relationship between technological systems and human identity has been a central concern of social theory since the industrial era. What distinguishes the present moment is the degree to which identity formation is now mediated not merely by institutions or social norms, but by opaque algorithmic systems that continuously model, predict, and shape individual behavior at scale. Social media recommendation engines, large language models, personalized advertising ecosystems, and automated content moderation systems collectively constitute an environment in Castro Quiles | Dismantled Mindset Theory | p. 2which the self is perpetually reflected back to the individual in curated, fragmented, and commercially optimized forms. The Dismantled Mindset Theory (DMT), introduced by Castro Quiles (2024) and formalized mathematically in Castro Quiles (2025), provides a conceptual and quantitative framework for understanding these dynamics. At the heart of the theory are four foundational forces: greed, defined as the insatiable desire to control resources and power at the expense of others; fear, the anxiety of losing power or status that compels self-preserving behaviors harmful to collective well- being; influence, the capacity to inspire and lead through empathy and ethics; and responsibility, the ethical obligation to use power for the greater good. These forces interact to produce what the theory calls a dismantled mindset: a fractured sense of self and society that perpetuates division, disempowerment, and inequality. The theory emerges not from academic abstraction but from lived experience. The author's trajectory, from a family business in Puerto Rico, through entrepreneurship in post-earthquake Haiti, to policy dialogues at the World Bank and global innovation programs at Singularity University, gives the framework a grounded empirical intuition that purely theoretical accounts of AI and power often lack. The observation that algorithms had quietly shaped what people believe before they start speaking, illustrated in a kitchen debate in Santurce between the author and his uncle, both convinced they were seeing the full picture, both having been guided to their views by invisible systems designed to feed them what they were already inclined to accept, captures in everyday terms what the theory formalizes analytically. Crucially, the Dismantled Mindset is described not only as a phenomenon to be diagnosed but as one to be dismantled. The theory's central normative claim, captured in Quiles' Law of Dismantled Castro Quiles | Dismantled Mindset Theory | p. 3Mindsets, is that only by breaking down fear, greed, and control can we rebuild ourselves and unlock true potential. This dual character, critical and constructive, distinguishes DMT from most critical AI scholarship, which tends toward diagnosis without prescription. This paper has three objectives. First, it situates DMT within existing interdisciplinary literature, demonstrating both its alignment with established findings and its distinctive contributions. Second, it sharpens the theory's causal claims into falsifiable hypotheses. Third, it proposes a research agenda that would enable DMT to move from a framework toward an empirically validated theory of AI-mediated identity fragmentation. 2. Literature Review: Situating the Dismantled Mindset The Dismantled Mindset Theory does not emerge in an intellectual vacuum. Several well- established research programs address adjacent phenomena. This section maps the terrain, identifying where DMT builds on, diverges from, and advances these traditions. 2.1 Filter Bubbles and Epistemic Fragmentation Pariser (2011) introduced the concept of the filter bubble to describe how algorithmic personalization progressively narrows users' informational environments, reinforcing existing beliefs and limiting exposure to disconfirming perspectives. Subsequent empirical work has complicated the picture: Guess et al. (2023) found that algorithmic effects on political polarization are more modest than popularly assumed, and that user choice plays a substantial role in self- selection into homogeneous information environments. Castro Quiles | Dismantled Mindset Theory | p. 4DMT's contribution to this debate is to shift the unit of analysis from epistemic content, what people believe, to identity coherence, who people understand themselves to be. The fragmentation the theory describes is not primarily about holding incorrect beliefs, but about the progressive incoherence of the self-concept under conditions of algorithmic curation. An individual who encounters conflicting identity signals across algorithmically managed contexts does not simply hold inconsistent beliefs; they experience a structural erosion of the narrative self. This distinction is not addressed by existing filter bubble research. 2.2 Surveillance Capitalism and the Commodification of Identity Zuboff (2019) offers the most comprehensive account of how the commercial logic of digital platforms transforms human experience into raw material for behavioral prediction and modification. Her concept of behavioral futures markets, in which platforms sell predictions about future behavior to advertisers, implies a structural incentive for platforms to destabilize user identity, since identity instability increases engagement and therefore generates more predictive data. DMT's power fragmentation framework is directly consonant with Zuboff's analysis but extends it in two directions: first, it introduces a mathematical formalism for modeling fragmentation dynamics across social networks rather than merely within individuals; second, it proposes a constructive framework for collective restoration that is largely absent from Zuboff's critical project. Where Zuboff describes the problem in its fullest form, the Dismantled Mindset Theory attempts to specify the mechanism of reversal. 2.3 Algorithmic Identity and Context Collapse Castro Quiles | Dismantled Mindset Theory | p. 5A growing body of work in human-computer interaction and critical internet studies has documented how algorithmic systems shape self-presentation and identity performance. Bucher (2018) examines how platform algorithms create an algorithmic imaginary, a set of beliefs users develop about how algorithms work, which in turn shapes their behavior and self-conception. Research on context collapse (Marwick and boyd, 2011) has shown that the flattening of social contexts on platforms produces identity incoherence as users navigate incompatible audience expectations simultaneously. DMT's fragmentation construct maps productively onto this literature. The dismantled self described by the theory is, in computational social science terms, a self whose context management has broken down, an identity that has lost coherent narrative under the pressure of multiple, algorithmically mediated audience contexts. The theory's four forces operationalize the specific drivers: greed and fear on the platform side generate the commercial incentives for context collapse, while influence and responsibility describe the individual and collective capacities needed to resist it. 2.4 Structural Power and Identity: Sociological Antecedents DMT's attention to structural power as the driver of identity fragmentation connects it to foundational sociological work. Bourdieu (1986) describes how structural inequalities are reproduced through differential access to symbolic r
Felipe Castro Quiles (2026) studied this question.