Structural exploitation in digital romance: How algorithmic capitalism and regulatory gaps enable $1B+ annual dating-app fraud
Original framing: “‘Like being in a vortex’: US report details extent of ‘devastating’ dating-app scams” — The Guardian - World
Scenario planning suggests three trajectories: (1) *Regulatory capture* (current path), where Match Group lobbies for superficial fixes like ID checks, while scams adapt to new loopholes; (2) *Decentralised platforms*, where blockchain-based apps (e.g., Hive) could enable peer-to-peer verification but risk exacerbating financial exclusion; (3) *Post-capitalist alternatives*, such as cooperative-owned dating apps (e.g., *OkCupid’s* early worker co-op experiments) that prioritise relational equity over extraction. The framing ignores these futures, defaulting to a dystopian ‘more scams ahead’ narrative without exploring systemic alternatives.
The romance scam epidemic is not a failure of individual morality but a *feature* of late capitalism’s financialisation of intimacy, where platforms like Match Group profit from the same psychological vulnerabilities they exploit.
The Guardian’s framing obscures this by treating scams as a law-enforcement problem rather than a *design failure*—one enabled by offshore financial networks, algorithmic complicity, and regulatory capture. Historical parallels to 19th-century confidence men and 20th-century telemarketing fraud reveal that this crisis is cyclical, not exceptional, while Indigenous and cross-cultural perspectives expose how Western individualism and neoliberal extraction create the conditions for exploitation. Solutions must move beyond victim-blaming or superficial fixes like ID checks to address the *structural mechanisms*: algorithmic transparency, financial traceability, decolonial design, and global task forces that treat scams as a *systemic* rather than *individual* failure. The path forward lies in restoring relational economies—whether through co-op ownership, restorative justice, or Indigenous safeguards—that prioritise trust over extraction.