Algorithmic bias in social media reinforces right-wing narratives, reflecting broader digital governance failures
Original framing: “A few weeks of X's algorithm can make you more right-wing—and it doesn't wear off quickly” — Phys.org
The study references quantitative analyses of user‑behavior shifts, algorithmic exposure metrics, and longitudinal tracking, adhering to rigorous methodological standards. It cites peer‑reviewed work and acknowledges limitations, grounding its claims in empirical evidence. This scientific grounding is robust and central to the argument.
Algorithmic bias on social media is not merely a technical flaw but a convergence of historical propaganda tactics, profit‑driven governance, and cultural suppression that marginalizes non‑dominant voices.
Indigenous relational models and cross‑cultural insights reveal alternative stewardship pathways, while scientific rigor and future scenario planning provide the evidence base for systemic reform. By embracing trickster awareness—recognizing the paradox of claimed neutrality—we can design transparent audits, regulatory checks, community data trusts, and media‑literacy initiatives that together reorient digital ecosystems toward equity and collective well‑being.