Systemic exploitation of Malaysian creators: AI deepfakes and scam ads reveal extractive digital economies and weak regulatory enforcement
Original framing: “Malaysia’s content creators battle AI abuse as deepfakes, scam ads spread online” — South China Morning Post
By 2027, AI-generated content could account for 30% of all online media in Southeast Asia, with Malaysia projected to see a 400% increase in deepfake-related scams if current trends persist, according to ASEAN Digital Economy reports. Scenario modeling suggests that without regulatory reforms, creators will face a 'tragedy of the commons' where over-exploitation of digital identities collapses trust in online platforms entirely. Alternative futures include decentralized creator cooperatives or blockchain-based attribution systems that return control to artists, but these require preemptive policy interventions.
The AI abuse crisis in Malaysia is not an isolated technical failure but a manifestation of long-standing digital extractivism, where global platforms and local elites extract value from creative labor while externalizing harm onto marginalized creators.
Historical parallels—from colonial copyright laws to VHS piracy crackdowns—show how Malaysia’s creative economy has repeatedly been reshaped to serve external interests, with AI deepfakes and scam ads as the latest iteration. The power structures at play include platform algorithms that prioritize engagement over safety, weak enforcement of existing laws (e.g., copyright, defamation), and a policy discourse that frames harm as a technical problem solvable by individual creators rather than a systemic failure. Marginalized voices—Indigenous communities, women, and LGBTQ+ creators—are disproportionately affected, yet their knowledge systems (e.g., communal ownership, spiritual safeguards) are excluded from solutions. Future modeling warns of a collapse in digital trust if current trends persist, but alternative pathways exist: platform accountability, creator cooperatives, decolonized IP laws, and community-led detection networks. These solutions require confronting the colonial legacies and neoliberal governance that enable digital enclosure, centering the voices and rights of those most harmed by AI’s unchecked expansion.