[Post] Artificial Intelligence(AI) Malfunction Cases and Response Strategies

The Double-Edged Sword of AI: Accelerating Innovation and Trust Crisis

Generative AI technology is revolutionizing productivity across industries, but it also spreads negative effects that erode the intangible asset of social trust. Deepfakes and AI-based false information are disseminated with precision that surpasses human cognitive limits, sharply increasing the cost for individuals to discern truth. This article categorizes AI’s negative effects into three types: “Digital Divide Widening,” “Overdependence on AI,” and “Crime and Illegal Activities Abuse,” aiming to diagnose their risks and explore effective countermeasures.

Three Major Types of AI Negative Effects: Divide, Overdependence, and Crime

First, the Digital Divide (AI Divide) has gone beyond simple accessibility issues, evolving into a gap in “utilization quality,” and exacerbates inequality through the compounding effects of productivity. Small and medium-sized enterprises lacking capital and data face significant risks of being eliminated in competition with large corporations. Second, Overdependence on AI leads to a phenomenon of “de-skilling,” where humans’ innate problem-solving abilities decline. Meanwhile, the process of verifying AI outputs and being responsible for them may result in increased workload. Third, Crime & Illegal Acts manifest as financial scams and public opinion manipulation using deepfakes (such as Sora 2.0) and voice synthesis. This even triggers the “Liar’s Dividend,” where genuine evidence is questioned, shaking the foundation of societal trust.

Solutions to Restore Trust: Combining Web 3.0 Technologies and Systems

To address AI’s negative effects, a comprehensive approach involving technology, policy, and education is crucial. Technologically, it is urgent to introduce trust infrastructure based on Web 3.0. This includes using Distributed Identity (DID) to cryptographically verify sender identities to prevent impersonation, employing Zero-Knowledge Proofs (ZKP) to verify credentials without exposing personal information, and linking C2PA standards with blockchain for transparent content source tracking. Policy-wise, it is necessary to strengthen penalties for AI-related crimes and impose proactive management obligations on platforms, while also supporting small and medium-sized enterprises with AI infrastructure to eliminate gaps. In education, literacy programs should be implemented across all age groups, focusing on cultivating habits of source verification and understanding algorithmic biases through critical thinking.

Building a Human-Centric AI Ecosystem Governance

AI is a “double-edged sword” that simultaneously grants humans unlimited possibilities and risks. More important than the pace of technological development is how we use technology safely and responsibly. Governments, enterprises, and civil society must work together to build a flexible governance framework that does not hinder innovation while upholding human-centric values. When trust is secured through Web 3.0 technologies and safety nets are built via laws and education, AI can truly become a tool for human prosperity.

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