Kaito: The Double-Edged Sword of Yap-to-Earn
@KaitoAI Backed by Top Capital, Monetizing Influence through AI
The Yap-to-Earn Mechanism is Causing Controversy
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Core Issues:
Flood of Low-Quality Content:
Under algorithmic incentives, a large amount of spam content floods the platform, resembling elevator advertisements in the Crypto space, creating an information closed loop.
Intensified Head Effect:
Algorithm bias and group behavior allow top KOLs to gain advantages, squeezing the living space of mid-tier and new creators.
Questioning Algorithm Fairness:
High-read content has ratings similar to paid advertisement posts, while non-Kaito related content is suppressed, raising doubts about the fairness of algorithms.
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Impact:
Harmed Creator Ecosystem:
Mid-tier creators are forced to cater to algorithms, resulting in decreased content quality and obstructed paths for newcomers to rise.
Community Trust Crisis:
Algorithmic unfairness and low-quality content lead to the community losing patience with the platform.
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Key to the Future:
Algorithm Optimization:
Weaken interaction data, strengthen content quality assessment (originality, depth, user feedback).
Community Governance:
Involve users in content rating and platform governance to reduce algorithmic bias.
Enhance Transparency:
Improve technical security and data processing transparency to rebuild trust.
Kaito's exploration provides new ideas for the attention economy, but the drawbacks of an algorithm-driven model are also evident. If issues regarding content quality, algorithm fairness, and community trust cannot be effectively resolved, Kaito's vision of information financialization will be difficult to achieve. We look forward to better performance in the future.
#Kaito
#yap