The proposed universal basic income (UBI) policy, funded by a 5% tax on AI and automated systems, addresses critical economic and social challenges. First, it directly acknowledges the wealth generated by AI, which displaces human labor and concentrates profits among corporations, ensuring a more equitable distribution of gains. Second, the tax creates a sustainable revenue stream for UBI, which can alleviate poverty, reduce inequality, and provide financial stability amid rapid automation. Third, by incentivizing investment in AI while redistributing its benefits, the policy fosters a balanced transition to a future where human labor is complemented rather than replaced by technology. These measures collectively position UBI as a pragmatic solution to systemic economic shifts, offering both immediate relief and long-term adaptability.  

Opponents argue the policy risks stifling innovation and economic growth. The 5% tax could deter investment in AI development, as companies may divert resources from research to compliance, slowing technological progress. Additionally, enforcing such a tax on decentralized or borderless AI systems poses significant administrative challenges, potentially leading to loopholes or inefficiencies. Lastly, the funding mechanism may be insufficient to sustain a meaningful UBI, as the tax’s revenue could fall short of demand, requiring additional burdens on traditional sectors or reducing the program’s impact. These concerns highlight the need for careful economic modeling and alternative strategies to ensure both fairness and feasibility.