Paper Title
WHAT ARE THE SHORT-TERM AND LONG-TERM ECONOMIC IMPACTS OF AI-DRIVEN AUTOMATION ON INCOME INEQUALITY
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Authors
VEDIKA PAL
Keywords
Abstract
AI driven automation, which is the use of artificial intelligence technology to perform tasks, conventionally done by humans, is revolutionizing the labour market and industries across various sectors. This is having and will continue to have profound impact on the income inequality in both short term and long term which this study explores. Short-term causes contributing to growing income inequality include the swift replacing of low-skilled workers and wage reduction in regular employment. On the other hand, because of unequal access to higher education and training, artificial intelligence may eventually worsen income polarization even while it has the potential to offer new, highly skilled work possibilities. This research paper explores these structural changes in the labour market in near future and their impacts on the income distribution in an economy and potential strategies to gear the economy for such imbalances. These include labour market reforms like skills development and workforce adaptations. Additionally, the study also highlights the need for urgent policies and educational reforms that workers would need to thrive in the increasingly omnipresent AI dominated economy assuring a more equitable distribution of income and minimizing the risks associated with technological advancement
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How To Cite (APA)
VEDIKA PAL (August-2024). WHAT ARE THE SHORT-TERM AND LONG-TERM ECONOMIC IMPACTS OF AI-DRIVEN AUTOMATION ON INCOME INEQUALITY. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(8), d451-d462. https://ijnrd.org/papers/IJNRD2408388.pdf
Issue
Volume 9 Issue 8, August-2024
Pages : d451-d462
Other Publication Details
Paper Reg. ID: IJNRD_227229
Published Paper Id: IJNRD2408388
Downloads: 000121986
Research Area: Social Science and HumanitiesÂ
Country: Ambernath, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2408388.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408388
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