ARTIFICIAL INTELLIGENCE: RECENT TRENDS AND FUTURE IMPLICATIONS

Artificial Intelligence (AI) has turned out to be one of the most revolutionary technologies of the 21st century, transforming industries, economies, and societies. Current trends in AI are centered on the development of machine learning techniques, natural language processing, computer vision, and generative AI systems with the ability to execute creative as well as analytical processes. The trend of increasing AI usage in healthcare, education, business, and governance identifies its potential to improve productivity, decision-making, and accessibility. But these developments also pose fundamental questions about ethics, privacy, job losses, and security threats. Future prospects envision AI continuing to transform the global workforce, speeding up scientific discovery, and affecting human conduct through smart systems. Ethical AI development, clear policies, and global cooperation will be critical to reconcile innovation with moral protections. This paper critically assesses the latest trends in AI, including generative AI models, autonomous systems, and AI in big data analytics, and discusses future implications such as prospects for sustainable growth and challenges such as algorithmic bias and socio-economic inequality. The argument is that the path of AI will be determined by how well humanity treats these challenges and utilizes the technology for sustainable and inclusive development.

Authors

Institutions

Publication Details

Journal
Journal of Emerging Technologies and Innovative Research
Published
2025-01-01
DOI
https://doi.org/10.56975/jetir.v12i10.570596
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ARTIFICIAL INTELLIGENCE: RECENT TRENDS AND FUTURE IMPLICATIONS

Neelam Sinha
Journal of Emerging Technologies and Innovative Research
Ethics and Social Impacts of AI
article

ARTIFICIAL INTELLIGENCE: RECENT TRENDS AND FUTURE IMPLICATIONS

Neelam Sinha
article en

Abstract

Artificial Intelligence (AI) has turned out to be one of the most revolutionary technologies of the 21st century, transforming industries, economies, and societies. Current trends in AI are centered on the development of machine learning techniques, natural language processing, computer vision, and generative AI systems with the ability to execute creative as well as analytical processes. The trend of increasing AI usage in healthcare, education, business, and governance identifies its potential to improve productivity, decision-making, and accessibility. But these developments also pose fundamental questions about ethics, privacy, job losses, and security threats. Future prospects envision AI continuing to transform the global workforce, speeding up scientific discovery, and affecting human conduct through smart systems. Ethical AI development, clear policies, and global cooperation will be critical to reconcile innovation with moral protections. This paper critically assesses the latest trends in AI, including generative AI models, autonomous systems, and AI in big data analytics, and discusses future implications such as prospects for sustainable growth and challenges such as algorithmic bias and socio-economic inequality. The argument is that the path of AI will be determined by how well humanity treats these challenges and utilizes the technology for sustainable and inclusive development.

Journal of Emerging Technologies and Innovative ResearchVol. 12(10)
Bhagwant University (IN)
Openalex Percentile: Top 69%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.