Open Access Research Article

THE EVOLUTION OF MACHINE INTELLIGENCE: A DOCTRINAL ANALYSIS OF AI ARCHITECTURE, APPLICATIONS, AND SOCIO-TECHNICAL LIABILITIES

Author(s):
ESTHER MARIA DCOUTO
Journal IJLRA
ISSN 2582-6433
Access Open Access
Volume 3
Issue 8
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Abstract

Artificial Intelligence (AI) has emerged as a transformative technological paradigm that integrates principles from computer science, data analytics, linguistics, and neuroscience to replicate human cognitive functions. This paper provides a comprehensive synthesis of the developmental trajectory, architectural frameworks, and domain deployments of modern machine intelligence. Architecturally, the execution of AI rests upon a critical triad of high-volume datasets, mathematical algorithms, and computational power, which manifests through Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Computer Vision. Historically, the discipline has evolved from ancient philosophical concepts into a formalized academic field, surviving funding contractions known as "AI Winters" to achieve widespread modern public integration. Today, these computational models power a vast array of practical applications across everyday life and industry. This paper evaluates these ubiquitous uses, including conversational virtual agents, real-time cross-lingual translation engines, and personalized adaptive learning platforms in education. Furthermore, it analyzes the deployment of AI in high-stakes environments, such as autonomous vehicular navigation, advanced clinical imaging diagnostics in healthcare, automated inventory and dynamic pricing frameworks in retail, and high-frequency financial trading. In industrial settings, AI-driven robotics optimize mechanical manufacturing and agricultural yields, while generative algorithms upgrade the gaming and interactive entertainment sectors. Mechanistically, these frameworks offer profound operational advantages, including macro-productivity optimization, accelerated real-time decision agility, and precise error mitigation. However, extensive machine integration also introduces severe socio-technical liabilities, most notably structural labor displacement, data security vulnerabilities, and algorithmic bias that can perpetuate systemic discrimination. Ultimately, this paper underscores that while AI offers unprecedented capacity to accelerate global innovation, its sustainable deployment depends heavily on navigating its inherent ethical boundaries, technological dependencies, and systemic risks.

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Authors: ESTHER MARIA DCOUTORegistration ID: 1013538 | Published Paper ID: IJLRA13538Approved ISSN: 2582-6433 | Country: Delhi, IndiaPage No.: 107-123

Article Information

THE EVOLUTION OF MACHINE INTELLIGENCE: A DOCTRINAL ANALYSIS OF AI ARCHITECTURE, APPLICATIONS, AND SOCIO-TECHNICAL LIABILITIES

Authors: ESTHER MARIA DCOUTO

  • Journal IJLRA
  • ISSN 2582-6433
  • Volume 3
  • Issue 8
Citation Download Paper Full Details Search on Google Search on Google Scholar

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International Journal for Legal Research and Analysis

  • AbbreviationIJLRA
  • ISSN2582-6433
  • AccessOpen Access
  • LicenseCC 4.0

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