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what is ai
Used tools Searching academic papers for Artificial Intelligence definition comprehensive overview, found 28 papers

Artificial Intelligence (AI) is a broad field of computer science focused on creating systems or machines capable of performing tasks that typically require human intelligence. These tasks include reasoning, learning, problem solving, perception, language understanding, and decision making. AI encompasses a variety of techniques and methodologies, prominently including machine learning, natural language processing, computer vision, and generative AI.

AI can be understood as the simulation or automation of intelligent behaviors by computers. It often involves the development of algorithms that enable machines to learn from data, adapt to new inputs, and execute complex functions without explicit human programming for every specific task. For example, machine learning algorithms improve their performance through exposure to data over time, enabling applications such as speech recognition, image analysis, and autonomous driving (Latorre, 2024).

Classifications of AI include narrow or weak AI, which is designed to perform specific tasks, and Artificial General Intelligence (AGI), which aspires to replicate human cognitive abilities across a wide range of domains. AGI is still a theoretical and developing area, distinct from specialized AI systems, and presents unique challenges and ethical considerations as it evolves (Joshi, 2025).

The significance of AI is evident across various sectors including healthcare, logistics, finance, security, and education. AI applications range from decision support systems, predictive analytics, personalized learning, to advanced automation and intelligent virtual agents. It enables enhanced accuracy, efficiency, and scalability in these applications (Latorre, 2024).

Moreover, AI systems raise important ethical, social, and fairness concerns, such as biases in decision-making processes that may perpetuate inequalities. Addressing these issues involves ensuring transparency, accountability, and the inclusion of diverse and representative data to develop fair and unbiased AI solutions (Ferrara, 2023).

In summary, AI is the field of creating intelligent computational systems capable of performing cognitive tasks, driven largely by data and algorithms that enable learning and adaptation, with broad applications and growing societal impact (Latorre, 2024), (Joshi, 2025), (Ferrara, 2023).

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Citation Lists

Emilio Ferrara · 2023-12-26 · Multidisciplinary Digital Publishing Institute

Satyadhar Joshi · 2025-05-01 · None

Luca Latorre, Valentn Muro, Eduardo Rego, Mariana Gutierrez, Ignacio Cerrato, Jose Daniel Zarate · 2024-06-13 · None

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what is ai

Abstract
Source 1: Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies

Emilio Ferrara · 2023 · Multidisciplinary Digital Publishing Institute · 292 citations

10.3390/sci6010003

The significant advancements in applying artificial intelligence (AI) to healthcare decision-making, medical diagnosis, and other domains have simultaneously raised concerns about the fairness bias of AI systems. This is particularly critical areas like healthcare, employment, criminal justice, credit scoring, increasingly, generative models (GenAI) that produce synthetic media. Such systems can l…

Source 2: Comprehensive review of Artificial General Intelligence (AGI): Applications in Business and Finance

Satyadhar Joshi · 2025

10.35629/5252-0705250261

This paper delves into themultifaceted realm of Artificial General Intelligence(AGI), exploring its definition, evolution, potentialapplications, and the ongoing debates surroundingits development. We examine AGIs theoreticalunderpinnings, contrasting it with narrow AI andartificial superintelligence (ASI). Furthermore, wediscuss the impact of AGI across various sectors,including finance, research…

Source 3: Tech Report Artificial Intelligence

Luca Latorre, Valentn Muro, +4 · 2024

10.18235/0013015

This report provides a comprehensive overview of AI, from its fundamentals to its practical applications, covering topics such as its definition, evolution, and implementation. It also delves into various applications, such as machine learning, natural language processing, computer vision, and generative AI, providing specific examples and use cases across sectors like healthcare, logistics, envir…

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