AI Algorithms for Positive Change in Digital Futures

Abstract

Artificial Intelligence (AI) is transforming industries and revolutionizing how we interact with technology at an unprecedented pace, playing a crucial role in shaping our digital future. The global issues we face today are complex, and AI provides us with a valuable tool for augmenting human efforts in formulating hardware and software solutions to complex problems. In the current age of the Fourth Industrial Revolution (Industry 4.0), to analyze the wealth of data provided by the Internet of Things (IoT), cybersecurity, mobile, business, social media applications, and medical records, there is greater need for machine learning (ML) and Artificial Intelligence (AI) algorithms [1]. Driven by increased productivity, digitalization requires novel AI algorithms to enhance safety, reduce human error, and enable more sophisticated data analysis. While AI refers to the simulation of human intelligence in machines, which allows them to perform tasks that typically require human cognitive functions such as learning, reasoning, problem solving, perception, and decision making, ML refers to technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience and data. The ultimate goal of AI is to develop machines that can think, reason, act autonomously, and, in some cases, surpass human capabilities across various domains, including healthcare, finance, transportation, and entertainment. Since the birth of AI with the “Logic Theorist” program created by Allen Newell and Herbert A. Simon in 1955, AI algorithms have led to innovations such as autonomous vehicles, smart homes, automated manufacturing systems, and medical robotics, creating a digital future.

Publication DOI: https://doi.org/10.3390/a18010043
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Aston Digital Futures Institute
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics
College of Engineering & Physical Sciences > Smart and Sustainable Manufacturing
College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Aston University (General)
Additional Information: Copyright © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Publication ISSN: 1999-4893
Last Modified: 25 Mar 2025 18:23
Date Deposited: 10 Feb 2025 16:58
Full Text Link:
Related URLs: https://www.mdp ... 99-4893/18/1/43 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Editorial
Published Date: 2025-01
Published Online Date: 2025-01-13
Accepted Date: 2025-01-09
Authors: Kavakli-Thorne, Manolya (ORCID Profile 0000-0003-3241-6839)
Dai, Zhuangzhuang (ORCID Profile 0000-0002-6098-115X)

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