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Ethical rules
Published in Vahap Tecim, Sezer Bozkus Kahyaoglu, Artificial Intelligence Perspective for Smart Cities, 2023
Types of AI are categorised under three categories (Joshi, 2019):Artificial Narrow Intelligence (which refers to the existing AI technologies today)Artificial General Intelligence (AI agents that can perceive and learn just like the human brain)Artificial Superintelligence (AI agents that have a human level of intelligence and even can surpass human abilities)AI mentioned in the third category has superior intelligence and can make its own decisions is essential in terms of both ethics and safety (Bostrom and Yudkowsky, 2014). Therefore, singularity is another factor that shapes AI and ethical literature (Kurzweil, 2006). For instance, in 2017, citizenship of Saudi Arabia was given to the robot Sophia, and it became the first robot to be given legal personhood anywhere in the World. Moreover, why she did not even wear the black chador like Arab women became a debate (Sini, 2016). So, the main question arises as: “What is the status of these future residents?”.
Sensors, Embedded Systems, and IoT Components
Published in Mukesh Kumar Awasthi, Ravi Tomar, Maanak Gupta, Mathematical Modeling for Intelligent Systems, 2023
ML is the backbone of AI. The first half of ML entails utilizing algorithms to find meaning in random and disordered data, while the second half entails using learning algorithms to discover the relationship between that knowledge and improve the learning process. As a result, the overarching purpose of ML is to increase the computers’ performance on a certain task, such as stock market prediction. More than 80% of commercial IoT initiatives will have an AI component by 2022 (Internet of things (IoT), 2019). A self-driving car is an example of advanced AI that uses a combination of computer vision, image recognition, and deep learning to drive a vehicle while staying in a defined lane and avoiding obstacles like pedestrians. Healthcare, education, finance, law, and manufacturing are just a few of the fields where AI is being used to benefit both businesses and customers. AI is used in a variety of technologies, including automation, ML, machine vision, natural language processing, and robotics. AI raises ethical, legal, and security concerns. If an autonomous vehicle is involved in an accident, for example, it is difficult to determine who is to blame. In addition, advanced ML technologies are being used by hackers to obtain access to sensitive networks. Despite the dangers, the usage of AI tools is governed by few restrictions. Experts assure us, however, that AI will simply improve products and services in the near future, not replace us, the people.
Nomadic Artificial Intelligence and Royal Research Councils
Published in Maurizio Tinnirello, The Global Politics of Artificial Intelligence, 2022
The same report recommends “[o]ne way to elicit frequent judgements is to run ‘forecasting tournaments' such as prediction markets, in which participants have financial incentives to make accurate predictions”67—thus, bringing us back to the strategies advanced by the State in order to incentivise scientific progress in a regulated manner. Such attempts at regulatory frameworks of AI suffered from a very vague understanding of what constitutes AI—in a sense, they were more speculation-based than evidence-based. AI can be seen as an umbrella term containing many component technologies and many output technologies which might call for regulation or are already being regulated (e.g. autonomous weapons in terms of future regulation and/or the General Data Protection Regulation framework of current regulation).
Impact of AI and COVID-19 on manufacturing systems: An Asia Pacific Perspective on the two Competing exigencies
Published in Production & Manufacturing Research, 2023
Malini Mittal Bishnoi, Swamynathan Ramakrishnan, Swathi Suraj, Ashish Dwivedi
Artificial Intelligence (AI) refers to a field of science that focuses on creating computer hardware or software capable of exhibiting characteristics associated with human intelligence (Lucci et al., 2022). With the turbulence of COVID-19, the Asia Pacific (APAC) region has witnessed a steeper and faster intervention of AI. APAC countries are factories of the world with forty-eight countries and almost sixty percent of the world population contributing to more than fifty percent of the world’s GDP, APAC is seen as a significant provider to world economy (Leke et al., 2018). Currently, the region is gearing up for exploitation of opportunities created inadvertently by the pandemic and the increasing technological alteration to AI. With a $48.45 trillion GDP output and holding 59.76% of the world population, the Asian continent is the most vulnerable part of the world in case of any economic chaos and investment turbulences (Andersson, 2022).
The Use of Responsible Artificial Intelligence Techniques in the Context of Loan Approval Processes
Published in International Journal of Human–Computer Interaction, 2023
Erasmo Purificato, Flavio Lorenzo, Francesca Fallucchi, Ernesto William De Luca
Due to this ubiquity, concerns are starting to arise about whether the development of AI systems, and the decisions made by them, should be based on a set of ethical principles to promote transparency, social equity, sustainability, and avoid social injustices. In particular, considering our case study on automatic predictions in loan approval processes, several critical elements in the European law have to be taken into account when individuals are assessed by such an algorithm (Commission, n.d.; Goodman & Flaxman, 2017): their rights to not be subject to an automated decision in the first place, their right to get an explanation of the decision and their right to non-discrimination. As well-reported in the article written by Angel Perez for 2021.AI, “Fairness in Machine Learning,”1 ML practitioners should develop models that, by design, take care of possible discriminations and that are explainable to users, requiring high transparency and reproducibility throughout the whole ML workflow.
Application of UAVs in the mining industry and towards an integrated UAV-AI-MR technology for mine rehabilitation surveillance
Published in Mining Technology, 2023
Phillip Stothard, Roohollah Shirani Faradonbeh
Artificial intelligence (AI) can be defined as the capability of a computer or computer-controlled system to conduct tasks with minimal human intervention in an intelligent manner. Indeed, AI promotes machines/robots to mimic human brain activities, such as perception, decision-making, and feedback (Russell and Norvig 2022). Due to significant progress in sensor technology, which has given rise to increased data quantity and variety, and the increase in processing power in recent decades, robust AI algorithms in different industries, specifically in the mining industry, have been utilized extensively for operational decision-making, performance evaluation, and automation (Ali and Frimpong 2020; Shirani Faradonbeh et al. 2022). AI and its related algorithms play a critical role in the fields of UAV and simulation within mining operations. Thanks to computer vision and image processing algorithms, it is possible to extract valuable information from UAV images resulting in innovative functions, such as autonomous mapping, object/individual detection, motion analysis, etc. For instance, UAVs equipped with a Vision Processing Unit (VPU) and neural computer chips can perform deep-learning calculations and feature detection locally, in semi-real-time, and without an internet connection (Al-Turjman and Zahmatkesh 2020).