scholarly journals AI for Everyone? Critical Perspectives

2021 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Data Driven ◽  
Technological Determinism ◽  
New Era ◽  
The Right ◽  
Critical Perspectives

We are entering a new era of technological determinism and solutionism in which governments and business actors are seeking data-driven change, assuming that Artificial Intelligence is now inevitable and ubiquitous. But we have not even started asking the right questions, let alone developed an understanding of the consequences. Urgently needed is debate that asks and answers fundamental questions about power. This book brings together critical interrogations of what constitutes AI, its impact and its inequalities in order to offer an analysis of what it means for AI to deliver benefits for everyone. The book is structured in three parts: Part 1, AI: Humans vs. Machines, presents critical perspectives on human-machine dualism. Part 2, Discourses and Myths About AI, excavates metaphors and policies to ask normative questions about what is ‘desirable’ AI and what conditions make this possible. Part 3, AI Power and Inequalities, discusses how the implementation of AI creates important challenges that urgently need to be addressed. Bringing together scholars from diverse disciplinary backgrounds and regional contexts, this book offers a vital intervention on one of the most hyped concepts of our times.

scholarly journals Adoption of Big Data by Global Chemical Industries

2021 ◽  
Author(s):  
Ashiff Khan ◽  
A Seetharaman ◽  
Abhijit Dasgupta
Keyword(s):  
Big Data ◽  
Data Science ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Time Data ◽  
New Era ◽  
Potential Applications ◽  
Data Driven Approach ◽  
Process Plants ◽  
The Right

The new era of Big Data (BD) is influencing the chemical industries tremendously, providing several opportunities to reshape the way they operate and for shifting towards smart manufacturing. Given the availability of free software, and the large amount of real-time data generated and stored in process plants why many chemical industries are still not fully adopting BD? The industry is just starting to realize the importance of a large amount of data that they own to make the right decisions and to support their strategies. This article is exploring the importance of professional competencies and data science that influence BD in chemical industries for shifting towards smart manufacturing in a fast and reliable manner. This article utilizes a literature review and identifies potential applications in the chemical industry to shift from conventional methods towards a data-driven approach.

scholarly journals Artificial Intelligence: Serving American Security and Chinese Ambitions

2020 ◽  
Vol 4 (3) ◽  
pp. 42-52
Author(s):  
H. Obeid ◽  
F Hillani, ◽  
R. Fakih ◽  
K. Mozannar
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Technological Development ◽  
The United States ◽  
New Era ◽  
The Us ◽  
The One ◽  
The Right ◽  
Technological Strength

In recent years artificial intelligence has entered a new era, which gives rise to many hopes for powerful states such as the United States and China. In this paper, we analyze the importance and role of artificial intelligence in technological development in each of the two countries on the one hand, and its influence on China-American relations in terms of technological and geopolitical conflict. To get the right results, we rely on a literature review of dozens of articles published on the phenomenon in order to compare the power of artificial intelligence between the United States and China where we found that the US still has technological strength, especially in the field of artificial intelligence, but we can say that a large force is beginning pose a threat for it which is China that has great technological capabilities so, we can say that the United States should work more in this field. Also, we found that artificial intelligence has a primary goal in both countries, it helps China to achieve its ambitions to be the leader of the world, and this intelligence, on the other hand, provides protection and security to the United States. This paper is divided into three sections. The first section focuses on the importance of artificial intelligence in achieving China’s ambitions, the second section explains the role of artificial intelligence in the US protection service, and the third section describes the technological and geopolitical conflict resulting from the competition in artificial intelligence between these two countries. Keywords: Artificial intelligence, United States, China, Conflict, leader.

scholarly journals Artificial Intelligence-Assisted Surgery: Potential and Challenges

2020 ◽  
Vol 36 (6) ◽  
pp. 450-455
Author(s):  
Sebastian Bodenstedt ◽  
Martin Wagner ◽  
Beat Peter Müller-Stich ◽  
Jürgen Weitz ◽  
Stefanie Speidel
Keyword(s):  
Artificial Intelligence ◽  
Improve Patient Care ◽  
Data Driven ◽  
Full Potential ◽  
Computer Scientists ◽  
Close Cooperation ◽  
Scientists And Engineers ◽  
The Right ◽  
Cognitive Robotic ◽  
Improve Patient

<b><i>Background:</i></b> Artificial intelligence (AI) has recently achieved considerable success in different domains including medical applications. Although current advances are expected to impact surgery, up until now AI has not been able to leverage its full potential due to several challenges that are specific to that field. <b><i>Summary:</i></b> This review summarizes data-driven methods and technologies needed as a prerequisite for different AI-based assistance functions in the operating room. Potential effects of AI usage in surgery will be highlighted, concluding with ongoing challenges to enabling AI for surgery. <b><i>Key Messages:</i></b> AI-assisted surgery will enable data-driven decision-making via decision support systems and cognitive robotic assistance. The use of AI for workflow analysis will help provide appropriate assistance in the right context. The requirements for such assistance must be defined by surgeons in close cooperation with computer scientists and engineers. Once the existing challenges will have been solved, AI assistance has the potential to improve patient care by supporting the surgeon without replacing him or her.

scholarly journals La inteligencia artificial en el proceso penal español: un analisis de su admisibilidad sobre la base de los derechos fundamentales implicados

2020 ◽  
pp. 531
Author(s):  
Iñigo De Miguel Beriain ◽  
Miren Josune Pérez Estrada
Keyword(s):  
Artificial Intelligence ◽  
Supreme Court ◽  
Due Process ◽  
Criminal Procedure ◽  
Intelligent Algorithm ◽  
New Era ◽  
The Law ◽  
The Right ◽  
First Time

En julio de 2016, el Tribunal Supremo de Wisconsin emitió una sentencia llamada a pasar a la historia. Por primera un tribunal de esa categoría utilizaba un algoritmo inteligente graduar la sanción a un reo. Se abría así una nueva era en la que los juristas tendremos que empezar a discutir sobre los cambios que introducirá esta impactante tecnología en nuestro modo de conformar el Derecho. Este artículo pretende contribuir a esta apasionante tarea acometiendo una discusión absolutamente trascendental al respecto: la constitucionalidad o no del uso de mecanismos relacionados con la inteligencia artificial en el proceso penal. Con tal fin, haremos especial hincapié en la importancia del derecho a un proceso con todas las garantías, y en las implicaciones que el respeto a dicho precepto contiene para la materia que nos ocupa. In July 2016, the Wisconsin Supreme Court issued a ruling that is set to become history. For the first time a court of such importance used an intelligent algorithm to grade a defendant punishment. This opened a new era in which we, the jurists, will have to begin to discuss the changes that this impressive technology will introduce in our way of shaping the Law. This article aims to contribute to this exciting task by undertaking an absolutely transcendental discussion on a key topic: the constitutionality of the use of mechanisms related to artificial intelligence in criminal procedure. To this purpose, we will emphasize the importance of the right to due process and the implications that the respect of this provision implies for the issue at stake.

The Oxford Handbook of Ethics of AI

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Rapid Development ◽  
Data Driven ◽  
International Human Rights Law ◽  
Human Knowledge ◽  
Human Rights Law ◽  
Ai Ethics ◽  
And Behavior ◽  
Control Complex

This book explores the intertwining domains of artificial intelligence (AI) and ethics—two highly divergent fields which at first seem to have nothing to do with one another. AI is a collection of computational methods for studying human knowledge, learning, and behavior, including by building agents able to know, learn, and behave. Ethics is a body of human knowledge—far from completely understood—that helps agents (humans today, but perhaps eventually robots and other AIs) decide how they and others should behave. Despite these differences, however, the rapid development in AI technology today has led to a growing number of ethical issues in a multitude of fields, ranging from disciplines as far-reaching as international human rights law to issues as intimate as personal identity and sexuality. In fact, the number and variety of topics in this volume illustrate the width, diversity of content, and at times exasperating vagueness of the boundaries of “AI Ethics” as a domain of inquiry. Within this discourse, the book points to the capacity of sociotechnical systems that utilize data-driven algorithms to classify, to make decisions, and to control complex systems. Given the wide-reaching and often intimate impact these AI systems have on daily human lives, this volume attempts to address the increasingly complicated relations between humanity and artificial intelligence. It considers not only how humanity must conduct themselves toward AI but also how AI must behave toward humanity.

scholarly journals How Do Machines Learn? Artificial Intelligence as a New Era in Medicine

2021 ◽  
Vol 11 (1) ◽  
pp. 32
Author(s):  
Oliwia Koteluk ◽  
Adrian Wartecki ◽  
Sylwia Mazurek ◽  
Iga Kołodziejczak ◽  
Andrzej Mackiewicz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Health Care ◽  
Medical Data ◽  
General Process ◽  
New Era ◽  
Automated Evaluation ◽  
Machine Learning Applications ◽  
And Training ◽  
Current Standards

With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to make faster and more correct decisions and improving current standards of treatment. Today, machines can analyze, learn, communicate, and understand processed data and are used in health care increasingly. This review explains different models and the general process of machine learning and training the algorithms. Furthermore, it summarizes the most useful machine learning applications and tools in different branches of medicine and health care (radiology, pathology, pharmacology, infectious diseases, personalized decision making, and many others). The review also addresses the futuristic prospects and threats of applying artificial intelligence as an advanced, automated medicine tool.

scholarly journals The core academic and scientific disciplines underlying data-driven smart sustainable urbanism: an interdisciplinary and transdisciplinary framework

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
The Body ◽  
Data Driven ◽  
New Era ◽  
The Core ◽  
Sustainable Urbanism ◽  
Scientific Disciplines ◽  
Specific Direction ◽  
Research Problems ◽  
Urban Planning And Development ◽  
Application Potential

AbstractA new era is presently unfolding wherein both smart urbanism and sustainable urbanism processes and practices are becoming highly responsive to a form of data-driven urbanism under what has to be identified as data-driven smart sustainable urbanism. This flourishing field of research is profoundly interdisciplinary and transdisciplinary in nature. It operates out of the understanding that advances in knowledge necessitate pursuing multifaceted questions that can only be resolved from the vantage point of interdisciplinarity and transdisciplinarity. This implies that the research problems within the field of data-driven smart sustainable urbanism are inherently too complex and dynamic to be addressed by single disciplines. As this field is not a specific direction of research, it does not have a unitary disciplinary framework in terms of a uniform set of the academic and scientific disciplines from which the underlying theories can be drawn. These theories constitute a unified foundation for the practice of data-driven smart sustainable urbanism. Therefore, it is of significant importance to develop an interdisciplinary and transdisciplinary framework. With that in regard, this paper identifies, describes, discusses, evaluates, and thematically organizes the core academic and scientific disciplines underlying the field of data-driven smart sustainable urbanism. This work provides an important lens through which to understand the set of established and emerging disciplines that have high integration, fusion, and application potential for informing the processes and practices of data-driven smart sustainable urbanism. As such, it provides fertile insights into the core foundational principles of data-driven smart sustainable urbanism as an applied domain in terms of its scientific, technological, and computational strands. The novelty of the proposed framework lies in its original contribution to the body of foundational knowledge of an emerging field of urban planning and development.

Impact of Big Data and Artificial Intelligence on Industry: Developing a Workforce Roadmap for a Data Driven Economy

2021 ◽  
Author(s):  
Marina Johnson ◽  
Rashmi Jain ◽  
Peggy Brennan-Tonetta ◽  
Ethne Swartz ◽  
Deborah Silver ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Data Driven

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

scholarly journals An Artificial Intelligence of Things-Based Picking Algorithm for Online Shop in the Society 5.0’s Context

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2813
Author(s):  
Muslikhin Muslikhin ◽  
Jenq-Ruey Horng ◽  
Szu-Yueh Yang ◽  
Ming-Shyan Wang ◽  
Baiti-Ahmad Awaluddin
Keyword(s):  
Artificial Intelligence ◽  
System Performance ◽  
Industry 4.0 ◽  
Online Shopping ◽  
Robotic Manipulators ◽  
Data Driven ◽  
Key Points ◽  
Detection And Localization ◽  
Picking System

In this study, an Artificial Intelligence of Things (AIoT)-based automated picking system was proposed for the development of an online shop and the services for automated shipping systems. Speed and convenience are two key points in Industry 4.0 and Society 5.0. In the context of online shopping, speed and convenience can be provided by integrating e-commerce platforms with AIoT systems and robots that are following consumers’ needs. Therefore, this proposed system diverts consumers who are moved by AIoT, while robotic manipulators replace human tasks to pick. To prove this idea, we implemented a modified YOLO (You Only Look Once) algorithm as a detection and localization tool for items purchased by consumers. At the same time, the modified YOLOv2 with data-driven mode was used for the process of taking goods from unstructured shop shelves. Our system performance is proven by experiments to meet the expectations in evaluating efficiency, speed, and convenience of the system in Society 5.0’s context.

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