AI in Medicine

2021 ◽  
pp. 83-92
Author(s):  
Angeliki Kerasidou ◽  
Xaroula (Charalampia) Kerasidou
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Machines ◽  
To Come ◽  
Healthcare Values

This chapter explores the use of artificial intelligence in medicine. AI promises major benefits for healthcare. But along with the benefits come risks. Not so much the risk of powerful super-intelligent machines taking over, but the risk of structural injustices, biases, and inequalities being perpetuated in a system that cannot be challenged because nobody actually knows how the algorithms work. Or the risk that there might be no doctor or nurse present to hold your hand and reassure you when you are at your most vulnerable. There are many initiatives to come up with ethical or trustworthy AI and these efforts are important. Yet we should demand more than this. Technological solutionism and the urge to “move fast and break things” often dominate the tech industry but are inappropriate for the healthcare context and incompatible with basic healthcare values of empathy, solidarity, and trust.

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

2019 ◽  
pp. 21-30
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Interaction Analysis ◽  
Educational Data Mining ◽  
Main Task ◽  
Intellectual System ◽  
Will Force ◽  
To Come ◽  
Artificial Intelligence Systems

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

AI Narratives

2020 ◽  
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Ancient Greece ◽  
Historical Overview ◽  
Intelligent Machines ◽  
Narrative History ◽  
History Of ◽  
Imaginative Thinking ◽  
The Relationship ◽  
Insight Into

This book is the first to examine the history of imaginative thinking about intelligent machines. As real artificial intelligence (AI) begins to touch on all aspects of our lives, this long narrative history shapes how the technology is developed, deployed, and regulated. It is therefore a crucial social and ethical issue. Part I of this book provides a historical overview from ancient Greece to the start of modernity. These chapters explore the revealing prehistory of key concerns of contemporary AI discourse, from the nature of mind and creativity to issues of power and rights, from the tension between fascination and ambivalence to investigations into artificial voices and technophobia. Part II focuses on the twentieth and twenty-first centuries in which a greater density of narratives emerged alongside rapid developments in AI technology. These chapters reveal not only how AI narratives have consistently been entangled with the emergence of real robotics and AI, but also how they offer a rich source of insight into how we might live with these revolutionary machines. Through their close textual engagements, these chapters explore the relationship between imaginative narratives and contemporary debates about AI’s social, ethical, and philosophical consequences, including questions of dehumanization, automation, anthropomorphization, cybernetics, cyberpunk, immortality, slavery, and governance. The contributions, from leading humanities and social science scholars, show that narratives about AI offer a crucial epistemic site for exploring contemporary debates about these powerful new technologies.

scholarly journals The Role of Artificial Intelligence in Fighting the COVID-19 Pandemic

2021 ◽  
Author(s):  
Francesco Piccialli ◽  
Vincenzo Schiano di Cola ◽  
Fabio Giampaolo ◽  
Salvatore Cuomo
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trials ◽  
Digital Transformation ◽  
Daily Activities ◽  
Commercial Vehicles ◽  
Human Skills ◽  
To Come ◽  
Complex Scenario ◽  
The Impact

AbstractThe first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.

Artificial intelligence: criminal and procedural aspects

2021 ◽  
pp. 75-89
Author(s):  
Igor I. Kartashov ◽  
Ivan I. Kartashov
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Human Beings ◽  
Criminal Proceedings ◽  
Legal Advice ◽  
Judicial Practice ◽  
Legal Expert ◽  
To Come ◽  
Definition Of ◽  
Self Learning

For millennia, mankind has dreamed of creating an artificial creature capable of thinking and acting “like human beings”. These dreams are gradually starting to come true. The trends in the development of modern so-ciety, taking into account the increasing level of its informatization, require the use of new technologies for information processing and assistance in de-cision-making. Expanding the boundaries of the use of artificial intelligence requires not only the establishment of ethical restrictions, but also gives rise to the need to promptly resolve legal problems, including criminal and proce-dural ones. This is primarily due to the emergence and spread of legal expert systems that predict the decision on a particular case, based on a variety of parameters. Based on a comprehensive study, we formulate a definition of artificial intelligence suitable for use in law. It is proposed to understand artificial intelligence as systems capable of interpreting the received data, making optimal decisions on their basis using self-learning (adaptation). The main directions of using artificial intelligence in criminal proceedings are: search and generalization of judicial practice; legal advice; preparation of formalized documents or statistical reports; forecasting court decisions; predictive jurisprudence. Despite the promise of using artificial intelligence, there are a number of problems associated with a low level of reliability in predicting rare events, self-excitation of the system, opacity of the algorithms and architecture used, etc.

scholarly journals Artificial Intelligence (AI) and Its Associated Ethical Issues

ICR Journal ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 124-126
Author(s):  
Shahino Mah Abdulllah
Keyword(s):  
Artificial Intelligence ◽  
Real World ◽  
Ethical Issues ◽  
Economic Inequality ◽  
Human Behaviour ◽  
Intelligent Machines ◽  
Normal Shift

The adoption of AI in many industries has been regarded by some as a threat to low- and middle-skill workers, as it will drastically cut down reliance on the human workforce. Besides unemployment, there are also concerns about rising economic inequality caused by AI-driven companies. With fewer employees, these companies could gain a disproportionate advantage over conventional companies that still depend on normal, shift-based systems. There is also the issue that some AI bots have achieved the capability to interact with humans and build relationships through conversations. This influential communication could eventually enable these bots to affect human behaviour and possibly trigger certain actions. Significantly, therefore, such intelligent machines are not immune to mistakes and confusion since not all possible examples of real world interaction are covered during their training; this weakness could be manipulated to fulfil certain ends. Also, Al cannot be expected to be entirely fair and neutral, since it is dependent on human programmers, who have their own interests and whims.

scholarly journals El sesgo de la máquina en la toma de decisiones en el proceso penal.

2020 ◽  
Vol 6 (2) ◽  
pp. 54-71
Author(s):  
Raquel Borges Blázquez
Keyword(s):  
Artificial Intelligence ◽  
The Other ◽  
Human Being ◽  
Criminal Process ◽  
Ethical Problems ◽  
Intelligent Machines ◽  
Other Hand ◽  
Toma De Decisiones ◽  
Legal Thinking ◽  
The One

Artificial intelligence has countless advantages in our lives. On the one hand, computer’s capacity to store and connect data is far superior to human capacity. On the other hand, its “intelligence” also involves deep ethical problems that the law must respond to. I say “intelligence” because nowadays machines are not intelligent. Machines only use the data that a human being has previously offered as true. The truth is relative and the data will have the same biases and prejudices as the human who programs the machine. In other words, machines will be racist, sexist and classist if their programmers are. Furthermore, we are facing a new problem: the difficulty to understand the algorithm of those who apply the law.This situation forces us to rethink the criminal process, including artificial intelligence and spinning very thinly indicating how, when, why and under what assumptions we can make use of artificial intelligence and, above all, who is going to program it. At the end of the day, as Silvia Barona indicates, perhaps the question should be: who is going to control global legal thinking?

Artificially Intelligent Physiotherapy

2021 ◽  
Vol 10 (1) ◽  
pp. 77-88
Author(s):  
Sachin Pandurang Godse ◽  
Shalini Singh ◽  
Sonal Khule ◽  
Shubham Chandrakant Wakhare ◽  
Vedant Yadav
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Range Of Motion ◽  
Real Time ◽  
Severe Pain ◽  
User Performance ◽  
Computer Aided ◽  
To Come ◽  
And Performance ◽  
At Home

Physiotherapy is the trending medication for curing bone-related injuries and pain. In many cases, due to sudden jerks or accidents, the patient might suffer from severe pain. Therefore, it is the miracle medication for curing patients. The aim here is to build a framework using artificial intelligence and machine learning for providing patients with a digitalized system for physiotherapy. Even though various computer-aided assessment of physiotherapy rehabilitation exist, recent approaches for computer-aided monitoring and performance lack versatility and robustness. In the authors' approach is to come up with proposition of an application which will record patient physiotherapy exercises and also provide personalized advice based on user performance for refinement of therapy. By using OpenPose Library, the system will detect angle between the joints, and depending upon the range of motion, it will guide patients in accomplishing physiotherapy at home. It will also suggest to patients different physio-exercises. With the help of OpenPose, it is possible to render patient images or real-time video.

A Behavioral Economics Approach to Digitalization

2019 ◽  
pp. 107-122
Author(s):  
Dirk Beerbaum ◽  
Julia Margarete Puaschunder
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Social Media ◽  
Behavioral Economics ◽  
Field Research ◽  
Learning Systems ◽  
Business Reporting ◽  
Intelligent Machines ◽  
Private Investors ◽  
Coding Rules

Technological improvement in the age of information has increased the possibilities to control the innocent social media users or penalize private investors and reap the benefits of their existence in hidden persuasion and discrimination. This chapter takes as a case the transparency technology XBRL (eXtensible Business Reporting Language), which should make data more accessible as well as usable for private investors. Considering theoretical literature and field research, a representation issue for principles-based accounting taxonomies exists, which intelligent machines applying artificial intelligence (AI) nudge to facilitate decision usefulness. This chapter conceptualizes ethical questions arising from the taxonomy engineering based on machine learning systems and advocates for a democratization of information, education, and transparency about nudges and coding rules.

Predictive Analysis for Digital Marketing Using Big Data

2017 ◽  
pp. 259-283
Author(s):  
Balamurugan Balusamy ◽  
Priya Jha ◽  
Tamizh Arasi ◽  
Malathi Velu
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Big Data ◽  
Statistical Analysis ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Predictive Analysis ◽  
Cognitive Computing ◽  
Internet Resources ◽  
To Come

Big data analytics in recent years had developed lightning fast applications that deal with predictive analysis of huge volumes of data in domains of finance, health, weather, travel, marketing and more. Business analysts take their decisions using the statistical analysis of the available data pulled in from social media, user surveys, blogs and internet resources. Customer sentiment has to be taken into account for designing, launching and pricing a product to be inducted into the market and the emotions of the consumers changes and is influenced by several tangible and intangible factors. The possibility of using Big data analytics to present data in a quickly viewable format giving different perspectives of the same data is appreciated in the field of finance and health, where the advent of decision support system is possible in all aspects of their working. Cognitive computing and artificial intelligence are making big data analytical algorithms to think more on their own, leading to come out with Big data agents with their own functionalities.

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