Artificial Intelligence

2021 ◽  
pp. 325-334
Author(s):  
Laszlo Solymar
Keyword(s):  
Artificial Intelligence ◽  
Human Intelligence ◽  
Autonomous Cars ◽  
Driverless Cars ◽  
The Future ◽  
The Moment

The claims of artificial intelligence are criticized. Most of the claims are regarded as hype or simple examples of automation. The progress of machines in playing games and beating world champions is described, but the artificial intelligence is still thought not to represent human intelligence. It is concluded that the programs are intelligent but not the machines. A 1921 play by Capek coining the word and introducing the modern interpretation of robots is analysed. Examples of robots and of virtual assistants in service at the moment are provided. The future of driverless cars is discussed, and it is concluded that fully autonomous cars are still many decades, rather than years, away.

scholarly journals Criminal Liability of the Artificial Intelligence

2020 ◽  
Vol 159 ◽  
pp. 04025
Author(s):  
Danila Kirpichnikov ◽  
Albert Pavlyuk ◽  
Yulia Grebneva ◽  
Hilary Okagbue
Keyword(s):  
Artificial Intelligence ◽  
Criminal Liability ◽  
Human Intelligence ◽  
Coercive Measures ◽  
Self Development ◽  
The Future ◽  
Almost All ◽  
Self Learning ◽  
New Formation

Today, artificial intelligence (hereinafter – AI) becomes an integral part of almost all branches of science. The ability of AI to self-learning and self-development are properties that allow this new formation to compete with the human intelligence and perform actions that put it on a par with humans. In this regard, the author aims to determine whether it is possible to apply criminal liability to AI, since the latter is likely to be recognized as a subject of legal relations in the future. Based on a number of examinations and practical examples, the author makes the following conclusion: AI is fundamentally capable of being criminally liable; in addition, it is capable of correcting its own behavior under the influence of coercive measures.

Artificial Intelligence Surpassing Human Intelligence: Factual or Hoax

2020 ◽  
Author(s):  
Sana Khanam ◽  
Safdar Tanweer ◽  
Syed Khalid
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Research Paper ◽  
Human Intelligence ◽  
Technological Changes ◽  
The Future ◽  
The Subject ◽  
Trending Topics ◽  
Near Future

Abstract Artificial intelligence is one of the most trending topics in the field of Computer Science which aims to make machines and computers ‘smart’. There are multiple diverse technical and specialized research associated with it. Due to the accelerating rate of technological changes, artificial intelligence has taken over a lot of human jobs and is giving excellent results that are more efficient and effective, than humans. However, a lot of time there has been a concern about the following: will artificial intelligence surpass human intelligence in the near future? Are computers’ ever accelerating abilities to outpace human jobs and skills a matter of concern? The different views and myths on the subject have made it even a more than just a topic of discussion. In this research paper, we will study the existing facts and literature to understand the true definitions of artificial intelligence (AI) and human intelligence (HI) by classifying each of its types separately and analyzing the extent of their full capabilities. Later, we will discuss the possibilities if AI eventually can replace human jobs in the market. Finally, we will synthesize and summarize results and findings of why artificial intelligence cannot surpass human intelligence completely in the future.

scholarly journals Future trends: businness view and high tech

2020 ◽  
pp. 6
Author(s):  
José Rafael Marques da Silva ◽  
Manuela Correia
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Business Models ◽  
High Tech ◽  
Human Intelligence ◽  
Future Trends ◽  
Arable Crops ◽  
Food Traceability ◽  
Slide Presentation ◽  
The Future

This topic presents the macro-design of SPA that will surely appear in the coming years and also the future technological trends in SPA applied to viticulture and arable crops. A vision of the future of SPA is presented in three layers: i) human intelligence (related to soil, plants, climate, pests, diseases, environment, food production, fibre and energy) on top; ii) artificial intelligence (related to hardware, communications, data) in the middle; iii) and again human intelligence on the bottom (consumers, business models, transparency, food traceability). “Big Data” challenges are discussed regarding the specific needs of agriculture. The technological groups identified in a Foresight Analysis report are discussed and the future technological trends on arable crops and vineyards are presented. In this topic, materials include a slide presentation, a document text and the Foresight Analysis report.

Editorial for the Special Section on Humans, Algorithms, and Augmented Intelligence: The Future of Work, Organizations, and Society

2021 ◽  
Vol 32 (3) ◽  
pp. 675-687
Author(s):  
Hemant Jain ◽  
Balaji Padmanabhan ◽  
Paul A. Pavlou ◽  
T. S. Raghu
Keyword(s):  
Artificial Intelligence ◽  
Special Section ◽  
Human Intelligence ◽  
Work Organizations ◽  
Research Directions ◽  
Research Issues ◽  
Future Of Work ◽  
The Future ◽  
Recent Developments ◽  
Working Together

Recent developments in artificial intelligence (AI) have increased interest in combining AI with human intelligence to develop superior systems that augment human and artificial intelligence. In this paper, augmented intelligence informally means computers and humans working together, by design, to enhance one another, such that the intelligence of the resulting system improves. Intelligence augmentation (IA) can pool the joint intelligence of humans and computers to transform individual work, organizations, and society. Notably, applications of IA are beginning to emerge in several domains, such as cybersecurity, privacy, counterterrorism, and healthcare, among others. We provide a brief summary of papers in this special section that represent early attempts to address some of the rapidly emerging research issues. We also present a framework to guide research on IA and advocate for the important implications of IA for the future of work, organizations, and society. We conclude by outlining promising research directions based on this framework for the information systems and related disciplines.

Artificial Intelligence in Medicine

2021 ◽  
pp. 49-68
Author(s):  
Gia Merlo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
New Technologies ◽  
New Technology ◽  
Technological System ◽  
Medical Professionals ◽  
Human Intelligence ◽  
Connected Health ◽  
The Future

Disruptive forces are challenging the future of medicine. One of the key forces bringing change is the development of artificial intelligence (AI). AI is a technological system designed to perform tasks that are commonly associated with human intelligence and ability. Machine learning is a subset of AI, and deep learning is an aspect of machine learning. AI can be categorized as either applied or generalized. Machine learning is key to applied AI; it is dynamic and can become more accurate through processing different results. Other new technologies include blockchain, which allows for the storage of all of patients’ records to create a connected health ecosystem. Medical professionals ought to be willing to accept new technology, while also developing the skills that technology will not be able to replicate.

Artificial Intelligence Emerges

2020 ◽  
pp. 75-92
Author(s):  
Chris Bleakley
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Program ◽  
Human Intelligence ◽  
Board Game ◽  
Mathematics Textbook ◽  
The Future ◽  
The Right ◽  
Intelligent Computer

Chapter 5 delves into the origins of artificial intelligence (AI). By the end of the 1940s, a few visionaries realised that computers were more than mere automatic calculators. They believed that computers running the right algorithms could perform tasks previously thought to require human intelligence. Christopher Strachey completed the first artificially intelligent computer program in 1952. The program played the board game Checkers. Arthur Samuel of IBM extended and improved on Strachey’s program by including machine learning - the ability of a program to learn from experience. A team from Carnegie Melon University developed the first computer program that could perform algebra. The program eventually reproduced 38 of the 52 proofs in a classic mathematics textbook. Flushed by these successes, serious scientists made wildly optimistic pronouncements about the future of AI. In the event, project after project failed to deliver and the first “AI winter” set in.

scholarly journals Human vs machine intelligence:

2019 ◽  
Vol 9 (1) ◽  
pp. 17-24
Author(s):  
Thomas Bolander
Keyword(s):  
Artificial Intelligence ◽  
Machine Intelligence ◽  
Human Intelligence ◽  
The Future ◽  
The Impact

To be able to predict the impact of artificial intelligence (AI) on the required human competences of the future, it is firstand foremost necessary to get an overview of what AI at all is and how it differs from human intelligence. The main goalof this paper is to provide such an overview to readers who are not experts in the area. The focus of the paper is on thesimilarities and differences between human and machine intelligence, since understanding that is of essential importanceto be able to predict which human tasks and jobs are likely to be automatised by AI - and what consequences it will have.

Teaching and Explanation: Aligning Priors between Machines and Humans

2021 ◽  
pp. 171-196
Author(s):  
José Hernández-Orallo ◽  
Cèsar Ferri
Keyword(s):  
Artificial Intelligence ◽  
Human Perception ◽  
Human Learning ◽  
Machine Intelligence ◽  
Human Intelligence ◽  
Machine Perception ◽  
Explainable Artificial Intelligence ◽  
The Future ◽  
The Way

Machine intelligence differs signficantly from human intelligence. While human perception has similarities to the way machine perception works, human learning is mostly a directed process, guided by other people: parents, teachers, ... The area of machine teaching is becoming increasingly popular as a different paradigm for making machines learn. In this chapter, we start from recent results in machine teaching that show the relevance of prior alignment between humans and machines. From here, we focus on the scenario when a machine has to teach humans, a situation more and more common in the future. Specifically, we analyse how machine teaching relates to explainable artificial intelligence, and how simplicity priors play a role beyond intelligibility. We illustrate this with a general teaching protocol and a few examples in several representation languages: feature-value vectors and sequences. Some straightforward experiments with humans indicate when a strong simplicity prior is --and is not-- sufficient.

Administration of Mega and Open Universities With Technological Singularity Beyond Master-Human

2021 ◽  
pp. 537-544
Author(s):  
Serap Sisman-Ugur ◽  
Gulsun Kurubacak
Keyword(s):  
Artificial Intelligence ◽  
Distance Learning ◽  
Learning Environments ◽  
Human Intelligence ◽  
Learning Practices ◽  
The Future ◽  
Technological Singularity ◽  
Open And Distance Learning ◽  
Study Participants

The aim of this study is to foresee a futuristic view of how open universities can achieve their sustainability in the context of technological singularity. Technological singularity predicts that artificial intelligence will prevent human intelligence in the future. Not only can artificial intelligence radically change human habits, but it can also alter learning practices. The foundation of a revolutionary transformation on humanity learning will be established for both the open universities and for the technological singularity beyond master-human. Thus, open universities are not only sustainable, but, at the same time, they can be transformed into ecological learning environments. The framework of the internalizations and predictions of the study participants on open and distance learning environments will help us save open universities in the future.

Sign in / Sign up

Export Citation Format

Share Document