Creativity, Human and Transhuman

2018 ◽  
Vol 22 (2) ◽  
pp. 158-190
Author(s):  
Eduardo R. Cruz ◽  
Keyword(s):  
Pretend Play ◽  
Human Enhancement ◽  
Human Beings ◽  
Human Machine Interaction ◽  
Human Creativity ◽  
Technological Interventions ◽  
Delayed Maturation ◽  
Machine Interaction ◽  
Philosophical Questions ◽  
Subjective Side

Transhumanists, like other elites in modernity, place great value on human creativity, and advances in human enhancement and AI form the basis of their proposals for boosting it. However, there are problems with this perspective, due to the unique ways in which humans have evolved, procreated and socialized. I first describe how creativity is related to past evolution and developmental aspects in children, stressing pretend play and the ambivalent character of creativity. Then, I outline proposals for enhancing creativity, be it in embodied humans on the way to a superior species, in AI-related beings (virtual reality, robotics), or even in any degree of mixture in human-machine interaction. In the final section, I describe intrinsic limits to these proposals, such as the absence of a good understanding of human psychology by the proponents of enhancement; the lack of interest in the subjective side of creativity (for one’s own sake); delayed maturation and the ambivalence of pretend play in childhood; and the contrariness typical of new human generations. As for the enhancement of creativity, it is argued that creativity in its social context may be the victim of its own past success. On the other hand, an asymmetry between virtual beings and children is described—the latter can behave in a nasty way, it is part of their growth and creativity, whereas the former are not supposed to cause any harm to human beings. In sum, despite impressive progress in several scientific and technological interventions in creativity, philosophical questions emerge that place many constraints on transhumanist dreams of endless creativity.

scholarly journals Conditional Text Generation for Harmonious Human-Machine Interaction

2021 ◽  
Vol 12 (2) ◽  
pp. 1-50
Author(s):  
Bin Guo ◽  
Hao Wang ◽  
Yasan Ding ◽  
Wei Wu ◽  
Shaoyang Hao ◽  
...  
Keyword(s):  
Research Field ◽  
Human Beings ◽  
Text Generation ◽  
Human Machine Interaction ◽  
Research Directions ◽  
Concept Model ◽  
New Research ◽  
Key Techniques ◽  
Machine Interaction ◽  
Generation Technology

In recent years, with the development of deep learning, text-generation technology has undergone great changes and provided many kinds of services for human beings, such as restaurant reservation and daily communication. The automatically generated text is becoming more and more fluent so researchers begin to consider more anthropomorphic text-generation technology, that is, the conditional text generation, including emotional text generation, personalized text generation, and so on. Conditional Text Generation (CTG) has thus become a research hotspot. As a promising research field, we find that much attention has been paid to exploring it. Therefore, we aim to give a comprehensive review of the new research trends of CTG. We first summarize several key techniques and illustrate the technical evolution route in the field of neural text generation, based on the concept model of CTG. We further make an investigation of existing CTG fields and propose several general learning models for CTG. Finally, we discuss the open issues and promising research directions of CTG.

scholarly journals What Safety are We Entitled to Expect of Self-driving Vehicles?

2019 ◽  
Vol 28 ◽  
pp. 95-102
Author(s):  
Taivo Liivak
Keyword(s):  
Product Liability ◽  
Human Beings ◽  
Human Machine Interaction ◽  
Liability Law ◽  
Machine Interaction

A manufacturer of self-driving vehicles could face claims involving assertions of the product’s defectiveness. Under the Product Liability Directive, a product is deemed defective when it does not provide the safety that a person is entitled to expect. Efforts to ascertain the possibility of defectiveness connected with a self-driving vehicle could necessitate evaluating the design of the vehicle, matters of human–machine interaction, and the role of the human in the relevant incident of damage. This article lays groundwork by considering the capabilities of self-driving vehicles, the role and expectations of human beings, and legislation aimed at ensuring safety and preventing damage. This discussion concretely situates the concept of the safety of self-driving vehicles in the context of product liability law, which is inherently preoccupied mainly with the consequences.

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

Holistic, Context-sensitive Human-machine Interaction for Automated Vehicles

ATZ worldwide ◽  
2021 ◽  
Vol 123 (3) ◽  
pp. 46-49
Author(s):  
Tobias Hesse ◽  
Michael Oehl ◽  
Uwe Drewitz ◽  
Meike Jipp
Keyword(s):  
Automated Vehicles ◽  
Human Machine Interaction ◽  
Context Sensitive ◽  
Machine Interaction

scholarly journals Radiology Community Attitude in Saudi Arabia about the Applications of Artificial Intelligence in Radiology

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 834
Author(s):  
Magbool Alelyani ◽  
Sultan Alamri ◽  
Mohammed S. Alqahtani ◽  
Alamin Musa ◽  
Hajar Almater ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Vital Role ◽  
Human Machine Interaction ◽  
The Future ◽  
Level Of Knowledge ◽  
Electronic Questionnaires ◽  
Machine Interaction ◽  
Applications Of Ai

Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community’s attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using electronic questionnaires in 2019 and 2020. The study included a total of 714 participants. Data analysis was performed using SPSS Statistics (version 25). Results: The majority of the participants (61.2%) had read or heard about the role of AI in radiology. We also found that radiologists had statistically different responses and tended to read more about AI compared to all other specialists. In addition, 82% of the participants thought that AI must be included in the curriculum of medical and allied health colleges, and 86% of the participants agreed that AI would be essential in the future. Even though human–machine interaction was considered to be one of the most important skills in the future, 89% of the participants thought that it would never replace radiologists. Conclusion: Because AI plays a vital role in radiology, it is important to ensure that radiologists and radiographers have at least a minimum understanding of the technology. Our finding shows an acceptable level of knowledge regarding AI technology and that AI applications should be included in the curriculum of the medical and health sciences colleges.

Sign in / Sign up

Export Citation Format

Share Document