State-of-the-Art Artificial Intelligence Based Cyber Defense Model

2021 ◽  
Author(s):  
Shah Md Istiaque ◽  
Md Toki Tahmid ◽  
Asif Iqbal Khan ◽  
Zaber Al Hassan ◽  
Sajjad Waheed
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Cyber Defense ◽  
Defense Model

scholarly journals A Survey on Bias and Fairness in Machine Learning

2021 ◽  
Vol 54 (6) ◽  
pp. 1-35
Author(s):  
Ninareh Mehrabi ◽  
Fred Morstatter ◽  
Nripsuta Saxena ◽  
Kristina Lerman ◽  
Aram Galstyan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Real World ◽  
State Of The Art ◽  
Future Directions ◽  
Discriminatory Behavior ◽  
Real World Applications ◽  
Near Future ◽  
Different Sources

With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields.

scholarly journals Artificial intelligence and machine learning in design of mechanical materials

2021 ◽  
Author(s):  
Kai Guo ◽  
Zhenze Yang ◽  
Chi-Hua Yu ◽  
Markus J. Buehler
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
State Of The Art ◽  
The State

This review revisits the state of the art of research efforts on the design of mechanical materials using machine learning.

scholarly journals A Survey of Robots in Healthcare

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 8 ◽  
Author(s):  
Maria Kyrarini ◽  
Fotios Lygerakis ◽  
Akilesh Rajavenkatanarayanan ◽  
Christos Sevastopoulos ◽  
Harish Ram Nambiappan ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
The Elderly ◽  
Robotic Systems ◽  
Care Hospital ◽  
Robotic Technology ◽  
Persons With Disabilities ◽  
Survey Paper ◽  
Recent Advances ◽  
Art Research

In recent years, with the current advancements in Robotics and Artificial Intelligence (AI), robots have the potential to support the field of healthcare. Robotic systems are often introduced in the care of the elderly, children, and persons with disabilities, in hospitals, in rehabilitation and walking assistance, and other healthcare situations. In this survey paper, the recent advances in robotic technology applied in the healthcare domain are discussed. The paper provides detailed information about state-of-the-art research in care, hospital, assistive, rehabilitation, and walking assisting robots. The paper also discusses the open challenges healthcare robots face to be integrated into our society.

scholarly journals What you always wanted to know about the deterministic part of the International Planning Competition (IPC) 2014 (but were too afraid to ask)

2018 ◽  
Vol 33 ◽  
Author(s):  
Mauro Vallati ◽  
Lukáš Chrpa ◽  
Thomas L. Mccluskey
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
The State ◽  
Strong Impact ◽  
Significant Progress ◽  
Planning Techniques ◽  
Artificial Intelligence Planning ◽  
The Future ◽  
International Planning ◽  
Planning Approaches

AbstractThe International Planning Competition (IPC) is a prominent event of the artificial intelligence planning community that has been organized since 1998; it aims at fostering the development and comparison of planning approaches, assessing the state-of-the-art in planning and identifying new challenging benchmarks. IPC has a strong impact also outside the planning community, by providing a large number of ready-to-use planning engines and testing pioneering applications of planning techniques.This paper focusses on the deterministic part of IPC 2014, and describes format, participants, benchmarks as well as a thorough analysis of the results. Generally, results of the competition indicates some significant progress, but they also highlight issues and challenges that the planning community will have to face in the future.

scholarly journals Análisis crítico de los NeuroDerechos Humanos al libre albedrío y al acceso equitativo a tecnologías de mejora.

2020 ◽  
Vol 6 (2) ◽  
pp. 135-161
Author(s):  
Diego Alejandro Borbón Rodríguez ◽  
◽  
Luisa Fernanda Borbón Rodríguez ◽  
Jeniffer Laverde Pinzón
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Free Will ◽  
New Technologies ◽  
State Of The Art ◽  
The State ◽  
Columbia University ◽  
Equitable Access ◽  
Ethical Implications ◽  
Legal Limits

Advances in neurotechnologies and artificial intelligence have led to an innovative proposal to establish ethical and legal limits to the development of technologies: Human NeuroRights. In this sense, the article addresses, first, some advances in neurotechnologies and artificial intelligence, as well as their ethical implications. Second, the state of the art on the innovative proposal of Human NeuroRights is exposed, specifically, the proposal of the NeuroRights Initiative of Columbia University. Third, the proposal for the rights of free will and equitable access to augmentation technologies is critically analyzed to conclude that, although it is necessary to propose new regulations for neurotechnologies and artificial intelligence, the debate is still very premature as if to try to incorporate a new category of human rights that may be inconvenient or unnecessary. Finally, some considerations on how to regulate new technologies are explained and the conclusions of the work are presented.

scholarly journals Artificial intelligence maturity model: a systematic literature review

2021 ◽  
Vol 7 ◽  
pp. e661
Author(s):  
Raghad Baker Sadiq ◽  
Nurhizam Safie ◽  
Abdul Hadi Abd Rahman ◽  
Shidrokh Goudarzi
Keyword(s):  
Artificial Intelligence ◽  
Systematic Approach ◽  
State Of The Art ◽  
Model Development ◽  
Significant Proportion ◽  
Maturity Model ◽  
Methodological Issues ◽  
Maturity Models ◽  
Essential Contribution ◽  
Review State

Organizations in various industries have widely developed the artificial intelligence (AI) maturity model as a systematic approach. This study aims to review state-of-the-art studies related to AI maturity models systematically. It allows a deeper understanding of the methodological issues relevant to maturity models, especially in terms of the objectives, methods employed to develop and validate the models, and the scope and characteristics of maturity model development. Our analysis reveals that most works concentrate on developing maturity models with or without their empirical validation. It shows that the most significant proportion of models were designed for specific domains and purposes. Maturity model development typically uses a bottom-up design approach, and most of the models have a descriptive characteristic. Besides that, maturity grid and continuous representation with five levels are currently trending in maturity model development. Six out of 13 studies (46%) on AI maturity pertain to assess the technology aspect, even in specific domains. It confirms that organizations still require an improvement in their AI capability and in strengthening AI maturity. This review provides an essential contribution to the evolution of organizations using AI to explain the concepts, approaches, and elements of maturity models.

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