Breeding better bees, and training artificial intelligence on emotional imagery

Science ◽  
2019 ◽  
Author(s):  
Sarah Crespi
Keyword(s):  
Artificial Intelligence ◽  
Emotional Imagery ◽  
And Training

Artificial intelligence and the management transformation

2020 ◽  
Vol 16 (4) ◽  
pp. 600-612
Author(s):  
L.F. Nikulin ◽  
V.V. Velikorossov ◽  
S.A. Filin ◽  
A.B. Lanchakov
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Soft Power ◽  
Process Integration ◽  
Management Practice ◽  
Scientific School ◽  
Strategic Culture ◽  
Analysis And Synthesis ◽  
And Training

Subject. The article discusses how management transforms as artificial intelligence gets more important in governance, production and social life. Objectives. We identify and substantiate trends in management transformation as artificial intelligence evolves and gets more important in governance, production and social life. The article also provides our suggestions for management and training of managers dealing with artificial intelligence. Methods. The study employs methods of logic research, analysis and synthesis through the systems and creative approach, methodology of technological waves. Results. We analyzed the scope of management as is and found that threats and global challenges escalate due to the advent of artificial intelligence. We provide the rationale for recognizing the strategic culture as the self-organizing system of business process integration. We suggest and substantiate the concept of soft power with reference to strategic culture, which should be raised, inter alia, through the scientific school of conflict studies. We give our recommendations on how management and training of managers should be improved in dealing with artificial intelligence as it evolves. The novelty hereof is that we trace trends in management transformation as the role of artificial intelligence evolves and growth in governance, production and social life. Conclusions and Relevance. Generic solutions are not very effective for the Russian management practice during the transition to the sixth and seventh waves of innovation. Any programming product represents artificial intelligence, which simulates a personality very well, though unable to substitute a manager in motivating, governing and interacting with people.

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 Questioning the Scope of AI Standardization in Learning, Education, and Training

2020 ◽  
pp. 107-122
Author(s):  
Jon Mason ◽  
Bruce E. Peoples ◽  
Jaeho Lee
Keyword(s):  
Artificial Intelligence ◽  
Public Discourse ◽  
Mixed Reality ◽  
Hot Spot ◽  
Learning Experience ◽  
Education And Training ◽  
Information And Communications Technology ◽  
Offline Learning ◽  
Human Ethics ◽  
And Training

Well-defined terminology and scope are essential in formal standardization work. In the broad domain of Information and Communications Technology (ICT) the necessity is even more so due to proliferation and appropriation of terms from other fields and public discourse – the term ‘smart’ is a classic example; as is ‘deep learning’. In reviewing the emerging impact of Artificial Intelligence (AI) on the field of Information Technology for Learning, Education, and Training (ITLET), this paper highlights several questions that might assist in developing scope statements of new work items.While learners and teachers are very much foregrounded in past and present standardization efforts in ITLET, little attention has been placed until recently on whether these learners and teachers are necessarily human. Now that AI is a hot spot of innovation it is receiving considerable attention from standardization bodies such as ISO/IEC, IEEE and pan-European initiatives such as the Next Generation Internet. Thus, terminology such as ‘blended learning’ necessarily now spans not just humans in a mix of online and offline learning, but also mixed reality and AI paradigms, developed to assist human learners in environments such as Adaptive Instructional Systems (AIS) that extend the scope and design of a learning experience where a symbiosis is formed between humans and AI. Although the fields of LET and AI may utilize similar terms, the language of AI is mathematics and terms can mean different things in each field. Nonetheless, in ‘symbiotic learning’ contexts where an AIS at times replaces a human teacher, a symbiosis between the human learner and the AIS occurs in such a way where both can exist as teacher and learner. While human ethics and values are preeminent in this new symbiosis, a shift towards a new ‘intelligence nexus’ is signalled where ethics and values can also apply to AI in learning, education, and training (LET) contexts. In making sense of the scope of standardization efforts in the context of LET based AI, issues for the human-computer interface become more complex than simply appropriating terminology such as ‘smart’ in the next era of standardization. Framed by ITLET perspectives, this paper focuses on detailing the implications for standardization and key questions arising from developments in Artificial Intelligence. At a high level, we need to ask: do the scopes of current LET related Standards Committees still apply and if not, what scope changes are needed?

Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health (Preprint)

2021 ◽  
Author(s):  
Winston R. Liaw ◽  
John M Westfall ◽  
Tyler S Williamson ◽  
Yalda Jabbarpour ◽  
Andrew Bazemore
Keyword(s):  
Artificial Intelligence ◽  
Primary Care ◽  
Vital Signs ◽  
Patient Privacy ◽  
Conversational Agents ◽  
Care Needs ◽  
Remote Sensors ◽  
Delivery Platform ◽  
And Training ◽  
Improve Health

UNSTRUCTURED With conversational agents triaging symptoms, cameras aiding diagnoses, and remote sensors monitoring vital signs, the use of artificial intelligence (AI) outside of hospitals has the potential to improve health, according to a recently released report from the National Academy of Medicine. Despite this promise, AI’s success is not guaranteed, and stakeholders need to be involved with its development to ensure that the resulting tools can be easily used by clinicians, protect patient privacy, and enhance the value of the care delivered. A crucial stakeholder group missing from the conversation is primary care. As the nation’s largest delivery platform, primary care will have a powerful impact on whether AI is adopted and subsequently exacerbates health disparities. To leverage these benefits, primary care needs to serve as a medical home for AI, broaden its teams and training, and build on government initiatives and funding.

Artificial intelligence speech recognition model for correcting spoken English teaching

2020 ◽  
pp. 1-12
Author(s):  
Duan Ran ◽  
Wang Yingli ◽  
Qin Haoxin
Keyword(s):  
Artificial Intelligence ◽  
Speech Recognition ◽  
Basic Knowledge ◽  
Correction Model ◽  
Spoken English ◽  
Speech Recognition Technology ◽  
Intelligence Models ◽  
Artificial Intelligence Models ◽  
Important Direction ◽  
And Training

Artificial intelligence speech recognition technology is an important direction in the field of human-computer interaction. The use of speech recognition technology to assist teachers in the correction of spoken English pronunciation in teaching has certain effects and can help students without being constrained by places, time and teachers. Based on artificial intelligence speech recognition technology, this paper improves and analyzes speech recognition algorithms, and uses effective algorithms as the system algorithms of artificial intelligence models. Meanwhile, based on phoneme-level speech error correction, after introducing the basic knowledge, construction and training of acoustic models, the basic process of speech cutting, including the front-end processing of speech and the extraction of feature parameters, is elaborated. In addition, this study designed a control experiment to verify and analyze the artificial intelligence speech recognition correction model. The research results show that the method proposed in this paper has a certain effect.

The role of artificial intelligence in learning and professional development for healthcare professionals

2019 ◽  
Vol 33 (1) ◽  
pp. 19-24 ◽  
Author(s):  
Gurprit K. Randhawa ◽  
Mary Jackson
Keyword(s):  
Artificial Intelligence ◽  
Professional Development ◽  
Education System ◽  
Healthcare Professionals ◽  
Education And Training ◽  
Healthcare Education ◽  
Clinical Educators ◽  
History Of ◽  
And Training

This article discusses the emerging role of Artificial Intelligence (AI) in the learning and professional development of healthcare professionals. It provides a brief history of AI, current and past applications in healthcare education and training, and discusses why and how health leaders can revolutionize education system practices using AI in healthcare education. It also discusses potential implications of AI on human educators like clinical educators and provides recommendations for health leaders to support the application of AI in the learning and professional development of healthcare professionals.

Using Extended Reality to Support Cyber Security

2020 ◽  
pp. 146-166
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Game Design ◽  
Design Principles ◽  
Education And Training ◽  
Entertainment Industry ◽  
Security Threats ◽  
New Methods ◽  
Area Of Interest ◽  
And Training

Cyber security is a constantly evolving area of interest. Many solutions are currently available and new methods and technologies are emerging. Although some solutions already exist in extended reality, a lack of engagement and storytelling is available, with a consequence of decreasing the probability of dissemination and awareness of the risks involved in cybersecurity. This chapter gives an overview of an extended reality platform that can be potentially used for the simulation of security threats and that combines artificial intelligence and game design principles. The main goal of this research is to develop an extended reality solution to simulate a story involving virtual characters and objects for the entertainment industry, with possible applications in other sectors such as education and training. After an introduction to extended reality, the chapter focuses on an overview on the available extended reality technologies in the context of cybersecurity.

scholarly journals International Academy of Health Sciences Informatics (IAHSI): Strategy and Focus Areas, 1st Version

2020 ◽  
Vol 29 (01) ◽  
pp. 015-025
Author(s):  
Fernando Martin-Sanchez ◽  
Marion J. Ball ◽  
Michio Kimura ◽  
Paula Otero ◽  
Elaine Huesing ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Informatics ◽  
Performance Indicators ◽  
Health Informatics ◽  
Digital Health ◽  
Health Sciences ◽  
Research Education ◽  
Living Nature ◽  
International Academy ◽  
And Training

Background: The International Academy of Health Sciences Informatics (IAHSI) is the Academy of the International Medical Informatics Association (IMIA). As an international forum for peers in biomedical and health informatics, the Academy shall play an important role in exchanging knowledge, providing education and training, and producing policy documents. Objectives: A major priority of the Academy’s activities in its inaugural phase was to define its strategy and focus areas in accordance with its objectives and to prioritize the Academy’s work, which can then be transferred to respective taskforces. Method: This document reflects the major outcomes of intensive discussions that occurred during 2019. It was presented at the Academy’s 3rd Plenary on August 25th, 2019, in Lyon, France. Results: Regardless of the ‘living nature’ of the strategy and focus areas document, it was concluded during the Plenary that the first version, which will be used as a base for decisions on the Academy’s future activities, should be made available to a broad audience. Three out of eight ‘Visions for IAHSI‘, presented in the IMIA Yearbook of Medical Informatics 2018, were identified as central for developing, implementing, and evaluating the Academy’s strategic directions: (1) advise governments and organizations on developing health and health sciences through informatics, (2) stimulate progress in biomedical and health informatics research, education, and practice, and (3) share and exchange knowledge. Taskforces shall be implemented to work in the following areas, which were considered as priority themes: (1) artificial intelligence in health: future collaboration of entities with natural and with artificial intelligence in health care, and (2) current landscape of standards for digital health. Conclusions: Taskforces are now being established. Besides specific key performance indicators, suggested for monitoring the work of theses taskforces, the strategy to monitor the progress of the Academy itself has to be measured by relevant and acceptable metrics.

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