Columns

2020 ◽  
Vol 24 (02) ◽  
pp. 14-26
Keyword(s):  
Artificial Intelligence ◽  
Robotic Surgery ◽  
Medical Device ◽  
Muscle Mass ◽  
Tobacco Industry ◽  
Glycaemic Index ◽  
Factors Associated ◽  
Disruptive Technologies ◽  
Medical Device Company

The following topics are under this section: Game Changers – Medical Device company leverages on artificial intelligence for robotic surgery Epidemiology of Factors associated with Low Muscle Mass in Elderly Low Glycaemic Index Foods for Healthier Diets Disruptive Technologies in the Tobacco Industry

Future Education within Disruptive Technologies Developments

2020 ◽  
Vol 26 (2) ◽  
pp. 288-293
Author(s):  
Codrin-Leonard Herţanu
Keyword(s):  
Artificial Intelligence ◽  
New Paradigm ◽  
Contemporary World ◽  
Disruptive Technologies ◽  
Educational Domain ◽  
Blockchain Technology ◽  
How People Learn ◽  
Future Education ◽  
Present World ◽  
Technology Domain

AbstractOur contemporary world is on the verge of crucial changes of an unparalleled pace. The ‘technological changeover’ is the new paradigm caused by the unprecedented evolution of the disruptive technologies. The present world has the tendency to evolve at least exponential, therefore future educational environment is fairly different than its present layout. An entire array of nowadays studies widely recognizes that the progress of the disruptive technologies will pose a meaningful impact over the educational system evolution. Among the most spectacular technologies with disruptive features we should encounter Artificial Intelligence, Blockchain Technology, Cloud Computing, and the like. In an era of technological disruption the education is seen as the new currency. With the help of Artificial Intelligence, for instance, the education system could track how people learn from kindergarten to retirement. Besides, the technology domain will move the centre of gravity from the institutional area to that of the education’s beneficiaries, as we might expect that they will recruit and employ the needed teacher staff, not the institutions. Moreover, the education’s recipients will be the main creators of tomorrow’s professions and within their community the overarching events will happen and the main decisions will be taken in the educational domain.

scholarly journals Factors associated with skeletal muscle mass, sarcopenia, and sarcopenic obesity in older adults: a multi-continent study

2015 ◽  
Vol 7 (3) ◽  
pp. 312-321 ◽  
Author(s):  
Stefanos Tyrovolas ◽  
Ai Koyanagi ◽  
Beatriz Olaya ◽  
Jose Luis Ayuso-Mateos ◽  
Marta Miret ◽  
...  
Keyword(s):  
Older Adults ◽  
Skeletal Muscle ◽  
Muscle Mass ◽  
Skeletal Muscle Mass ◽  
Sarcopenic Obesity ◽  
Factors Associated

scholarly journals Factors Associated with Medical Device Related Pressure Ulcer Caused by Ankle Foot Orthosis

2021 ◽  
Author(s):  
Hideyuki Ogawa ◽  
Naohito Nishio ◽  
Ryohei Makino ◽  
Yuki Echizenya ◽  
Miwako Otsuka ◽  
...  
Keyword(s):  
Medical Device ◽  
Pressure Ulcer ◽  
Ankle Foot Orthosis ◽  
Factors Associated ◽  
Foot Orthosis

EXPRESS: Home-Tutoring Services Assisted with Technology: Investigating the Role of Artificial Intelligence Using a Randomized Field Experiment

2021 ◽  
pp. 002224372110503
Author(s):  
Jun Hyung Kim ◽  
Minki Kim ◽  
Do Won Kwak ◽  
Sol Lee
Keyword(s):  
Artificial Intelligence ◽  
Controlled Trial ◽  
Services Marketing ◽  
Learning Needs ◽  
Service Employees ◽  
Factors Associated ◽  
Randomized Controlled ◽  
Randomized Field Experiment ◽  
Service Outcomes

Despite a rising interest in artificial intelligence (AI) technology, research in services marketing has not evaluated its role in helping firms learn about customers’ needs and increasing the adaptability of service employees. Therefore, the authors develop a conceptual framework and investigate whether and to what extent providing AI assistance to service employees improves service outcomes. The randomized controlled trial in the context of tutoring services shows that helping service employees (tutors) adapt to students’ learning needs by providing AI-generated diagnoses significantly improves service outcomes measured by academic performance. However, the authors find that some tutors may not utilize AI assistance (i.e., AI aversion), and factors associated with unforeseen barriers to usage (i.e., technology overload) can moderate its impact on outcomes. Interestingly, tutors significantly contributing to the firm’s revenue relied heavily on AI assistance but unexpectedly benefited little from AI in improving service outcomes. Given the wide applicability of AI assistance in a variety of services marketing contexts, the authors suggest that firms should consider the potential difficulties employees face in using the technology rather than encourage them to use it as it is.

Software documentation is not enough! Requirements for the documentation of AI

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Königstorfer ◽  
Stefan Thalmann
Keyword(s):  
Artificial Intelligence ◽  
Business Process ◽  
Design Methodology ◽  
Governance Mechanism ◽  
It Industry ◽  
Specific Nature ◽  
Content Type ◽  
Software Documentation ◽  
Disruptive Technologies ◽  
Present Information

Purpose Artificial intelligence (AI) is currently one of the most disruptive technologies and can be applied in many different use cases. However, applying AI in regulated environments is challenging, as it is currently not clear how to achieve and assess the fairness, accountability and transparency (FAT) of AI. Documentation is one promising governance mechanism to ensure that AI is FAT when it is applied in practice. However, due to the nature of AI, documentation standards from software engineering are not suitable to collect the required evidence. Even though FAT AI is called for by lawmakers, academics and practitioners, suitable guidelines on how to document AI are not available. This interview study aims to investigate the requirements for AI documentations. Design/methodology/approach A total of 16 interviews were conducted with senior employees from companies in the banking and IT industry as well as with consultants. The interviews were then analyzed using an informed-inductive coding approach. Findings The authors found five requirements for AI documentation, taking the specific nature of AI into account. The interviews show that documenting AI is not a purely technical task, but also requires engineers to present information on how the AI is understandably integrated into the business process. Originality/value This paper benefits from the unique insights of senior employees into the documentation of AI.

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