scholarly journals Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities

2020 ◽  
Vol 3 ◽  
Author(s):  
Remy Kusters ◽  
Dusan Misevic ◽  
Hugues Berry ◽  
Antoine Cully ◽  
Yann Le Cunff ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Interdisciplinary Research ◽  
Autonomous Driving ◽  
Regulatory Agencies ◽  
Scientific Communities ◽  
Evaluation Methodologies ◽  
Research Fields ◽  
The World ◽  
Challenges And Opportunities ◽  
The Masses

The use of artificial intelligence (AI) in a variety of research fields is speeding up multiple digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable sensing, to public services and education offered to the masses around the world, to future cities made optimally efficient by autonomous driving. When a revolution happens, the consequences are not obvious straight away, and to date, there is no uniformly adapted framework to guide AI research to ensure a sustainable societal transition. To answer this need, here we analyze three key challenges to interdisciplinary AI research, and deliver three broad conclusions: 1) future development of AI should not only impact other scientific domains but should also take inspiration and benefit from other fields of science, 2) AI research must be accompanied by decision explainability, dataset bias transparency as well as development of evaluation methodologies and creation of regulatory agencies to ensure responsibility, and 3) AI education should receive more attention, efforts and innovation from the educational and scientific communities. Our analysis is of interest not only to AI practitioners but also to other researchers and the general public as it offers ways to guide the emerging collaborations and interactions toward the most fruitful outcomes.

scholarly journals Review of Data Integrity in Pharmaceutical Industry

2020 ◽  
Vol 11 (SPL4) ◽  
pp. 1323-1328
Author(s):  
Pralesha sahoo ◽  
Kamaraj R
Keyword(s):  
Artificial Intelligence ◽  
Pharmaceutical Industry ◽  
Data Integrity ◽  
Regulatory Agencies ◽  
Quality And Safety ◽  
The Past ◽  
Warning Letter ◽  
The World ◽  
A Company

Data integrity has been in the world for a quite some time. In the pharmaceutical industry, it has been playing a major role in ensuring the correctness and truthfulness of the data. The industry has been upgrading the technologies for the production of drugs, storage and distribution. In the past, the man-made workforce has been upgraded to the machine that too Artificial Intelligence machine, computers etc. In such a case integrity of data is utmost priority for ensuring correctness. Machine and the computer are built to reduce the workforce and make the work convenient for workers. It is helpful in reducing the time load of work but to ensure the honesty of the work; data integrity came into effect. A company which runs with the full GMP regulations will get less warning letter during the audit trials, but a company with proper GMP as well as proper implementation of data integrity will percolate into the audit trials successfully. Ensuring data integrity will help the firm to acquire a smaller number of warning letters or form 483. Efficacy; quality and safety of the drug can be easily achieved by data integrity. Data integrity has revolutionized the pharmaceutical industry. Terms such as ALCOA ALCOA+ plays a major role in the integrity of data and been used by various regulatory agencies such as FDA MHRA etc.

scholarly journals International cooperation in research and development of Artificial Intelligence – publication and patent activity

Ergo ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. 3-15
Author(s):  
Zdeněk Kučera ◽  
Tomáš Vondrák
Keyword(s):  
Artificial Intelligence ◽  
Czech Republic ◽  
International Cooperation ◽  
International Collaboration ◽  
Patent Activity ◽  
The Czech Republic ◽  
World Average ◽  
Research Fields ◽  
The World ◽  
Patent Applications

Abstract Artificial Intelligence (AI) is one of the dynamically evolving research fields on the global scale. The world production of publication associated with the AI field increased by a third over the four-year period 2013–2017. Even less research intensive countries as Iran, Turkey, India and Indonesia appear to increase the share of the AI topics in their publication output. In the Czech Republic the fraction of publications in the AI field increased by approximately 10 % over this period. It makes the lowest increase within the EU/EEA. The field normalized citation index of the Czech publications in the year 2016 was above the world average but it is deeply below the top countries USA, United Kingdom, Switzerland, Singapore, and Norway. The extent of international cooperation in AI is generally below the world average. The Czech Republic falls into the group of less cooperating countries. The countries exhibiting the highest growth in AI research are underrepresented in the Czech cooperation portfolio. The fraction of Czech publications in AI coauthored by foreign authors is lower than the national average. It indicates a lower international collaboration in comparison with other research fields. CR falls also in the group of countries less engaged in the international cooperation. The Czech international collaboration misses the countries exhibiting the most vigorous R&D in AI. The international collaboration adds to the quality of the research. The Czech publications originating from the international collaboration are cited above the country average for the AI field. It is even more significant in the collaboration with researchers from the top countries in the AI R&D. The patent activity in the AI field has grown significantly in recent years. There is a marked increase of patent applications having inventors/applicants from more than one country. It indicates that the applied R&D in AI has a more international character in comparison with other technology fields. A high intensity of collaboration in the authorship of patent applications is within language and geographically neighbouring countries and with countries having a highly internationalized R&D system. Multinational corporations involved in international innovation networks contribute also to the international cooperation. ICT corporations like IBM, Google, or Microsoft which often employ foreign researchers have a dominant role in international cooperation. The R&D of the Czech enterprises is relatively closed to the international cooperation. Domestic enterprises in AI use foreign employees in a small extent. The domestic enterprises even do not tap into the pool of intellectual property authored by the Czech researchers. The majority of patents with participation of Czech inventors is registered by foreign corporations.

scholarly journals Challenges and Opportunities in Developing Next Generation In-Vehicle HMI Systems

2019 ◽  
Vol 63 (1) ◽  
pp. 2115-2116
Author(s):  
Rebecca Williamson ◽  
Yu Zhang ◽  
Bruce Mehler ◽  
Ying Wang
Keyword(s):  
Artificial Intelligence ◽  
Human Factors ◽  
Market Share ◽  
User Behavior ◽  
Autonomous Driving ◽  
Human Machine Interface ◽  
Next Generation ◽  
Challenges And Opportunities ◽  
Machine Interface ◽  
User Friendly

The next generation of automotive human machine interface (HMI) systems is expected to be heavily dependent upon artificial intelligence; from autonomous driving to speech assistance, from gesture & touch-enabled interfaces to web & mobile integration. Smooth, safe, and user-friendly interaction between the driver and the vehicle is a key to winning market share. This panel aims to discuss challenges and opportunities for the next generation of automotive HMI from the perspective of human factors and user behavior. Panelists from industry and academia will offer their unique perspectives on the concerns and opportunities in developing future in-vehicle HMIs.

CHALLENGES AND OPPORTUNITIES ON THE HOSPITALITY INDUSTRY IN THE COLLECTING’S CONDITIONS THE SPREAD OF COVID-19

2017 ◽  
Author(s):  
Valeriia Kostynets ◽  
Keyword(s):  
Artificial Intelligence ◽  
Hong Kong ◽  
Information And Communication Technologies ◽  
Hospitality Industry ◽  
Market Uncertainty ◽  
Safety Standards ◽  
The World ◽  
Challenges And Opportunities ◽  
Hotel Chains ◽  
Coronavirus Infection

The article is devoted to the study of the main opportunities of the hospitality industry as a component of the tourist services market in the face of the challenge of the spread of coronavirus infection and taking into account the existing trends, respectively, prevailing in the economic environment. The author examines the features of the problems of the functioning of enterprises in the hospitality industry in the current conditions of market uncertainty associated with the consequences of countering the spread of coronavirus infection in the world. The article notes the peculiarity of the formation of a new portrait of a consumer of hotel services, taking into account modern requirements for ensuring the safety of stay in an accommodation establishment. The presented study identifies the opportunities and prospects for the development and implementation of digital technologies in the hospitality industry. The analysis of the world experience of the functioning of the leading hotel chains in the conditions of the coronavirus crisis was carried out and it was found that the pandemic contributes to the active use of advanced information and communication technologies. The article notes that automation of service processes in order to ensure sanitary safety standards using artificial intelligence technologies, integrated guest applications and contactless service have become unconditional trends of the past year, which will take on new forms and development this year. In order to highlight the practical use of existing digital development opportunities, the author analyzed the world experience of individual hotels and hotel chains in terms of attracting customers and serving guests. In particular, the experience of "A-One Hotels Group" (Thailand), "Park Lane Hong Kong" (Hong Kong), "Fairmont Singapore" (Singapore), "Novotel Sydney Brighton Beach" (Australia), "Bijou Hotel & Resort" (Switzerland), "Palladium Hotel Group" (Spain), etc. Based on the analysis, the author identified three key trends that open up new opportunities for the hospitality industry in 2021, namely: service automation using artificial intelligence (which will allow free up hotel staff to work on other tasks, eliminate language barriers in service), contactless service (which will allow guests to stay safe, minimizing contact with the staff), cloud solutions (which will be especially in demand for eco-hotels, glamping sites and country houses that are now actively popularized).

scholarly journals Artificial intelligence and rationalized unaccountability: Ideology of the elites?

Organization ◽  
2020 ◽  
pp. 135050842096387
Author(s):  
Mikko Vesa ◽  
Janne Tienari
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Intelligent Agent ◽  
Cutting Edge ◽  
Organization And Management ◽  
Power And Control ◽  
The World ◽  
The Masses ◽  
And Control ◽  
Ideological Assumptions

In this Connexions essay, we focus on intelligent agent programs that are cutting-edge solutions of contemporary artificial intelligence (AI). We explore how these programs become objects of desire that contain a radical promise to change organizing and organizations. We make sense of this condition and its implications through the idea of ‘rationalized unaccountability’ that is an ideological state in which power and control are exerted algorithmically. While populist uses of new technologies receive growing attention in critical organization and management studies, we argue that rationalized unaccountability is the hidden end of a spectrum of populism affecting societies across the world. Rather than populism of the masses, this is a populism of elites. This essay lays out some premises for critical scholars to expose the workings of intelligent agent programs and to call into question the problematic ideological assumptions that they are grounded in.

Linguistic Data Model for Natural Languages and Artificial Intelligence. Part 5. Introduction to Logic

Discourse ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 109-117
Author(s):  
O. M. Polyakov
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Logic ◽  
Natural Language ◽  
Semantic Interpretation ◽  
General View ◽  
World Model ◽  
Semantic Approach ◽  
Natural Languages ◽  
The World ◽  
Linguistic Aspect

Introduction. The article continues the series of publications on the linguistics of relations (hereinafter R–linguistics) and is devoted to an introduction to the logic of natural language in relation to the approach considered in the series. The problem of natural language logic still remains relevant, since this logic differs significantly from traditional mathematical logic. Moreover, with the appearance of artificial intelligence systems, the importance of this problem only increases. The article analyzes logical problems that prevent the application of classical logic methods to natural languages. This is possible because R-linguistics forms the semantics of a language in the form of world model structures in which language sentences are interpreted.Methodology and sources. The results obtained in the previous parts of the series are used as research tools. To develop the necessary mathematical representations in the field of logic and semantics, the formulated concept of the interpretation operator is used.Results and discussion. The problems that arise when studying the logic of natural language in the framework of R–linguistics are analyzed. These issues are discussed in three aspects: the logical aspect itself; the linguistic aspect; the aspect of correlation with reality. A very General approach to language semantics is considered and semantic axioms of the language are formulated. The problems of the language and its logic related to the most General view of semantics are shown.Conclusion. It is shown that the application of mathematical logic, regardless of its type, to the study of natural language logic faces significant problems. This is a consequence of the inconsistency of existing approaches with the world model. But it is the coherence with the world model that allows us to build a new logical approach. Matching with the model means a semantic approach to logic. Even the most General view of semantics allows to formulate important results about the properties of languages that lack meaning. The simplest examples of semantic interpretation of traditional logic demonstrate its semantic problems (primarily related to negation).

The Power of Matrix Factorization: Methods for Deconvoluting Genetic Heterogeneous Data at Expression Level

2021 ◽  
Vol 15 (8) ◽  
pp. 841-853
Author(s):  
Yuan Liu ◽  
Zhining Wen ◽  
Menglong Li
Keyword(s):  
Artificial Intelligence ◽  
Matrix Factorization ◽  
In Silico ◽  
Genetic Data ◽  
Heterogeneous Data ◽  
Expression Level ◽  
Mathematical Methods ◽  
Challenges And Opportunities ◽  
Factorization Methods ◽  
Genetic Profiles

Background:: The utilization of genetic data to investigate biological problems has recently become a vital approach. However, it is undeniable that the heterogeneity of original samples at the biological level is usually ignored when utilizing genetic data. Different cell-constitutions of a sample could differentiate the expression profile, and set considerable biases for downstream research. Matrix factorization (MF) which originated as a set of mathematical methods, has contributed massively to deconvoluting genetic profiles in silico, especially at the expression level. Objective: With the development of artificial intelligence algorithms and machine learning, the number of computational methods for solving heterogeneous problems is also rapidly abundant. However, a structural view from the angle of using MF to deconvolute genetic data is quite limited. This study was conducted to review the usages of MF methods on heterogeneous problems of genetic data on expression level. Methods: MF methods involved in deconvolution were reviewed according to their individual strengths. The demonstration is presented separately into three sections: application scenarios, method categories and summarization for tools. Specifically, application scenarios defined deconvoluting problem with applying scenarios. Method categories summarized MF algorithms contributed to different scenarios. Summarization for tools listed functions and developed web-servers over the latest decade. Additionally, challenges and opportunities of relative fields are discussed. Results and Conclusion: Based on the investigation, this study aims to present a relatively global picture to assist researchers to achieve a quicker access of deconvoluting genetic data in silico, further to help researchers in selecting suitable MF methods based on the different scenarios.

The Future of Work and the Changing Workplace

2018 ◽  
Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein
Keyword(s):  
Artificial Intelligence ◽  
Machine Intelligence ◽  
Political Issue ◽  
Digital Innovation ◽  
Future Of Work ◽  
The Past ◽  
The World ◽  
Public Debates ◽  
The Future ◽  
Market Opportunities

The world of work has been impacted by technology. Work is different than it was in the past due to digital innovation. Labor market opportunities are becoming polarized between high-end and low-end skilled jobs. Migration and its effects on employment have become a sensitive political issue. From Buffalo to Beijing public debates are raging about the future of work. Developments like artificial intelligence and machine intelligence are contributing to productivity, efficiency, safety, and convenience but are also having an impact on jobs, skills, wages, and the nature of work. The “undiscovered country” of the workplace today is the combination of the changing landscape of work itself and the availability of ill-fitting tools, platforms, and knowledge to train for the requirements, skills, and structure of this new age.

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