scholarly journals THE IMPACT OF ATTITUDES TOWARDS GOVERNMENT AND CORPORATIONS ON TRUST IN TECHNOLOGY

2019 ◽  
Vol 2019 ◽  
Author(s):  
Yi-Ning Katherine Chen ◽  
Chia-Ho Ryan Wen
Keyword(s):  
Artificial Intelligence ◽  
Radio Frequency ◽  
Electromagnetic Fields ◽  
Political Ideology ◽  
Online Survey ◽  
Two Dimensions ◽  
Trust In Technology ◽  
The Impact

Understanding public distrust of technology is both theoretically and practically important, yet while previous research has focused on the association between political ideology and trust in science, it is at best an inconsistent predictor. This study shall demonstrate that two dimensions of political ideology, attitudes towards governments and corporations, can more precisely predict trust in technology across issues. We will conduct an online survey on the science of radio frequency electromagnetic fields (RF-EMF) and Artificial Intelligence (AI) applications to test our hypotheses that trust in technology varies across issues and that attitudes towards government and corporations are important predictors of this trust.

scholarly journals Use of Artificial Intelligence to understand adults’ thoughts and behaviours relating to COVID-19

2021 ◽  
pp. 175791392097933
Author(s):  
SW Flint ◽  
A Piotrkowicz ◽  
K Watts
Keyword(s):  
Artificial Intelligence ◽  
Online Survey ◽  
Severe Illness ◽  
Free Text ◽  
Community Recovery ◽  
Substantial Impact ◽  
Lifestyle Behaviours ◽  
Artificial Intelligence Methods ◽  
High Concern ◽  
The Impact

Aims: The outbreak of severe acute respiratory syndrome coronavirus 2 (COVID-19) is a global pandemic that has had substantial impact across societies. An attempt to reduce infection and spread of the disease, for most nations, has led to a lockdown period, where people’s movement has been restricted resulting in a consequential impact on employment, lifestyle behaviours and wellbeing. As such, this study aimed to explore adults’ thoughts and behaviours in response to the outbreak and resulting lockdown measures. Methods: Using an online survey, 1126 adults responded to invitations to participate in the study. Participants, all aged 18 years or older, were recruited using social media, email distribution lists, website advertisement and word of mouth. Sentiment and personality features extracted from free-text responses using Artificial Intelligence methods were used to cluster participants. Results: Findings demonstrated that there was varied knowledge of the symptoms of COVID-19 and high concern about infection, severe illness and death, spread to others, the impact on the health service and on the economy. Higher concerns about infection, illness and death were reported by people identified at high risk of severe illness from COVID-19. Behavioural clusters, identified using Artificial Intelligence methods, differed significantly in sentiment and personality traits, as well as concerns about COVID-19, actions, lifestyle behaviours and wellbeing during the COVID-19 lockdown. Conclusions: This time-sensitive study provides important insights into adults’ perceptions and behaviours in response to the COVID-19 pandemic and associated lockdown. The use of Artificial Intelligence has identified that there are two behavioural clusters that can predict people’s responses during the COVID-19 pandemic, which goes beyond simple demographic groupings. Considering these insights may improve the effectiveness of communication, actions to reduce the direct and indirect impact of the COVID-19 pandemic and to support community recovery.

scholarly journals How far is too far? An analysis of students’ perceptions of the impact of distance between university and family home on academic performance

2017 ◽  
Vol 10 (15) ◽  
pp. 28-40
Author(s):  
Rosalina Pisco Costa ◽  
Carlos Vieira ◽  
Isabel Vieira
Keyword(s):  
Academic Performance ◽  
Undergraduate Students ◽  
Online Survey ◽  
Negative Impact ◽  
Two Dimensions ◽  
Family Home ◽  
Socially Relevant ◽  
The University ◽  
Work Done ◽  
The Impact

AbstractTransition to university is a challenging phase in youngsters’ lives. The literature indicates that geographical distance separating the places of study and of family residence adds to the difficulties of transition and adjustment to university. Recent evidence suggests that it also negatively impacts students’ grades. Despite important work done by economists, geographers and psychologists, sociology has devoted scarce interest in understanding this topic. This article seeks to bridge this gap, specifically exploring the reasons justifying the largely ignored effect of distance between the university and family home in academic performance. The study draws on data on undergraduate students of a Portuguese public university, collected through an online survey. Two dimensions, one more related to practical life occupations and another more linked to personal feelings and activities, are examined. It is argued that the negative impact of distance is mainly due to homesickness and to the time spent traveling home. Results from such analysis are twofold socially relevant: of the utmost importance for families, academics and students’ support services, deserve to be seriously considered by policy makers deciding on the territorial distribution of higher-education institutions.

scholarly journals Parents’ Perspectives on Using Artificial Intelligence to Reduce Technology Interference During Early Childhood: Cross-sectional Online Survey

10.2196/19461 ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. e19461
Author(s):  
Jill Glassman ◽  
Kathryn Humphreys ◽  
Serena Yeung ◽  
Michelle Smith ◽  
Adam Jauregui ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Technology Use ◽  
Online Survey ◽  
Family Income ◽  
Sociodemographic Factors ◽  
Mobile Technologies ◽  
Computer Assisted ◽  
Device Use ◽  
The Impact ◽  
Parent Child

Background Parents’ use of mobile technologies may interfere with important parent-child interactions that are critical to healthy child development. This phenomenon is known as technoference. However, little is known about the population-wide awareness of this problem and the acceptability of artificial intelligence (AI)–based tools that help with mitigating technoference. Objective This study aims to assess parents’ awareness of technoference and its harms, the acceptability of AI tools for mitigating technoference, and how each of these constructs vary across sociodemographic factors. Methods We administered a web-based survey to a nationally representative sample of parents of children aged ≤5 years. Parents’ perceptions that their own technology use had risen to potentially problematic levels in general, their perceptions of their own parenting technoference, and the degree to which they found AI tools for mitigating technoference acceptable were assessed by using adaptations of previously validated scales. Multiple regression and mediation analyses were used to assess the relationships between these scales and each of the 6 sociodemographic factors (parent age, sex, language, ethnicity, educational attainment, and family income). Results Of the 305 respondents, 280 provided data that met the established standards for analysis. Parents reported that a mean of 3.03 devices (SD 2.07) interfered daily in their interactions with their child. Almost two-thirds of the parents agreed with the statements “I am worried about the impact of my mobile electronic device use on my child” and “Using a computer-assisted coach while caring for my child would help me notice more quickly when my device use is interfering with my caregiving” (187/281, 66.5% and 184/282, 65.1%, respectively). Younger age, Hispanic ethnicity, and Spanish language spoken at home were associated with increased technoference awareness. Compared to parents’ perceived technoference and sociodemographic factors, parents’ perceptions of their own problematic technology use was the factor that was most associated with the acceptance of AI tools. Conclusions Parents reported high levels of mobile device use and technoference around their youngest children. Most parents across a wide sociodemographic spectrum, especially younger parents, found the use of AI tools to help mitigate technoference during parent-child daily interaction acceptable and useful.

METHOD OF SYNTHESIS OF MATHEMATICAL MODELS FOR DISEASES PREDICTING AND DIAGNOSING CAUSED BY ELECTROMAGNETIC FIELDS OF THE RADIO FREQUENCY RANGE

2020 ◽  
pp. 122-128
Author(s):  
Николай Алексеевич Кореневский ◽  
Анна Владимировна Титова
Keyword(s):  
Radio Frequency ◽  
Electromagnetic Fields ◽  
Human Body ◽  
Energy State ◽  
Synthesis Method ◽  
Biologically Active ◽  
Similar Data ◽  
Frequency Range ◽  
Low Intensity ◽  
The Impact

В работе рассматривается метод синтеза математических моделей прогнозирования и диагностики заболеваний, провоцируемых воздействием электромагнитных полей радиочастотного диапазона, позволяющий контролировать текущее состояние человека с целью дальнейшего принятия решений о возможной коррекции функций организма в случае необходимости. С учетом неполного и нечеткого описания исследуемого класса заболеваний в качестве базового математического аппарата выбраны технология мягких вычислений и, в частности, методология синтеза гибридных нечетких решающих правил, хорошо зарекомендовавшая себя при решении задач с аналогичной структурой данных и типом неопределенности. Предлагаемый метод синтеза позволяет учитывать мультипликативный эффект воздействия на организм человека электромагнитных полей (ЭМП) различной модальности и интенсивности с учетом других эндогенных и экзогенных факторов риска. С учетом того, что для достаточно мощных ЭМП радиочастного диапазона определены предельно допустимые уровни с известными последствиями, а для низкоинтенсивных ЭМП указаны лишь тенденции возможных заболеваний в основном на качественном уровне, предлагаются две различные ветви синтеза соответствующих решающих правил. Для мощных и стабильных ЭМП предлагается использовать модификацию известных моделей, полученных для промышленных энергосетей. Для оценки влияния низкоинтенсивных, нестабильных ЭМП радиочастотного диапазона на организм человека предлагается использовать нечеткие табличные модели и ряд чувствительных к действию ЭМП радиочастотного диапазона индикаторов. К таким индикаторам относятся состояние внимания, памяти, мышления, а также динамика изменения энергетического состояния биологически активных точек (БАТ), связанных с исследуемой патологией, и общесистемных БАТ Taking into account the incomplete and fuzzy description of the studied class of diseases, the basic mathematical apparatus was chosen as a soft computing technology, and, in particular, the methodology for the synthesis of hybrid fuzzy solving rules, which has proven itself well in solving problems with a similar data structure and type of uncertainty. The proposed synthesis method allows us to take into account the multiplicative effect of electromagnetic fields (EMF) of different modality and intensity on the human body, taking into account other endogenous and exogenous risk factors. Taking into account that the maximum permissible levels with known consequences are defined for sufficiently powerful EMF of the radio frequency range, and only trends of possible diseases are indicated for low-intensity EMF, two different branches of synthesis of the corresponding decisive rules are proposed at the qualitative level. For powerful and stable EMF, it is proposed to use a modification of known models obtained for industrial power grids. To assess the impact of low-intensity, unstable RF EMF on the human body, it is proposed to use fuzzy tabular models and a number of indicators sensitive to the action of RF EMF. These indicators include the state of attention, memory, thinking, as well as the dynamics of changes in the energy state of biologically active points (BAP) associated with the studied pathology and system-wide BAP

scholarly journals Artificial Intelligence as the New Realm for Online Advertising

2021 ◽  
Author(s):  
Nouran Tahoun ◽  
Ahmed Taher
Keyword(s):  
Artificial Intelligence ◽  
Significant Relationship ◽  
Process Model ◽  
Online Survey ◽  
Online Advertising ◽  
Data Driven ◽  
Perceived Effectiveness ◽  
Media Planning ◽  
Client Side ◽  
The Impact

This study explores the utilization of Artificial Intelligence (AI) in the online advertising process and the impact of using AI in each stage on overall perceived effectiveness. It also provides a better understanding of the magnitude of using AI in the four stages of advertising online: namely, consumer insights, ad creation, media planning and buying, and ad evaluation. <i>The Process model of AI utilization in online advertising </i>is the study's conceptual model developed based on the literature. An online survey is conducted with digital advertisers worldwide from both agency and client-side. The findings showed that AI is emerging progressively in the four stages of the data-driven online advertising process. Moreover, it showed a significant relationship between AI utilization in each stage and the following one. Using AI in each advertising stage promotes the perceived effectiveness of the overall online ad process.

Ice and snow talent training based on construction and analysis of artificial intelligence education informatization teaching model

2020 ◽  
pp. 1-11
Author(s):  
Shuo Liu ◽  
Jin Wang
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Visual Processing ◽  
Two Dimensions ◽  
Mixed Data ◽  
Teaching Model ◽  
Analysis Framework ◽  
Intelligence Education ◽  
The Impact ◽  
Instruction Design

Based on the analysis of the artificial intelligence education informatization teaching model for the training of ice and snow talents, this article first builds an artificial intelligence education informatization teaching model, reads and organizes a large number of documents such as big data and personalized teaching of ice and snow talent training. It needs to analyze the existing problems and condense the relevant concepts of educational big data, personalized teaching. We personalized teaching systems based on big data and elaborate on the related theoretical basis. It constructed a visual analysis framework for artificial intelligence teaching data, discussed the realization process and mechanism of data visualization of mixed ice and snow talent cultivation from the two dimensions of timeliness and media form, and introduced the mixed data of numerical and text for visual processing methods. We discussed the interactive presentation process of the visualization results. The research explores the impact of artificial intelligence on the elements of ice and snow talent training instruction design one by one and uses the paradigm migration analysis framework to prove that the ice and snow talent training instruction design paradigm in the context of artificial intelligence has produced a migration.

scholarly journals Audience Views on Professional Norms of Journalism. A Media Repertoire Approach

2021 ◽  
Vol 2 (2) ◽  
pp. 258-274
Author(s):  
Pauljan Truyens ◽  
Ike Picone
Keyword(s):  
Political Ideology ◽  
Representative Sample ◽  
Online Survey ◽  
News Consumption ◽  
Professional Norms ◽  
The Cross ◽  
The Impact ◽  
Consumption Strategies

Despite several studies showing discrepancies between audience expectations of journalism and journalists’ professional norms, what remains largely unknown is the audience view on the adherence of journalism to these seemingly essential professional norms. Recent research mainly focused on analysing audience expectations within the context of specific cases. Moreover, these studies rarely take into consideration characteristics that might shape people’s views on journalism such as political ideology. This article seeks to complement these studies by exploring the impact that a user’s news consumption might have on their expectations of journalism. Utilizing data from an online survey among a representative sample of the Flemish audience, we analyse views on adherence to the main professional norms by the Flemish media, and subsequently relate these to news consumption. To grasp the cross- and multi-medial news consumer, we use a news repertoire approach. Flemish news repertoires differ significantly in views on several professional journalistic norms. By linking these distinct news repertoires to their views on professional norms of journalism, we first question how essential these professional norms put forward by journalists really are. Secondly, we discuss if expectations of journalism result in divergent news consumption strategies or vice versa, laying the groundwork for further exploring audience views on professional journalistic norms.

scholarly journals Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alison L. Antes ◽  
Sara Burrous ◽  
Bryan A. Sisk ◽  
Matthew J. Schuelke ◽  
Jason D. Keune ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Healthcare System ◽  
Online Survey ◽  
The United States ◽  
Full Time ◽  
Psychosocial Variables ◽  
Perceived Benefit ◽  
Health Related ◽  
Healthcare Technologies ◽  
Trust In Technology

Abstract Background Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding perceptions of these tools is essential to successful development and adoption. This exploratory study gauged participants’ level of openness, concern, and perceived benefit associated with AI-driven healthcare technologies. We also explored socio-demographic, health-related, and psychosocial correlates of these perceptions. Methods We developed a measure depicting six AI-driven technologies that either diagnose, predict, or suggest treatment. We administered the measure via an online survey to adults (N = 936) in the United States using MTurk, a crowdsourcing platform. Participants indicated their level of openness to using the AI technology in the healthcare scenario. Items reflecting potential concerns and benefits associated with each technology accompanied the scenarios. Participants rated the extent that the statements of concerns and benefits influenced their perception of favorability toward the technology. Participants completed measures of socio-demographics, health variables, and psychosocial variables such as trust in the healthcare system and trust in technology. Exploratory and confirmatory factor analyses of the concern and benefit items identified two factors representing overall level of concern and perceived benefit. Descriptive analyses examined levels of openness, concern, and perceived benefit. Correlational analyses explored associations of socio-demographic, health, and psychosocial variables with openness, concern, and benefit scores while multivariable regression models examined these relationships concurrently. Results Participants were moderately open to AI-driven healthcare technologies (M = 3.1/5.0 ± 0.9), but there was variation depending on the type of application, and the statements of concerns and benefits swayed views. Trust in the healthcare system and trust in technology were the strongest, most consistent correlates of openness, concern, and perceived benefit. Most other socio-demographic, health-related, and psychosocial variables were less strongly, or not, associated, but multivariable models indicated some personality characteristics (e.g., conscientiousness and agreeableness) and socio-demographics (e.g., full-time employment, age, sex, and race) were modestly related to perceptions. Conclusions Participants’ openness appears tenuous, suggesting early promotion strategies and experiences with novel AI technologies may strongly influence views, especially if implementation of AI technologies increases or undermines trust. The exploratory nature of these findings warrants additional research.

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