Analyzing the Impact of Big Data and Artificial Intelligence on the Communications Profession: A Case Study on Public Relations (PR) Practitioners in Indonesia

2020 ◽  
Vol 10 (3) ◽  
pp. 1066
Author(s):  
N. Nurlaela Arief ◽  
Aurik Gustomo
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Public Relations ◽  
The Impact

Prinsip Kearifan Lokal dalam Pengembangan Strategi Kehumasan pada Pemerintah Daerah Kabupaten Bandung

2020 ◽  
Vol 4 (2) ◽  
pp. 229-248
Author(s):  
Betty Tresnawaty
Keyword(s):  
Public Relations ◽  
Local Knowledge ◽  
Case Study Approach ◽  
West Java ◽  
Study Approach ◽  
Positive Image ◽  
The Government ◽  
The Impact ◽  
Public Relations Strategy

Public Relations of the Bandung Regency Government realizes that its area has a lot of potential for various local wisdom and has a heterogeneous society. This study aims to explore and analyze the values of local knowledge in developing public relations strategies in the government of Bandung Regency, West Java province. This study uses a constructivist interpretive (subjective) paradigm through a case study approach. The results showed that the Bandung Regency Government runs its government based on local wisdom. Bandung Regency Public Relations utilizes local insight and the region's potential to develop a public relations strategy to build and maintain a positive image of Bandung Regency. The impact of this research is expected to become a source of new scientific references in the development of public relations strategies in every region of Indonesia, which is very rich with various philosophies.Humas Pemerintah Kabupaten Bandung menyadari wilayahnya memiliki banyak potensi kearifan lokal yang beragam, serta memiliki masyarakatnya yang heterogen. Penelitian ini bertujuan menggali dan menganalisis nilai-nilai kearifan lokal dalam pengembangan strategi kehumasan di pemerintahan Kabupaten Bandung provinsi Jawa Barat.  Penelitian ini menggunakan paradigma interpretif (subjektif) konstruktivis melalui pendekatan studi kasus. Hasil penelitian menunjukkan bahwa Pemerintah Kabupaten (Pemkab) Bandung menjalankan pemerintahannya berlandaskan pada kearifal lokal. Humas Pemkab Bandung memanfaatkan kearifan lokal dan potensi wilayahnya untuk mengembangkan strategi humas dalam membangun dan mempertahankan citra positif Kabupaten Bandung.Dampak penelitian ini diharapkan menjadi sumber rujukan ilmiah baru dalam pengembangan strategi kehumasan di setiap daerah Indonesia yang sangat kaya dengan beragam filosofi. 

The impact of artificial intelligence and big data on end-stage kidney disease treatments

2021 ◽  
pp. 115076
Author(s):  
Covadonga Díez-Sanmartín ◽  
Antonio Sarasa-Cabezuelo ◽  
Amado Andrés Belmonte
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Kidney Disease ◽  
End Stage Kidney Disease ◽  
End Stage ◽  
The Impact

scholarly journals Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases

Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Expert System ◽  
Population Monitoring ◽  
High Definition ◽  
Contagious Diseases ◽  
The World ◽  
General Guide ◽  
The Impact ◽  
Back To Work

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.

scholarly journals Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study

2021 ◽  
Author(s):  
Suzanne L. van Winkel ◽  
Alejandro Rodríguez-Ruiz ◽  
Linda Appelman ◽  
Albert Gubern-Mérida ◽  
Nico Karssemeijer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Detection ◽  
Support System ◽  
Reading Time ◽  
Digital Breast Tomosynthesis ◽  
Breast Tomosynthesis ◽  
Screening Programs ◽  
The Impact

Abstract Objectives Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is increasingly implemented in breast cancer screening. However, the large volume of images increases the risk of reading errors and reading time. This study aims to investigate whether the accuracy of breast radiologists reading wide-angle DBT increases with the aid of an artificial intelligence (AI) support system. Also, the impact on reading time was assessed and the stand-alone performance of the AI system in the detection of malignancies was compared to the average radiologist. Methods A multi-reader multi-case study was performed with 240 bilateral DBT exams (71 breasts with cancer lesions, 70 breasts with benign findings, 339 normal breasts). Exams were interpreted by 18 radiologists, with and without AI support, providing cancer suspicion scores per breast. Using AI support, radiologists were shown examination-based and region-based cancer likelihood scores. Area under the receiver operating characteristic curve (AUC) and reading time per exam were compared between reading conditions using mixed-models analysis of variance. Results On average, the AUC was higher using AI support (0.863 vs 0.833; p = 0.0025). Using AI support, reading time per DBT exam was reduced (p < 0.001) from 41 (95% CI = 39–42 s) to 36 s (95% CI = 35– 37 s). The AUC of the stand-alone AI system was non-inferior to the AUC of the average radiologist (+0.007, p = 0.8115). Conclusions Radiologists improved their cancer detection and reduced reading time when evaluating DBT examinations using an AI reading support system. Key Points • Radiologists improved their cancer detection accuracy in digital breast tomosynthesis (DBT) when using an AI system for support, while simultaneously reducing reading time. • The stand-alone breast cancer detection performance of an AI system is non-inferior to the average performance of radiologists for reading digital breast tomosynthesis exams. • The use of an AI support system could make advanced and more reliable imaging techniques more accessible and could allow for more cost-effective breast screening programs with DBT.

Big data and artificial intelligence for health system sustainability: The case of Veneto Region

2021 ◽  
pp. 31-52
Author(s):  
Grazia Dicuonzo ◽  
Francesca Donofrio ◽  
Antonio Fusco ◽  
Vittorio Dell’Atti
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Healthcare System ◽  
Care Delivery ◽  
Research Question ◽  
Health Agency ◽  
Time Frame ◽  
Structured Interviews ◽  
Case Study Methodology ◽  
The Impact

This paper investigates the digitalization challenges facing the Italian healthcare system. The aim of the paper is to support healthcare organizations as they take advantage of the potential of big data and artificial intelligence (AI) to promote sustainable healthcare systems. Both the development of innovative processes in the management of health care activities and the introduction of healthcare forecasting systems are valuable resources for clinical and care activities and enable a more efficient use of inputs in essential-level care delivery. By examining an innovative project developed by the Regional Social Health Agency (ARSS) of Veneto, this study analyses the impact of big data and AI on the sustainability of a healthcare system. In order to answer the research question, we used a case study methodology. We conducted semi-structured interviews with key members of the organizational group involved in the case. The results show that the implementation of AI algorithms based on big data in healthcare both improves the interpretation and processing of data, and reduces the time frame necessary for clinical processes, having a positive effect on sustainability.

scholarly journals Gender and feminist considerations in Artificial Intelligence from a developing-world perspective, with India as a case study

2021 ◽  
Author(s):  
SANGHAMITRA CHOUDHURY ◽  
Shailendra Kumar
Keyword(s):  
Artificial Intelligence ◽  
Developing Countries ◽  
Developing World ◽  
Developed Countries ◽  
High Level ◽  
The Impact ◽  
The Relationship ◽  
Precarious Situation ◽  
And Robotics

<p>The relationship between women, technology manifestation, and likely prospects in the developing world is discussed in this manuscript. Using India as a case study, the paper goes on to discuss how ontology and epistemology views utilised in AI (Artificial Intelligence) and robotics will affect women's prospects in developing countries. Women in developing countries, notably in South Asia, are perceived as doing domestic work and are underrepresented in high-level professions. They are disproportionately underemployed and face prejudice in the workplace. The purpose of this study is to determine if the introduction of AI would exacerbate the already precarious situation of women in the developing world or if it would serve as a liberating force. While studies on the impact of AI on women have been undertaken in developed countries, there has been less research in developing countries. This manuscript attempts to fill that need.</p>

scholarly journals ‘Issues’ y ‘big data’ en la gestión de relaciones públicas. El caso de la implementación del nuevo sistema de tratamiento de residuos “Recuperando Valor” en Córdoba, Argentina

Tripodos ◽  
2021 ◽  
pp. 73-87
Author(s):  
Antonio Castillo-Esparcia ◽  
Alejandro Álvarez-Nobell ◽  
María Belén Barroso
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Latin America ◽  
Public Relations ◽  
Analytical Models ◽  
Issues Management ◽  
Redes Sociales ◽  
Political Function ◽  
Toma De Decisiones ◽  
The Impact

El LCM 2016-2017 (Moreno et al., 2017) mostró el déficit en Latinoaméri­ca en el uso de big data para la toma de decisiones basada en issues; una de las grandes transformaciones actuales en relaciones públicas. El objetivo de esta investigación fue analizar el impacto de la implementación de estrategias de is­sues management y big data para el nuevo sistema de residuos de Córdoba (Argentina) —“Recuperando Valor”— durante diciembre 2018. Se analizaron más de 10.000 publicaciones en redes sociales mediante un sistema de aler­tas programadas (QSocial) por temas, actores, impactos y frecuencia a través de distintos modelos analíticos: Imagen de Gestión; Sentimientos; Preocupacio­nes Ciudadanas, Género, Humor Social y Valoraciones. Las organizaciones no solo comunican estratégicamente: son comunicación estratégica (Grandien y Johansson, 2016). Ello implica una función de dirección y asesoramiento (Zerfass y Franke, 2013) —o función política (Simões, 2001 inspirado en Matrat, 1971)—, atendiendo la opi­nión pública mediante la gestión de issues (Nothhaft, 2010). En la prácti­ca implica construir, administrar y mo­nitorear en tiempo real el desarrollo e impacto de un conjunto de temas que cobran relevancia en las distintas agen­das y por consecuencia en la producción de contenidos y la gestión de relaciones con los distintos públicos en función de sus intereses. Issues and Big Data in Public Relations Management. The Case of the Implementation of the New Garbage System Called “Recuperando Valor” in Córdoba, ArgentinaThe LCM 2016-2017 (Moreno et al., 2017) showed the deficit in the use of big data for making decisions based on issues in Latin America; this is one of the great transformations that we currently envision in public relations. The objec­tive of this research was to analyze the impact of the implementation of Issues Management and big data strategies for the new garbage system in Córdoba (Ar­gentina) —“Recuperando Valor”— du­ring December 2018. More than 10,000 publications on social networks were analyzed through a system of program­med alerts (QSocial) taking into accou­nt topics, actors, impact and frequency through different analytical models: measurement of Management Ima­ge; Feelings; Citizen Concerns, Gender, Social Humor and Evaluations. Orga­nizations not only communicate strate­gically: they are indeed strategic com­munication (Grandien and Johansson, 2016). This requires a management and advisory function (Zerfass and Franke, 2013) —or political function (Simões, 2001 as inspired by Matrat, 1971)—, considering public opinion through is­sues management (Nothhaft, 2010). In practice it involves building, managing and monitoring in real time the develo­pment and impact of a set of issues that become relevant in the different agendas and, consequently, in the production of contents and the management of rela­tions with the different stakeholders ba­sed on their interests.Palabras clave: issues, big data, rela­ciones públicas, ambiente, residuos en Argentina.Key words: issues; big data, public rela­tions, environment, garbage in Argen­tina.

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