Dinamika Kebenaran Epistemik Keagamaan dalam Tantangan dan Pembaharuan Pada Era Penggunaan Kecerdasan Buatan

In a period of advanced data and communication innovations, artificial intelligence (AI) has become a fundamental part of various parts of human existence. The research aims to explore artificial intelligence's impact on contemporary human religious understanding, especially on epistemic truth. This research applies a qualitative methodology to detail and understand epistemic truth in the context of religion in the era of artificial intelligence. This approach provides space for complex and contextual insights into the impact of artificial intelligence on religious understanding. Exploring religious epistemic truth involves analysing epistemological theories such as coherence, correlation and pragmatism, which provide deep insights. The main criterion of coherence theory is internal consistency, correlation theory focuses on correspondence with spiritual reality, and pragmatic theory emphasises practical impact in religious practice. The era of utilising artificial intelligence brings significant ethical concerns and social impacts. Challenges, such as the risk of bias in religious interpretation by algorithms, the potential to replace the spiritual role of humans and ethical concerns regarding privacy and data security, are issues that need attention. Therefore, this article contributes to integrating theories of religious epistemology with the modern challenges that arise with the use of artificial intelligence in religious life. The holistic approach adopted by this article provides deep insights into the complexity of truth and ethical values in the technological era

EFFECTIVENESS OF CHATBOT TO REDUCE THE RISK OF CORONARY HEART DISEASE WITH DOKTERKIT MOBILE APPLICATION

Background: An innovative approach in the form of a discussion platform designed to help users deal with health issues related to coronary artery disease. Chatbot platforms allow the collection of users' data, which is analyzed through natural language processing and behavioral analysis to provide each user with a customized solution based on their current situation. The data collected and analyzed is accessible. The platform is developed using chatbot technology. Users can interact with chatbots to generate personal chat data stored on the platform.Conflicting information and sensitivity to Coronary heart disease (CHD) issues hinder effective communication. Recent technological solutions to maintain weight loss are limited. A chatbot would be suitable to support weight loss as it requires no human intervention, is available 24 hours a day, and supports natural communication while maintaining anonymity. CHD is a non-communicable disease with increased mortality in both developed and developing countries. It is a major public health problem worldwide. There are many risk factors for coronary heart disease, divided into primary risk factors (age, gender, genetics) and secondary risk factors (hypertension, smoking, dyslipidemia, diabetes, obesity, physical inactivity), and other risk factors (stress, alcohol, diet, and nutrition).The health system needs an effective and low-cost way to provide optimal health outcomes. Conversational Artificial Intelligence (AI) capabilities in the form of a fully automated and self-contained text-based mobile tutoring service. CHD is a serious health problem worldwide with multiple and interrelated causes. At the same time, chatbots are becoming more popular for interacting with users in mobile health apps.Objective: Dokterkit mobile application (available on the Google Play Store) prevents lifestyle-related diseases that are a risk for CHD, which has been considered to be at risk for multiple coronary artery disease (CAD), with the overarching goal of gaining compassion through mobile health improvements Opportunities for the healthcare of the heart. The insights gained in this preview article are used to plan future healthcare systems and design a system embedded with artificial intelligence to advance healthcare, chronic disease prevention, and self-treatment.Results: The Role of Artificial Intelligence in preventing Coronary Heart Disease (CHD) is to routinely carry out health screenings, make users aware of exercising regularly, and maintain food intake by reducing foods that are high in calories and adding foods that are high in fiber.Conclusion: Using AI in healthcare is associated with preventing CHD, which alters healthy lifestyles. It can also encourage a change in attitude, a high level of user concern for health, and obtain complete health information. Research on artificial intelligence and its use in telemedicine needs to be continued, with clinical trials examining the impact on blood pressure, body mass index, smoking, diabetes mellitus, and user engagement and feedback

Evaluation of off-road terrain with static stereo and monoscopic displays

The National Aeronautics and Space Administration is currently funding research into the design of a Mars rover vehicle. This unmanned rover will be used to explore a number of scientific and geologic sites on the Martian surface. Since the rover can not be driven from Earth in real-time, due to lengthy communication time delays, a locomotion strategy that optimizes vehicle range and minimizes potential risk must be developed. In order to assess the degree of on-board artificial intelligence (AI) required for a rover to carry out its' mission, researchers conducted an experiment to define a no AI baseline. In the experiment 24 subjects, divided into stereo and monoscopic groups, were shown video snapshots of four terrain scenes. The subjects' task was to choose a suitable path for the vehicle through each of the four scenes. Paths were scored based on distance travelled and hazard avoidance. Study results are presented with respect to: (1) risk versus range; (2) stereo versus monocular video; (3) vehicle camera height; and (4) camera field-of-view

Computational Language Assessment in patients with speech, language, and communication impairments

Speech, language, and communication symptoms enable the early detection, diagnosis, treatment planning, and monitoring of neurocognitive disease progression. Nevertheless, traditional manual neurologic assessment, the speech and language evaluation standard, is time-consuming and resource-intensive for clinicians. We argue that Computational Language Assessment (C.L.A.) is an improvement over conventional manual neurological assessment. Using machine learning, natural language processing, and signal processing, C.L.A. provides a neuro-cognitive evaluation of speech, language, and communication in elderly and high-risk individuals for dementia. ii. facilitates the diagnosis, prognosis, and therapy efficacy in at-risk and language-impaired populations; and iii. allows easier extensibility to assess patients from a wide range of languages. Also, C.L.A. employs Artificial Intelligence models to inform theory on the relationship between language symptoms and their neural bases. It significantly advances our ability to optimize the prevention and treatment of elderly individuals with communication disorders, allowing them to age gracefully with social engagement.Comment: 36 pages, 2 figures, to be submite

New Paths of Attacks: Revealing the Adaptive Integration of Artificial Intelligence in Evolving Cyber Threats Targeting Social Media Users and Their Data

The intersection between artificial intelligence tools and social media has opened doors to numerous opportunities and risks. This research delves into the escalating threat landscape in a society heavily dependent on social media. Despite the efforts by social media companies and cybersecurity professionals to mitigate cyber-attacks, the constant advancements of new technologies render social media platforms increasingly vulnerable. Malicious actors exploit generative AI to collect user data, enhancing cyber threats on social media. Notably, generative AI amplifies phishing attacks, disseminates false information, and propagates propaganda, posing substantial challenges to platform security. Ease access to large language models (LLMs) further complicates the distinction between fake and genuine accounts, as malicious actors employ learned techniques from summarized and translated text to masquerade human communication. This research explores the multiple challenges social media platforms face, including the ingrained human dependence on these platforms, the risk associated with user data, the integration of artificial intelligence, and the evolving landscape of deep fakes. Examining these challenges elucidates the profound implications for the public, emphasizing the critical need for effective countermeasures to safeguard the integrity of social media platforms in the face of these new paths of attacks

APPLICATIONS: Financial risk and financial Risk Management Technology (RMT): Issues and advances

Methods for sound risk management are of increasing interest among Wall Street investment banking and brokerage firms in the aftermath of the October 1987 crash of the stock market. As the knowledge of advanced technology applications in risk management increases, financial firms are finding innovative ways to use them practically, in order to insulate themselves. The recent development in models, the software and hardware, and the market data to track risk are all considered advances in Risk Management Technology (RMT). -. These advances have affected all three stages of risk management: the identification, the measurement, and the formulation of strategies to control financial risk. This article discusses the advances made in five areas of RMT: communication software, object-oriented programming, parallel processing, neural nets and artificial intelligence. Systems based on any of these areas may be used to add value to the business of a firm. A business value linkage analysis shows how the utility of advanced systems can be measured to justify their costs.Information Systems Working Papers Serie

Ways of Applying Artificial Intelligence in Software Engineering

As Artificial Intelligence (AI) techniques have become more powerful and easier to use they are increasingly deployed as key components of modern software systems. While this enables new functionality and often allows better adaptation to user needs it also creates additional problems for software engineers and exposes companies to new risks. Some work has been done to better understand the interaction between Software Engineering and AI but we lack methods to classify ways of applying AI in software systems and to analyse and understand the risks this poses. Only by doing so can we devise tools and solutions to help mitigate them. This paper presents the AI in SE Application Levels (AI-SEAL) taxonomy that categorises applications according to their point of AI application, the type of AI technology used and the automation level allowed. We show the usefulness of this taxonomy by classifying 15 papers from previous editions of the RAISE workshop. Results show that the taxonomy allows classification of distinct AI applications and provides insights concerning the risks associated with them. We argue that this will be important for companies in deciding how to apply AI in their software applications and to create strategies for its use

Elections in digital times: a guide for electoral practitioners

Strengthening democracy and electoral processes in the era of social media and Artificial Intelligence Democracy requires free, periodic, transparent, and inclusive elections. Freedom of expression, freedom of the press, and the right to political participation are also critical to societies ruled by the respect of human rights. In today’s rapidly evolving digital environment, opportunities for communication between citizens, politicians and political parties are unprecedented –– with information related to elections flowing faster and easier than ever, coupled with expanded opportunities for its verification and correction by a growing number of stakeholders. However, with billions of human beings connected, and disinformation and misinformation circulating unhinged around the networks, democratic processes and access to reliable information are at risk. With an estimated 56.8% of the world’s population active on social media and an estimate of 4 billion eligible voters, the ubiquity of social networks and the impact of Artificial Intelligence can intentionally or unintentionally undermine electoral processes, thereby delegitimizing democracies worldwide. In this context, all actors involved in electoral processes have an essential role to play. Electoral management bodies, electoral practitioners, the media, voters, political parties, and civil society organizations must understand the scope and impact of social media and Artificial Intelligence in the electoral cycle. They also need to have access to the tools to identify who instigates and spreads disinformation and misinformation, and the tools and strategies to combat it. This handbook aims to be a toolbox that helps better understand the current scenario and share experiences of good practices in different electoral settings and equip electoral practitioners and other key actors from all over the world to ensure the credibility of the democratic system in times of profound transformations

FINANCIAL RISK AND FINANCIAL RISK MANAGEMENT TECHNOLOGY (RMT): ISSUES AND ADVANTAGES

Methods for sound risk management are of increasing interest among Wall Street investment banking and brokerage firms in the aftermath of the October 1987 crash of the stock market. As the knowledge of advanced technology applications in risk management increases, financial firms are finding innovative ways to use them practically, in order to insulate themselves. The recent development in models, the software and hardware, and the market data to track risk are all considered advances in Risk Management Technology (RMT). These advances have affected all three stages of risk management: the identification, the measurement, and the formulation of strategies to control financial risk. This article discusses the advances made in five areas of RMT: communication software, object-oriented programming, parallel processing, neural nets and artificial intelligence. Systems based on any of these areas may be used to add value to the business of a firm. A business value linkage analysis shows how the utility of advanced systems can be measured to justify their costs.Information Systems Working Papers Serie