“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

USEFULNESS OF AI IN DAY-TO-DAY LIFE

This research paper aims to explore the diverse objectives of integrating artificial intelligence (AI) into everyday life. The rapid advancement of AI technologies has led to their widespread incorporation into various aspects of human existence. This paper delves into the key objectives that drive the integration of AI into daily life, presents concrete examples of AI applications, and discusses the potential implications and challenges that arise from this integration. Through a comprehensive analysis of AI's role in enhancing efficiency, convenience, safety, and decision-making, this paper highlights the transformative impact of AI on modern society. The AI program that senses signals and road angle completely controls the vehicle. The majority of ICT models are complex, overly reliant on huge data, and lacking in self-idea functionality. Deep learning and business collaboration are two growing examples of innovative technologies. In this essay, showcasing its computer power, smart devices, and upcoming developments. We are primarily concentrating on the more general and specific applications of artificial intelligence

A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare

Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizing the scheduling of surgeries and appointments. It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering. This paper presents a review of the RL techniques in NLP, highlighting key advancements, challenges, and applications in healthcare. The review begins by visualizing a roadmap of machine learning and its applications in healthcare. And then it explores the integration of RL with NLP tasks. We examined dialogue systems where RL enables the learning of conversational strategies, RL-based machine translation models, question-answering systems, text summarization, and information extraction. Additionally, ethical considerations and biases in RL-NLP systems are addressed

Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems

Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done. Although chatbots have been studied since the dawn of AI, they have particularly caught the imagination of the public and businesses since the launch of easy-to-use and general-purpose Large Language Model-based chatbots like ChatGPT. As businesses look towards chatbots as a potential technology to engage users, who may be end customers, suppliers, or even their own employees, proper testing of chatbots is important to address and mitigate issues of trust related to service or product performance, user satisfaction and long-term unintended consequences for society. This paper reviews current practices for chatbot testing, identifies gaps as open problems in pursuit of user trust, and outlines a path forward

Artificial Intelligence and Fake News

Artificial intelligence depends on digital devices’ performance to perform tasks regularly, requiring human intelligence, using special software to accomplish work easier and faster, carrying out data-packed tasks, and providing useful analytics or solutions. It also requires a specialized laboratory that provides high-performance computing capabilities and a technical platform for deep machine learning. These resources will enable the artificial intelligence platform to master the machine learning techniques of using, developing, simulating, predicting models, and building ready-to-use technological solutions such as analytics platforms. In general, the artificial intelligence system manipulates and manages large amounts of training data to form correlations and patterns used in building future predictions . A limited-memory artificial intelligence system can store a limited amount of information based on the data that have been processed and dealt with previously to build knowledge by memory when combined with pre-programmed data. Consequently, one may ask how artificial intelligence applications contribute to verifying the truthfulness of the media through digital media. How do they contribute to preventing the spread of misleading and false news? This study tries to answer the following question: What methods and tools are adopted by artificial intelligence to detect fake news, especially on social media platforms and depending on artificial intelligence laboratories? This paper is framed within automation control theory and by defining the needed control tools and programs to detect fake news and verify media facts

BEYOND THE BINARY: EVALUATING THE COMPLEXITIES OF AI REGULATION IN THE U.S.

This thesis explores the potential complex interactions between artificial intelligence (AI) and democracy, highlighting the need for the ethical use of AI and strong regulation to address possible adverse consequences for society and democracy. The research employs a comparative analytical framework, examining legislative texts, policy papers, and cultural studies literature to compare the United States (U.S.) and the European Union (EU). The thesis asserts that the EU’s approach is a beneficial template for the U.S. in constructing an AI regulatory framework at the federal level. An ideal framework should include ethical protections, encourage openness, and facilitate innovation, all while cultivating public confidence and promoting international cooperation on AI governance principles. The thesis argues that by conforming to international norms and recognizing culture’s impact on policy, the U.S. may improve its ethical practices in the AI field and maintain its position as a worldwide leader in technology.Distribution Statement A. Approved for public release: Distribution is unlimited.Civilian, Department of Homeland Securit

Toward an Understanding of Responsible Artificial Intelligence Practices

Artificial Intelligence (AI) is influencing all aspects of human and business activities nowadays. Although potential benefits emerged from AI technologies have been widely discussed in many current literature, there is an urgently need to understand how AI can be designed to operate responsibly and act in a manner meeting stakeholders’ expectations and applicable regulations. We seek to fill the gap by exploring the practices of responsible AI and identifying the potential benefits when implementing responsible AI practices. In this study, 10 responsible AI cases were selected from different industries to better understand the use of responsible AI in practices. Four responsible AI practices are identified, including governance, ethically design solutions, risk control and training and education and five strategies for firms who are considering to adopt responsible AI practices are recommended