Academic literature on the topic 'AI ChatBot'
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Journal articles on the topic "AI ChatBot"
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Joshi, Kalpesh. "AI Mental Health Therapist Chatbot." International Journal for Research in Applied Science and Engineering Technology 11, no. 11 (November 30, 2023): 308–11. http://dx.doi.org/10.22214/ijraset.2023.56393.
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Chatbots have become very popular these days as the technology is growing with a very high rate. Due to advancements in the technology chatbots have made our lives easier as we can get to know about many things at our finger tips. So, there are many chatbots available which do the work related to particular things. One such chatbot is ChatGPT, Bard etc. AI chatbots provide a more human like experience with the help of natural language processing and leverage semantics to understand the context of what a person says. Thinking of it we have created a AI Mental Health Therapist Chatbot to provide a medical recommendations according to the problem the user might be facing. It will be able to provide medical support in minimal cost and also recommend the treatment required to the user. This can be a type of advancement in the field of AI which can gain popularity among people. The best AI chatbots can unlock incredible efficiency and also the breadth of AI chatbots available today is incredible.
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Lee, Ju Yoen. "Can an artificial intelligence chatbot be the author of a scholarly article?" Journal of Educational Evaluation for Health Professions 20 (February 27, 2023): 6. http://dx.doi.org/10.3352/jeehp.2022.20.6.
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At the end of 2022, the appearance of ChatGPT, an artificial intelligence (AI) chatbot with amazing writing ability, caused a great sensation in academia. The chatbot turned out to be very capable, but also capable of deception, and the news broke that several researchers had listed the chatbot (including its earlier version) as co-authors of their academic papers. In response, Nature and Science expressed their position that this chatbot cannot be listed as an author in the papers they publish. Since an AI chatbot is not a human being, in the current legal system, the text automatically generated by an AI chatbot cannot be a copyrighted work; thus, an AI chatbot cannot be an author of a copyrighted work. Current AI chatbots such as ChatGPT are much more advanced than search engines in that they produce original text, but they still remain at the level of a search engine in that they cannot take responsibility for their writing. For this reason, they also cannot be authors from the perspective of research ethics.
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Lee, Ju Yoen. "Can an artificial intelligence chatbot be the author of a scholarly article?" Journal of Educational Evaluation for Health Professions 20 (February 27, 2023): 6. http://dx.doi.org/10.3352/jeehp.2023.20.6.
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At the end of 2022, the appearance of ChatGPT, an artificial intelligence (AI) chatbot with amazing writing ability, caused a great sensation in academia. The chatbot turned out to be very capable, but also capable of deception, and the news broke that several researchers had listed the chatbot (including its earlier version) as co-authors of their academic papers. In response, Nature and Science expressed their position that this chatbot cannot be listed as an author in the papers they publish. Since an AI chatbot is not a human being, in the current legal system, the text automatically generated by an AI chatbot cannot be a copyrighted work; thus, an AI chatbot cannot be an author of a copyrighted work. Current AI chatbots such as ChatGPT are much more advanced than search engines in that they produce original text, but they still remain at the level of a search engine in that they cannot take responsibility for their writing. For this reason, they also cannot be authors from the perspective of research ethics.
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Lee, Ju Yoen. "Can an artificial intelligence chatbot be the author of a scholarly article?" Science Editing 10, no. 1 (February 16, 2023): 7–12. http://dx.doi.org/10.6087/kcse.292.
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At the end of 2022, the appearance of ChatGPT, an artificial intelligence (AI) chatbot with amazing writing ability, caused a great sensation in academia. The chatbot turned out to be very capable, but also capable of deception, and the news broke that several researchers had listed the chatbot (including its earlier version) as co-authors of their academic papers. In response, Nature and Science expressed their position that this chatbot cannot be listed as an author in the papers they publish. Since an AI chatbot is not a human being, in the current legal system, the text automatically generated by an AI chatbot cannot be a copyrighted work; thus, an AI chatbot cannot be an author of a copyrighted work. Current AI chatbots such as ChatGPT are much more advanced than search engines in that they produce original text, but they still remain at the level of a search engine in that they cannot take responsibility for their writing. For this reason, they also cannot be authors from the perspective of research ethics.
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Zhang, Jingwen, Yoo Jung Oh, Patrick Lange, Zhou Yu, and Yoshimi Fukuoka. "Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint." Journal of Medical Internet Research 22, no. 9 (September 30, 2020): e22845. http://dx.doi.org/10.2196/22845.
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Background Chatbots empowered by artificial intelligence (AI) can increasingly engage in natural conversations and build relationships with users. Applying AI chatbots to lifestyle modification programs is one of the promising areas to develop cost-effective and feasible behavior interventions to promote physical activity and a healthy diet. Objective The purposes of this perspective paper are to present a brief literature review of chatbot use in promoting physical activity and a healthy diet, describe the AI chatbot behavior change model our research team developed based on extensive interdisciplinary research, and discuss ethical principles and considerations. Methods We conducted a preliminary search of studies reporting chatbots for improving physical activity and/or diet in four databases in July 2020. We summarized the characteristics of the chatbot studies and reviewed recent developments in human-AI communication research and innovations in natural language processing. Based on the identified gaps and opportunities, as well as our own clinical and research experience and findings, we propose an AI chatbot behavior change model. Results Our review found a lack of understanding around theoretical guidance and practical recommendations on designing AI chatbots for lifestyle modification programs. The proposed AI chatbot behavior change model consists of the following four components to provide such guidance: (1) designing chatbot characteristics and understanding user background; (2) building relational capacity; (3) building persuasive conversational capacity; and (4) evaluating mechanisms and outcomes. The rationale and evidence supporting the design and evaluation choices for this model are presented in this paper. Conclusions As AI chatbots become increasingly integrated into various digital communications, our proposed theoretical framework is the first step to conceptualize the scope of utilization in health behavior change domains and to synthesize all possible dimensions of chatbot features to inform intervention design and evaluation. There is a need for more interdisciplinary work to continue developing AI techniques to improve a chatbot’s relational and persuasive capacities to change physical activity and diet behaviors with strong ethical principles.
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Temsah, Mohamad-Hani, Fadi Aljamaan, Khalid H. Malki, Khalid Alhasan, Ibraheem Altamimi, Razan Aljarbou, Faisal Bazuhair, et al. "ChatGPT and the Future of Digital Health: A Study on Healthcare Workers’ Perceptions and Expectations." Healthcare 11, no. 13 (June 21, 2023): 1812. http://dx.doi.org/10.3390/healthcare11131812.
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This study aimed to assess the knowledge, attitudes, and intended practices of healthcare workers (HCWs) in Saudi Arabia towards ChatGPT, an artificial intelligence (AI) Chatbot, within the first three months after its launch. We also aimed to identify potential barriers to AI Chatbot adoption among healthcare professionals. A cross-sectional survey was conducted among 1057 HCWs in Saudi Arabia, distributed electronically via social media channels from 21 February to 6 March 2023. The survey evaluated HCWs’ familiarity with ChatGPT-3.5, their satisfaction, intended future use, and perceived usefulness in healthcare practice. Of the respondents, 18.4% had used ChatGPT for healthcare purposes, while 84.1% of non-users expressed interest in utilizing AI Chatbots in the future. Most participants (75.1%) were comfortable with incorporating ChatGPT into their healthcare practice. HCWs perceived the Chatbot to be useful in various aspects of healthcare, such as medical decision-making (39.5%), patient and family support (44.7%), medical literature appraisal (48.5%), and medical research assistance (65.9%). A majority (76.7%) believed ChatGPT could positively impact the future of healthcare systems. Nevertheless, concerns about credibility and the source of information provided by AI Chatbots (46.9%) were identified as the main barriers. Although HCWs recognize ChatGPT as a valuable addition to digital health in the early stages of adoption, addressing concerns regarding accuracy, reliability, and medicolegal implications is crucial. Therefore, due to their unreliability, the current forms of ChatGPT and other Chatbots should not be used for diagnostic or treatment purposes without human expert oversight. Ensuring the trustworthiness and dependability of AI Chatbots is essential for successful implementation in healthcare settings. Future research should focus on evaluating the clinical outcomes of ChatGPT and benchmarking its performance against other AI Chatbots.
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Abdallah, Wael, Arezou Harraf, Osama Mosusa, and Abdalmuttaleb Sartawi. "Investigating Factors Impacting Customer Acceptance of Artificial Intelligence Chatbot: Banking Sector of Kuwait." International Journal of Applied Research in Management and Economics 5, no. 4 (January 7, 2023): 45–58. http://dx.doi.org/10.33422/ijarme.v5i4.961.
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The Purpose: This study investigates the role of Artificial Intelligence- chatbot (AI chatbot) quality and AI chatbot users across various banking needs and its impact on customer acceptance of AI chatbots through the mediating role of perceived usefulness and ease of use. Design/methodology/approach – This quantitative study uses a cross-sectional time dimension. The questionnaire of this study was developed using multiple academic sources. Partial least square structural equation modeling was used to analyze the data, and the SmartPLS 4 software was used for the calculation. Finding - The findings indicated a significant positive direct relationship between AI chatbot quality and acceptance of AI chatbot (path coefficient of 0.138 and p-value of 0.022). At the same time, the direct relationship between the AI-chatbot user and the acceptance of the AI chatbot was insignificant (path coefficient = 0.0.096, and p-value = 0.246). While the results of the indirect relationship reveal that perceived usefulness and ease of use partially mediated the relationship between AI chatbot quality and acceptance of AI chatbots. The perceived usefulness and ease of use fully mediated the relationship between AI chatbot users and acceptance of the AI chatbot. Originality/value – The results of this study developed a framework for banking and other customer-oriented businesses in understanding and developing AI chatbots to address customer needs.
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Pandey, Siddhant, Nikhil Chandra Pandey, and Yash Bajaj. "AI Enabled Chatbot." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (April 30, 2024): 1761–64. http://dx.doi.org/10.22214/ijraset.2024.60147.
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Abstract: As technology continues its rapid evolution, the integration of Artificial Intelligence (AI) into chatbot systems emerges as a pivotal frontier in reshaping human-computer interaction. This research paper embarks on a comprehensive exploration of the intricate synergy between AI technologies and chatbot development, with a primary focus on elevating user interactions to unprecedented levels of sophistication and intuitiveness. By delving into a nuanced understanding of methodologies, technologies, and challenges, this study aims to provide a holistic perspective on the present state and future potential of AIenabled chatbots. The journey begins with a retrospective analysis of the evolution of chatbots, tracing their trajectory from rulebased systems to the forefront of AI-driven conversational agents. The advent of AI, particularly Natural Language Processing (NLP) and machine learning algorithms, has ushered in a new era, enabling chatbots to not only comprehend but also respond intelligently, mirroring the complexities of human language.
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Kumar, Kartik. "An Educational Chatbot Using AI in Radiotherapy." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 16, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem34122.
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The surge in demand for information in cancer centers and hospitals, particularly during the pandemic, overwhelmed the limited manpower available. To address this challenge, there arose a need to develop an educational chatbot tailored for diverse user groups in the field of radiotherapy, including patients and their families, the general public, and radiation staff. Objective: In response to the pressing clinical demands, the primary aim of this endeavor is to delve into the intricacies of designing an educational chatbot for radiotherapy using artificial intelligence.Methods: The chatbot is meticulously crafted using a dialogue tree and layered structure, seamlessly integrated with artificial intelligence functionalities, notably natural language processing (NLP). This adaptable chatbot can be deployed across various platforms, such as IBM Watson Assistant, and embedded in websites or diverse social media channels.Results: Employing a question-and-answer methodology, the chatbot adeptly engages users seeking information on radiotherapy, presenting an approachable and reassuring interface. Recognizing that users, often anxious, may struggle to articulate precise questions, the chatbot facilitates the interaction by offering a curated list of questions. The NLP system augments the chatbot's ability to discern user intent, ensuring the provision of accurate and targeted responses. Notably, the study reveals that functional features, including mathematical operations, are preferred in educational chatbots, necessitating routine updates to furnish fresh content and features.Conclusions: The study culminates in the affirmation that leveraging artificial intelligence facilitates the creation of an educational chatbot capable of disseminating information to users with diverse backgrounds in radiotherapy. Furthermore, the importance of rigorous testing and evaluation, informed by user feedback, is emphasized to iteratively enhance and refine the chatbot's performance. Keywords: AI, machine learning, NLP, chatbot, radiotherapy, IoT, healthcare.
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Lin, Chien-Chang, Anna Y. Q. Huang, and Stephen J. H. Yang. "A Review of AI-Driven Conversational Chatbots Implementation Methodologies and Challenges (1999–2022)." Sustainability 15, no. 5 (February 22, 2023): 4012. http://dx.doi.org/10.3390/su15054012.
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A conversational chatbot or dialogue system is a computer program designed to simulate conversation with human users, especially over the Internet. These chatbots can be integrated into messaging apps, mobile apps, or websites, and are designed to engage in natural language conversations with users. There are also many applications in which chatbots are used for educational support to improve students’ performance during the learning cycle. The recent success of ChatGPT also encourages researchers to explore more possibilities in the field of chatbot applications. One of the main benefits of conversational chatbots is their ability to provide an instant and automated response, which can be leveraged in many application areas. Chatbots can handle a wide range of inquiries and tasks, such as answering frequently asked questions, booking appointments, or making recommendations. Modern conversational chatbots use artificial intelligence (AI) techniques, such as natural language processing (NLP) and artificial neural networks, to understand and respond to users’ input. In this study, we will explore the objectives of why chatbot systems were built and what key methodologies and datasets were leveraged to build a chatbot. Finally, the achievement of the objectives will be discussed, as well as the associated challenges and future chatbot development trends.
Dissertations / Theses on the topic "AI ChatBot"
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Aljadri, Sinan. "Chatbot : A qualitative study of users' experience of Chatbots." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105434.
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The aim of the present study has been to examine users' experience of Chatbot from a business perspective and a consumer perspective. The study has also focused on highlighting what limitations a Chatbot can have and possible improvements for future development. The study is based on a qualitative research method with semi-structured interviews that have been analyzed on the basis of a thematic analysis. The results of the interview material have been analyzed based on previous research and various theoretical perspectives such as Artificial Intelligence (AI), Natural Language Processing (NLP). The results of the study have shown that the experience of Chatbot can differ between businesses that offer Chatbot, which are more positive and consumers who use it as customer service. Limitations and suggestions for improvements around Chatbotar are also a consistent result of the study.Den föreliggande studie har haft som syfte att undersöka användarnas upplevelse av Chatbot utifrån verksamhetsperspektiv och konsumentperspektiv. Studien har också fokuserat på att lyfta fram vilka begränsningar en Chatbot kan ha och eventuella förbättringar för framtida utvecklingen. Studien är baserad på en kvalitativ forskningsmetod med semistrukturerade intervjuer som har analyserats utifrån en tematisk analys. Resultatet av intervjumaterialet har analyserat utifrån tidigare forskning och olika teoretiska perspektiv som Artificial Intelligence (AI), Natural Language Processing (NLP). Resultatet av studien har visat att upplevelsen av Chatbot kan skilja sig mellan verksamheter som erbjuder Chatbot, som är mer positiva och konsumenter som använder det som kundtjänst. Begränsningar och förslag på förbättringar kring Chatbotar är också ett genomgående resultat i studien.
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Jusko, Ján. "Chatbot pro Smart Cities." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403204.
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The aim of this work is to simplify access to information for citizens of the city of Brno and at the same time to innovate the way of communication between the citizen and his city. The problem is solved by creating a conversational agent - chatbot Kroko. Using artificial intelligence and a Czech language analyzer, the agent is able to understand and respond to a certain set of textual, natural language queries. The agent is available on the Messenger platform and has a knowledge base that includes data provided by the city council. After conducting an extensive user testing on a total of 76 citizens of the city, it turned out that up to 97\% of respondents like the idea of a city-oriented chatbot and can imagine using it regularly. The main finding of this work is that the general public can easily adopt and effectively use a chatbot. The results of this work motivate further development of practical applications of conversational agents.
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Eklund, Joakim, and Fred Isaksson. "Identifying & Evaluating SystemComponents for Cognitive Trustin AI-Automated Service Encounters : Trusting a Study- & Vocational Chatbot." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-386044.
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The intensifying idea that AI soon will be a part of our everyday life allows for dreams about the complex relationship we one day could have with non-biological social intelligence. However, establishing societal and individual acceptance of AI-powered autonomy in disciplines built upon to the reliance to human competence raises a number of pressing challenges. One of them being, what system components will engender respectively counteract cognitive trust in socially oriented AI-automated processes? This masters thesis tackles the seemingly ambiguous concept of trust in automation by identifying and evaluating system components that affect trust in a confined and contextualised setting. Practically, we design, construct and test an AI-powered chatbot, Ava, that contains socially oriented questions and feedback about study- and vocational guidance. Through a comparative study of different system versions, including both quantitative and qualitative data, we contribute to the framework for identifying and evaluating human trust in AI-Automated service encounters. We show how targeted alterations to design choices constituting the system components transparency, unbiasses and system performance, identified to affect trust, has consequences on the perception of the cognitive trust concepts integrity, benevolence and ability. Our results display a way of conduct for practitioners looking to prioritise and develop trustworthy autonomy. More specifically, we account for how cognitive trust is decreased when system opacity is increased. Moreover, we display even more concerning effects on trust due to micking contextual bias in the conversation agent.
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Gligorijevic, Ilic Nemanja. "Utveckling av en FAQ chatbot - för frågor om ett program på ett universitet." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85197.
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The implementation of chatbots and service services is becoming more common. The reason for this is that they are constantly available to answer questions, no matter what time it is. To make one chatbot is not just to write questions and specific answers. Communicating with one chatbot should, as much as possible, look like communicating with another human. The purpose of this report is to create a chatbot that will be used at Luleå university of technology and that will answer questions about system science. Furthermore, the goal is to investigate which design principles should be implemented, their possible concretization, when making chatbots, and possibly coming to new principles. The method used to make the chatbot is Design Science Research Methodology (DSRM). DSRM focuses on solving the problem by creating an IT artifact, which in this case is a chatbot. The result of this work is a created chatbot and design principles that were implemented during the development process.
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Svenningsson, Nina. "What’s up AI?! : En undersökning kring människoliknande beteende hos chatbotar och dess påverkan på användarupplevelsen." Thesis, Högskolan Kristianstad, Fakulteten för ekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-19854.
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Artificiell intelligens (AI) sprider sig genom samhället och används mer och mer inom flera olika områden. Chatbotar är en populär form av social AI som använder sig av naturligt språk för att kommunicera med användare. Det finns olika åsikter kring huruvida en chatbot ska prata och bete sig människolikt eller inte. Den ena sidan argumenterar att chatbotar ska fortsätta utvecklas för att kunna simulera mänskligt beteende och intelligens, å andra sidan argumenteras att chatbotar ska vara tydliga med att de är maskiner och att det även kan vara positivt för användarupplevelsen om chatbotar inte är alltför människolika. Dessutom finns det teorier om att ett beteende som är för människolikt kan skapa obehag hos användaren. Detta examensarbete syftar till att undersöka den diskrepans som har observerats i resultaten från vetenskapliga studier för att ge indikationer på vilka faktorer som bidrar till en positiv användarupplevelse i interaktionen med chatbotar i förhållande till hur människolika de uppfattas. Resultatet visar på att det finns en stor bredd i användares preferenser för hur en chatbot bör bete sig vilket gör det svårt att nämna specifika människoliknande faktorer som är tilltalande för en större grupp användare. Om man idag vill designa en chatbot som tilltalar så många användare som möjligt bör man ge den en officiell/formell ton samt låta den svara kort, koncist och med sofistikerade ordval och välkonstruerade meningar. För att gå vidare rekommenderas bland annat att undersöka hur chatbotar kan anpassa sitt beteende efter olika användare för att skapa en positiv användarupplevelse.
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Andersson, Ludvig, and Erik Felin. "AI inom vårdrådgivning : En attitydanalys på 1177 Vårdguidens sjuksköterskor." Thesis, Uppsala universitet, Institutionen för informatik och media, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-376660.
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Artificiell intelligens (AI) är en teknik som blir allt vanligare inom en rad områden, inte minst i syfte att effektivisera. I Sverige har kritik riktats mot vårdbranschen och de långa vårdköer som tynger den. Undersökningen syftar till att undersöka AI:s potential inom vårdbranschen i allmänhet och 1177 Vårdguiden i synnerhet. Genom en attitydanalys baserad på fyra intervjuer med 1177 Vårdguidens sjuksköterskor, kommer undersökningen fram till att AI har en viss potential när det gäller administrativa ärenden. Vad gäller vårdärenden är attityden inför AI mer negativ och dess potential tros inte vara tillräcklig för att ersätta den mänskliga faktorn.Artificial intelligence is a technology that is becoming increasingly common in a number of fields, not least in order to streamline. In Sweden criticism has been directed at the healthcare industry and the long queues that overburden it. The study aims to investigate AI's potential in the healthcare industry in general and 1177 Vårdguiden in particular. Through an attitude analysis based on four interviews with 1177 Vårdguiden nurses, the survey concludes that AI has some potential in terms of administrative matters. When it comes to care-related cases, the attitude towards AI is more negative and its potential is not believed to be sufficient in order to replace the human factor.
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Kero, Chanelle, and Veronica Törnblom. "Utveckling av en chatbots dialog för implementation i en webbaserad kundtjänst." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-69046.
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Automatisering av kundtjänster genom implementering av chatbotar blir allt vanligare för att kunna erbjuda kunder en mer tillgänglig och effektiv service. Vid implementering av chatbotar i kundtjänster lämnas den mänskliga kontrollen och kundens upplevelse delvis över till ett digitalt system, vilket ställer krav på utformning av chatbotars dialoger. Syftet med arbetet är att ta fram en artefakt i form av en chatbot och utveckla dess dialog för en framtida implementation i en kundtjänst. Arbetet ämnar att ta fram designprinciper för utformning och utveckling av chatbotar och deras dialoger i en kundtjänstmiljö. Den forskningsmetod som tillämpades vid utvecklingen av artefakten var Design Science Research Methodology (DSRM). En litteraturstudie genomfördes och data samlades in genom möten samt en intervju med det företag som varit uppdragsgivare till arbetet. Arbetet resulterade i en demosida innehållande en chatbot, samt en sida för administratörer där de har en översikt av chatbotens genomförda interaktioner. Tre designprinciper togs även fram för utveckling av chatbotars dialog inom kundtjänst, vilka blev arbetets bidrag. De slutsatser som identifierades var att en chatbot bör kontrollera att användaren fått svar på sitt kundtjänstärende, en chatbot bör erbjuda mänsklig service vid missförstånd, en chatbot kan inte ersätta mänsklig service fullt ut samt att en chatbot bör ha en strukturerad datainsamling av genomförda interaktioner för att kunna utveckla och förbättra chatbotens dialog.Automation of customer service through implementation of chatbots is becoming increasingly common in order to provide customers with a more accessible and efficient service. When implementing chatbots in customer services, human control and the customer experience are partially shifted to a digital system, which puts requirement on the chatbot’s dialogue. The purpose of this report is to develop an artifact for a client. The artifact is a web page containing a chatbot. The report aims to develop design principles for development of chatbots and their dialogues in a customer service. The research method used in the development of the artifact was Design Science Research Methodology (DSRM). A literature study was conducted, and data was collected through meetings and an interview with the client. The report resulted in a demo page containing a chatbot and a page for administrators with an overview of saved chats. Three design principles were also formulated for developing chatbots in customer service, which is the contribution of the report. The conclusions identified were that a chatbot should check that the user got the correct answer, a chatbot should offer human service in case of misunderstanding, a chatbot cannot fully replace human service and a chatbot should have a structured data collection of completed interactions for developing and improvement of the chatbot’s dialogue.
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Wärmegård, Erik. "Intelligent chatbot assistant: A study of integration with VOIP and Artificial Intelligence." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42693.
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Development and research on Artificial Intelligence have increased during recent years, and the field of medicine is not excluded as a target audience for this top modern technology. Despite new research and tools in favor of medical care, the staff is still under heavy workloads. The goal of this thesis is to analyze and propose the possibility of a chatbot that aims to ease the pressure on the medical staff. To provide a guarantee that patients are being monitored. With Artificial Intelligence, VOIP, Natural Language Processing, and web development, this chatbot can communicate with a patient, which will act as an assistant tool that conducts preparatory work for the medical staff. The system of the chatbot is integrated through a web application where the administrator can initiate call and store clients onto the database. To ascertain that the system operates in real-time, several tests have been carried out to tests concerning the latency between subsystems and the quality of service.I utvecklingen av intelligenta system har sjukvården etablerat sig som en stor målgrupp. Trots avancerade tekniker så är sjukvården fortfarande under tung belastning. Målet för detta examensarbete är att undersöka möjligheten av en chatbot vars syfte är att lätta på arbetsbelastningen hos sjukvårdspersonalen och samtidigt erbjuda en garanti för att patienter får den tillsyn och återkoppling de behöver. Med hjälp av Artificiell Intelligens, VOIP, Natural Language Processing och webbutveckling kan denna chatbot kommunicera med patienten. Chatboten agerar som ett assisterande verktyg som står för ett förarbete i beslutstagandet för sjukvårdspersonal. Ett systemsom inte bara ger praktisk nytta utan också ett främjande av den utveckling som Artificiell Intelligens gör inom sjukvården. Systemet administreras genom en hemsida som kopplar samman de flera olika komponenterna. Här kan en administratör initiera samtal och spara klienter som ska ringas till databasen. För att kunna fastställa att systemet opererar i realtid har görs flertalet prestandatester avseende både tidsfördröjningar och samtalskvalité.
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Lilja, Adam, and Max Kihlborg. "Important criteria when choosing a conversational AI platform for enterprises." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280896.
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This paper evaluates and analyzes three conversational AI-platforms; Dialogflow (Google), Watson Assistant (IBM) and Teneo (Artificial Solutions) on how they perform based on a set of criteria; pricing model, ease-of-use, efficiency, experience working in the software and what results to expect from each platform. The main focus was to investigate the platforms in order to acquire an understanding of which platform would best be suited for enterprises. The platforms were compared by performing a variety of tasks aiming to answer these questions. The technical research was combined with an analysis of each company’s pricing model and strategy to get an understanding of how they target their products on the market. This study concludes that different softwares may be suitable for different settings depending on the size of an enterprise and the demand for complex solutions. Overall, Teneo outperformed its competitors in these tests and seems to be the most scalable solution with the ability to create both simple and complicated solutions. It was more demanding to get started in comparison with the other platforms, but became more efficient as time progressed. Some findings include that Dialogflow and Watson Assistant lacked capabilities when faced with complex and complicated tasks. From a pricing strategy point of view, the companies are similar in their approach but Artificial Solutions and IBM has more flexible methods while Google has a fixed pricing strategy. Combining the pricing strategy and technical analysis this implicates that Teneo would be a better choice for larger enterprises while Watson Assistant and Dialogflow may be more suitable for smaller ones.Det här arbetet evaluerar och analyserar tre konversationella AI-plattformar; Dialogflow (Google), Watson Assistant (IBM) och Teneo (Artificial Solutions) utifrån hur de presterar baserat på ett antal kriterier; prismodell, enkel användning, effektivitet, upplevelse att arbeta i programvaran och vilka resultat man förväntar sig från varje plattform. Huvudsakligt fokus var att undersöka plattformarna för att få en uppfattning om vilken plattform som skulle passa bäst för företag. Plattformarna jämfördes genom att utföra en mängd olika uppgifter som syftade till att besvara dessa frågor. Den tekniska forskningen kombinerades med en analys av varje företags prismodell och prisstrategi för att få en uppfattning av hur de riktar sina produkter på marknaden. Denna studie drar slutsatsen att olika programvaror kan vara lämpliga för olika sammanhang beroende på ett företags storlek och dess efterfrågan på komplexa lösningar. Sammantaget överträffade Teneo sina konkurrenter i dessa tester och verkar vara den mest skalbara lösningen med förmågan att skapa både enkla och komplicerade lösningar. Det var mer krävande att komma igång i jämförelse med de andra plattformarna, men det blev mer effektivt med tiden. Vissa fynd inkluderar att Dialogflow och Watson Assistant saknade kapacitet när de mötte komplexa och komplicerade uppgifter. Från en prissättningsstrategisk synvinkel är företagen liknande i sin metod men Artificial Solutions och IBM har mer flexibla metoder medan Google har en fast prissättningstrategi. Genom att kombinera prisstrategi och teknisk analys innebär detta att Teneo skulle vara ett bättre val för större företag medan Watson Assistant och Dialogflow kan vara mer lämpade för mindre.
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Castellucci, Matteo. "Applicazione di tecniche AI per la progettazione di un sistema a supporto del paziente iperteso." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21654/.
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In questa tesi si è cercato di trovare le soluzioni più efficaci a supporto delle questioni legate all'ipertensione di seguito descritte attraverso l'uso di tecniche riguardanti l'intelligenza artificiale e l'Internet of Things.
Uno tra i compiti dei medici che si occupano di curare i malati di ipertensione è quello di elaborare protocolli per quanto riguarda la prevenzione e la cura di questa malattia, i quali vengono periodicamente aggiornati. Per supportare ciò, il primo progetto sviluppato è consistito in un'analisi dei dati sul dataset ottenuto a partire dall'elaborazione delle risposte date ai questionari che sono stati distribuiti durante la Giornata Mondiale dell'Ipertensione. A partire da questo, si è cercato di evidenziare la classe di persone che con più probabilità sono malate di ipertensione in modo tale che le linee guida aggiornate si concentrino maggiormente su costoro.
La seconda questione affrontata è che non sempre le cure che vengono prescritte sono efficaci, talvolta a causa del medico, talvolta a causa del paziente. Si rende perciò necessario fornire ai pazienti degli strumenti che li aiutino direttamente nella cura della loro malattia. Devono avere anche lo scopo di aiutare il medico nel suo lavoro di monitoraggio periodico delle condizioni di salute del paziente, perché possa avere realmente il polso della situazione. Per fare questo, il secondo progetto ha riguardato lo sviluppo di un chatbot disponibile sulla piattaforma di messaggistica istantanea Telegram ad uso dei malati di ipertensione. Questo assistente virtuale permette loro di registrare le misurazioni di pressione che settimanalmente devono effettuare e ricorda loro di farlo quando passa troppo tempo dall'ultima misurazione. Il sistema permette inoltre di visualizzare medie e grafici delle misurazioni che sono state raccolte cosicché il medico può affidarsi ad uno strumento più evoluto del semplice libretto diario in cui il paziente annota tutte le misurazioni.
Books on the topic "AI ChatBot"
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Crowder, James. AI Chatbots. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-45509-4.
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Arnone, Gioia. AI and Chatbots in Fintech. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55536-7.
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Kempt, Hendrik. Chatbots and the Domestication of AI. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56290-8.
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Femia, Ivan. SAP Conversational AI for Chatbot Development. Rheinwerk Publishing Inc., 2019.
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Rusell, Phillip, and Daniel Morris. Facebook Chatbot Secrets 2019: How to Build Highly Converting AI Powered Chatbots Marketing for Free with Chatfuel In 1hour. Independently Published, 2018.
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Bisser, Stephan. Microsoft Conversational AI Platform for Developers: End-To-End Chatbot Development from Planning to Deployment. Apress L. P., 2021.
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Bisser, Stephan. Microsoft Conversational AI-Platform Für Entwickler: Ende-Zu-Ende-Chatbot-Entwicklung Von der Planung Bis Zum Einsatz. Springer Berlin / Heidelberg, 2023.
Find full textBook chapters on the topic "AI ChatBot"
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Leung, Rosanna, and Iris Sheungting Lo. "Can ChatGPT Inspire Me? Evaluate Students’ Questioning Techniques on AI Tool for Overcoming Fixation." In Information and Communication Technologies in Tourism 2024, 75–86. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-58839-6_9.
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AbstractAI-powered large language models are shaping a new era of learning. Students use AI chatbots for information search and idea inspiration. However, are students’ questioning skills effective enough to interact with an AI Chatbot? This study explores the interaction between students and ChatGPT on idea generation and identifies whether participants can effectively use AI chatbots to simulate creativity for idea generation. The results indicated that, rather than discussing their idea with AI Chatbot for suggestions and recommendations to enhance the existing ideas, many students ask AI to generate more ideas without providing directions. Participants reflected that ChatGPT provided generic ideas and were unsatisfied with its creativity. They are more positive towards using the question guide, developed using SCAMPER questioning technique combined with a narrative approach by the researcher, compared to ChatGPT because the question guide enables perspective-shifting to generate ideas from a new perspective.
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Biswas, Manisha. "Chatbot with TensorFlow." In Beginning AI Bot Frameworks, 139–82. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3754-0_5.
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Cronin, Irena. "Exploring Chatbot Technologies." In Understanding Generative AI Business Applications, 87–95. Berkeley, CA: Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0282-9_6.
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Bisser, Stephan. "Building a Chatbot." In Microsoft Conversational AI Platform for Developers, 177–238. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6837-7_5.
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Bisser, Stephan. "Testing a Chatbot." In Microsoft Conversational AI Platform for Developers, 239–51. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6837-7_6.
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Bisser, Stephan. "Publishing a Chatbot." In Microsoft Conversational AI Platform for Developers, 253–62. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6837-7_7.
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Harris, Preethi, S. Manisha, S. Deepika, S. Dharshini, and M. Dikshita. "AI Chatbot for Organ Donation." In Advances in Intelligent Systems and Computing, 1021–31. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7330-6_76.
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Bialkova, Svetlana. "Introduction to Chatbot AI Applications." In The Rise of AI User Applications, 3–16. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56471-0_1.
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Assayed, Suha Khalil, Manar Alkhatib, and Khaled Shaalan. "A Systematic Review of Conversational AI Chatbots in Academic Advising." In BUiD Doctoral Research Conference 2023, 346–59. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56121-4_33.
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AbstractPurpose – This paper aims to review several studies published between 2018 to 2022 about advising chatbots in schools and universities as well as evaluating the state-of-the-art machine learning models that are deployed into these models.Methodology – This paper follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), it demonstrated the main phases of the systematic review, it starts with screening 128 articles and then including 11 articles for systematic review which focused on the current services of the advising chatbots in schools and universities, as well the artificial models that are embedded into the chatbots.Findings– Two main dimensions with other sub-dimensions are extracted from the 11 included studies as it shows the following: 1- Advising chatbots AI Architecture which includes other sub-dimensions on identifying the deep learning based chatbots, hybrid chatbots and other open-resources for customizing chatbots; 2- The goals of the advising chatbot as it includes both the admission advising and academic advising.Conclusion – Most of studies shows that advising chatbots are developed for admission and academic advising. Few researchers who study the chatbots in high schools, there is a lack of studies in developing chatbots for students advising in high schools.Limitations and future work – This study is constrained to review the studies from 2018–2022, and it is not exposed to the chatbots artifacts, even though, the human-chatbot interaction has an essential impact on students’ experiences. Future research should include the impact of chatbots interactive design and students’ experiences.
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Bialkova, Svetlana. "Chatbot Agency—Model Testing." In The Rise of AI User Applications, 109–26. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56471-0_7.
Full textConference papers on the topic "AI ChatBot"
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Jain, Manali, Prasad Nathe, Khushit Rathod, Navneet Kumar Tiwari, Suruchi Dedgaonkar, and Chaitali Shewale. "AI HealthCare Chatbot." In 2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon). IEEE, 2024. http://dx.doi.org/10.1109/mitadtsocicon60330.2024.10575622.
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Donnellan, Mark, Michael Wilkins, and Kane Linton. "An investigation of the efficacy of a ChatGPT-powered chatbot." In EuroCALL 2023: CALL for all Languages. Editorial Universitat Politécnica de Valéncia: Editorial Universitat Politécnica de Valéncia, 2023. http://dx.doi.org/10.4995/eurocall2023.2023.16976.
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One of the newest tools for language learning is AI-powered chatbots which allow students to engage in interactive conversations with a chatbot. English Central is a digital language learning platform that allows students to watch videos, study vocabulary, and produce spoken language through short interactive videos. In addition to these three core components, English Central has recently added a chatbot powered by ChatGPT. This paper shares the results of a pilot study that analysed data from Japanese university students who engaged in interactions with this chatbot. The authors introduce quantitative data showing the quantity and quality of the interactions and discuss the strategies they implemented to encourage longer interactions. A student feedback survey was conducted and the results of this are also shared. The results suggested that although many students reported benefits to using a chatbot, the strategies implemented did not lead to significantly longer interactions, and that many students felt frustrated when the chatbot did not understand their utterances.
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Bilal, Mushtaq. "Beyond Boundaries: Generative AI for Sustainable Academic Advancements." In Congreso Internacional de Ingeniería de Sistemas. Universidad de Lima, 2024. http://dx.doi.org/10.26439/ciis2023.7076.
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Since its launch in November 2022, Open AI’s chatbot Generative Pre-trained Transformer, commonly known as ChatGPT, has become one of the most popular generative AI applications in the world (OpenIA, n. d.). Academics across the world are concerned about how ChatGPT is dramatically changing the pedagogical and research landscape. In this paper, I discuss some of the best practices for using ChatGPT for academic purposes.
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Athikkal, Sagina, and John Jenq. "Voice Chatbot for Hospitality." In 12th International Conference on Computer Science and Information Technology (CCSIT 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.121315.
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Chatbot is a machine with the ability to answer automatically through a conversational interface. A chatbot is considered as one of the most exceptional and promising expressions of human computer interaction. Voice-based chatbots or artificial intelligence (AI) devices transform human-computer bidirectional interactions that allow users to navigate an interactive voice response (IVR) system with their voice generally using natural language. In this paper, we focus on voice based chatbots for mediating interactions between hotels and guests from both the hospitality technology providers’ and guests’ perspectives. We developed a hotel web application with the capability to receive a voice input. The application was developed with Speech recognition and deep synthesis API for voice to text and text to voice conversion, a closed domain question answering (cdQA) NLP solution was used for query the answer.
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Neji, Wissal, Naouel Boughattas, and Faten Ziadi. "Exploring New AI-Based Technologies to Enhance Students’ Motivation." In InSITE 2023: Informing Science + IT Education Conferences. Informing Science Institute, 2023. http://dx.doi.org/10.28945/5143.
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Aim/Purpose. The aim of this study is to propose a teaching approach based on AI-based chatbot agents and to determine whether the use of this approach increases the students’ motivation. Background. Today, chatbots are an integral part of students’ lives where they are used in various contexts. Therefore, we are interested in incorporating these tools into our teaching process in order to profit from their benefits, assist and guide students while working with to prevent issues such as plagiarism and mainly to boost students’ motivation. Methodology. Using the proposed approach, new chatbot based learning activities were de-signed in three different courses for computer science engineering students. A mixed-method experimental study was conducted to evaluate students’ impression and satisfaction. Survey results of the students (N=58) who participated in the experiment (experimental group) were compared to the results of the students from the control group (N=60). Contribution. Trending AI conversational agents can be engaged in daily teaching activities as a learning assistant and coach to boost students motivation and skills development. Findings. Our study focuses on the impact of chatbots on student’s motivation. The study aimed to analyze the benefits and drawbacks associated with these conversational chatbots. Our findings revealed the significant role that chatbots can play in enhancing student motivation and improving teaching practices.
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Singh, Ajay, Tianxia Jia, and Varun Nalagatla. "Generative AI Enabled Conversational Chatbot for Drilling and Production Analytics." In ADIPEC. SPE, 2023. http://dx.doi.org/10.2118/216267-ms.
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Abstract Getting intelligent insight from large amount of dataset is critical for Energy companies to optimize their operations across various business segments such as drilling, production and completion etc. The paper proposes end-to-end workflow to 1) extract data form rig and production reports and store dataset into databases 2) build a conversational generative AI enabled chatbot which is trained to answer questions related to drilling and production monitoring, queries dataset, frequently performed diagnostic analysis and can generate recommendations to improve operations. The chatbot is integrated with large language models (LLM) and machine learning models (ML) on the cloud and based on questions asked by user it provides answers in conversational settings. Chatbot is hosted in cloud and is integrated with various databases, document repositories and several machine learning model. The machine learning models are built to enable chatbot's capability to answer questions related to drilling and production analytics. Chatbot is integrated with user interface where user can type or ask questions. Using natural language process (NLP) and artificial intelligence (Al), chatbot understands intent of question and if needed asks relevant follow-up questions to provide the answer. Chatbot can also perform statistical analysis, generate SQL queries on datasets and can use those statistics to answer questions. Further if enabled, chatbot can also search information from drilling and production reports and scientific articles. Three case studies are presented. In case study#1, chatbot was integrated with operator's historical PDF drilling reports (Volve dataset), which traditionally are not easy to extract and analyze at scale. Several thousand drilling reports were extracted and stored in database. Various capabilities were added to chatbot such has Cross-documents insights and trend, for example, well progression, operation history, can be generated and displayed on user interface and further analysis can be performed in conversational manner. The dataset created was used to perform comparative analysis identifying wells having significant higher non production time (NPT) due to repair or fishing events. In this manner, chatbot can compare one well's operational statistics with other well and generate various visuals which helps identifying possible ways to improve drilling operations. Similarly, chatbot was also trained to provide answers for production diagnostics such as comparing well's relative performances and root cause identification for poor performing wells. When analyzed on test dataset chatbot was able to identify 20% uplift in production for wells supported on plunger lift. Finally, chatbot was enabled to support NLP based searches. Engineers can ask specific questions such as "provide operational log for well F4 when fishing happened and sort the result by reporting date in ascending order. Show me both SQL query and the resulted table" and chatbot will generate SQL query and resulted table. The work demonstrates that generative AI has great potential to transform the Energy industry.
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Bozic, Josip, Oliver A. Tazl, and Franz Wotawa. "Chatbot Testing Using AI Planning." In 2019 IEEE International Conference On Artificial Intelligence Testing (AITest). IEEE, 2019. http://dx.doi.org/10.1109/aitest.2019.00-10.
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Vannala, Rachana, S. B. Swathi, and Yuvaraj Puranam. "AI Chatbot For Answering FAQ’s." In 2022 IEEE 2nd International Conference on Sustainable Energy and Future Electric Transportation (SeFeT). IEEE, 2022. http://dx.doi.org/10.1109/sefet55524.2022.9908774.
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Boudjani, N., V. Colas, C. Joubert, and D. Ben Amor. "AI Chatbot For Job Interview." In 2023 46th MIPRO ICT and Electronics Convention (MIPRO). IEEE, 2023. http://dx.doi.org/10.23919/mipro57284.2023.10159831.
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Bhharathee, A., Sandeep Vemuri, B. Bhavana, and K. Nishitha. "AI-Powered Student Assistance Chatbot." In 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT). IEEE, 2023. http://dx.doi.org/10.1109/idciot56793.2023.10053439.
Full textReports on the topic "AI ChatBot"
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Cao, Larry. IV. Chatbot, Knowledge Graphs, and AI Infrastructure. CFA Institute Research Foundation, April 2023. http://dx.doi.org/10.56227/23.1.10.
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Expert contributors discuss AI and big data applications that are being developed for financial services, such as AI-powered intelligent customer service systems; “factories” for data processing, AI, simulation, and visualization; and symbolic AI.
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Fariborzi, Hadi, and Piers Steel. Using ChatGPT for Systematic Literature Reviews. Instats Inc., 2023. http://dx.doi.org/10.61700/j8f4zpzyi3o47469.
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This workshop is designed to equip PhD students, professors, and professional researchers with the skills to leverage AI for systematic literature reviews. Participants will gain a comprehensive understanding of AI and its applications in academic research, learn how to use ChatGPT, OpenAI, Python, and HubMeta for systematic reviews, and develop strategies for integrating AI into their current research methodology. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.
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Fariborzi, Hadi, and Piers Steel. Using ChatGPT for Systematic Literature Reviews. Instats Inc., 2023. http://dx.doi.org/10.61700/tunnuyr63vbvf469.
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This workshop is designed to equip PhD students, professors, and professional researchers with the skills to leverage AI for systematic literature reviews. Participants will gain a comprehensive understanding of AI and its applications in academic research, learn how to use ChatGPT, OpenAI, Python, and HubMeta for systematic reviews, and develop strategies for integrating AI into their current research methodology. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.
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Fariborzi, Hadi, and Piers Steel. Using ChatGPT to Maximize Research Productivity. Instats Inc., 2024. http://dx.doi.org/10.61700/c08dbpwlywt02706.
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This 2-day seminar aims to enhance research productivity through the strategic use of AI tools like ChatGPT, addressing common work obstacles such as procrastination. It offers a comprehensive learning experience, focusing on the application of AI in research, the psychological aspects of procrastination, and creating personal productivity plans and sticking to them with AI assistants. Participants will gain practical skills to effectively use ChatGPT and other productivity tools to reduce their workloads and increase research outputs.
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Steel, Piers, and Hadi Fariborzi. Using ChatGPT for Dissertations and Theses. Instats Inc., 2023. http://dx.doi.org/10.61700/jwjwiapcl6fow469.
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This comprehensive seminar is designed to equip PhD students and research-oriented masters students with the skills to leverage advanced AI tools like ChatGPT in their academic research. The seminar covers a range of topics including the role of AI in literature reviews, data collection and analysis, data interpretation, and practical applications of these tools for drafting dissertations and theses, alongside ethical considerations of using AI in research. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.
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Fariborzi, Hadi, and Piers Steel. Using ChatGPT for Dissertations and Theses. Instats Inc., 2023. http://dx.doi.org/10.61700/w3911b54epoz1469.
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This comprehensive seminar is designed to equip PhD students and research-oriented masters students with the skills to leverage advanced AI tools like ChatGPT in their academic research. The seminar covers a range of topics including the role of AI in literature reviews, data collection and analysis, data interpretation, and practical applications of these tools for drafting dissertations and theses, alongside ethical considerations of using AI in research. An official Instats certificate of completion and 2 ECTS Equivalent points are provided at the conclusion of the seminar.
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Fariborzi, Hadi, and Piers Steel. New ChatGPT and AI Tools for Academic Research and Publishing. Instats Inc., 2024. http://dx.doi.org/10.61700/wdf7gomkxo8yh1080.
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This transformative half-day seminar is designed to equip participants with the latest AI tools and techniques to assist the process of academic research and publishing. Perfect for both newcomers and seasoned AI users, this seminar promises to revolutionize your approach to scholarly work by using AI tools as research assistants. The seminar is comprised of four separate sessions, each designed to explore different facets of AI in academic research, including: revolutionizing research with AI tools and technologies; mastering prompt engineering; navigating the ethics and security of AI; and applying AI in advanced research and writing.
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Gruber, Peter. Teaching and Learning Statistics with ChatGPT. Instats Inc., 2023. http://dx.doi.org/10.61700/m71hf8ug0ces1469.
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This two-day workshop responds to the disruption that the AI revolution introduces to statistics education and practice. This seminar will equip academics and PhD students with the skills and insights needed to integrate ChatGPT into their statistics teaching and learning. Participants will gain hands-on experience with ChatGPT in classroom and assessment settings, as well as using it to prepare course material and exercises, while gaining a deeper understanding of how to use it to enhance statistics learning and practice. The seminar will also explore the wider institutional and ethical ramifications that the use of AI brings to education institutions and the wider economy. An official Instats certificate of completion and 2 ECTS Equivalent points are provided upon completion.
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Gruber, Peter. Using ChatGPT and Copilot for Efficient Data Analysis in R. Instats Inc., 2023. http://dx.doi.org/10.61700/0lgrq7wtqjztt469.
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This workshop provides a 21st-century introduction to [b]Statistical Analysis with R,[/b] focusing on the efficient use of [b]AI assistants[/b] such as Github Copilot and ChatGPT. Participants will learn step by step how to install AI tools and how to harness their power. They will be able to create R code in the blink of an eye and with unprecedented ease of use. They will learn the principles of the R language, an important fundament for competently assessing and using AI-generated code. An official Instats certificate of completion is provided at the conclusion of the seminar along with 2 ECTS Equivalent points.
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Miller, Kyle, and Andrew Lohn. Onboard AI: Constraints and Limitations. Center for Security and Emerging Technology, August 2023. http://dx.doi.org/10.51593/2022ca008.
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Artificial intelligence that makes news headlines, such as ChatGPT, typically runs in well-maintained data centers with an abundant supply of compute and power. However, these resources are more limited on many systems in the real world, such as drones, satellites, or ground vehicles. As a result, the AI that can run onboard these devices will often be inferior to state of the art models. That can affect their usability and the need for additional safeguards in high-risk contexts. This issue brief contextualizes these challenges and provides policymakers with recommendations on how to engage with these technologies.