Opportunities and challenges in using AI Chatbots in Higher Education

Artificial intelligence (AI) conversational chatbots have gained popularity over time, and have been widely used in the fields of e-commerce, online banking, and digital healthcare and well-being, among others. The technology has the potential to provide personalised service to a range of consumers. However, the use of chatbots within educational settings is still limited. In this paper, we present three chatbot prototypes, the Warwick Manufacturing Group, University of Warwick, are currently developing, and discuss the potential opportunities and technical challenges we face when considering AI chatbots to support our daily activities within the department. Three AI virtual agents are under development: 1) to support the delivery of a taught Master's course simulation game; 2) to support the training and use of a newly introduced educational application; 3) to improve the processing of helpdesk requests within a university department. We hope this paper is informative to those interested in using chatbots in the educational domain. We also aim to improve awareness among those within the chatbot development industry, in particular the chatbot engine providers, about the educational and operational needs within educational institutes, which may differ from those in other domains

Multimodal Interaction Techniques for Chatbots

Chatbots have become popular and are being used in the most diverse areas. The most common use for chatbot are the ones integrated in our smartphones, like Google Assistant and Siri. This kind of technology evolved significantly in the past few years and now the users have the feeling to be talking to another human being. In a near future, most of the interaction between large organisations and their users will be mediated by AI agents. A market that benefited a lot from this arising technology are the e-commerce websites. Sometimes, it can be a struggle to find a product in a web site due to bad interface designs. When integrated in these websites, the clients have immediate access to a seller that is able to help them find the product they want or clarify some doubts that they might have. Despite the great evolution in the responsiveness of these systems, when talking about the User Interface (UI) of the systems, there are no major changes. Normally, chatbots are represented using the common chat box in the bottom right corner of the screen. In the scope of iFetch project, that the main focus is revolutionise the chatbot assistance in online sales, it is proposed for this dissertation the development of a user interface for a chatbot with multimodal interaction, making the user experience more interactive and engaging. This interface is a representation of a virtual room where the user can see the products that he/she wants to buy. The is also a component of image processing to be able to use the 2D images for the generation of their 3D representation.Atualmente, a utilização de chatbots alargou-se para as mais diversas áreas. O exemplo mais comum são os chatbots integrados nos smartphones como o Google assistant ou a Siri. Esta tecnologia tem evoluído significativamente nos últimos anos, dando a sensação ao utilizador que está a falar com outro ser humano. Num futuro próximo, a maioria das interações entre os clientes e as empresas será feito através de agentes AI. Uma área que tem beneficiado muito com a introdução desta tecnologia, são os websites de vendas online. Por vezes, poderá ser complicado um utilizador encontrar o produto que pretende no site da loja, devido ao mau design da interface. Assim, os chatbot permitem que os seus clientes tenham acesso rápido a um vendedor a qualquer momento, que os ajudará a encontrar o artigo pretendido e tirar possíveis dúvidas que tenham. Apesar de ser notória uma grande evolução na capacidade de resposta destes sistema, no que toca a interface digital dos chatbots, não se tem notado grande inovação. A maioria dos chatbots que encontramos hoje em dia, são a típica caixa de texto que se encontra no canto inferior do ecrã. Assim, dentro do contexto do projecto iFetch, que pretende desenvolver um chatbot para a assistência no mundo das vendas online, surge este trabalho cujo objetivo passa por desenvolver uma interface inovadora multimodal que permita tornar a experiência dos utilizadores do website mais interativa. Esta interface consistirá numa loja virtual onde o utilizador poderá visualizar os produtos que pretende comprar. Existe também uma componente de processamento de imagem para que seja possível a visualização das imagens 2D em manequins 3D

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use

We introduce VisIT-Bench (Visual InsTruction Benchmark), a benchmark for evaluation of instruction-following vision-language models for real-world use. Our starting point is curating 70 'instruction families' that we envision instruction tuned vision-language models should be able to address. Extending beyond evaluations like VQAv2 and COCO, tasks range from basic recognition to game playing and creative generation. Following curation, our dataset comprises 592 test queries, each with a human-authored instruction-conditioned caption. These descriptions surface instruction-specific factors, e.g., for an instruction asking about the accessibility of a storefront for wheelchair users, the instruction-conditioned caption describes ramps/potential obstacles. These descriptions enable 1) collecting human-verified reference outputs for each instance; and 2) automatic evaluation of candidate multimodal generations using a text-only LLM, aligning with human judgment. We quantify quality gaps between models and references using both human and automatic evaluations; e.g., the top-performing instruction-following model wins against the GPT-4 reference in just 27% of the comparison. VisIT-Bench is dynamic to participate, practitioners simply submit their model's response on the project website; Data, code and leaderboard is available at visit-bench.github.io

AI and Gender in Persuasion: Using Chatbots to Prevent Driving Under The Influence of Marijuana

Will new media techniques, such as artificial intelligence (AI), help refresh public safety advertising campaigns and help better target specific populations, and aid in persuasive, preventative marketing? This paper used hypocrisy induction as a persuasive tool for standalone artificial intelligence chatbots to test potential behavioral change in the context of marijuana. This research further tested whether the chatbots\u27 gender and language styles impact how persuasive and effective the chat agents are perceived to be using hypocrisy induction. An online experiment conducted with 705 participants (Mage = 42.9, 392 women). where participants interact with a chatbot that is manipulated as male/female and uses formal/causal language. Half of the participants received the hypocrisy induction manipulation. hypocrisy induction is more effective when chatbot gender and linguistic styles are appropriately paired. Participants in the hypocrisy induction condition exhibited higher WTP than those in the non-hypocrisy induction condition when the chatbot they interacted with was female in gender and used casual language. However, hypocrisy induction increased WTP than those who did not receive the hypocrisy induction manipulation when the gender of the chatbot they interacted with was male and used formal language. To the researchers\u27 knowledge, this is among the first studies testing the persuasive power of hypocrisy induction using new media platforms in public safety and health advertising in marijuana studies. Findings not only help to shed light on the persuasiveness of gender and language in standalone chatbots but also provide practical implications for practitioners on the future usage of chatbots