Опубликована: Апрель 19, 2024
Язык: Английский
International Journal of Production Economics, Год журнала: 2023, Номер 265, С. 109015 - 109015
Опубликована: Авг. 23, 2023
Язык: Английский
Процитировано
125
Business Horizons, Год журнала: 2024, Номер 67(5), С. 561 - 570
Опубликована: Апрель 24, 2024
This article focuses on how recent advances in artificial intelligence (AI), particularly chatbots based large language models (LLMs), such as ChatGPT, can be used for innovation purposes. The begins with a brief overview of the development and characteristics generative AI (GenAI). Elaborating implications GenAI, we provide examples to demonstrate four mechanisms LLMs: translation, summarization, classification, amplification. These inform framework that highlights LLMs enable creation innovative solutions organizations through capacities two dimensions: context awareness content awareness. strength lies combination both these dimensions, which enables them comprehend amplify content. Four managerial suggestions are presented, ranging from starting out small-scale projects data exploration, scaling integration efforts educating prompt engineers. By presenting framework, recommendations, use cases various contexts, contributes emerging literature GenAI innovation.
Язык: Английский
Процитировано
18
Business Horizons, Год журнала: 2024, Номер 67(5), С. 615 - 627
Опубликована: Май 24, 2024
The new generative AI paradigm offers unprecedented opportunities for users to tap into. capabilities are increasingly helpful in creative and knowledge-intensive domains that have long been considered a territory of human expertise. breed chatbots is based on large language models, they overcome many constraints plague the everyday use previous technologies. This article employs theory affordances understand how ChatGPT facilitates (i.e., affords) disaffords) usefulness chatbots. We further divide two distinct yet interrelated dimensions affordances: creational conversational. Using 29 interviews with professionals using various sectors, we identify three (content creation enhancement, knowledge acquisition creativity augmentation, task automation) conversational (contextual sensitivity, interactive accessibility, human–AI workflow synergy) affordances. Creational refer system's ability produce novel outputs as well automate routine work, whereas encompass variety interaction possibilities an system. Interestingly, both also involve disaffordances limit types systems. Furthermore, introduce integrated framework shows reinforce each other via meta-affordances accumulation, adaptability. illustrate our findings practical examples offer guidelines these emerging company settings.
Язык: Английский
Процитировано
18
Kybernetes, Год журнала: 2024, Номер unknown
Опубликована: Фев. 20, 2024
Purpose Generative AI and more specifically ChatGPT has brought a revolution in the lives of people by providing them with required knowledge that it learnt from an exponentially large base. In this viewpoint, we are initiating debate offer first step towards based management systems organizations. Design/methodology/approach This study is viewpoint develops conceptual foundation using existing literature on how can enhance KM capability Nonaka’s SECI model. It further supports concept collecting data public sector univesity Hong Kong to strenghten our argument mediated system. Findings We posit all four processes, Socialization, Externalization, Combination Internalization significantly improve when integrated ChatGPT. users are, general, satisfied use being capable facilitating generation flow Research limitations/implications The provides be within organizations Further, understanding managers executives for effective through improving processes Originality/value one earliest studies linkage lays system
Язык: Английский
Процитировано
14
Information Systems Research, Год журнала: 2024, Номер 35(4), С. 1507 - 1523
Опубликована: Ноя. 4, 2024
Язык: Английский
Процитировано
8
Advances in media, entertainment and the arts (AMEA) book series, Год журнала: 2024, Номер unknown, С. 45 - 71
Опубликована: Апрель 1, 2024
Generative AI, such as generative pre-trained transformer (GPT), has seen rapid advancements in recent years, offering a wide range of applications, but it also presents several challenges and opportunities. GPT can automate content generation for various industries, including journalism, marketing, entertainment, reducing the need manual creation. AI personalize recommendations e-commerce, streaming services, more, enhancing user experiences. GPT, offers immense potential across sectors requires careful management to address bias, ethics, quality control challenges. As technology evolves, finding right balance between creativity will be crucial maximizing its benefits while minimizing risks. Based on above, authors systematically review bibliometric literature how applications challenge opportunities using Scopus database by analysing 49 academic and/or scientific documents.
Язык: Английский
Процитировано
7
IEEE Transactions on Affective Computing, Год журнала: 2024, Номер 15(3), С. 1769 - 1785
Опубликована: Март 8, 2024
The advent of Artificial Intelligence (AI) technologies has precipitated the rise asynchronous video interviews (AVIs) as an alternative to conventional job interviews. These one-way are conducted online and can be analyzed using AI algorithms automate speed up selection procedure. In particular, swift advancement Large Language Models (LLMs) significantly decreased cost technical barrier developing systems for automatic personality interview performance evaluation. However, generative task-unspecific nature LLMs might pose potential risks biases when evaluating humans based on their AVI responses. this study, we a comprehensive evaluation validity, reliability, fairness, rating patterns two widely-used LLMs, GPT-3.5 GPT-4, in assessing from AVI. We compared ratings with task-specific model human annotators simulated responses 685 participants. results show that achieve similar or even better zero-shot validity predicting traits. verbal explanations traits generated by interpretable items designed according psychological theories. also suffered uneven across different traits, insufficient test-retest emergence certain biases. Thus, it is necessary exercise caution applying human-related application scenarios, especially significant decisions such employment.
Язык: Английский
Процитировано
6
Intelligent Pharmacy, Год журнала: 2024, Номер 2(3), С. 392 - 414
Опубликована: Март 23, 2024
The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This built on the transformer architecture, which enables it process massive volumes of data text that both cohesive illuminating. Service a crucial component everywhere as provides basis establishing client rapport offering aid support. In healthcare, application ChatGPT patient service support has been one most significant advances in recent years. can help overcome obstacles improve satisfaction facilitating communication with healthcare personnel understanding care. It assist enhancing entire experience personalised information patients making more straightforward them communicate professionals. Its goal be expedite streamline promptly accurately responding customers. Businesses all sizes increasingly use since allows provide 24/7 customer without requiring human contact. paper briefly discusses need better services. Various perspectives improving services through are discussed. article also discussed major key enablers refining assistance. Further, identifies critical areas service. With ability handle several requests simultaneously, respond quickly questions, gain knowledge from every interaction, revolutionising accessibility compatibility various channels make desirable solution businesses looking As technology advances, positioned become an essential tool wishing speedy customised Although may give convincing solutions, chance providing accurate updated poses problem usage jobs up-to-date information. future, will efficient due AI.
Язык: Английский
Процитировано
6
Journal of Computer Information Systems, Год журнала: 2023, Номер unknown, С. 1 - 15
Опубликована: Дек. 14, 2023
Generative Artificial Intelligence (AI) tools like ChatGPT offer significant potential in the corporate world and organizational leadership. Organizations are actively integrating AI (GenAI) into their operations to leverage its benefits. However, research is yet explore factors supporting continuity of GenAI-powered Optimization (GenAI-OI) processes contexts. This study seeks address this gap by focusing on challenges standardizing such optimization intelligence systems. It utilizes Normalization Process Theory (NPT) facilitate a theoretical exploration standardization process. From both practical standpoint, it elucidates how NPT can be applied provide structured framework for understanding theorizing involved embedding sustaining GenAI-OI systems, which play pivotal role shaping future agility. endeavors uncover valuable insights organizations seeking not only adopt but sustain technology effectively.
Язык: Английский
Процитировано
15
Technovation, Год журнала: 2024, Номер 138, С. 103120 - 103120
Опубликована: Окт. 15, 2024
Язык: Английский
Процитировано
4