# Is Everyone an Artist? A Study on User Experience of AI-Based Painting System
## 2 Theoretical Background and Hypothesis Development
### Technology Acceptance Model (TAM)  
The Technology Acceptance Model (TAM) is used to explain and predict the adoption of computer technology. [PERSON] argued that for a new technology to be accepted, it is crucial that it be used and easily identified [25]. His research developed and validated new scales for two specific variables: Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) [42]. TAM is also one of the most commonly used models to understand the level of user adoption of emerging and communication technologies [43]. A meta-analysis conducted by some scholars proved that TAM is a valid and robust model and has been widely used [44]. In addition, PU and Attitude toward Using (ATT) directly affect Behavioral Intention (BI), whereas PEOU affects BI by PU directly or indirectly [45]. In the context of this study, users' ATT and BI were higher if they perceived that using AIBPS in their painting creation process was beneficial.  
TAM is an important theoretical basis for studying users' acceptance of new technologies. In this model, PU and PEOU are two important influencing factors and they are both influenced by external variables, and many scholars have proposed new models by combining these variables. These models provide system developers with a better way to control user Behavioral Intention (BI) [46]. For example, the Technology Acceptance Model for the Elderly (STAM) explores the acceptance of new technologies among older Hong Kong residents [47]; the Technology-Organization-Environment (TOE) framework combined with TAM examines the factors influencing end-user ATT and BI regarding AI-based technologies in construction companies [28]; and the Learning Behavior Acceptance Model (T-LBAM) explores the intrinsic influences of students' participation in gamified online courses on willingness [26]. It is important to note that there are many influencing factors in TAM, and these factors vary significantly across different research areas. Therefore, in order to better understand the extent to which users accept new technologies, it is essential to thoroughly consider the influence of various external variables on user perception [27]. Several external variables, based on different research subjects, have been identified and incorporated into studies by scholars [26; 27; 28; 29; 30; 31; 32; 33]. The inclusion of these external variables helps expand our understanding of user acceptance of new technologies and provides a more comprehensive analysis of the related phenomena. In addition, TAM has been used by many scholars as a theoretical basis for research describing users' ATT and BI regarding new systems or technologies for AI, and the model has been validated in areas such as Smart Banking [48], mobile payments [49], healthcare [50], service delivery [51], learning platforms [52], architecture companies [28], and digital libraries [46].  
Although many scholars have applied TAM to the AI field, no scholars have yet combined TAM with the AI art field in an empirical study. The process by which various TAM factors in the AI field influence the acceptance of AIBPS is not clear. Therefore, this study aims to propose an Extended Technology Acceptance Model (ETAM) and combine it with AIBPS to investigate the factors that influence users' acceptance and use of AIBPS. Through this study, we can provide new ideas for applying the ETAM model in the AI field, and also help to promote the development of the AI art field.