TWI818741B - Artificial intelligence anxiety level detection analysis system - Google Patents

Abstract

An artificial intelligence anxiety level detection analysis system includes an anxiety problem generation module, an anxiety Q&A module, and an anxiety result analyzing module. The anxiety problem generation module generates multiple preliminary anxiety problem data according to the anxiety interview data, and performs exploratory factor analysis and reliability and validity analysis on the preliminary anxiety problem data to generate multiple anxiety factor items and multiple final anxiety questions data corresponding to the anxiety factor items. The anxiety Q&A module receives and displays the anxiety factor items and the final anxiety question data through a display module of a mobile terminal device for a user to answer the question and output the answer information. The anxiety result analysis module calculates and analyzes the anxiety result information according to the answer information, and the anxiety result analysis module displays the anxiety result information through the display module.

Description

Artificial Intelligence Worry Level Detection and Analysis System

The present invention relates to a detection and analysis system, in particular to an artificial intelligence worry level detection and analysis system.

With the gradual development of science and technology, comprehensive automation and intelligence have become the goals pursued by various industries. Among them, artificial intelligence is one of the important factors in whether it can be fully automated and intelligent. Therefore, artificial intelligence has become a key development and research project in many industries.

However, current research on artificial intelligence focuses on the performance of artificial intelligence and the improvement of technology. There is no research on the impact of artificial intelligence on human physiology and psychology.

In order to solve the above problems, the present invention discloses an artificial intelligence worry level detection and analysis system, which allows users to accurately detect and understand their own level of worry about artificial intelligence.

In order to achieve the above object, one embodiment of the present invention provides an artificial intelligence worry level detection and analysis system, which is applied to a mobile terminal device. The present invention includes a worry question generation module, a worry question and answer module and a worry result analysis Mods. The worry question generation module generates multiple preliminary worry question data based on a worry interview data. The worry question generation module performs exploratory factor analysis and reliability and validity analysis on the preliminary worry question data to generate multiple worry factor items and their corresponding Multiple final worry question data of the worry factor items; the worry question and answer module is coupled to the worry question generation module, the worry question and answer module receives the worry factor items and the final worry question data, and displays the worry factors through a display module of the mobile terminal device The items and final worry question data are for a user to answer questions and output a piece of answer information; the worry result analysis module is coupled to the worry question and answer module, and the worry result analysis module calculates and analyzes a worry result information based on the answer information. The worry result analysis module displays the worry result information through the display module.

In this way, the present invention allows users to accurately detect and understand their level of worry about artificial intelligence through the worry question generation module, the worry question and answer module, and the worry result analysis module. Furthermore, the present invention is applied to mobile terminal devices, so that users can detect artificial worry levels at any time, and can achieve the effect of regularly checking their own artificial worry levels.

In order to facilitate the explanation of the central idea of the present invention expressed in the above creative content column, specific embodiments are hereby expressed. Various objects in the embodiments are drawn according to proportions suitable for enumeration and description, rather than according to the proportions of actual components, and will be described first.

Please refer to FIG. 1 to FIG. 4 , which discloses an artificial intelligence worry level detection and analysis system 100 according to an embodiment of the present invention, which is applied to a mobile terminal device 200. The present invention includes a worry problem generation module 10, a worry A question and answer module 20 and a worry result analysis module 30. The mobile terminal device 200 has a display module 210, and the information of the present invention can be displayed through the display module 210 so that the user can view it. Among them, the mobile terminal device 200 is a smart phone, a tablet computer, or any mobile terminal device with computing functions.

The worry question generation module 10 generates multiple preliminary worry question data 11 based on a worry interview data. The worry question generation module 10 performs exploratory factor analysis (EFA) and information on the preliminary worry question data 11. Scale and validity analysis is performed to generate plural worry factor items 12 and plural final worry question data 13 corresponding to the worry factor items 12. Among them, in the embodiment of the present invention, the worry interview data was obtained by filling out an interview form from 301 interviewees.

In the embodiment of the present invention, the worry problem generation module 10 is based on the aforementioned worry interview data and uses the exploratory factor analysis (EFA) method to generate the worry factor items 12, and uses the principal component analysis (Principal components analysis, PCA) method to determine Worry factor item 12 has validity. Among them, the worry factor items 12 are an artificial intelligence learning worry factor item, an artificial intelligence work replacement worry factor item, an artificial intelligence misuse worry factor item and an artificial intelligence anthropomorphic worry factor item.

In the embodiment of the present invention, the worry question generation module 10 performs reliability and validity analysis on the preliminary worry question data 11 to generate final worry question data 13 with high reliability and high validity. Among them, the worry problem generation module 10 uses Cronbach's alpha and the exploratory factor analysis (EFA) method to conduct reliability analysis and validity analysis on the preliminary worry problem data 11 to generate a product with high reliability and efficiency. The final worry question information 13.

In the embodiment of the present invention, the final worry problem data 13 corresponds to the worry factor item 12 and includes an artificial intelligence learning worry problem data, an artificial intelligence work replacement worry problem data, an artificial intelligence misuse worry problem data and an artificial intelligence personified worry Problem information. Among them, the said artificial intelligence learning worry question information includes 8 questions including "Learning to understand all the functions of AI technology/products will make me feel anxious" and "Learning to use AI technology/products will make me feel anxious"; The information on the worries about replacing jobs with artificial intelligence includes "People will become more and more dependent on AI technology/products, which makes me feel anxious" and "AI technology/products will make people more and more lazy, which makes me feel anxious." 6 questions including "I am worried that AI technology/products may be misused" and "AI technology/products may have some risky issues, which makes me feel... "Worry" and other 4 questions; the information on the concerns about anthropomorphic artificial intelligence includes "I am afraid of anthropomorphic AI technology/products (such as anthropomorphic robots)", "I feel afraid of anthropomorphic AI technology/products (such as anthropomorphic robots)" "robots) have a sense of oppression" and other three issues.

The worry question and answer module 20 is coupled to the worry question generation module 10. The worry question and answer module 20 receives the worry factor item 12 and the final worry question data 13, and displays the worry factor item 12 and the final worry through the display module 210. Question data 13 is used for users to answer questions and output answer information 21.

In the embodiment of the present invention, the worry question and answer module 20 displays a plurality of answer options on the display module 210 corresponding to each final worry question data 13 for the user to answer the question. Among them, as shown in Figure 3, the answer options are divided into seven options based on a seven-point Likert scale. The seven options are Strongly Agree, Agree, Somewhat Agree, Average/No Opinion, Somewhat Disagree, Disagree and strongly disagree, users can choose the answer options that best suit their wishes based on the questions in each final worry question information 13.

The worry result analysis module 30 is coupled to the worry question and answer module 20. The worry result analysis module 30 calculates and analyzes a worry result information 31 based on the answer information 21. The worry result analysis module 30 displays it through the display module 210. Worry result information 31 (shown in Figure 4). Among them, the answer information 21 records the answer options selected by the user corresponding to the questions of each final worry question information 13 .

As shown in Figure 2, in the embodiment of the present invention, the worry result analysis module 30 has a score calculation unit 32, a hundredth level calculation unit 33 and a worry level calculation unit 34, and the worry result information 31 includes a worry score information. 311. A worry percentage information 312 and a worry level information 313. Among them, the worry result analysis module 30 displays the worry score information 311 and the worry percentage level information 312 in numbers or radar charts through the display module 210 .

The score calculation unit 32 calculates the worry score information 311 based on the answer information 21. More specifically, the score of the worry score information 311 corresponds to the answer option selected by the user in the answer information 21. For example , if the option selected by the user is Strongly Agree, the score will be the highest; conversely, if the option selected by the user is Strongly Disagree, the score will be the lowest.

The percentile level calculation unit 33 is preset with the percentile level standard data 331 , and the percentile level calculation unit 33 calculates the worry percentile level information 312 based on the worry score information 311 and the percentile level standard data 331 . Among them, the percentage level standard data 331 is the average standard data calculated from the worry interview data and the worry score information 311, and each worry factor item 12 corresponds to different worry score information 311 and has different percentage level standards respectively. Information 331.

In the embodiment of the present invention, the percentile level calculation unit 33 will compare the score value of the worry score information 311 with the percentage level corresponding to the score value in the percentile level standard data 331 to calculate the correct worry percentage level. Information 312. As shown in Figure 4, for example, if the score value 311 of the worry score information 311 of the artificial intelligence misuse worry factor item is 20, and the percentage standard data 331 of the artificial intelligence misuse worry factor item corresponds to a score value of 20 The percentage level is 47.5, then the percentage level calculation unit 33 can calculate the correct worry percentage level information 312 as the percentage level 47.5.

The worry level calculation unit 34 presets a worry level standard data 341, and the worry level calculation unit 34 calculates the worry level information 313 based on the worry percentile information 312 and the worry level standard data 341. Among them, the worry levels of the worry level standard data 341 can be divided into extremely high (percentage level 0.1~20), high (percentage level 21~40), medium (percentage level 41~60), and low (percentage level 61). ~80) and extremely low (percentage level 81~99.9).

In the embodiment of the present invention, the worry level calculation unit 34 compares the percentage level of the worry percentage level information 312 with the worry level corresponding to the percentage level in the worry level standard data 341 to calculate the correct worry level information. 313. As shown in Figure 4, for example, if the worry percentile information 312 of the artificial intelligence misuse worry factor item has a percentile rank of 47.5, and the worry level standard data 341 corresponds to a worry level of 47.5, which is medium, Then the worry level calculation unit 34 can calculate that the worry level information 313 corresponding to the artificial intelligence misuse worry factor item is medium.

In the embodiment of the present invention, the present invention further includes a detection description module 40, which is coupled to the central processing module. The detection description module 40 is preset with a detection description data 41, and the detection description module 40 passes through the display module 210. The detection description information 41 is displayed for the user to view, so that the user can understand how to answer the final worry question information 13 displayed on the display module 210, and understand how to know his own artificial intelligence worry level through the worry result information 31.

In the embodiment of the present invention, the present invention further includes a data storage module 50 coupled to the worry result analysis module 30. The data storage module 50 is used to store the final worry question data 13, answer information 21 and worry result information 31. , among which, the worry result analysis module 30 can make the calculated worry result information 31 more accurate through continuous training and calculation as the worry result information 31 in the data storage module 50 continues to increase.

In this way, the present invention allows users to accurately detect and understand their level of worry about artificial intelligence through the worry question generation module 10, the worry question and answer module 20, and the worry result analysis module 30. Furthermore, the present invention is applied to the mobile terminal device 200, so that the user can detect the artificial worry level at any time, and can achieve the effect of regularly checking the artificial worry level of the user.

Although the present invention has been described with a preferred embodiment, those skilled in the art can make various modifications without departing from the spirit and scope of the present invention. The above embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. All modifications or changes that do not violate the spirit of this creation are within the scope of the patent application for this creation.

100: Artificial Intelligence Worry Level Detection and Analysis System 200:Mobile terminal device 210:Display module 10: Worry problem generation module 11: Preliminary worry information 12: Worry factor items 13:Final worry information 20: Worry Q&A module 21:Answer information 30: Worry result analysis module 31: Worry about result information 311: Worry Score Information 312: Worry percentile information 313: Worry level information 32: Score calculation unit 33: Percentage calculation unit 331: Percentage standard data 34: Worry level calculation unit 341: Worry level standard data 40: Detection description module 41: Testing instructions 50:Data storage module

[Figure 1] is a schematic block diagram of the connection between the artificial intelligence worry level detection and analysis system and the mobile terminal device according to the embodiment of the present invention. [Fig. 2] is a block diagram of an artificial intelligence worry level detection and analysis system according to an embodiment of the present invention. [Fig. 3] is an actual usage status diagram of the artificial intelligence worry level detection and analysis system according to the embodiment of the present invention, which is used to show the actual screen of the mobile terminal device displaying the worry factor items and the final worry problem data. [Figure 4] is an actual usage status diagram of the artificial intelligence worry level detection and analysis system according to the embodiment of the present invention, which is used to show the actual screen of the mobile terminal device displaying worry result information.

100: Artificial Intelligence Worry Level Detection and Analysis System

10: Worry problem generation module

11: Preliminary worry information

12: Worry factor items

13:Final worry information

20: Worry Q&A module

21:Answer information

30: Worry result analysis module

31: Worry about result information

311: Worry Score Information

312: Worry percentile information

313: Worry level information

32: Score calculation unit

33: Percentage calculation unit

331: Percentage standard data

34: Worry level calculation unit

341: Worry level standard data

40: Detection description module

41: Testing instructions

50:Data storage module

Claims (10)

An artificial intelligence worry level detection and analysis system, which is applied to a mobile terminal device. The artificial intelligence worry level detection and analysis system includes: A worry question generation module, which generates multiple preliminary worry question data based on a worry interview data. The worry question generation module performs exploratory factor analysis and reliability and validity analysis on these preliminary worry question data to generate Multiple worry factor items and multiple final worry question data corresponding to these worry factor items; A worry question and answer module coupled to the worry question generation module, the worry question and answer module receives the worry factor items and the final worry question data, and displays the worry question data through a display module of the mobile terminal device The worry factor items and the final worry question information are used for a user to answer questions and output answer information; and A worry result analysis module is coupled to the worry question and answer module. The worry result analysis module calculates and analyzes a worry result information based on the answer information. The worry result analysis module displays the worry result information through the display module. Worry about outcome information. The artificial intelligence worry level detection and analysis system as described in claim 1, wherein the worry factor items include an artificial intelligence learning worry factor item, an artificial intelligence work replacement worry factor item, an artificial intelligence misuse worry factor item and an artificial intelligence worry factor item. Intelligent personification worry factor items, the final worry problem data corresponding to the worry factor items include an artificial intelligence learning worry problem data, an artificial intelligence work replacement worry problem data, an artificial intelligence misuse worry problem data and an artificial intelligence anthropomorphism Worry problem information. The artificial intelligence worry level detection and analysis system as described in claim 1, wherein the worry question and answer module displays a plurality of answer options on the display module corresponding to each final worry question data for the user to answer questions. The answer options are divided into seven answer options based on a seven-point Likert scale. The artificial intelligence worry level detection and analysis system described in claim 1 further includes a detection explanation module coupled to the worry question and answer module. The detection explanation module is preset with a detection explanation data. The detection explanation module The detection description data is displayed through the display module for the user to view. The artificial intelligence worry level detection and analysis system described in claim 1 further includes a data storage module coupled to the worry result analysis module. The data storage module provides the final worry question data and the answer information. And the worry result information is stored. The artificial intelligence worry level detection and analysis system as described in claim 1, wherein the worry result information includes a worry score information, a worry percentile information and a worry level information. The artificial intelligence worry level detection and analysis system as described in claim 6, wherein the worry result analysis module has a score calculation unit, and the score calculation unit correspondingly calculates the worry score information based on the answer information. The artificial intelligence worry level detection and analysis system as described in claim 7, wherein the worry result analysis module has a hundred percent grade calculation unit, and the percentile grade calculation unit is preset with hundred percent grade standard data, and the percentile grade calculation unit is preset with hundred percent grade standard data. The level calculation unit calculates the worry percentile information based on the worry score information and the percentile standard data. The artificial intelligence worry level detection and analysis system as described in claim 8, wherein the worry result analysis module has a worry level calculation unit, and the worry level calculation unit is preset with a worry level standard data, and the worry level calculation unit is based on the worry level calculation unit. The worry level information is calculated from the worry percentile level information and the worry level standard data. The artificial intelligence worry level detection and analysis system described in claim 9, wherein the worry result analysis module displays the worry score information and the worry percentile level information in numbers or radar charts through the display module.

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