A chatbot that conducts first-round interviews

Presenter Information

Joey GruberFollow

Advisor Information

Ryan Schuetzler

Location

MBSC 201

Presentation Type

Poster

Start Date

6-3-2020 2:00 PM

End Date

6-3-2020 3:15 PM

Abstract

The average amount of applications for any new job is estimated to be around 36, and the initial interview for each applicant is estimated to last 54 to 65 minutes. This means that the hiring company or individual is spending over 36 hours conducting initial screenings for one position. A chatbot is "an artificial entity that is designed to simulate an intelligent conversation with human partners", and may provide hiring entities a time-saving advantage in the interview process. This project will utilize chatbot capabilities to automize the interview process to allow interviewers to spend more time on the final applicant and other job duties. This software, with the help of natural language understanding, has successfully interviewed users and also computes user likeability, ease of use, and many other variables not easily obtained through in-person interviews. This research project not only automates this process but also looks to understand users likeability, ease of use, and more towards the interview compared to traditional, in-person interviews.

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Mar 6th, 2:00 PM Mar 6th, 3:15 PM

A chatbot that conducts first-round interviews

MBSC 201

The average amount of applications for any new job is estimated to be around 36, and the initial interview for each applicant is estimated to last 54 to 65 minutes. This means that the hiring company or individual is spending over 36 hours conducting initial screenings for one position. A chatbot is "an artificial entity that is designed to simulate an intelligent conversation with human partners", and may provide hiring entities a time-saving advantage in the interview process. This project will utilize chatbot capabilities to automize the interview process to allow interviewers to spend more time on the final applicant and other job duties. This software, with the help of natural language understanding, has successfully interviewed users and also computes user likeability, ease of use, and many other variables not easily obtained through in-person interviews. This research project not only automates this process but also looks to understand users likeability, ease of use, and more towards the interview compared to traditional, in-person interviews.