EconPapers    
Economics at your fingertips  
 

GOOGLE'S Duplex: Pretending to be human

Daniel O'Leary

Intelligent Systems in Accounting, Finance and Management, 2019, vol. 26, issue 1, 46-53

Abstract: Google's Duplex is a computer‐based system with natural language capabilities that provides a human sounding conversation as it performs a set of tasks, such as making restaurant reservations. This paper analyses Google's Duplex and some of the initial reaction to the system and its capabilities. The paper does a text analysis and finds that the system‐generated text creates standardized ratings that suggest the text is analytical, authentic and possesses a generally positive tone. As would be expected for the applications for which it is being used, the text is heavily focused on the present. In addition, this analysis indicates that the text provides evidence of social processes, cognitive processes, tentativeness and affiliation. Further, this paper examines some of the characteristics of speech that Duplex uses to sound human. Those capabilities appear to allow the system pass the Turing test for some well‐structured tasks. However, this paper investigates some of the ethics of pretending to be human and suggests that such impersonation is against evolving computer codes of ethics.

Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/isaf.1443

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:isacfm:v:26:y:2019:i:1:p:46-53

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1099-1174

Access Statistics for this article

More articles in Intelligent Systems in Accounting, Finance and Management from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:isacfm:v:26:y:2019:i:1:p:46-53