Abstract
Original language | English |
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Journal | AI and Society |
Volume | January |
DOIs | |
Publication status | Published - Jan 2014 |
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Bibliographical note
This article is not available on the repositoryKeywords
- Artificial Intelligence (incl. Robotics)
- Computer Science
- general
- Engineering Economics
- Organization
- Logistics
- Marketing
- Control
- Robotics
- Mechatronics
- Performing Arts
- Methodology of the Social Sciences
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Effects of lying in practical Turing tests. / Warwick, Kevin; Shah, Huma.
In: AI and Society, Vol. January, 01.2014.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Effects of lying in practical Turing tests
AU - Warwick, Kevin
AU - Shah, Huma
N1 - This article is not available on the repository
PY - 2014/1
Y1 - 2014/1
N2 - Interpretation of utterances affects an interrogator’s determination of human from machine during live Turing tests. Here, we consider transcripts realised as a result of a series of practical Turing tests that were held on 23 June 2012 at Bletchley Park, England. The focus in this paper is to consider the effects of lying and truth-telling on the human judges by the hidden entities, whether human or a machine. Turing test transcripts provide a glimpse into short text communication, the type that occurs in emails: how does the reader determine truth from the content of a stranger’s textual message? Different types of lying in the conversations are explored, and the judge’s attribution of human or machine is investigated in each test.
AB - Interpretation of utterances affects an interrogator’s determination of human from machine during live Turing tests. Here, we consider transcripts realised as a result of a series of practical Turing tests that were held on 23 June 2012 at Bletchley Park, England. The focus in this paper is to consider the effects of lying and truth-telling on the human judges by the hidden entities, whether human or a machine. Turing test transcripts provide a glimpse into short text communication, the type that occurs in emails: how does the reader determine truth from the content of a stranger’s textual message? Different types of lying in the conversations are explored, and the judge’s attribution of human or machine is investigated in each test.
KW - Artificial Intelligence (incl. Robotics)
KW - Computer Science
KW - general
KW - Engineering Economics
KW - Organization
KW - Logistics
KW - Marketing
KW - Control
KW - Robotics
KW - Mechatronics
KW - Performing Arts
KW - Methodology of the Social Sciences
U2 - 10.1007/s00146-013-0534-3
DO - 10.1007/s00146-013-0534-3
M3 - Article
VL - January
JO - AI & Society
JF - AI & Society
SN - 0951-5666
ER -