Download The Turing test: verbal behaviour as the hallmark of intelligence

1. The Turing test: verbal behaviour as the hallmark of intelligence - The Turing Test is
part of the vocabulary of popular culture - it has appeared in works ranging from the
Broadway play breaking the Code to the comic strip "Robotman".
2. Turing Test - In honour of Alan Turing, mathematician, cryptanalyst, and progenitor
of computer science, we wanted to provide you with a demonstration of one of the
areas in which his work has had an influence on the English language. The Turing
test, ‘a test for intelligence in a computer, requiring that a human being should be
unable to distinguish the machine from another human being by using the replies to
questions put to both’, is commonly regarded as the barrier which a computer
program must break to be considered an artificial intelligence. Though he didn’t use
the word himself to describe it, the test was set out by Turing in his 1950 paper
Computing machinery and intelligence, published in the journal Mind.
3. Beyond the Turing Test - Intelligence is, after all, a multidimensional variable, and
no one test could possibly ever be definitive truly to measure it.
4. Visual Turing test for computer vision systems - Today, computer vision systems are
tested by their accuracy in detecting and localizing instances of objects. As an
alternative, and motivated by the ability of humans to provide far richer descriptions
and even tell a story about an image, we construct a "visual Turing test": an
operator-assisted device that produces a stochastic sequence of binary questions
from a given test image. The query engine proposes a question; the operator either
provides the correct answer or rejects the question as ambiguous; the engine
proposes the next question ("just-in-time truthing"). The test is then administered to
the computer-vision system, one question at a time. After the system's answer is
recorded, the system is provided the correct answer and the next question. Parsing
is trivial and deterministic; the system being tested requires no natural language
processing. The query engine employs statistical constraints, learned from a training
set, to produce questions with essentially unpredictable answers--the answer to a
question, given the history of questions and their correct answers, is nearly equally
likely to be positive or negative. In this sense, the test is only about vision. The
system is designed to produce streams of questions that follow natural story lines,
from the instantiation of a unique object, through an exploration of its properties,
and on to its relationships with other uniquely instantiated objects.
5. Turing Test Considered Mostly Harmless - Turing’s landmark paper on computing
machinery and intelligence is multifaceted and has an underemphasized ethical
dimension. Turing’s notion of “intelligence” and “thinking” was far more
encompassing than the common anthropocentric view may suggest. We discuss a
number of open and underrated problems that the common interpretation of the
Turing test as a test of machine intelligence entails. We suggest that a more
meaningful question than “Can machines think?” is whether modern computing
machinery can amplify human intelligence. We cite examples ranging from
traditional silicon-based environments to carbon-based, living organisms in order to
illustrate that this kind of intelligence amplification is indeed happening today. We
conclude that in its interpretation as a test of machine intelligence, the Turing test
may indeed be harmful for artificial intelligence (AI); in its wider interpretation,
however, it remains an inspiring source for philosophy and AI alike.
6. Twitter turing test: Identifying social machines - Many machine-controlled Twitter
accounts (also called “Sybils”) are created each day to provide services, flood out
messages for astro turf political campaigns, write fake product reviews, or produce
an underground marketplace for purchasing Twitter followers, retweets, or URL
advertisements. In addition, fake identities and user accounts in online communities
are resources used by adversaries to spread malware, spam, and harmful links over
social networks. In social networks, Sybil detectors rely on the assumption that
Sybils will find it harder to befriend real users; thus, Sybils that are connected to
each other form strongly connected subgraphs, which can be detected using the
graph theory. However, a majority of Sybils have actually successfully integrated
themselves into real social media user communities (such as Twitter and Facebook).
In this study, we compared the current methods used for detecting Sybil accounts.
We also explored the detection features of various types of Twitter Sybil accounts in
order to build an effective and practical classifier. To evaluate our classifier.
7. I-athlon: Toward a Multidimensional Turing Test - While the Turing test is a wellknown method for evaluating machine intelligence, it has a number of drawbacks
that make it problematic as a rigorous and practical test for assessing progress in
general-purpose AI. For example, the Turing test is deception based, subjectively
evaluated, and narrowly focused on language use. We suggest that a test would
benefit from including the following requirements: focus on rational behavior, test
several dimensions of intelligence, automate as much as possible, score as
objectively as possible, and allow incremental progress to be measured. In this
article we propose a methodology for designing a test that consists of a series of
events, analogous to the Olympic Decathlon, which complies with these
requirements. The approach, which we call the I-athlon, is intended ultimately to
enable the community to evaluate progress toward machine intelligence in a
practical and repeatable way.
8. Machine humour: examples from Turing test experiments - In this paper, we look
at the possibility of a machine having a sense of humour. In particular, we focus on
actual machine utterances in Turing test discourses. In doing so, we do not consider
the Turing test in depth and what this might mean for humanity, rather we merely
look at cases in conversations when the output from a machine can be considered to
be humorous.
9. A Turing test for collective motion – A widespread problem in biological research is
assessing whether a model adequately describes some real-world data. However,
even if a model captures the large-scale statistical properties of the data, should we
be satisfied with it? We developed a method, inspired by Alan Turing, to assess the
effectiveness of model fitting. We first built a self-propelled particle model whose
properties (order and cohesion) statistically matched those of real fish schools. We
then asked members of the public to play an online game (a modified Turing test) in
which they attempted to distinguish between the movements of real fish schools or
those generated by the model. Even though the statistical properties of the real data
and the model were consistent with each other, the public could still distinguish
between the two, highlighting the need for model refinement. Our results
demonstrate that we can use ‘citizen science’ to cross-validate and improve model
fitting not only in the field of collective behaviour, but also across a broad range of
biological systems. J.E.H.-R., M.R. and D.J.T.S. conceived/designed the study and
wrote the paper. J.E.H.-R. performed the experiments. M.R. designed the online
game. M.R. and J.E.H.-R. analysed the data and prepared figures. All authors gave
final approval for publication and agree to be held accountable for the work
performed.
10. A Turing test for free will – Before Alan Turing made his crucial contributions to the
theory of computation, he studied the question of whether quantum mechanics
could throw light on the nature of free will. This paper investigates the roles of
quantum mechanics and computation in free will. Although quantum mechanics
implies that events are intrinsically unpredictable, the ‘pure stochasticity’ of
quantum mechanics adds randomness only to decision-making processes, not
freedom. By contrast, the theory of computation implies that, even when our
decisions arise from a completely deterministic decision-making process, the
outcomes of that process can be intrinsically unpredictable, even to—especially to—
ourselves. I argue that this intrinsic computational unpredictability of the decisionmaking process is what gives rise to our impression that we possess free will. Finally,
I propose a ‘Turing test’ for free will: a decision-maker who passes this test will tend
to believe that he, she, or it possesses free will, whether the world is deterministic
or not.
11. Dehumanising the Turing test – In the test devised by Alan Turing bearing his name
in his seminal 1950 paper “Computing machinery and intelligence”, to determine
whether a machine is able to demonstrate intelligence – in Turing’s words “Can
machines act like they are thinking?” – a human examiner is asked to determine
whether one or other of two subjects with whom he is communicating via a teletype
is human. The examiner does this by establishing a question-and-answer session
made up of a series of questions, possible identical, to the two subjects and the
responses from both. He then assesses these responses against each other and his
expectations of an intelligent human response. It is the contention of this letter that
the direct involvement of a human questioner and a human “standard of
intelligence” subject in determining the outcome of the Turing test creates a flawed
and questionable set of results, because of the level of subjectivity involved.
12. An Artistic Turing Test – Alan Turing, the centenary of whose birth we are
celebrating this year, had an important influence on artists. He has often been called
one of the greatest minds Britain has ever produced - his theory of computation and
formalisation of the concept of the algorithm laid down the scientific basis for the
digital age.
13. A Turing Test for Computer Game Bots – In this paper, a version of the Turing Test is
proposed, to test the ability of computer game playing agents (“bots”) to imitate
human game players. The proposed test has been implemented as a bot design and
programming competition, the 2K BotPrize Contest. The results of the 2008
competition are presented and analyzed. We find that the Test is challenging, but
that current techniques show promise. We also suggest probable future directions
for developing improved bots.
14. Beyond the Turing Test – Despite the technological marvel of the Internet and the
rapidly proliferating mobile technologies that are fundamentally changing the way
we interact, AI's original "grand dream" remains elusive as we approach the twilight
of the first decade in the 21st century. By designing a roadmap to AGI (artificial
general intelligence) and creating important benchmarks, we may yet achieve that
dream. However, this will only happen if the nascent AGI community coalesces and
works toward a common vision.
15. Teaching to the Turing Test with Cleverbot – The author describes how the program
Cleverbot was subjected to the Turing Test of machine intelligence to see how
technology is socially constructed. He states that Cleverbot learns conversation
through imitation of human utterances and is not a neutral system apart from
human culture, and that its Turing Testing can shed light on how language shapes
perception. The author notes that the study allowed students to better deal with the
politics of being human in a time of ubiquitous computing.
16. The Turing Test and the legal process – In this paper, the author proposes a novel
thought-experiment, the “Turing litigation game,” or “Turing game” for short.
Specifically, we propose replacing the existing arcane and archaic systems of civil
and criminal procedure with a simple and probabilistic litigation game resembling
the Turing Test from the world of computer science. This paper is divided into five
parts. Part 1 provides some background by describing the original Turing Test and
explaining how the Turing Test resembles the process of adjudication. Part 2 then
describes our proposed Turing litigation game and identifies the conditions for
implementing this alternative approach to litigation, while Part 3 introduces the
possibility of probabilistic verdicts (as opposed to the traditional system of binary
verdicts). Part 4 reviews (and refutes) several philosophical objections against our
Turing-game concept. Part 5 concludes.
17. Passing a Hide-and-Seek Third-Person Turing Test – The authors try to demonstrate
the difference between the cognitive abilities can be replicate by the AI.
18. Software passes Turing test – The article
19. Computing machinery and creativity: lessons learned from the Turing test – The
authors open a new avenue for viable and more meaningful testing procedures.
20. Computers, Conversation, and Controversy: Passing the Turing Test? - The author
talking on the Turing test and some method for do it.





















Alarifi, Abdulrahman; Alsaleh, Mansour; Al-Salman, AbdulMalik - Information Sciences,
12/2016, Volume 372
Arel, I; Livingston, S - Computer, 2009, Volume 42, Issue 3
Berrar, Daniel; Konagaya, Akihiko; Schuster, Alfons - New Generation Computing, 10/2013,
Volume 31, Issue 4
Catherine Mason is the author of A Computer in the Art Room: the origins of British
computer arts 1950-80, published in 2008.
Cenkner, Andrew; Bulitko, Vadim; Spetch, Marcia; Legge, Eric; Anderson, Craig G; Brown,
Matthew - IEEE Transactions on Computational Intelligence and AI in Games, 2014, Volume
6, Issue 1
Donald Geman; Stuart Geman; Neil Hallonquist; Laurent Younes - Proceedings of the
National Academy of Sciences, 03/2015, Volume 112, Issue 12
Gary Marcus; Francesca Rossi; Manuela Veloso - AI Magazine, 04/2016
Gehl, Robert W - Transformations: The Journal of Inclusive Scholarship and Pedagogy, 2013,
Volume 24, Issue 1-2
Guerra-Pujol, F.E - Information & Communications Technology Law, 06/2012, Volume 21,
Issue 2
Herbert-Read, J E; Romenskyy, M; Sumpter, D J T - Biology letters, 12/2015, Volume 11, Issue
12
Herzfeld, Noreen - Theology and Science, 10/2014, Volume 12, Issue 4
Hingston, P - IEEE Transactions on Computational Intelligence and AI in Games, 2009,
Volume 1, Issue 3
ITNOW, 06/2012, Volume 54, Issue 2
ITNOW, 12/2012, Volume 54, Issue 4
Peter Berrar, Daniel; Schuster, Alfons - Kybernetes, 01/2014, Volume 43, Issue 1
Physics Today, 2011
Pleming, Robert - Kybernetes, 05/2010, Volume 39, Issue 3
Sam S Adams; Guruduth Banavar; Murray Campbell - AI Magazine, 04/2016, Volume 37,
Issue 1
Seth Lloyd - Philosophical Transactions: Mathematical, Physical and Engineering Sciences,
07/2012, Volume 370, Issue 1971
Shah, Huma; Warwick, Kevin - AI & SOCIETY, 06/2016
Shieber, Stuart M – 2004