Language
Games is the title of a forthcoming issue with LEA edited by Lanfranco Aceti,
Sheena Calvert, and Hannah Lammin. We invite a range of submissions initially
in the form of abstract. The description of the issue is below with all the
related information for submission.
Language is
a technology, as theorists including Martin Heidegger and Marshall McLuhan have
argued, and yet its manifestation in both speech and writing is fundamentally
human-centred: anthropological. However, speech and writing are rapidly
becoming an interface not just between humans and the ‘out there’, as
traditional philosophies of language assert, but between humans and machines, and
machines and other machines. As a result, the usual presuppositions we might
make about language as a technology which is predicated on human utterance and
man-made material transcription is rapidly shifting, and in the process the
line between human and machine is becoming less clear.
Current
developments in computing, and the rise of artificial intelligence (AI), are
bringing about a new perceptual transformation of the technology called
language, and offer us an opportunity to reflect on what we value in language
and how it continues to form (and inform) our life-world. The mass availability
of intelligent personal assistants—such as Apple’s Siri, IBM’s Watson and
Amazon’s Alexa, and Google’s Duplex—has brought (and promises to further
introduce) speaking machines into everyday life for many people, and makes it
clear that such interfaces will be increasingly indistinguishable from human
voice.
These
emergent systems replicate the nuances, inflections, and vernacular qualities
of speech to a degree that has made many commentators uncomfortable (invoking a
linguistic/social version of Masahiro Mori’s “Uncanny Valley”). Previous
barriers to acceptance of machine-produced language, such as lack of nuance,
context, and the subtleties of timing associated with human language are
beginning to be surpassed, such that the distinction between them dissolves.
This raises
ethical questions about language, and its ongoing role in human (and machine)
interaction. These technologies also threaten to replace large areas of
voice-related employment, such as service industry call centre roles, and so
involve the implications of automation more generally. In the fields of
computer science and technology there is already well-developed research
producing systems that are able to generate ever more “natural” linguistic
fluency. Our aim is to add another dimension to this research, by asserting the
importance of a dialogue between humanities/science/creative disciplines in
addressing the implications of speaking machines. If (as many claim), language
is of singular importance to the constitution of the human; the migration of
language to machines provides an opportunity for us to interrogate the value of
language at an ontological level.
Current
research in the digital humanities and the philosophy of technology considers a
range of questions, including the nature of human/machine intelligence,
algorithmic agency, the narratives used to contextualize AI in the broader
social context, and the ethics of using machines to mediate various aspects of
our personal lives. Yet, the complex relationship between language and
intelligence that has preoccupied philosophers since Aristotle has rarely been
taken as a central research theme in critical discussions of AI. This journal
aims to fill this gap by creating an interdisciplinary platform for reflection
on the implications of AI as a linguistic technology.
The goal of
this issue is to bring together a range of perspectives—including those from
philosophy, linguistics, computer sciences, digital humanities and the creative
arts—in order to examine in detail the particular role of language in creating
the interface between humans and AI/machine learning technologies. It will
address languages’ role in getting us to accept these technologies,
investigating how the creation of believable/convincing linguistic parallels to
human forms of language (via mimicry), invites us to engage with machines as
social beings, and builds trust in machine utterances (written and spoken). By
approaching computational technologies through a linguistic lens we hope to
establish that language needs to become a central (not incidental) aspect of
the discourses around the ethics of AI and machine learning.
We invite
submissions addressing questions including, but not limited to:
- What is the ontological status of language when it is no longer made by humans, but by machines?
- How do the frameworks that ground our understanding of ethics need to be rethought to account for the social effects of linguistic machines?
- What epistemological models do we need to understand the relationship between ‘natural’ language and computer language/code?
- Do machinic languages require us to re-think the relationship between language and cognition?
- Do computational systems have the agency for linguistic creativity, and what poetic forms might emerge from them and/or our interaction with them?
- What new pragmatics of language arise from our interactions with non-human linguistic agents?
- What methodologies—creative, philosophical, scientific—can we develop to address these questions, and to communicate between disciplines?
Submissions:
Abstract:
We ask you to submit an abstract of 250 words and 5 to 7 keywords, by April 30,
2019, to: Hannah.lammin@gre.ac.uk and s.calvert@csm.arts.ac.uk
The Abstract
should also contain:
your name, your address, your email, your affiliation (university or
other institution you work for/with).
We will
review abstracts within three weeks and invited full essays (5,000 words
maximum, unless otherwise agreed with the editors) will be due by July 30,
2019.
Final
acceptance will be subject to peer review. Papers will be published online as
ready after September 30, 2019, and the final (full) edition will be available
for print, by December 1, 2019.
Deadlines
Abstract
submission: April 30, 2019
Paper
submission: July 30, 2019
Final
papers: September 30, 2019
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