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Sorry about confusion on deadline. Here are corrected dates:
Call for Papers: Special Issue of Information Systems Research
Humans, Algorithms, and Augmented Intelligence:
The Future of Work, Organizations and Society
Guest Editors:
Hemant Jain, University of Tennessee Chattanooga
Balaji Padmanabhan, University of South Florida
Paul A. Pavlou, Temple University
Raghu T Santanam, Arizona State University
“…the main intellectual advances will be made by men and computers
working together in intimate association” -- J C R Licklider,
1960.
While artificial intelligence, machine learning, and other
autonomic technologies are usually in the spotlight, many
important problems are often solved through human beings and
computers working cooperatively. The design of information systems
has to focus as much on Intelligence Augmentation (IA), defined as
computers enhancing human intelligence, as it would on Artificial
Intelligence (AI), commonly defined as computers replacing human
beings. Additionally, recent concerns about AI raised by pioneers
like Stephen Hawking, Bill Gates, and Elon Musk raises major
issues related to control in system design.1 IA requires a focus
on design that optimally combines the abilities of human beings
with various AI technologies and algorithms while keeping the
ultimate control of human beings. As such, designers of
information systems have to increase their focus on interactions,
control, and interface points such that the resulting system is
efficient, effective and addresses the issues of appropriate human
control. Applications of IA are beginning to emerge in a number of
domains such as cybersecurity, counter-terrorism, healthcare, and
space exploration, among others. There are also several
applications to the design of information systems. This Special
Issue of Information Systems Research invites researchers to
submit their best work to highlight how they are beginning to
seamlessly integrate human and computer intelligence to solve
interesting and important problems that impact the future of work,
organizations, and broadly society.
BACKGROUND
In the 1960’s, Engelbart and Licklider (both managed research
programs at DARPA) pioneered the arguments for “human-computer
symbiosis” (Licklider 1960). A fundamental assumption behind the
need for human-computer symbiosis is that computers and human
brains have different problem-solving capabilities. As such, IA
research pursues design ideas that are intended to optimize the
combined computational potential of human beings and computers.
One branch of IA very familiar to Information Systems researchers
is Human Computer Interaction (HCI). One of the pioneers of the
HCI approach, Terry Winograd, has commented on the tensions
between the AI and the HCI camps, and the associated
“rationalistic” and “design” perspectives that they represent
(Winograd 2006). Some parts of AI attempted to model human beings
as cognitive machines and sought to build human-like AI systems.
HCI, on the other hand, focused on a design approach which
emphasizes interpretation, human behavior, and experimentation.
Winograd quotes David Kelley, the renowned design thinker, as
saying: “Enlightened trial and error outperforms the planning of
flawless intellect”, suggesting the importance of iteratively
improving by modeling the interaction between humans and AI.
However, HCI is not the only perspective to human-computer
symbiosis. Large scale computational problems often cannot be
solved by either computer or humans alone – such problems are
termed “human computation problems” (von Ahn 2008). For instance,
crowd-sourcing strategies for many messy large-scale image or
character recognition problems fall into this domain. Human
computation problems rely on harnessing human processing power
(i.e., common sense) to solve problems that computers are not yet
good at solving. More interestingly, many early human computation
problem-solving approaches have utilized gamification strategies
that seem to be very well aligned with the HCI tradition of
“design approach.”
Given the increasing role AI plays in society today, the White
House issued an RFI in 2016 to solicit commentaries and feedback
on the role of AI for current and future needs of the economy. A
report summarizing the responses to the RFI was released recently
by the White House. IBM’s response to the RFI declared an emphasis
on Augmented Intelligence in IBM’s approach to AI – “We call our
particular approach to augmented intelligence “cognitive
computing.” Cognitive computing is a comprehensive set of
capabilities based on technologies such as machine learning,
reasoning and decision technologies; language, speech and vision
technologies; human interface technologies; distributed and
high-performance computing; and new computing architectures and
devices. When purposefully integrated, these capabilities are
designed to solve a wide range of practical problems, boost
productivity, and foster new discoveries across many industries.”
In contrast, Google’s approach to AI, especially its search engine
design, is also arguably more in the tradition of IA than AI.
SPECIAL ISSUE FOCUS
Recent developments in hardware, sensor and networking
technologies combined with significant growth in Internet of
Things (IOT) devices has increased interested in combining them
with AI technologies to develop completely autonomous systems,
such as driverless cars. The design of these systems poses unique
technical, organizational, societal, and ethical questions. The
human-computer symbiosis has potential to address some of these
difficult issues.
IS researchers (including many authors in ISR) have embraced both
AI and IA traditions. Recent publications in ISR have revived both
the design and rational schools of thoughts in research papers,
notes and commentaries (see for example, Gregory and Muntermann
(2014); Dhar et al., (2014); Clarke et al., (2016); and Meyer et
al., (2014)). However, there is still a lack of coherent
discussion and an integrated body of literature on the direct
implications of how IA and AI research can contribute to
organizational and societal applications and to their impact on
the future of work. This Special Issue of Information Systems
Research is intended to begin a new dialog on the potential
synergies between IA and AI within the context of IS research.
Given the long tradition of IS researchers to cross-disciplinary
boundaries, we are confident of attracting a large number of
high-quality submissions that will highlight the prevailing
knowledge and research endeavors in the discipline and beyond. We
hope to showcase the best research in this domain as part of this
Special Issue.
Topics of interest include but are not limited to:
* Design approaches for effectively combining human and computer
cognitive power.
* Applications and evaluation of human-computer symbiosis in
various industry sectors, including healthcare, education,
finance, cybersecurity, and transportation, among others.
* Generalizable modeling innovations and applications that bridge
IA and AI concepts.
* Evaluation of theoretical predictions on how human beings and
computers collaborate in solving large-scale computational
problems.
* Social, behavioral, and economic implications of AI and IA,
including how they may impact the nature and future of work,
productivity, jobs, and industries.
* Theoretical predictions and evaluations of legal, policy,
governance and business models associated with applications of AI
and IA systems in various industries and markets.
* Issues related to human control in the design of IA systems.
TIMELINE
Full Paper Due: January 15, 2019 (Extended)
Initial Screening Decisions: March 1, 2019
Round 1 Decisions: June 1, 2019
Workshop: July 27-28, 2019 (tentative)
1st Round Revisions Due: December 1, 2019
Round 2 Decisions: March 1, 2020
EDITORIAL BOARD
Ohad Barzilay, Tel Aviv University
Gordon Burtch, University of Minnesota
Ram Chellappa, Emory University
Theodoros Evgenious, INSEAD
Tomer Geva, Tel Aviv University
Alan Hevner, University of South Florida
Kevin (Yili) Hong, Arizona State University
Panos Ipeirotis, New York University
Nishtha Langer, Rensselaer Polytechnic Institute
Ting Li, Rotterdam School of Management
Xitong Li, HEC Paris
Jiahui Mo, Nanyang Technological University
Joe Nandakumar, University of Warwick
Gautam Pant, University of Iowa
Sandeep Purao, Bentley University
Liangfei Qiu, University of Florida
Sam Ransbotham, Boston College
Benjamin Shao, Arizona State University
Atish Sinha, University of Wisconsin-Milwaukee
Tianshu Sun, University of Southern California
Anjana Susarla, Michigan State University
Prasanna Tambe, University of Pennsylvania
Monica Tremblay, College of William and Mary
Sunil Wattal, Temple University
Heng Xu, Pennsylvania State University
Jingjing Zhang, Indiana University
Rong Zheng, Hong Kong University of Science and Technology
Leon Zhao, City University of Hong Kong
Hangjung Zo, KAIST
References
Clarke, R., Burton-Jones, A., & Weber, R. (2016). On the
Ontological Quality and Logical Quality of Conceptual-Modeling
Grammars: The Need for a Dual Perspective. Information Systems
Research, 27(2), 365-382.
Dhar, V., Geva, T., Oestreicher-Singer, G., & Sundararajan, A.
(2014). Prediction in economic networks. Information Systems
Research, 25(2), 264-284.
Gregory, R. W., & Muntermann, J. (2014). Research
Note—Heuristic Theorizing: Proactively Generating Design Theories.
Information Systems Research, 25(3), 639-653.
Licklider, J. C. (1960). Man-computer symbiosis. IRE transactions
on human factors in electronics, (1), 4-11.
Meyer, G., Adomavicius, G., Johnson, P. E., Elidrisi, M., Rush, W.
A., Sperl-Hillen, J. M., & O'Connor, P. J. (2014). A machine
learning approach to improving dynamic decision making.
Information Systems Research, 25(2), 239-263.
Von Ahn, L., & Dabbish, L. (2008). Designing games with a
purpose. Communications of the ACM, 51(8), 58-67.
Winograd, T. (2006). Shifting viewpoints: Artificial intelligence
and human–computer interaction. Artificial Intelligence, 170(18),
1256-1258.
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