-------- Forwarded Message --------
*AIS Transactions on HCI (THCI)
<https://aisel.aisnet.org/thci/>*
*Special issue on AI Fairness, Trust and Ethics*
*Special Issue Editors:*
Lionel P. Robert Jr., University of Michigan
Gaurav Bansal, University of Wisconsin-Green Bay
Nigel Melville, University of Michigan
Tom Stafford, Louisiana Tech University
*Submission Deadline: Full papers due February 15, 2020*
AI is rapidly changing every aspect of our society from how we
conduct
business, socialize and exercise. AI has amplified our
productivity as well
as biases. John Giannandrea, who leads AI at Google, recently
lamented in
the MIT Technology Review that the dangers posed by the ability of
AI
systems to learn human prejudices were far greater than those
posed by
killer-robots. This phenomenon is problematic because AI systems
are making
millions of decisions every minute many of which are invisible to
the users
and incomprehensible to the designers. Their opaqueness is a
significant
cause of worry and leaves many unanswered questions.
Fairness, Trust and Ethics are at the core of many of the issues
underlying
the implications of AI. Fairness is undermined when managers rely
blindly
on “objective” AI outputs to “augment” or replace their decision
making.
Managers often ignore the limitations of their assumptions and the
relevance of the data that was used to train and test AI models,
resulting
in bias decisions that are hard to detect or appeal. Trust is
undercut,
when AI is used to render false or misleading images of
individuals saying
or doing things that are simply not true. These false images are
making it
difficult for society to trust what they see or hear. Ethical
challenges
are presented when decisions used by AI lead to further
inequalities in the
society. Examples include: displaced workers and shortages of
affordable
housing due to rental apartments and housing units being diverted
to higher
paying Airbnb short term vacationers.
Despite the potential transformative effects, research on AI in
the
Information Systems field is still scarce, and as a result, our
knowledge
on the impacts of AI are still far from conclusive. Yet, it is
very
important from the business and technical perspective that we
research and
examine issues of fairness, trust and ethics with AI. This
examination is
critical as issues of fairness, trust and ethics lie at the heart
of
addressing the new challenges facing the development and use of AI
throughout our society. This is especially true, as there has been
a rapid
increase in the number of applications of AI in an ever increasing
number
of new areas. In all, AI has the potential to disrupt and
dramatically
change the interactions between humans and technologies.
This Special Issue on AI Fairness, Trust and Ethics calls for
research that
can unpack the potential, challenges, impacts, and theoretical
implications
of AI. We welcome research from different perspectives regardless
of the
approach or methodology. Submissions with novel theoretical
implications
that span disciplines are strongly encouraged. We seek submissions
that can
improve our understanding about the impacts of AI in organizations
and our
broader society.
*Potential topics include (but are not limited to):*
- Defining fair, ethical and trustworthy AI
- Antecedents and consequents for fair, ethical and trustworthy AI
- Designing, implementing and deploying fair, ethical and
trustworthy AI
- Theories of fair, ethical and trustworthy AI
- Policy and governance for fair, ethical and trustworthy AI
- Appropriate and inappropriate applications of AI
- Legal responsibilities for decisions made by AI
- AI biases
- AI algorithm transparency – how to improve
- The dark side of AI
- AI equality vs AI equity
- Implications of unfair, unethical and untrustworthy AI
*Key Dates:*
Optional one page abstract submissions: Oct 1, 2019
Selected abstracts invited for poster presentations at Pre-ICIS
2019 SIGHCI
workshop on Dec 15, 2019
First round submissions: Feb 15, 2020
First round decisions: April 15, 2020
Second round submissions: July 15, 2020
Second round decisions to authors: Sep 15, 2020
Third and final round submissions: November 1, 2020
Final decisions to authors: November 15, 2020
Targeted publication date: December 31, 2020
To submit a manuscript, read the "Information for Authors" and
"THCI
Policy" pages, then go to
http://mc.manuscriptcentral.com/thci.
*Contact:*
All questions about submissions should be emailed to:
*AIS-THCI-AI-FTE-SI-requests@umich.edu
<AIS-THCI-AI-FTE-SI-requests@umich.edu>.*
Linke to: *Call For Papers: Special issue on AI Fairness, Trust
and Ethics
<https://bit.ly/2JcrDT7>*
Best regards,
Lionel
*New Paper(s):*
Du, N., Haspiel, J., Zhang, Q., Tilbury, D., Pradhan, A., Yang, X.
J.
and *Robert,
L. P. *(Accepted 2019). *Look Who’s Talking Now: Implications of
AV’s
Explanations on Driver’s Trust, AV Preference, Anxiety and Mental
Workload*,
*Transportation Research Part C: Emerging Technologies*, (pdf
<http://hdl.handle.net/2027.42/149154>), forthcoming, link
to the article
provided by the author:
http://hdl.handle.net/2027.42/149154 and
http://arxiv.org/abs/1905.08878.
*Robert, L. P. *(2019*)*. *Are Automated Vehicles Safer than
Manually
Driven Cars?*, *AI & Society*, (pdf
<https://deepblue.lib.umich.edu/bitstream/handle/2027.42/149146/AI%26S%20Are%20Automated%20Vehicles%20Safe%20Final%20Version.pdf?sequence=1&isAllowed=y>
), link to publisher's site:
https://doi.org/10.1007/s00146-019-00894-y copy
provided by the author:
http://hdl.handle.net/2027.42/149146.
*Robert, L. P.* ( 2019). *The Future of Pedestrian-Automated
Vehicle
Interactions*, *XRDS: Crossroads*, 25(3), pp. 30-33. (pdf
<https://deepblue.lib.umich.edu/bitstream/handle/2027.42/148533/Robert%202019.pdf?sequence=1&isAllowed=y>
), DOI:
https://doi.org/10.1145/3313115 article provided by
author:
http://hdl.handle.net/2027.42/148533 or
http://arxiv.org/abs/1904.06417 or
http://ssrn.com/abstract=3370618.
Petersen, L., *Robert, L.P.*, Yang, X. J. Tilbury, D. (2019).
*Situational
Awareness, Driver’s Trust in Automated Driving Systems and
Secondary Task
Performance*, *SAE International Journal of Connected and
Automated
Vehicles*, 2(2), (pdf
<https://deepblue.lib.umich.edu/bitstream/handle/2027.42/148141/SA%20Trust%20-%20SAE-%20Public.pdf?sequence=1&isAllowed=y>),
DOI:10.4271/12-02-02-0009 link to the article
https://saemobilus.sae.org/content/12-02-02-0009/ and copy
provided by the
author:
http://hdl.handle.net/2027.42/148141 and
http://arxiv.org/abs/1903.05251.
Lionel P. Robert Jr.
Associate Professor, School of Information
<https://www.si.umich.edu/people/lionel-robert>
Core Faculty, Michigan Robotics Institute
<https://robotics.umich.edu/core-faculty/>
Affiliate Faculty, National Center for Institutional Diversity
<https://lsa.umich.edu/ncid>
Affiliate Faculty, Michigan Interactive and Social Computing
<http://misc.si.umich.edu/>
Director of MAVRIC
<https://mavric.si.umich.edu>
Co-Director of DOW Lab
University of Michigan
Email:
lprobert@umich.edu
UMSI Website
<https://www.si.umich.edu/directory/lionel-robert> |
Personal
Website
<https://sites.google.com/a/umich.edu/lionelrobert/home>
MAVRIC:
https://mavric.si.umich.edu
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