Call: Human Interaction with Artificial Advice Givers – Special issue of ACM Transactions on Interactive Intelligent Systems

Call for Papers

Special Issue of the
ACM Transactions on Interactive Intelligent Systems
on HUMAN INTERACTION WITH ARTIFICIAL ADVICE GIVERS

Main submission deadline: June 23rd, 2015

http://tiis.acm.org/special-issues.html

AIMS AND SCOPE

Some types of system that support people in making choices and decisions can be viewed as artificial *advice givers*: They propose options and help to evaluate them while involving their human user in the decision making process. These systems differ in terms of their degree of autonomy and the extent to which users can influence reasoning processes and conclusions. For example, a system that supports exploratory search for products will in general leave much of the judgment and decision making to the user, whereas a system that executes semiautonomous maneuvers in a car may offer the driver only the possibility of overriding the system’s choices. In all such situations, there can be benefits and challenges to keeping the human decision makers in the loop, enabling them not only to understand the system’s advice and reasoning but also to call it into question and to influence the system’s reasoning. In particular, over time such a collaboration can support the evolution of the decision makers’ understanding and requirements concerning the domain in question, as well as the evolution of the advice-giving system.

This special issue addresses the asymmetries and synergies that exist between human decision makers and artificial advice givers. It considers how an agent of each type can influence and understand the reasoning, working models, and conclusions of the other agent, especially with the help of recent advances such as novel forms of interaction and advanced methods for generating explanations.

By designing and testing improved forms of support for interactive collaboration between human decision makers and artificial advice givers, we can enable decision making processes that better leverage the strengths of both collaborators.

TOPIC DIMENSIONS

The following topic dimensions indicate the range of work that is relevant to the special issue. Each dimension is a question that can be asked about a possible submission to the special issue, accompanied by several possible answers to that question. A manuscript is probably relevant to the special issue if you can give meaningful answers to most of these questions (including possibly answers that are not listed here).

What type of advice-giving system does the research concern?

  • Recommender systems
  • Interactive decision support systems (e.g., for medicine or finance)
  • Systems that help mediate group decision making
  • Semiautonomous control systems (e.g., in factories or vehicles)

What aspects of the interaction between system and user does the research concern?

  • Ways in which the user understands the system’s reasoning, or vice-versa
  • Ways in which the user influences the system’s reasoning, or vice-versa

What support is there for the user’s understanding of the system’s reasoning?

  • Visualization of the system’s reasoning
  • Explanations of the system’s reasoning (textual, example-based, adaptive, …)
  • Design of the system’s reasoning processes to be inherently understandable

What techniques does the system employ to understand the user’s reasoning?

  • Process tracing
  • Preference modeling
  • Cognitive modeling
  • Error analysis

How does the user influence the system’s reasoning?

  • (Implicit or explicit) provision by the user of relevant information or requirements
  • Provision by the user of procedural guidance to the system (e.g., concerning the algorithm to be used)
  • Critiquing by the user of the system’s advice, procedures, or models

How does the system influence the user’s reasoning?

  • By giving access to information or experience
  • Through its representation of the choice situation
  • By offering tools that support a particular type of reasoning
  • By offering procedural advice
  • By suggesting evaluations or choices

Is the goal of the interaction to explore a domain or to make a decision?

  • Explore a domain
  • Make a decision
  • A goal intermediate between these

By what criteria is the advice-giving process evaluated?

  • Quality of the outcome
  • Time and effort required
  • Quality of the user’s subjective experience while deciding
  • Extent of the user’s learning with regard to future choices
  • User’s acceptance of the system’s advice
  • User’s general trust in the system

SPECIAL ISSUE ASSOCIATE EDITORS

  • Nava Tintarev, University Of Aberdeen, UK
    (contact: n[dot]tintarev[at]abdn[dot]ac[dot]uk)
  • John O’Donovan, University of California, Santa Barbara, USA
  • Alexander Felfernig, Graz University of Technology, Austria

IMPORTANT DATES

  • By June 23rd, 2015: Submission of manuscripts
  • By September 21st, 2015: Notification about decisions on initial submissions
  • By December 20th, 2015: Submission of revised manuscripts
  • By February 18th, 2016: Notification about decisions on revised manuscripts
  • By March 19th, 2016: Submission of manuscripts with final minor changes
  • By April, 2016: Announcement of accepted articles on the TiiS website
  • July, 2016: Publication of accepted articles in the ACM Digital Library

Except for the initial submission deadline, these dates are indicative rather than definitive. Some submissions will be processed more quickly, while others may require more reviewing and revision. Each accepted article will be announced on the TiiS website shortly after its acceptance and published in the ACM Digital Library within 2-3 months, even if other articles for the special issue are not yet ready for publication.

HOW TO SUBMIT

Please see the instructions for authors on the TiiS website (http://tiis.acm.org).

ABOUT ACM TiiS

TiiS (pronounced “T double-eye S”), founded in 2010, is an ACM journal for research about intelligent systems that people interact with.

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