About
ACM Transactions on Interactive Intelligent Systems (TiiS, pronounced “T double-eye S”) is an ACM journal for research on intelligent systems that people interact with.
TiiS publishes articles on research concerning the design, realization, or evaluation of interactive systems that incorporate certain form of machine intelligence. Such interactive intelligent systems are associated with a set of defining characteristics. In addition, TiiS articles come from a wide range of research areas and communities. An article can take any of several complementary views of interactive intelligent systems as described below, with a focus on (a) the intelligent technology, (b) the interaction of users with the system, or (c) both aspects at the same time. This journal is published on a quarterly basis.
Defining Characteristics
The first defining characteristic of interactive intelligent systems is that they include some form of intelligence – in the sense used in the field of artificial intelligence (AI), though in some cases the technology in question is no longer primarily or strongly associated with the AI field.
The second defining characteristic, interactivity, normally means that what the system does is perceived by – and influenced by – its users. Where no user input to a system is possible, the system can still be considered interactive if it is intended to support some sort of action on the part of the users. For example, a system that generates performances of virtual characters for the entertainment of passive viewers would not be considered interactive. But if the characters’ performances are intended to support some sort of decision-making or action by users, the system can be viewed as interactive, because it raises many of the same general issues that are raised by systems that are interactive in a narrower sense.
Complementary Views
The graphic below visualizes three complementary views in research on interactive intelligent systems, all of which will be found in TiiS published articles:
Focus on Intelligent Technology
At one end of the spectrum lies research that focuses primarily on understanding or improving intelligent technology for interactive systems. It often takes as its point of departure some form of interaction with intelligent systems that has already been realized successfully and aims to enhance it by improving the technology (e.g., by providing faster learning, more accurate recognition, or more reliable prediction).
Focus on Users' Interaction With Intelligent Systems
At the other end of the spectrum, we find research that takes as a starting point some existing intelligent technology and aims to find better ways of interacting with systems that incorporate such technology (e.g., by exploring new interface designs, interaction styles, or usage contexts).
Binocular View
In the middle of the spectrum, we have research that aims to advance understanding of both intelligent technology and users’ interaction with it – for example, by looking for better combinations of intelligent technology and interaction (e.g., a novel algorithm accompanied by a new interaction design that enables people to use it effectively).
Ensuring Relevance to the Journal
Articles anywhere on this continuum can make valuable contributions, and all of them are welcome in TiiS. But there is an important requirement: A manuscript that focuses almost exclusively either on intelligent technology or on interaction must also include at least a brief discussion of the “other” side of the picture, so as to make clear the relevance of the article’s contributions to the general issues addressed by TiiS. (See the subsection “Explaining Relevance” in the Authors’ Introduction for hints about how to formulate such a brief discussion.)
Research on Interactive Intelligent Systems
Although interactive intelligent systems can take many specific forms, there are some general research questions that arise whenever human intelligence comes into contact with machine intelligence, such as the following:
- In what ways can artificial and human intelligence work together effectively?
For example, where does machine intelligence offer the greatest added value? How can effective mixed-initiative interaction be achieved?
- What challenges to usability and acceptability can the incorporation of intelligence in an interactive system raise, and what strategies are effective in meeting these challenges?
For example, how can it be ensured that users have adequate forms and levels of control over an autonomously acting system’s behavior and that responsibility is assigned appropriately?
- What types of methodology for research, design, and evaluation are especially suitable for interactive intelligent systems – and how can such methodologies be improved?
Although most individual TiiS articles will focus on answering such questions in a specific context (e.g., a particular system or study), the whole collection of TiiS articles will advance our general understanding of these issues.
Indexed by SCI. TiiS is now approved and indexed by SCI. See its Impact Factor here.