Intelligent Interfaces

IICS2208

vanessa.camilleri@um.edu.mt

Topic 4: Overview• Intelligent user interface agents & user

adaptivity;

• Benefits of user adaptivity

• Usability challenges

• Collecting data from users

• Future needs in IUI’s

Intelligence User Interfaces Why design them?

• To improve communication between humans and computers.

• To enhance the flexibility, usability, and power of human-computer interaction for all users.

HCI scientists exploit knowledge of users, tasks, tools, and content, as well as devices for supporting interaction within different contexts of use.

In simple terms, an intelligent interface provides a way for a system to learn something about each individual user and adapt its behaviour to them in some nontrivial way.

• Amazon adapts its recommendation system to the user’s previous history of purchase. Depending on their function and form, systems that adapt to their users have been given labels ranging from adaptive interfaces through user modelling systems to software agents or intelligent agents.

• However a common property binding these systems or agents is user-adaptivity

Systems where the intelligence lies mainly in

UIs• Systems with adaptive user interfaces that are automatically adapted to the inferred capabilities or needs of the user.

• Multimodal systems that aim to enable more natural, human-like forms of input and output.

• Systems with human-like virtual characters that enable the user to interact with a system in a way that is partly similar to human-human interaction.

• Smart environments in which embedded objects interact intelligently with their users.

• Personalised websites, in which the displayed content is adapted to the inferred interests of the user.

Systems where the intelligence lies mainly

behind UIs• Recommender systems, which present products, documents, or other items that are expected to be of interest to the current user.

• Systems that employ intelligent technology to support information retrieval.

• Learning environments that offer learning assistance on the basis of assessments of each learner’s capabilities and needs.

• Interface agents that perform complex or repetitive tasks with some guidance from the user.

• Situated assistance systems that monitor and support a user’s daily activities.

• Systems for capturing knowledge from domain experts who are not knowledge engineers.

• Games that make use of AI technology to create the opponents against which the human players play.

General schema for the processing in a user adaptivesystem

(Dotted arrows: use of information; solidarrows: production of results.)

• A user-adaptive system can be defined as:

An interactive system that adapts its behaviour to individual users on the basis of processes of user model acquisition and application that involve some form of learning, inference, or decision making

Overview of adaptation in amazon

Interface pro-activity continuum; moving towards a completely automated and

intelligent task completion

Benefits of user-adaptivity:

Functions: supporting system use

• Taking over parts of routine tasks;

• Adapting the interface;

• Helping with system use;

• Mediating interaction with the real world;

• Controlling a dialog;

Benefits of user-adaptivity:

Functions: supporting information acquisition

• Helping users find information;

• Recommending products;

• Tailoring information presentation;

• Supporting collaboration;

• Supporting learning;

Usability challenges for user-adaptive systems

Strategies for dealing withtradeoffs among usability goals

in user-adaptive systems

Obtaining information about users:

• Explicit self-reports & assessments;

• self reports about objective personal characteristics;

• self assessments of interests & knowledge;

• self reports on specific evaluations;

• responses to test items;

Obtaining information about users:

• Non explicit input;

• naturally occurring actions;

• previously stored information;

• low levels of psychological states;

• signals concerning the current surroundings;

Use of Data Collected• The key difference between user-adaptive

systems and other interactive systems is the inclusion of some method for acquiring and exploiting a user model.

• What is needed are (a) some implementation of the adaptation algorithm, not necessarily embedded in any interactive system; and (b) a database of behavioural data from a number of users who have used a relevant nonadaptive system. The researcher can then apply the modelling method to the data in order to determine how well the system would adapt to the users in question.

Future of User-adaptive Systems

• Growing need for user-adaptivity;

• Diversity of Users and Contexts of Use

• Number and Complexity of Interactive Systems

• Scope of Information to Be Dealt With

Future of User-adaptive Systems

• Increasing Feasibility of Successful Adaptation

• Ways of Acquiring Information About Users

• Advances in Techniques for Learning, Inference, and Decision

• Attention to Empirical Methods