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Software Engineering in the Twenty-First Century

AI Magazine

There is substantial evidence that AI technology can meet the requirements of the large potential market that will exist for knowledge-based software engineering at the turn of the century. In this article, which forms the conclusion to the AAAI Press book Automating Software Design, edited by Michael Lowry and Robert McCartney, Michael Lowry discusses the future of software engineering, and how knowledge-based software engineering (KBSE) progress will lead to system development environments. Specifically, Lowry examines how KBSE techniques promote additive programming methods and how they can be developed and introduced in an evolutionary way.


User Interface Goals, AI Opportunities

AI Magazine

This is an opinion piece about the relationship between the fields of human-computer interaction (HCI) and artificial intelligence (AI). The ultimate goal of both fields is to make user interfaces more effective and easier for people to use. But historically, researchers have disagreed about whether "intelligence" or "direct manipulation" is the better route to achieving this. There is an unjustified perception in HCI that AI is unreliable. There is an unjustified perception in AI that interfaces are merely cosmetic.


User Interface Goals, AI Opportunities

AI Magazine

This is an opinion piece about the relationship between the fields of human-computer interaction (HCI), and artificial intelligence (AI). The ultimate goal of both fields is to make user interfaces more effective and easier to use for people. But historically, they have disagreed about whether "intelligence" or "direct manipulation" is the better route to achieving this. There is an unjustified perception in HCI that AI is unreliable. There is an unjustified perception in AI that interfaces are merely cosmetic. This disagreement is counterproductive.This article argues that AI's goals of intelligent interfaces would benefit enormously by the user-centered design and testing principles of HCI. It argues that HCI's stated goals of meeting the needs of users and interacting in natural ways, would be best served by application of AI. Peace.


Agency plus automation: Designing artificial intelligence into interactive systems

#artificialintelligence

Much contemporary rhetoric regards the prospects and pitfalls of using artificial intelligence techniques to automate an increasing range of tasks, especially those once considered the purview of people alone. These accounts are often wildly optimistic, understating outstanding challenges while turning a blind eye to the human labor that undergirds and sustains ostensibly "automated" services. This long-standing focus on purely automated methods unnecessarily cedes a promising design space: one in which computational assistance augments and enriches, rather than replaces, people's intellectual work. This tension between human agency and machine automation poses vital challenges for design and engineering. In this work, we consider the design of systems that enable rich, adaptive interaction between people and algorithms. We seek to balance the often-complementary strengths and weaknesses of each, while promoting human control and skillful action. We share case studies of interactive systems we have developed in three arenas--data wrangling, exploratory analysis, and natural language translation--that integrate proactive computational support into interactive systems. To improve outcomes and support learning by both people and machines, we describe the use of shared representations of tasks augmented with predictive models of human capabilities and actions. We conclude with a discussion of future prospects and scientific frontiers for intelligence augmentation research. Although sharing overlapping origins in midcentury computer science, research programs in intelligence augmentation (IA; using computers to extend people's ability to process information and reason about complex problems) and artificial intelligence (AI; developing computational methods for perception, reasoning, and action) have to date charted largely separate trajectories.


Software Engineering in the Twenty-First Century

AI Magazine

Michael R. Lowry There is substantial evidence that AI technology can meet the requirements of the large potential market that will exist for knowledge-based software engineering at the turn of the century. In this article, which forms the conclusion to the AAAI Press book Automating Software Design, edited by Michael Lowry and Robert McCartney, Michael Lowry discusses the future of software engineering, and how knowledge-based software engineering (KBSE) progress will lead to system development environments. Specifically, Lowry examines how KBSE techniques promote additive programming methods and how they can be developed and introduced in an evolutionary way. The enabling technology will come from AI, formal methods, programming language theory, and other areas of computer science. This technology will enable much of the knowledge now lost in the software development process to be captured in machineencoded form and automated.