Presents reviews for the following list of books, Integrating Human and Artificial Intelligence: Software in the Age of AI.

This book provides a useful and practical framework for professional user-experience (UX) teams and students who need to understand how consumers think. It has achieved its purpose in the following ways: educating designers about the Six Minds of Experience Framework; showing researchers how to uncover new insights from customers; and demonstrating how to use the Six Minds of Experience framework to enhance the design for products and services. This book sets itself apart from the other technical communication books that discuss understanding audience experience because the author suggests that UX is multidimensional and multisensory, and that looking at more than one cognitive process will unwrap many more facets of the consumer’s thoughts behind the experience. The book concludes by leaving designers with a thought for the future. The author briefly discusses the history of artificial intelligence (AI) and its current evolutionary stage as Siri, Amazon Alexa, Google Assistant, etc. He argues that Six Minds can be a framework to explore how machine learning and AI can support humans by augmenting their cognitive abilities. Whether in the workplace or the classroom, this short book will supplement UX designers and technical communication students in exploring what it means to truly know the target audience.

The quest to understand the nuances of professional communication using computational tools have continued since, and many researchers in our field have embraced the new interdisciplinary approach now known as data science. Our quick metadata search on the journals and conference proceedings in technical and professional communication (TPC) revealed an increasing number of articles associated with terms commonly used in data science (e.g., big data, content analysis, text mining, sentiment analysis, topic modeling, network analysis) originating from numerous disciplines (e.g., corpus linguistics, computational linguistics, artificial intelligence, statistics, business analytics). Yet, the field of TPC is just beginning to embrace the power of data-driven approaches. This special issue extends Orr’s work by taking a snapshot of current work in data-driven approaches to the study of TPC.

When faced with the tasks of reading and writing a complex technical paper, many nonnative scientists and engineers who have a solid background in English grammar and vocabulary lack an adequate knowledge of commonly used structural patterns at the discourse level. In this paper, we propose a novel computer software tool that can assist these people in the understanding and construction of technical papers, by automatically identifying the structure of writing in different fields and disciplines. The system is tested using research article abstracts and is shown to be a fast, accurate, and useful aid in the reading and writing process.

The paper surveys studies of the process model for understanding writing, focusing in particular on problem-solving strategies in the writing process. It then presents a case study of the use of issue trees-a hierarchal network of goals not unlike the decision trees used in management science and artificial intelligence-to guide the writing process of the second author as he wrote a technical report. A good issue tree shows the relationships between various pieces of information: which information is central and which is supportive or incidental. Issue trees offer engineers a visual view of their writing plan. By building a hierarchal issue tree to illustrate the logical links of the proposed writing task, the engineer can put an overlay of "technology" on the task of writing-an overlay that may "trick" the unwilling writer into writing, and writing well.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Reviews of several electronic dictionaries are presented. As part of the review process, to determine how up-to-date these dictionaries are, the reviewer chose 50 words (such as artificial intelligence, backplane, digital switching, graded-index fiber, and virtual circuit) that he believed should be in a recent dictionary, even though a writing/publishing cycle could take up to 3 years. Then the dictionaries were checked against this list to arrive at a Current Factor for each.

An expert system is an application of artificial intelligence which requires the transfer of knowledge from human to machine. The acquisition of this knowledge from experienced practitioners (domain experts) is typically inefficient. Problems associated with the subjective reporting of knowledge must be overcome. To do this, a structured rather than unstructured interviewing approach can be used by knowledge engineers. Open, closed, and probing questions as well as direction responses should be used, together with a general-to-specific technique. The goal of the knowledge acquisition interview is to obtain complete, accurate, and reliable knowledge for the expert system.