In the 1980s, everyone got excited about the possibility of artificial intelligence. The excitement grew for a few years and then gradually faded as companies found that it was too hard to build and maintain useful expert systems or natural language interfaces.
However, there has been a renewed interest in developing software applications that can interact with people in natural languages, perform complex decision-making tasks, or assist human experts in complex analysis efforts. Today these systems are called cognitive computing systems or machine learning. They rely on research from artificial intelligence laboratories and use new techniques like deep learning and reinforcement which seem to overcome some of the problems that were encountered with earlier AI systems. Their capabilities have been demonstrated by IBM’s Watson winning TV games like Jeopardy! and by Google’s AlphaGO defeating the leading GO player in the world.
An upcoming issue of Cutter IT Journal with Guest Editor Paul Harmon will address the growing use of cognitive computing applications in business and industry. In some cases, organizations are building discrete applications to provide natural language interfaces or to simply do more sophisticated data mining with large databases. In other cases, companies are combining cognitive computing capabilities with existing applications and databases to create wholly new types of applications to significantly extend what computers have been used for in the recent past. Organizations are also developing applications designed to support or replace human decision makers.
We are interested in exploring all aspects of cognitive computing as it is being applied today. We’d like to consider both the technical aspects involved in creating cognitive applications and the broader social implications of using technologies that can replace human workers and we are especially interested in the practical experiences organizations have encountered in trying to use cognitive computing technologies in actual work environments.
Topics of discussion may include those stated above as well as – but not limited to — the following:
•What are the benefits and challenges of cognitive computing applications?
•What are the basic concepts of cognitive computing?
•What are the technological challenges of developing and maintaining cognitive computing systems and how can they be overcome?
•How do cognitive computing systems learn?
•What natural language enhancements can be made to existing applications?
•How can machine learning be used for intelligent search of large databases?
•How can robotics and machine learning applications (e.g. self-driving cars) be combined?
•What types of decision making applications are available?
•What are the social implications of supporting decision makers vs. replacing decision makers and in what situations is either better suited?
•What are the challenges of working with today’s cognitive development software tools?
•What types of challenges exist in acquiring knowledge from human experts and of creating and maintaining knowledge taxonomies and how can they be overcome?
TO SUBMIT AN ARTICLE IDEA
Please respond to Paul Harmon at npharmon[at]gmail[dot]com, with a copy to Christine Generali at cgenerali[at]cutter[dot]com and include an extended abstract and a short article outline showing major discussion points.
PUBLICATION DATE: OCTOBER/NOVEMBER 2016