Book reviews - Artificial intelligence and man-machine systems

1987 ◽  
Vol 7 (4) ◽  
pp. 51-51
Author(s):  
A. Klinger
Author(s):  
Dane A. Morey ◽  
Jesse M. Marquisee ◽  
Ryan C. Gifford ◽  
Morgan C. Fitzgerald ◽  
Michael F. Rayo

With all of the research and investment dedicated to artificial intelligence and other automation technologies, there is a paucity of evaluation methods for how these technologies integrate into effective joint human-machine teams. Current evaluation methods, which largely were designed to measure performance of discrete representative tasks, provide little information about how the system will perform when operating outside the bounds of the evaluation. We are exploring a method of generating Extensibility Plots, which predicts the ability of the human-machine system to respond to classes of challenges at intensities both within and outside of what was tested. In this paper we test and explore the method, using performance data collected from a healthcare setting in which a machine and nurse jointly detect signs of patient decompensation. We explore the validity and usefulness of these curves to predict the graceful extensibility of the system.


Author(s):  
Robin L. Zebrowski ◽  
Eli B. McGraw

Within artificial intelligence (AI) and machine consciousness research, social cognition as a whole is often ignored. When it is addressed, it is often thought of as one application of more traditional forms of cognition. However, while theoretical approaches to AI have been fairly stagnant in recent years, social cognition research has progressed in productive new ways, specifically through enactive approaches. Using participatory sense-making (PSM) as an approach, we rethink conceptions of autonomy and openness in AI and enactivism, shifting the focus away from living systems to allow incorporation of artificial systems into social forms of sense-making. PSM provides an entire level of analysis through an overlooked autonomous system produced via social interaction that can be both measured and modeled in order to instantiate and examine more robust artificial cognitive systems.


AI Magazine ◽  
2014 ◽  
Vol 35 (3) ◽  
pp. 70-76
Author(s):  
Manish Jain ◽  
Albert Xin Jiang ◽  
Takashi Kiddo ◽  
Keiki Takadama ◽  
Eric G. Mercer ◽  
...  

The Association for the Advancement of Artificial Intelligence was pleased to present the AAAI 2014 Spring Symposium Series, held Monday through Wednesday, March 24–26, 2014. The titles of the eight symposia were Applied Computational Game Theory, Big Data Becomes Personal: Knowledge into Meaning, Formal Verification and Modeling in Human-Machine Systems, Implementing Selves with Safe Motivational Systems and Self-Improvement, The Intersection of Robust Intelligence and Trust in Autonomous Systems, Knowledge Representation and Reasoning in Robotics, Qualitative Representations for Robots, and Social Hacking and Cognitive Security on the Internet and New Media). This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium.


Author(s):  
Syergyey Logvinov ◽  
S. Logvinov

Methodological approaches to the analysis of the effectiveness of complex human-machine systems (SMS) based on the use of methods of heuristic self-organization and artificial neural networks are considered. Modeling of the system taking into account a large number of factors and several output variables that characterize the MFM is based on obtaining multilayer perceptrons with the exception of factors with low sensitivity


Author(s):  
T. Çetin AKINCI

Cognitive engineering is the application of artificial intelligence, cognitive psychology and many different disciplines to human-machine systems with various software hardware elements. Cognitive engineering is supported by engineering disciplines and health, medical, psychology, sociology and even philosophical sciences. In this sense, it can be accepted as an interdisciplinary new science. Cognitive engineering is the transformation of human thought and psychology, even philosophy, into systems by modelling with software programs. Thus, machines or systems can be provided with more humane thinking and decision making capabilities than artificial intelligence. In this study, general information about Cognitive Engineering discipline will be given and recent applications in this field will be discussed.


Sign in / Sign up

Export Citation Format

Share Document