The Economic Approach To Human Behavior

Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable-though imperfect-clinical decisions or suggestions In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians' use and adoption of AI Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians However, assessing the magnitude and impact of human trust on AI technology demands substantial attention Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians.

Social media applications have proven to be a dependable communication channel even when traditional methods fail. Their application to emergency management offers new benefits to the domain. For instance, analysis of information as the event unfolds may increase situational awareness, news and alerts may reach larger audiences in less time and decision makers may monitor public activities as well as coordinate with stakeholders. With such benefits, it seems the adoption of social media applications to emergency management should be automatic. However, their implementation introduces risks as well. To better understand the benefits and challenges, a review and analysis of the literature regarding the application of social media to emergency management was conducted. Identified research gaps were mapped into social and technological challenges. These challenges were then analyzed to set research directions for practitioners and researchers.

Social media applications and emergency management: A literature review and research agenda

This paper presents results from a research project on the behavior of complex systems after they experience disruptive events that impact their performance. As systems become more complex, the probability increases that they will exhibit emergent behavior that could lead to system failures or widespread and prolonged service interruptions. A complex adaptive system CAS approach is used to conceptualize a complex network system that has been impacted by disruptions and perturbations. A combination of network analysis and agent-based modeling is used to measure the performance of the system as it responds to disruptive events and restoration efforts. This system-level behavior is an emergent property of the complex network and represents system resilience. Various resilience measures are used to quantify system resilience and assess the effectiveness of strategies system owners employ to restore the system. We illustrate our techniques by characterizing a critical infrastructure system network as a CAS, and applying an agent-based simulation with an adaptive algorithm.

Resilience in Complex Systems: An Agent-Based Approach

: The Future Combat Systems (FCS) program was the largest and most ambitious planned acquisition program in the Army s history. As a program it was intended to field not just a system, but an entire brigade: a system of systems developed from scratch and integrated by means of an advanced, wireless network. Moreover, the FCS-equipped brigade would operate with novel doctrine that was being developed and tested along with the materiel components of the unit. To paraphrase the Army at the time, FCS was Army modernization. In 2009 the FCS program was cancelled, although some of its efforts continued on as follow-on programs. The FCS program had garnered considerable attention throughout its existence, but few studies have been released documenting the lessons from the program to aid the Army in moving forward from such a large acquisition termination. In 2010, the Army s Acquisition Executive asked RAND Arroyo Center to conduct an after-action analysis of the FCS program in order to leverage its successes and learn from its problems.

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Lessons from the Army's Future Combat Systems Program

Silverfish is a case study of a fictional system of systems of medium complexity. It evaluates the FOREST methodologies referenced in part I of this article series in the contexts of system design, system test and evaluation, and training. The Silverfish case study illustrates implementation of the FOREST meta-process model and the Mission Aware metamodel described in part I. The case study demonstrates how to accomplish the modeling of functional behaviors and associated derivation of requirements for a realistic system. This article begins with a short description of Silverfish, then describes the outcome of cyber tabletop exercises captured into modeling artifacts, the outcome of a resilience analysis, and a full derivation of cyber resilience functional and performance requirements from the modeling and analysis. 

Framework for Operational Resilience in Engineering and System Test (FOREST) Part II: Case Study – Responding to “Security as a Functional Requirement”

The advancement of technology and information access has lowered threat barriers, and security challenges are diffusing across all domains, many of which have not been designed to be secure for current and future vulnerabilities. In addition to others, there are many gaps in current systems engineering (SE) security design processes, and there is a need to reevaluate how we design systems in response to real and potential security threats. Systems that were developed without any consideration of operational threats now are being disrupted, and systems are being used by threat actors in ways that were never intended uses of the system. Thus the consideration of system response to threats in the development phase has become a necessary process across many domains that have no experience with safe and secure design strategies. Uncertainty and rapid change in the threat environment and future threat scenarios prevent a requirements-driven and model-based design process that produces dynamic design strategies and solutions. Future systems need to be designed for agility in response to context-driven changes, resilience to threat intrusions and cascading failure modes, and the ability to gracefully degrade and/or self-heal in response to unintended use. Methods and tools must support greenfield (new) and brownfield (existing) implementations.

Systems Engineering Grand Challenges in Security and Safety

In the context of human-machine teaming, we are observing new kinds of automated and “intelligent” applications that effectively model and manage both producer and consumer aspects of information presentation. Information produced by the application can be easily accessed by the user at multiple levels of abstraction, depending on the user’s current context and necessity. The research described in this article applies this concept of information abstraction to complex command and control systems in which distributed autonomous systems are managed by multiple human teams. We explore three multidisciplinary and foundational concepts that can be used to design information flow in human-machine teaming situations: 1) formalizing a language we call “RECITAL” (Rules of Engagement, Commander’s Intent, and Transfer of Authority Language), which defines the information flow based on concepts of intent, rules, and delegated authority; 2) applying this language to well-established models of human-machine distributed teams represented as a systemic control hierarchy; and 3) applying construal level theory from social psychology as a means to guide the producer-consumer model of the information abstractions. All three of these are integrated into a novel user interface concept designed to make information available to both human and machine actors based on task-oriented decision criteria. In this research, we describe a conceptual model for future information design to inform shared control and decision-making across distributed human and machine teams. We describe the theoretical components of the concepts and present the conceptual approach to designing such systems. Using the concept, we describe a prototype user interface to situationally manage the information in a mission application.

Construal level theory in the design of informational systems

We have created a cross-disciplinary learning program across studio art, systems thinking, and systems architecture to improve systems competencies. Previous research produced a framework for relating learning concepts across these three domains. We describe how to apply these concepts to any learning situation to increase systems competencies using systems thinking and systems engineering tools. We have applied the framework in educational settings to teach systems thinking, critical thinking, and systems engineering using a tailored classroom approach derived from studio art classes. The studio format encourages the students to build their skills across a portfolio of work focused on creating appropriate views of a system, communicating them, and gaining critical review – three core aspects of the systems thinking process. An effective systems engineer conceptualizes and solves problems, addresses stakeholder concerns, explores and composes solutions, and manages system evolution. The use of art, as embodied in systems-related tools, has proven to be an effective method for developing these skills. This article presents the framework and an example graduate level Systems and Critical Thinking class taught using the studio art approach. 

Teaching Systems Engineering Practices Using Principles from Studio Art Education

Digital Engineering and Model-Based Engineering continue to grow in adoption across the systems engineering community. However, programs and enterprises still struggle to quantify the value of this digital transformation. Research conducted by the Systems Engineering Research Center in collaboration with a government/industry Digital Engineering Measures Working Group is creating the first formal measurement framework for this transformation. This article describes the research, formation of a causal measurement model, and initial specification of candidate measures. 

Tom McDermott

Papers

Framework for Operational Resilience in Engineering and System Test (FOREST) Part II: Case Study – Responding to “Security as a Functional Requirement”

Systems Engineering Grand Challenges in Security and Safety

Construal level theory in the design of informational systems

Teaching Systems Engineering Practices Using Principles from Studio Art Education

Digital Engineering Measures: Research and Guidance