Workforce Development and Intelligence Analysis for National Security Purposes Proceedings of a Workshop (2018) / Chapter Skim
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3 Systems and Collaborations
3 Systems and Collaborations
Pages 25-42
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INTEGRATING THE WORKFORCE INTO THE NATIONAL SECURITY SYSTEM Nancy Cooke, Arizona State University, began by defining human– systems integration as "an approach in which human capabilities and limitations across a variety of dimensions are considered in the context of a very dynamical system of people, technology, environments, and tasks, and with the ultimate goal of achieving system resilience." She identified human elements in this large system as including training, personnel, selection, survivability, human factors, manpower, and the interconnections among those elements. She explained that the human–systems approach differs from approaches that consider human factors, such as human–machine interactions, because it considers human factors to be only one dimension of a broader system.
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Similarly, she said, examining the interface with a single medical device differs from examining the coordination of patient care in a hospital. Human–systems integration emphasizes multidisciplinary and team research, Cooke continued, including such disciplines as cognitive psychology, industrial engineering, systems engineering, and other fields, depending on the particular setting.
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Cooke illustrated this approach with an example from her work on cybersecurity analysis for the Army Research Office. She explained that the work involved a series of steps toward understanding the system that was in place, beginning with a cognitive task analysis that involved interviews, observations, surveys, and the development of models.
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However, she stated, this often does not occur. Instead, she said, in this instance, "the cyber analysts that we talked to said stop it with the tools, stop giving me the tools, I cannot use them, they get in the way, they just take more time for me to learn, I don't want the tools." Her team's analyses also revealed that little information was being transferred from the top of the hierarchy to the bottom; rather, analysts poured over an enormous amount of information without any contextual guidance from leadership.
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Cooke went on to explain that the cognitive task analysis in the cybersecurity setting revealed little collaboration and minimal role differentiation. In addition, there was a bottom-up flow of information that appeared to emerge from the in-place reward structures for possessing interesting information.
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COLLABORATIVE KNOWLEDGE BUILDING: CYBERNETIC TEAM COGNITION In his presentation, Fiore presented his views on team cognition, including the problem with human cognition and building knowledge from multiple information sources, the theory behind team cognition, and a roadmap for a solution to the problem as it relates to intelligence analysis. He argued that an unnecessary and problematic divide exists between scientists and engineers, and that this relationship will need to improve if the technologies that will be useful to the IC are to be developed.
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Fiore explained that the model of macrocognition in teams builds on this understanding to focus on cognition in the face of complexity in a team context. His research has been aimed at understanding how teams build knowledge in the service of solving complex problems.
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Uniting these elements, then, can provide a roadmap for cybernetics research and development, enabling the development of hybrid human– machine technologies to support team tasks and complex collaborative problem solving. In Fiore's view, macrocognitive cybernetics can provide "a way forward for intelligence analysts" because it can provide guidance on how to work more effectively with the vast amounts of data and information analysts must understand and apply, including through human–machine teams.
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analysts' cognitive resources for knowledge building are on the short-term horizon, citing the example of the construction of visualizations of data and other artifacts (e.g., cognitive artifacts, distributed cognition, external representations) to improve the ability to express and represent cognition outside of oneself.
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Fiore noted that he and other researchers in this domain have examined and identified ways to quantify the use and transmission of internalized team knowledge, individual knowledge gathering and building, knowledge sharing, and information exchange across teams to evaluate alternatives.10,11 He described as an example studies of National Aeronautics and Space Administration (NASA) mission control teams that identified the qualitative problem-solving processes involved in effective collaborative problem solving,12 as well as the quantitative problem-solving processes in which 8 Available: https://sites.google.com/site/netdrawsoftware/home [March 2018]
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Specifically, she described SciTS's aim as developing an evidence base of team characteristics and processes and the institutional, funding, and other conditions that influence the effectiveness of collaboration in science, often with a focus on cross-disciplinary teams.14 Hall suggested that there are similarities, but also important differences, between the science and intelligence communities. She noted that scientists, like intelligence analysts, work in the knowledge space, and their work is shaped by multiple levels of factors, adding that the two communities also develop similar products, including publications, briefs, and presentations, and provide expert input.
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. Enhancing the Effectiveness of Team Science.
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During the discussion following her presentation, Fiore noted that coordination mechanisms can include regular meetings or technology that supports coordination. He suggested that it would be important for the IC to examine its current coordination mechanisms and the degree to which they have helped people develop shared understandings.
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To collaborate successfully, she explained, groups generate a shared mission and goals, develop an understanding of the strengths and weaknesses of different disciplines, cultivate a group environment of psychological safety, and encourage information sharing and knowledge creation. As the team matures, she added, its members develop shared language and ways of conceptualizing the problem and a greater sense of commitment to working together, and as its work progresses, the team develops sets of roles and processes for communicating and accomplishing the work.
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Managing massive amounts of data in the information age.
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In addition, he said, having conversations in which people offer different ideas or provide feedback on others' ideas can be challenging, but cultivating an environment of psychological safety in which different perspectives and ideas can be shared and built upon can lead to better sensemaking. Eisenberg asserted that applying key principles and best practices in communication can improve the effectiveness of intelligence analysts.
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In the discussion following Eisenberg's presentation, Clark explained that analysts currently engage in many of these communication practices, using whiteboards to display their ideas and engaging in productive argumentation. Another participant seconded Eisenberg's observation that in addition to being able to present one's own viewpoint, it is necessary to remain open to the ideas of others.
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