Emergence: From Chaos to Order by John H. Holland .

In this article, we outline the general concept of coactive emergence, an iterative process whereby joint sensemaking and decision-making activities are undertaken by analysts and software agents. Then we explain our rationale for the development of the Luna software agent framework. In particular, we focus on how we use capabilities for comprehensive policy-based governance to ensure that key requirements for security, declarative specification of taskwork, and built-in support for joint activity within mixed teams of humans and agents are satisfied.

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Human-agent teamwork in cyber operations: supporting co-evolution of tasks and artifacts with luna

In the mid-1980s, Brian Gaines first developed a model to predict the trajectory of progress in human-computer relationships, including how the knowledge science research programme would naturally transform itself over time into something he called ''symbiosis science.'' In this article, we reflect both on the extraordinary prescience of this model, and the contributions and challenges faced by researchers intent on progressive achievement toward the aspirations it inspires.

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From knowledge science to symbiosis science

ABSTRACT This article argues that artificial intelligence (AI) enabled capabilities cannot effectively or reliably compliment (let alone replace) the role of humans in understanding and apprehending the strategic environment to make predictions and judgments that inform strategic decisions. Furthermore, the rapid diffusion of and growing dependency on AI technology at all levels of warfare will have strategic consequences that counterintuitively increase the importance of human involvement in these tasks. Therefore, restricting the use of AI technology to automate decision-making tasks at a tactical level will do little to contain or control the effects of this synthesis at a strategic level of warfare. The article re-visits John Boyd’s observation-orientation-decision-action metaphorical decision-making cycle (or “OODA loop”) to advance an epistemological critique of AI-enabled capabilities (especially machine learning approaches) to augment command-and-control decision-making processes. In particular, the article draws insights from Boyd’s emphasis on “orientation” as a schema to elucidate the role of human cognition (perception, emotion, and heuristics) in defense planning in a non-linear world characterized by complexity, novelty, and uncertainty. It also engages with the Clausewitzian notion of “military genius” – and its role in “mission command” – human cognition, systems, and evolution theory to consider the strategic implications of automating the OODA loop.

https://www.tandfonline.com/doi/pdf/10.1080/14702436.2022.2102486?needAccess=true

Automating the OODA loop in the age of intelligent machines: reaffirming the role of humans in command-and-control decision-making in the digital age

As technology evolves to the Internet of Things (IoT), understanding context of the information about and from those things can be challenging. Numerous distributed heterogeneous devices reporting large quantities of data, and that may be interconnected to provide evolving services to multiple stakeholders will be characteristic of IoT ecosystems. Although the IoT is in the incubation phase, we can gain perspectives from current Networks of Things. In this article the author defines characteristics of complex domains that affect network management, including a case study of the Federal Aviation Administration (FAA) National Airspace System (NAS). Today’s tools, standards, and models are not sufficient to capture operating domain knowledge consistent to these characteristics. The author offers a new model to serve as a framework to obtain domain knowledge context for the individual resources and their applicable services, while simplifying complexity needed for effective maintenance management.

Thing to Service: Perspectives from a Network of Things

In this article we describe how we apply the concept of coactive emergence as a phenomenon of complexity that has implications for the design of sensemaking support tools involving a combination of human analysts and software agents. We apply this concept in the design of work methods for distributed sensemaking in cyber operations. Sensemaking is a motivated, continuous effort to understand, anticipate, and act upon complex situations. We discuss selected results of a macrocognitive work analysis that informed our focus for design and development of support tools. In that analysis, we identified seven target topics that would be the focus of our research: engaging automation as a full partner, reducing the volume of uncorrelated events, continuous knowledge discovery, more effective visualizations, collaboration and sharing, minimizing tedious work, and architecting scalability and resilience. In addressing the first target topic, we show how coactive emergence inspires an agent-supported threat understanding process that is consistent with Klein’s Data/Frame theory of sensemaking. In subsequent sections, we describe our efforts to address the remaining six target topics as part of design and development of a cyber operations framework called Sol. Specifically, we describe the use of agents, policies, and visualization to enable coactive emergence for taskwork and teamwork. We also show how policy-governed agents working collaboratively with people can help in additional ways. We introduce the primary implementation frameworks that provide the core capabilities of our Sol cyber framework: the Luna Software Agent Framework, and the KAoS Policy Services Framework. We describe areas for future development of Sol, including the incorporation of the VIA Cross-Layer Communications Substrate. Finally, we describe recent results and current plans for empirical studies addressing some of the issues raised in this article.

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Chris Forsythe

Papers

Coactive Emergence as a Sensemaking Strategy for Cyber Operations