Borrowing from Keynes’ A Treatise on Probability: a non-probabilistic measure of uncertainty for scenario planning

Scenario planning is a tool used to formulate contingent but potentially impactful futures to aid strategic decision-making. A crucial element of many versions of scenario planning is an assessment of levels of uncertainty about the broad drivers of change within the system under consideration. Despite the importance of this element, the scenario planning literature is largely silent on the appropriate conception of uncertainty to use, exactly what it attaches to and how it might be measured. This paper seeks to fill this gap by advancing a non-probabilistic measure of uncertainty based on the concept of evidential weight drawn from the economist John Maynard Keynes' 1921 A Treatise on Probability

Uncovering unknown unknowns: towards a Baconian approach to management decision-making

Bayesian decision theory and inference have left a deep and indelible mark on the literature on management decision-making. There is however an important issue that the machinery of classical Bayesianism is ill equipped to deal with, that of “unknown unknowns” or, in the cases in which they are actualised, what are sometimes called “Black Swans”. This issue is closely related to the problems of constructing an appropriate state space under conditions of deficient foresight about what the future might hold, and our aim is to develop a theory and some of the practicalities of state space elaboration that addresses these problems. Building on ideas originally put forward by Bacon (1620), we show how our approach can be used to build and explore the state space, how it may reduce the extent to which organisations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases

De Finetti on the insurance of risks and uncertainties

In the insurance literature, it is often argued that private markets can provide insurance against ‘risks’ but not against ‘uncertainties’ in the sense of Knight ([1921]) or Keynes ([1921]). This claim is at odds with the standard economic model of risk exchange which, in assuming that decision-makers are always guided by point-valued subjective probabilities, predicts that all uncertainties can, in theory, be insured. Supporters of the standard model argue that the insuring of highly idiosyncratic risks by Lloyd's of London proves that this is so even in practice. The purpose of this article is to show that Bruno de Finetti, famous as one of the three founding fathers of the subjective approach to probability assumed by the standard model, actually made a theoretical case for uncertainty within the subjectivist approach. We draw on empirical evidence from the practice of underwriters to show how this case may help explain the reluctance of insurers to cover highly uncertain contingencies

Extending Cognitive Assistance with AI Courses of Action

NPS NRP Executive SummaryThe objectives of this study is to research and assess the initial stages of the evolution of Human-Machine Teaming (HMT) mission workflows which is focused on transitioning of automation tasks from humans to machines using a technique to digitize mission workflows. Also, study the advanced stage(s) of the evolution of HMT to include Courses-of-Action (COA) in Wargaming and how decision-making (DM) AI functions play what role natural language processing (NLP) plays. In addition, this study will explore the viability of NLP in HMT peer-to-peer COAs generation. Finally, this study will leverage complex Joint Naval Force EABO scenario (UNCLASS) designed by MCWL to explore NLP and distributed agents managing the decision making of operators using various modes of HMT interface of AI run-time execution agents thereby enriching digital workflows. The research questions that will be address will include: 1) What is the best approach for a cognitive assistant to learn mission workflows so that recommendations can be made to a human operator?, 2) How can cognitive assistants switch between modes of automatic, advisory, or monitoring?, 3) What are the key parameters for switching?, 4) How does the CA learn to switch to make appropriate recommendations?, 4) What is the cognitive intersection between domain specific environment awareness and situation awareness?, and 5) What happens when a target switches context? The methodology will use quantitative research methods. The methodology for this study will be based on SME input to gain an understanding of mission workflows and tasks, MCWL-developed Joint Force EABO scenario leveraged for a case study and collaboration with the Wargaming Center in Quantico, VA. Based on a scenario, the independent variables will be the inputs into the cognitive assistant. The dependent variable(s) are the output of the system such as if the system recommends the role of automatic, advisory, or monitoring. The plan for this study is to leverage a complex joint Naval Force EABO scenario in studying a role of enrichment digitization of the workflows including utilization of scenario-driven HMT modes and sub-modes; review digital workflows from Master Thesis: "Fire Support Coordination Cognitive Assistant", USMC Capt. Benjamin Herbold, NPS, Graduation Year: June 2020; gain understanding of wargaming COA Digital Mission Command Joint Forces hypergame; develop expertise on modes of Human-Machine Teaming control and their sub-modes of automatic, advisory, and monitoring; study evolution from a single "interactive" mode of HMT proposed for the Fire Support Coordination Digital Workflows to the planning phase in Fire Support Coordination; study NLP and associated theories as a framework to situate the research; and coordinate with other entities such as MIT LL, DARPA, BAE, USMC AI COI, MCWL, and ONR.HQMC Plans, Policies & Operations (PP&O)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Extending Cognitive Assistance with AI Courses of Action

NPS NRP Project PosterThe objectives of this study is to research and assess the initial stages of the evolution of Human-Machine Teaming (HMT) mission workflows which is focused on transitioning of automation tasks from humans to machines using a technique to digitize mission workflows. Also, study the advanced stage(s) of the evolution of HMT to include Courses-of-Action (COA) in Wargaming and how decision-making (DM) AI functions play what role natural language processing (NLP) plays. In addition, this study will explore the viability of NLP in HMT peer-to-peer COAs generation. Finally, this study will leverage complex Joint Naval Force EABO scenario (UNCLASS) designed by MCWL to explore NLP and distributed agents managing the decision making of operators using various modes of HMT interface of AI run-time execution agents thereby enriching digital workflows. The research questions that will be address will include: 1) What is the best approach for a cognitive assistant to learn mission workflows so that recommendations can be made to a human operator?, 2) How can cognitive assistants switch between modes of automatic, advisory, or monitoring?, 3) What are the key parameters for switching?, 4) How does the CA learn to switch to make appropriate recommendations?, 4) What is the cognitive intersection between domain specific environment awareness and situation awareness?, and 5) What happens when a target switches context? The methodology will use quantitative research methods. The methodology for this study will be based on SME input to gain an understanding of mission workflows and tasks, MCWL-developed Joint Force EABO scenario leveraged for a case study and collaboration with the Wargaming Center in Quantico, VA. Based on a scenario, the independent variables will be the inputs into the cognitive assistant. The dependent variable(s) are the output of the system such as if the system recommends the role of automatic, advisory, or monitoring. The plan for this study is to leverage a complex joint Naval Force EABO scenario in studying a role of enrichment digitization of the workflows including utilization of scenario-driven HMT modes and sub-modes; review digital workflows from Master Thesis: "Fire Support Coordination Cognitive Assistant", USMC Capt. Benjamin Herbold, NPS, Graduation Year: June 2020; gain understanding of wargaming COA Digital Mission Command Joint Forces hypergame; develop expertise on modes of Human-Machine Teaming control and their sub-modes of automatic, advisory, and monitoring; study evolution from a single "interactive" mode of HMT proposed for the Fire Support Coordination Digital Workflows to the planning phase in Fire Support Coordination; study NLP and associated theories as a framework to situate the research; and coordinate with other entities such as MIT LL, DARPA, BAE, USMC AI COI, MCWL, and ONR.HQMC Plans, Policies & Operations (PP&O)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

De Finetti on uncertainty

The well-known Knightian distinction between quantifiable risk and unquantifiable uncertainty is at odds with the dominant subjectivist conception of probability associated with de Finetti, Ramsey and Savage. Risk and uncertainty are rendered indistinguishable on the subjectivist approach insofar as an individual’s subjective estimate of the probability of any event can be elicited from the odds at which she would be prepared to bet for or against that event. The risk/uncertainty distinction has however never quite gone away and is currently under renewed theoretical scrutiny. The purpose of this article is to show that de Finetti’s understanding of the distinction is more nuanced than is usually admitted. Relying on usually overlooked excerpts of de Finetti’s works commenting on Keynes, Knight and interval valued probabilities, we argue that de Finetti suggested a relevant theoretical case for uncertainty to hold even when individuals are endowed with subjective probabilities. Indeed, de Finetti admitted that the distinction between risk and uncertainty is relevant when different individuals sensibly disagree about the probability of the occurrence of an event. We conclude that the received interpretation of de Finetti’s understanding of subjective probability needs to be qualified on this front

Extending Cognitive Assistance with AI Courses of Action

NPS NRP Technical ReportThe objectives of this study is to research and assess the initial stages of the evolution of Human-Machine Teaming (HMT) mission workflows which is focused on transitioning of automation tasks from humans to machines using a technique to digitize mission workflows. Also, study the advanced stage(s) of the evolution of HMT to include Courses-of-Action (COA) in Wargaming and how decision-making (DM) AI functions play what role natural language processing (NLP) plays. In addition, this study will explore the viability of NLP in HMT peer-to-peer COAs generation. Finally, this study will leverage complex Joint Naval Force EABO scenario (UNCLASS) designed by MCWL to explore NLP and distributed agents managing the decision making of operators using various modes of HMT interface of AI run-time execution agents thereby enriching digital workflows. The research questions that will be address will include: 1) What is the best approach for a cognitive assistant to learn mission workflows so that recommendations can be made to a human operator?, 2) How can cognitive assistants switch between modes of automatic, advisory, or monitoring?, 3) What are the key parameters for switching?, 4) How does the CA learn to switch to make appropriate recommendations?, 4) What is the cognitive intersection between domain specific environment awareness and situation awareness?, and 5) What happens when a target switches context? The methodology will use quantitative research methods. The methodology for this study will be based on SME input to gain an understanding of mission workflows and tasks, MCWL-developed Joint Force EABO scenario leveraged for a case study and collaboration with the Wargaming Center in Quantico, VA. Based on a scenario, the independent variables will be the inputs into the cognitive assistant. The dependent variable(s) are the output of the system such as if the system recommends the role of automatic, advisory, or monitoring. The plan for this study is to leverage a complex joint Naval Force EABO scenario in studying a role of enrichment digitization of the workflows including utilization of scenario-driven HMT modes and sub-modes; review digital workflows from Master Thesis: "Fire Support Coordination Cognitive Assistant", USMC Capt. Benjamin Herbold, NPS, Graduation Year: June 2020; gain understanding of wargaming COA Digital Mission Command Joint Forces hypergame; develop expertise on modes of Human-Machine Teaming control and their sub-modes of automatic, advisory, and monitoring; study evolution from a single "interactive" mode of HMT proposed for the Fire Support Coordination Digital Workflows to the planning phase in Fire Support Coordination; study NLP and associated theories as a framework to situate the research; and coordinate with other entities such as MIT LL, DARPA, BAE, USMC AI COI, MCWL, and ONR.HQMC Plans, Policies & Operations (PP&O)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Updating "small world representations" in strategic decision-making under extreme uncertainty

The behavioral strategy literature investigates how decision makers might use Small World Representations (SWRs) to guide their actions in situations of extreme uncertainty, but says little about how such representations should be updated during the implementation phase. In this paper, we provide a framework to capture the relationship between SWRs, unknowns and Black Swans, and, drawing on the psychology of reasoning literature, explore different heuristic methods of inquiry that decision makers might use to update their SWRs. We compare the performance of two such methods⎯disconfirmation and counterfactual reasoning⎯in highly uncertain situations characterized by ambiguous and non-definite information. We find that counterfactual reasoning is superior to disconfirmation with respect to (1) counteracting the confirmation bias, (2) promoting the exploration of the scenario space, and (3) favoring the adoption of actions able to mitigate or exploit the consequences of Black Swans

Noncommutative Figa-Talamanca-Herz algebras for Schur multipliers

We introduce a noncommutative analogue of the Fig\'a-Talamanca-Herz algebra $A_p(G)$ on the natural predual of the operator space $\frak{M}_{p,cb}$ of completely bounded Schur multipliers on Schatten space $S_p$. We determine the isometric Schur multipliers and prove that the space $\frak{M}_{p}$ of bounded Schur multipliers on Schatten space $S_p$ is the closure in the weak operator topology of the span of isometric multipliers.Comment: 24 pages; corrected typo