Conference Paper

Tools for Exploring the Unknowable: Intuition vs. Artificial Intelligence

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Abstract

Our inquiry began by attempting to understand whether there are contexts in which human intuition consistently outperforms Artificial Intelligence (AI) in producing successful pathways for action. In order to figure this out, in this paper we distinguish between known, unknown (but knowable), and unknowable situations, using the Knightian uncertainty as our departure point. It appears that in the known realm, AI can outperform intuition, if used properly, while in the unknown both intuition and AI can be useful. By processing the data and identifying patters, AI can make an unknown setting known. In the unknowable realm, intuition, particularly intuitive wayfinding, may be our most promising mode of exploring, as AI does not have enough to work with. Therefore, we are particularly curious to explore whether human intuition may be a better tool than AI for exploring the unknowable, and we suggest that this is where intuition research should focus in the near future.

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... Will machine ever be able to make something meaningful out of the unknown? [16]. ...
... Due to the limitation of time, we were only able to do this experiment with a few people but we can confidently do these claims because we know how much thought process went behind the simulation design. It is a light weight simulation where intuitive decision making is a must.If we look at the grid, every time a new game starts it is randomly shuffled and how many times 16 boxes can be shuffled to make unique patterns is about 16! /16 (16 factorial divided by16) which is 1,307,674,368,000 (one trillion, three hundred seven billion, six hundred seventy-four million, three hundred sixty-eight thousand) different unique patterns. It'll take a super computer which ca remind all the patterns, but an AI is to be trained on this environment using Reinforcement models like MuZero or others, and computer cannot increase its accuracy because every time the environment is randomized with a new starting point.Think of it this way, when a new game is started the game is randomized, and after it is done setting hints and everything else a separate random number is generated that opens up a hint box as a starting point but user still has a free will to open any box at any time. ...
Method
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How can we generate an intuitive thought process into an AI? My study presents a simulator that collects intuitive decision-making of humans as data points onto a small world of 16 tiles built upon psychological principles that drive intuitive behavior in real life. Using the data this simulator is generating the research continues to develop an algorithm in the future that will let a computer take an intuitive decision. This study presents the thought process and the development of the simulator with data points as well. This information might be old, but if you’re interested to get the latest information you can check: https://ibjects.gitbook.io/intuitiveai/
... Overlooking sensing may leave managers paralyzed in cases of unknowable uncertainty, where additional analysis does not yield additional actionable information (Dörfler and Bas, 2020b). As Polányi (1966b: 44) put it, "Nothing that ought to be, can be determined by knowing what is." Sensory-based physical and affective reactions facilitate the creation of a "from-the-body" narrative (de Rond et al., 2019(de Rond et al., : 1962 that enables individuals to move forward amid uncertainty (Cunliffe and Coupland, 2012;de Rond et al., 2019;Huang, 2018). ...
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This conceptual paper examines reasons why analytically educated learners may be reluctant to engage in sensory-based learning. Sensing is indispensable for constructing knowledge and should be employed on par with the intellect, particularly in today's complex and uncertain context. Yet, we have observed learners' reluctance to engage with sensing and attempted to understand the reasons for it. Our theoretical contribution illuminates the underlying causes of this phenomenon, thus furthering the study of sensing in the fields of individual learning and management learning. Our practical contribution prompts researchers, learners, educators, and managers to think more systematically about ways to overcome this reluctance and openly bring sensing into management learning practice on par with intellectual processing. With the help of phenomenal theorizing, the presented exploratory study identifies the following common barriers to sensory-based learning for analytically educated learners: corporate social norms against sensory-based evidence, discomfort of learning outside of one's comfort zone, inadequate vocabulary for sensory experiences, lack of sensory awareness, preference for sequential reasoning, mistrust in sensory-based evidence, dismissive attitude, and denying (or not admitting to) the use of sensing.
... Intuiting as a process of sensing and sensemaking (Dörfler and Bas, 2020a) can lead to creating a higher quality of viable ideas than deliberate decision-making in research design (Dörfler and Eden, 2014;Khatri and Ng, 2000;Kump, 2020). Wayfinding is often intuitive and sense-based (Strati, 2007) when analytical support such as sufficient, reliable data, and fast, reliable processing is unavailable (Dörfler and Bas, 2020b). The term wayfinding has been widely used in various disciplines including management (Chia, 2017;Spiller et al., 2015). ...
Conference Paper
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Book
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Chapter
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