#amomentwithmaghie #discussionzone
As a human factors professional, minimizing error and adverse effects on system components must be considered when designing integrated processes or program parameters to improve the error and limitations of decision trees as well as other machine-learning algorithms and analyses.
“Sometimes in high-workload situations, with high time pressure, concurrent performance is simply impossible, and people regress to a sequential mode of multitasking, requiring attention switching and therefore implicit decisions to continue to perform some tasks while shedding or ignoring others” (Wickens, 2014).
Guastello (2013) discusses task-switching as a stressor and function of healthy natural systematic balance. Task-switching can be seen at the cognitive level through the process of conditional reasoning in which response time can be affected by the presence of emotions at particular measurements. Due to the influence of human emotions on “expected and incidental emotions”, the play of implicit and explicit decisions become contingent on ambiguous choices (Wickens, 2014; Goldstein, pp. 416-17, 2018). As a result, final decisions can become functionally related based on other system processes that can influence reliability as well as validity (Goldstein, 2018).
Conditional reasoning and biased insight used in problem solving where priming and product interact to evaluate and employ reasonable resolutions, (though not well understood as discussed by the Goldstein text [2018]), reveal the use of divergent thinking as a proficiency of humans. Despite having uncanny adaptative skills, collaboration with robotic systems demonstrates limitations that lead to risk, performance obstacles, and other threats to safe operations due to the cap in expert mental sets that create domain knowledge.
Current research has not revealed a conclusive theory to increase system reliability where possible for collective acceptance in the scientific community; whereby, answering the question poses quite a challenge for this field of study (Goldstein, 2018). In noting that psychological research often delves into the Greek and Roman eras, would it be beneficial to consider the ancient philosophy that ‘”achieving stasis means that parties involved in a dialogue about a given issue have reached consensus on (or agreed upon) the information and conclusions in one or more of the stases” (Stasis Theory, 2022)? In support of mindfulness as the focus of human centric design, this ancient truth-in-process could provide relevant groundwork for future research.
By focusing on the commonality in which “this is ‘what is’,” a point of stasis from which attentional priming would initiate a review of the base rate presented to both operator and machine in consideration of all reasoning patterns (Goldstein, 2018). To reduce human limitation and error while employing the integrated processes of decision-making, human factors professionals must consider humans and algorithms perform in variance with responses to stimuli. As a result, the operator and machine are unable to achieve congruency when working simultaneously causing system failures due to excess workload points. To better discuss this concept, the idea of workload must be more concretely defined in the research community (Goldstein, 2018); however, the concept of overload is seemingly accepted as from which a definition could be built regarding a relationship to information.
Lexical ambiguity is a situation where “words can often have more than one meaning” (Goldstein, p. 327, 2018). Employing the concept of stasis and attentional priming to reduce lexical ambiguity would be met with an enhanced presentation of information when activating the permission schema to express connections manipulated in the working memory by anchoring effective heuristic responses (Goldstein, 2018; Guastello, 2013). An improvement to the stimuli would enhance neuroplasticity of reaction to elicit a more refined response: thus, allowing the sequential systems to produce a more harmonious interaction based on mindfulness in evaluation.
To construct a research project to examine how to demonstrate this aspect of cognition, the specific research question is:
“What features and absolute barriers could be implemented to address the conflicts of independent thinking to reduce limitation and error in human-machine interactions (HMI) using conditional reasoning?”
The challenges facing researchers and developers range from the approach in foundational model development itself, as concepts vary from domino models to fault trees which offer the potential for positive system testing and integration into a dynamic workplace (Guastello, 2013). In considering that the “lengthy trial-and-error process” of conditional reasoning is functionally relational to insight, the use of robotic systems in the workplace based on human cognition must overcome mental sets and preconceptions that hinder creativity as the process is iterated (Goldstein, p. 378, 2018). To evaluate these initial limitations and errors, fault tree analysis involving the creation of a diagram to represent the desired sequence of events in comparison to other opportunistic outcomes would be useful if probabilities were assigned to specific branch results (Guastello, 2013).
Current projects such as the “Air-Cobot” in France which “aims to develop a collaborative mobile robot to obtain a human-robot inspection of an aircraft during maintenance operations before takeoff on an airport” offer positive feedback regarding interactions provided that the “human operator supervises its mission, checks its non-destructive testing results, and intervenes if the robot is in trouble” (Futterlieb et al., 2017).
Threats to the security of operation, obstacles to efficient performance, and potential opportunities in error reduction must be considered to conduct an effective risk assessment. As language is the basis of communication for the human-robot interaction, variables regarding semantic development and lexical priming as discussed by Goldstein (2018) require determination to produce effective conditional reasoning with an increased level of accuracy in evaluation.
When considering Nature, systems are often inversely congruent which supports the various research theories of dynamic interactions based on dual systems (Goldstein, 2018). In comparing the relationship of the insula to the prefrontal cortex (PFC), the point of stasis for effective attentional priming may find validity and reliability in considering the analogous relationship of a breaking wave:
“When the carrier wave wavelength increases above a certain value, it turns out immediately that the phase velocity of carrier gravity component can be in excess of the group velocity of the parasitic capillaries riding on the orbital velocity of the gravity component, and the capillary wave train energy can never catch up with the propagation of the carrier GCW; the capillary ripples, however, continue being generated along the forward face of the GCW. As such, the capillary wave train appears to be blocked on the forward face between the crest and the trough. While on the contrary, when the phase velocity of a shorter GCW is lower than that of the group velocity of capillary waves, the capillary wave train can propagate over the entire surface of the carrier wave” (Hung & Tsai, 2009).
Using this as a mathematical example, a point of stasis can be determined in which vibrations find harmonic tones to create the cycle that maintains the existence of the process itself. This information could provide to be useful in implementing an algorithm based on commonalities at static points to determine mutually acceptable human machine interactions (HMI).
In employing an emotionally driven operator actively processing dynamic systems which are affected by unconsidered and inapparent variables, factors such as confirmation bias and cognitive dissonance could result in terminal situations when engaging a human-machine interface (HMI) without effective attentional priming (Donaldson, 2010; Goldstein, 2018).
“The status of your brain before you begin a problem can influence the approach you take to solving the problem” (Goldstein, p. 383, 2018).
This research supports the theory that human limitations (such as time and physical response) vary based on the availability of information at influx by functionally affecting the expected versus actual output to improve the priming to product cycle in the natural search for environmental stasis. By improving the quality of sources for monitoring to focus the ability of the systems to work as a natural wave of stasis, heuristics and other variables such as belief bias could result in a higher level of solution accuracy for conditional reasoning.
Conclusion
Conditional reasoning problems faced when interacting with machine programs or artificial intelligence (AI) due to human or machine error and limitation result in questions as to the validity of basing consolidated systems on the human cognitive structure (Goldstein, 2018; Guastello, 2013). The default mode network (DMN) processes with relation to internal and external sustained attention pose an area of pivotal research with specific applications to human-robotic system interactions. With research maintaining a primary focus on information processing, the development of human-machine interactions (HMI) has naturally followed sequence. Analogous analytics are suggested to combat cognitive overload while elevating human centric designs in workplace applications to ensure safety and error limitation in ventures of performance enhancement.
Human centric design supports an individual search for stasis based on the priming to product process of learning (Goldstein, 2108; LaBrie, 2014). By allowing the concept of learning to become the focus in a space of harmony while naturally seeking environmental interaction, technology remains a tool of organic human insight to innovative implementations.
References
Donaldson, A. (2010). Cognitive Dissonance. TEDxCanberra on YouTube. Retrieved December 18, 2022, from https://www.youtube.com/watch?v=NqONzcNbzh8&t=546s.
Futterlieb, M., Frejaville, J., Donadio, F., Devy, M., & Larnier, S. (1970, January 1). [PDF] Air-Cobot: Aircraft enhanced inspection by smart and collaborative robot: Semantic scholar. [PDF] Air-Cobot: Aircraft Enhanced Inspection by Smart and Collaborative Robot | Semantic Scholar. Retrieved December 10, 2022, from https://www.semanticscholar.org/paper/Air-Cobot-%3A-Aircraft-Enhanced-Inspection-by-Smart-Futterlieb-Frejaville/0a4c4c9a56465b700e4e0d68f683b8a344cd02f9
Goldstein, E. B. (2018). Cognitive psychology: connecting mind research and everyday experience (5th ed.). Wadsworth Cengage Learning.
Guastello, S. J. (2013). Human factors engineering and ergonomics: A systems approach, second edition. Taylor & Francis Group.
Hung, L.-P., & Tsai, W.-T. (2009). The formation of parasitic capillary ripples on gravity–capillary waves and the underlying vortical structures. AMETSOC. Retrieved December 18, 2022, from https://journals.ametsoc.org/view/journals/phoc/39/2/2008jpo3992.1.xml
LaBrie, R. (2014). The Cognitive Neuroscience of Sustained Attention and Classical Mindfulness: Volume 1. YouTube. Retrieved December 18, 2022, from https://www.youtube.com/watch?v=JusQmWAWc_I.
Stasis theory. Stasis Introduction – Purdue OWL® – Purdue University. (2022). Retrieved December 18, 2022, from https://owl.purdue.edu/owl/general_writing/the_writing_process/stasis_theory/index.html
Wickens, C. D. (2014, October 30). Effort Human Factors Performance and Decision Making. SAGE Journals. Retrieved December 18, 2022, from https://journals-sagepub-com.ezproxy.libproxy.db.erau.edu/doi/10.1177/0018720814558419
Human Centric Designs 