In several activities so far, you have approached the issue of human-machine interactions. This might involve programs, automation protocols, or other applications. For more critical or sensitive decision points, the system architecture gravitates toward either a human or machine-derived decision response, often with veto opportunity. What this invites is a situation where a collaborative decision may not be feasible, often found in distributed cognition systems. Working further into a cognitive or neural system, there is the learning component, both for the humans and the system, that present dynamic views and changing priorities based on experience. One of the challenges to the human factors engineer or specialist is in resolving any potential conflicts that might occur in the independent streams of thinking. If you were tasked to work with a team to develop a system that could include generated outcomes for decisions crafted with conditional reasoning, explain how you would structure an approach you might offer the team. Essentially, you would be suggesting how to accommodate conditional reasoning where human users are coupled with machine agents. A related issue here is that of the cognitive workload in this process. While your knowledge of this area may be limited at this time, you will find an example in the NASA Task Load Index tool. For now, include what benefits may be gained by applying a cognitive workload analysis as you develop your approach. Provide at least one scholarly resource to support your approach.

Present this as a brief. Your brief should be approximately 800 words in length and should be written in APA format.

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