This paper presents a continuation of the previous research on the interaction between a human traffic manager and the UATMS. In particular, we focus on the automation of the process of handling a vertiport outage, which was partially covered in the previous work. Once the manager reports that a vertiport is out of service, which means landings for all corresponding agents are prohibited, the air traffic system automates what it has to handle for this event. The entire process is simulated through knowledge representation and reasoning. Moreover, two distinct perspectives are respected for the human supervisor and the management system, and the related ontologies and rules address their interactions. We believe that applying non-monotonic reasoning can verify each step of the process and explain how the system works. After a short introduction with related works, this paper continues with problem formulation, primary solution, discussion, and conclusions.

The advancements in AI technology have left no field untouched. With Artificial Intelligence tools taking over mundane tasks, (in addition to seemingly creative tasks), it has become a question of when, not if, AI will replace human workers in various industries. While some may argue that AI will replace human workers in all industries, in this article, I'm about to give you the real tea on why managers are more likely to be replaced'first'. According to Gartner, by 2030, 80% of today's project management's work will be automated, eliminating the discipline and replacing PM traditional functions with AI. In a global survey by Pega, 78% of the executives surveyed believe that increasing the use of AI and robots will dramatically reduce the middle management ranks.

The 1999 cult classic film Office Space depicts Peter's dreary life as a cubicle-dwelling software engineer. Every Friday, Peter tries to avoid his boss and the dreaded words: "I'm going to need you to go ahead and come in tomorrow." This scene is still popular on the internet nearly 25 years later because it captures troubling aspects of the employment relationship -- the helplessness Peter feels, the fake sympathy his boss intones when issuing this directive, the never-ending demand for greater productivity. There is no shortage of pop culture depictions of horrible bosses. There is even a film with that title.

In new research, scientists tackle one of our greatest future fears head-on: What happens when a certain type of advanced, self-directing artificial intelligence (AI) runs into an ambiguity in its programming that affects the real world? Will the AI go haywire and begin trying to turn humans into paperclips, or whatever else is the extreme reductio ad absurdum version of its goal? And, most importantly, how can we prevent it? In their paper, researchers from Oxford University and Australian National University explain a fundamental pain point in the design of AI: "Given a few assumptions, we argue that it will encounter a fundamental ambiguity in the data about its goal. For example, if we provide a large reward to indicate that something about the world is satisfactory to us, it may hypothesize that what satisfied us was the sending of the reward itself; no observation can refute that." The Matrix is an example of a dystopian AI scenario, wherein an AI that seeks to farm resources gathers up most of humanity and pumps the imaginary Matrix into their brains, while extracting their mental resources.

The 1999 cult classic film Office Space depicts Peter's dreary life as a cubicle-dwelling software engineer. Every Friday, Peter tries to avoid his boss and the dreaded words: "I'm going to need you to go ahead and come in tomorrow." This scene is still popular on the internet nearly 25 years later because it captures troubling aspects of the employment relationship – the helplessness Peter feels, the fake sympathy his boss intones when issuing this directive, the never-ending demand for greater productivity. There is no shortage of pop culture depictions of horrible bosses. There is even a film with that title.

Retailers need more decision automation, faster coordination of supply chains, and faster interactions with consumers, which means they will increasingly rely on AI. Automated decisioning systems will soon be making fine-grained micro-decisions on the retailer's behalf, impacting customers, employees, partners, and suppliers. But these systems can't run autonomously -- they need human managers. Every system for making micro-decisions needs to be monitored. Monitoring ensures the decision-making is "good enough" while also creating the data needed to spot problems and systematically improve the decision-making over time.

Your business's use of AI is only going to increase, and that's a good thing. Digitalization allows businesses to operate at an atomic level and make millions of decisions each day about a single customer, product, supplier, asset, or transaction. But these decisions cannot be made by humans working in a spreadsheet. We call these granular, AI-powered decisions "micro-decisions" (borrowed from Taylor and Raden's "Smart Enough Systems"). They require a complete paradigm shift, a move from making decisions to making "decisions about decisions."

Workers have anticipated AI fearfully due to widespread distrust of employers and technology. Things are getting better, says this AI expert. Artificial Intelligence (AI) has taken over the way we live, work, and do business. Specifically, in the Asia Pacific (APAC) region, businesses are adopting AI faster than their counterparts in the rest of the world. Setting out to be the trailblazer in the region, Singapore has developed a National AI Strategy in late 2019 to construct frameworks to facilitate the adoption of AI capabilities.

Companies must choose whether humans or machines should get the last word on employee performance. Digital tools and technologies are now relentlessly and remorselessly transforming how performance management works. Customized and continuous data-driven feedback is becoming a new normal for enterprises worldwide. This feedback appears both qualitatively and quantitatively superior to its performance review precursors and should lead to better outcomes. But does AI-flavored feedback require a human touch to measurably improve its impact?

Artificial intelligence is changing how people perceive technology in the workplace, but it's also changing how people perceive each other, according to Oracle's new AI at Work study. Based on a poll of more than 8,000 employees, managers and HR leaders, the report says that the majority of people would trust a robot more than their manager. They'd rather turn to a robot for advice, than their manager. Indians would trust robots most, followed by the Chinese, Singaporeans and the Japanese. The Brits and the French are at the bottom of the list – roughly half of their workers would trust a robot.