Algorithm management is a system in which algorithms, rather than humans, decide how business operations should be performed. It was introduced as an attempt to explain how gig economies like UBER manage their workers. There are different types of algorithms such as taxi algorithms, call me algorithms, car rental algorithm, bus algorithm etc. All four of these algorithms are intended to achieve exactly the same goal, but each of these will do so in a completely different way. Each algorithm has a different cost and different travel time. Algorithms are usually chosen based on the circumstances, for example: Taking a taxi is probably the fastest way to reach a certain destination but it is also the most expensive way and taking the bus is certainly less expensive, but also much slower. In computer programming, there are often many different ways in which algorithms can perform a given task. Each algorithm has a number of advantages and disadvantages in different situations. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an original essay While managing algorithms in a gig economy can often paint a vision of a utopian future, the transition will be a long and arduous process that may never see the light of day and end up messing things up. Those who develop algorithm management claim that this creates new job opportunities, better and cheaper consumer services, transparency and fairness in parts of the labor market that can be classified by the inefficiency and opacity of human bosses, yet l he summer of wildcat strikes in London's gig economy shows that some workers are starting to chafe at the contradictions of being their own boss as they may be free to choose when to work but cannot choose how to work, which not only affects their psychology but also affects their competence outside of a gig economy as they get used to not using your brain in the work you do could also be a major contributor to leading us to dystopia. Human relations is the process of training employees, responding to their needs, promoting a workplace culture, and resolving conflicts between different employees or between employees and management. Different people have different needs and so expecting algorithms to consider the needs of all people may not be the right solution. best idea. Face-to-face communication allows us to get to know our subordinates better and therefore it is easy to contemplate their needs to encourage them to work harder, but algorithms present a more generalized way to contemplate chime needs which may not always encourage workers to work hard but so In many cases monitoring every step could end up putting them under pressure and, in turn, worsening the working environment. Estimates suggest that a fifth of employers in Europe had access to wearable technology in 2015, while in the US as many as 72% of CVs are unseen by human eyes. Amazon, Unilever, Deloitte, Tesco and most other large companies have immersed themselves in algorithmic management, but not everyone is happy with this trend. One of the main reasons for resilience is the fear that this will lead to a king of digital Taylorism, taking the principles of scientific management to another level of intrusions. Academic Phoebe Moore warned us about threats to work-life balance from algorithms because they can lead to a cultureof overemployment, which is something that scientific principles were created to avoid in the first place. The results of a recent ethnographic study of long-distance truck drivers show that electronic monitoring has led them to feel pressure not to take mandatory breaks and this may even be the first step towards a dystopian economy. There are algorithms such as the power of video surveillance in interviews or those that identify appropriate content in emails, risk creating a culture of guilty until proven innocent. In 2015, a California worker took her employer to court after she was allegedly fired for uninstalling a cell phone app that tracked her whereabouts 24 hours a day. The claimant alleged that her manager used the device to monitor her driving speed outside of working hours. Algorithms like these can easily offend a person and make them question their sense of privacy. In a work environment where scientific principles allowed people to have freedom at work by making decisions and having authority for those decisions, algorithms pose a serious threat to people's autonomy and sense of control. For example, couriers' daily rates and schedules are fully mapped by algorithms that infer their sense of control over their actions and this could also be as useful as turning them into robots that listen to what is said using their brains. But perhaps the biggest complaint is whether or not they work. Many of them have yet to be tested and are often erratic and subject to wild fluctuations. In her book Weapons of Maths Destruction, mathematician and technology polemicist Cathy O'Neil reports how a performance algorithm used in the New York City education system gave the same teacher 6/100 one year and 96/100 the next, without any change in score. their teaching style. For critics like Guy Standing, one man's flexibility is another man's insecurity. The gig economy is fueling a “precarious” class of workers who are denied the protections of traditional jobs, he says. Algorithms offer “fantastic opportunities for rapacious exploitation” of people who are already at the bottom of the job market. “They can monitor and ensure they only pay for the time they really want, and have people always available, waiting for their call.” In my opinion, a big part of why Taylor came up with these principles was to avoid exploitation of workers in any way and give them what they deserve, but companies use algorithms as an excuse to pay their workers just for the work they actually do. they want to pay and not the work they deserve to be paid for. Technology cannot be described as a uniform mass of tools but rather as a multitude of devices that have different consequences for workers. Much depends on how algorithms are developed, including how data is collected, how the collected data is analyzed, and how the results are interpreted and used. There is no denying that human judgment plays as much a role as technology itself. Therefore, it can be argued that algorithms might be a perception of a few people who cannot be fully trusted to guide us towards utopia. Furthermore, examples such as the Obama campaign in light of its political consequences, the war on terrorism, and the 300,000-person protests in Rio show almost clearly that algorithms are not good at expanding beyond the immediate present to give us solutions for political, economic long term. and the social challenges that.