Algorithmic surveillance and post-panopticism are considered the main means of surveillance used today. Most commonly recognized as surveillance as biopower, but for the purposes of this article we will particularly focus on gamification and its role in algorithmic surveillance, as well as simulation as a tool for cybernetics. The article will define gamification, its features and its effectiveness as a concept. It will also discuss the speculations and opinions made before the widespread popularity of gamification and the reasons that led to a different outcome than expected. Simulation techniques will be discussed through a summarized history, their theoretical definition in the context of post-panoptic surveillance and their current implementation in the context of cybernetics. The aim is to compare the two forms of post-panoptic surveillance to determine their similarities and main differences. A comparison will highlight the importance of surveillance in today's society and how it can work in our favor or be harmful without knowing it. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essay Quantified self gaming, also known as gamification, is a form of surveillance that also serves to be enjoyable. The concept of the “quantified self” is not new in itself, but it has seen increasing popularity since the emergence of new technologies. “Monitoring, measuring and recording elements of one's body and life as a form of self-improvement or self-reflection are practices that have been discussed since ancient times.” (Lupton, 2016. p.1), therefore, with the digital age, we followed these practices that allowed individuals to actively and easily track certain aspects of their daily lives. This data production can raise questions about the privacy and security of user information while being self-quantifying, requiring surveillance analysis. These self-tracking activities are generally related to an individual's behavior and bodily functions, which can be categorized into two purposes. The first concerns the simple collection of data, as a means of remembering and recording certain aspects of life and satisfying general curiosity. The second category involves goal-directed activities that “make sense of the information they choose to collect and discern patterns that will help improve characteristics such as their health, physical fitness, emotional well-being, relationships and their productivity at work. (Lupton, 2016. p.2). Goal-driven self-quantified gamification is prevalent in fields such as marketing, politics, and education. It provides instant feedback on collected data by creating incentives such as goals and achievements. A direct representation of gamification are video games, whether on mobile phones or computers. Gamification is defined as “the use of game design elements in non-game contexts” (Deterding et al., 2011) to promote an organizational principle that views work as the end result of a game and games as a “mechanism” for improved work. effectiveness (Encheva, 2018). “Games are often a set of systems and subsystems that provide a variety of feedback loops that respond to a single player or multiple players. » (O'Donnell, 2014). Feedback received through gamification helps govern behaviorindividuals and act as steps towards a better future or several steps to improve one's future. In recent times, we have seen gamification being commonly used to promote or advertise a business or product. There has been an influx of lifestyle and health/fitness apps available today, but the prospective power of gamification goes far beyond marketing for businesses or self-quantified health statistics. “Gamers voluntarily invest countless hours into developing their problem-solving skills in the context of games. They recognize the value of prolonged practice and developing personal qualities such as perseverance, creativity and resilience through extended play. (Lee & Hammer, 2011) Therefore, gamification attempts to use this motivational power present in games and attempts to apply it to daily activities to boost engagement and functionality. If education were to implement gamification, it would be to incentivize and motivate students to learn better and prioritize school more. But to do this, it must be clearly defined, evaluated and explored to better understand the “theoretical justification of gamification”. (Lee and Hammer, 2011). Gamification is important and while the goal is to promote a positive outcome, the act of mass data collection comes with its share of concerns. Educational gamification will require better tools to reward students, which will represent an environment that students will want to participate in instead of walking away from. With skillful designs and proper implementation, gamification can help administrators deliver better schooling to learners while evaluating better ways to fix and continue to fix. The problem arises when gamification begins to deprive students by depleting teachers' resources and encouraging them to learn only when there is an external reward. While the benefits of self-quantified gamification are obvious, it also raises public concerns. We've seen insurance companies offer discounts on premiums if their customers agree to a fitness tracker, and while some might see this as motivation, others also feel that their personal data should not be tracked by a external entity. Algorithmic monitoring, like gamification, is designed to uncover relationships between widely disparate information and enable predictive analysis of behavioral patterns. Foucault's panopticism relied on surveillance that implied the presence of a watchful eye, whether guards in a tower or a superficial being keeping watch. Post-panopticism such as algorithmic surveillance is “characterized by embedded, silent, and hidden processes that make it difficult for individuals and society to become aware of and examine” (Ceyhan, ndp43). As mentioned in Surveillance as biopower by Ayse Ceyhan, algorithms are the foundation of computing and the main layer of contemporary surveillance devices used today. “Algorithms can thus be deployed as event generators because they combine understanding of the scene with user-defined criteria to trigger special scheduled events or results (alarms, etc.). » (Ceyhan, sdp43). A key feature of this type of strategic surveillance is represented by the detection of criminal acts or “high-risk” individuals, also known as outliers in a set of normal behaviors. It is believed that through mechanisms and processesof sophisticated surveillance, a person's identity is not only the individual themselves, but also the information that makes up that individual. Considering the person in a population as a source of data that can be controlled or studied is a notion of biopower. Although this type of surveillance is attractive for security purposes, it raises concerns about the privacy and human rights of the individuals being interviewed. Furthermore, we note that “the network of targeted individuals is likely to include subversives, members of minority religious groups and journalists” (Murphy, 2017), which would imply forms of discrimination. While these implications of privacy threats and discrimination surrounding strategic surveillance and mass data collection are discussed, it is important to consider them in order to properly apply these techniques without disgust or public outrage. “Simulation is a technology of truth and reality. » Baudrillard says that simulations are reproductions of reality according to the model presented, that is to say that they do not necessarily “represent” real events but simply create a hypothetical scenario according to its limits. They are also considered "self-verifying", meaning that they are true and real in themselves without the need for outside input. As noted above, panopticism depends on “visibility and non-verifiability,” meaning that control and authority must appear present to have an effect, even if they are not present. Simulations, on the other hand, are characterized as “truths that mask the absence of truth” (Bogard, ndp31). Unlike panopticons, simulations are not enclosed in a certain space that is necessary to verify them. In their most ideal form, simulations reproduce truths “before” they are verified, providing the primary inspiration for upcoming simulation technologies introduced today. In their early days, simulation techniques were used to manage risk assessment, profiling, data mining and financial speculation. “By the end of the 19th century, these techniques were being applied to quality and process control problems in industrial engineering. By the mid-20th century, they were used to aid in the development of nuclear weapons. (Bogard, sdp31) The simulation technologies known today are based on statistical estimation and sampling methods that make it possible to collect as little data as possible to generate behavior models. The first application of simulation technology was used by the military to “improve the accuracy of artillery fire.” and assistance with logistics and combat preparations. (Bogard, sdp33). We saw an increase in simulation training for aviation in the early 20th century due to World War II. Since the inception of human flight, simulations have been recognized as an important training protocol due to their reduced costs and ability to provide efficiency and flexible practice times with minimal risk. As aircraft became more complex, simulators also became more complex and began to take statistical reasoning into account as well. Statistical reasoning controls the deviations created by the simulation, to remain within reasonable limits so that the user can effectively make corrections. Flight simulation, for example, is capable of training pilots in routine procedures and emergencies that may or may not include deviations that may require rectification. The post-World War II periodsaw an increase in simulation technology that made it possible to solve selection, ranking, and optimization modeling problems. Telecommunications models that needed help with call pickups and switching were simplified through simulations. “Models like these also played a key strategic role in Cold War deterrence, helping to assess the technical, military and political capabilities of rival superpowers. Simulations also offered a way to predict and control capital flows and manipulate labor markets and financial transactions. (Bogard, ndp 34).Recently, we have seen a growth in simulation techniques in the healthcare sector. It is believed that simulation-based learning can “develop the knowledge, skills and attitudes of healthcare professionals” (Lateef, 2010) while also protecting patients from unnecessary harm. As demonstrated by military and aviation simulation-based learning techniques, it will be a valuable tool for learning objectives and developing techniques. This will also ease tensions between patients and healthcare professionals in training and minimize ethical violations. It helps mitigate errors and maintain a level of safety by providing “unique opportunities to practice and manage dynamic, complex and unanticipated medical situations.” (Lateef, 2010). With increasing technological advancements, students and healthcare professionals are able to learn treatment procedures and protocols before using them in real-world scenarios. “The simulated environment allows for learning and relearning as often as necessary to correct errors, allowing the trainee to perfect steps and refine skills to optimize clinical outcomes.” This allows individuals to get realistic exposure before working in their chosen field. Simulations can lead to situations that are difficult to obtain on a regular basis, making them effective by not relying on chance encounters. In a news article published by the New York Times titled Training the Next Generation of Doctors and Nurses by Laura Pappano, she discusses the path that medical education has taken over the years and how it has gone from " piles of books and lectures, then clinical placements exposing students to “patient” simulation-based learning that uses devices such as virtual reality glasses and corresponding software designed for this type of learning. A student testimonial from Marlene Alfaro in the article discusses the benefits that virtual reality offers. Pappano explains how simulations allow students to rehearse their treatment choices, as well as ideal ways to converse with a patient in difficult circumstances. "MS. Alfaro sees technology “as a driver of healthcare improvement” that could make visits more efficient for his future patients. (Pappano, 2018). Simulation-based learning and training has introduced new educational applications in many professional sectors Using evidence-based practices, algorithms and corresponding protocols, simulation training and learning can be integrated with traditional educational programs to develop a defined curriculum. for further refinement and exploration. “The cost-effectiveness of potentially costly simulation-based medical education and training should be examined in detail...