Gamification as The New Form of Surveillance and Post-panopticism

Algorithmic surveillance and post-panopticism are considered as the main means of surveillance used today. Recognized more commonly as surveillance as biopower, but for the purpose of this paper we will focus particularly on gamification and how it plays a part in algorithmic surveillance, and simulation as a tool for cybernetics. The paper will define gamification, its functionalities, and effectiveness as a concept. It will also discuss speculations and opinions addressed before the widespread popularity of gamification and the reasons that caused a different outcome than the expected. Simulation techniques will be discussed by a summarized history, its theoretical definition as a part of post-panoptic surveillance, and its present-day implementation as a part of cybernetics. The purpose of this is to compare the two forms of post-panoptic surveillance to determine their similarities and key differences. A comparison will highlight the importance of surveillance in society today and how it can play in our favour or be unknowingly detrimental.

Gaming of the quantified self, also known as gamification, is a form of surveillance that also serves to be pleasurable. “Quantified self” as a concept is not a new per say, but it has seen a rise in popularity since newer technologies have emerged. “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 followed these practices that allowed individuals to actively and easily track aspects of their everyday lives. This production of data can cause questions about privacy and security of the users’ information while self-quantifying, calling for surveillance analysis. These self-tracking activities are usually linked to an individual’s behaviour and bodily functions, that can be categorized for two purposes. The first being for simple data collection, as a way to remember and record certain aspects of life, and to satisfy general curiosity. The second category involves goal-oriented activities that “make meaning out of the information they choose to collect and to discern patterns that will work to improve features such as their health, physical fitness, emotional wellbeing, social relationships and work productivity.” (Lupton, 2016. p.2).

The goal oriented self-quantified gamification is seen prevalent in domains such as marketing, politics, and education. It provides instant feedback on the data that is collected by creating incentives such as goals and achievements. A direct representation of gamification are video games, whether that is on a mobile phone or on a computer. Gamification is defined as “the use of game design elements in non-game contexts” (Deterding et al., 2011) to promote an organizational principle that envisions work as the end result of a game and games as a “mechanism” for improved work efficiency (Encheva, 2018). “Games are often a collection of systems and subsystems that provide a variety of feedback loops that respond to a single player or many.” (O’Donnell, 2014). The feedback that is received by gamification helps govern the individuals behaviour and acts as steps towards a better future or more steps for the betterment of one’s future.

In recent times, we have seen gamification being used commonly to promote or advertise a business or product. There has been an influx of lifestyle and health/fitness applications available now, but gamification’s prospective ability is far beyond marketing for businesses or self-quantified health statistics. “Gamers voluntarily invest countless hours in developing their problem-solving skills within the context of games. They recognize the value of extended practice, and develop personal qualities such as persistence, creativity, and resilience through extended play.” (Lee & Hammer, 2011) Therefore, gamification tries to use that motivational power present in games and tries to apply it to everyday 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 in order to do so, it must be clearly defined, evaluated and explored to further understand the “theoretical rationale behind gamification.” (Lee & Hammer, 2011). Gamification is important and while the purpose is to promote a positive outcome, the act of mass data collection has its set of concerns attached. Educational gamification will entail better tools to reward students, which will represent an environment that students want to partake in instead of stray away from. With skillful designs and proper implementation, gamification can help administrators provide better schooling for learners while evaluating for better ways to fix and keep fixing. The issue arises when gamification starts to take away from students by depleting teacher resources and only encouraging students to learn when there is an external reward.

While the benefits of self-quantified gamification are apparent, it also has concerns raised by the public. We have seen insurance companies offer discounts for premiums if their clients would agree to a fitness tracker, and while some might look at this as motivation, there are also others that feel like their personal data should not be tracked by an outside entity. Algorithmic surveillance like gamification, is designed to uncover relationships among 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 that is guards in a tower or a superficial being watching over. Post-panopticism such as algorithmic surveillance is “characterized by embedded, silent and hidden processes that make it difficult for individuals and society to be aware of and scrutinize it” (Ceyhan, n.d. p.43). As mentioned in Surveillance as biopower by Ayse Ceyhan, algorithms form the foundation of computing and the principal layer of contemporary surveillance apparatuses used today. “Algorithms can thus be deployed as event generators as they combine the understanding of the scene with the users defined criteria to trigger special programmed events (alarms, etc.) or outcomes.” (Ceyhan, n.d. p.43). One key feature of this type of strategic surveillance is represented by its detection of criminal acts or ‘high risk’ individuals, also known as outliers in a pool of normal behaviours. It is believed that through sophisticated surveillance mechanisms and processes, one’s identity is not merely the individual itself but the information that makes up that individual. Viewing the person in a population as a data source that can be controlled or surveyed as a notion of biopower.

While this type of surveillance is appealing for security purposes, it poses concerns about privacy and human rights of the individuals being surveyed. In addition, it is noticed 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. With these implications of privacy threats and discrimination surrounding strategic surveillance and mass data collection being brought up, it is important to consider them in order to properly apply these techniques without public distaste or outrage.

“Simulation is a technology of truth and reality.” Baudrillard says that simulations are reproductions of the real according to the presented model, meaning that they do not necessarily ‘represent’ real events but merely manufacturing a hypothetical scenario depending on its limitations. They are also considered to be ‘self-verifying’ meaning that they are true and real in themselves without the need of outside input. As discussed above, panopticism depends on “visibility and non-verifiability” meaning that control and authority must look present to have an effect, even if it is not present. Simulations on the other hand, are characterized as “truth(s) that mask the absence of truth(s)” (Bogard, n.d. p.31) Unlike panopticons, simulations are not enclosed to a certain space that is required to verify them. In its most ideal form, simulations reproduce truths “in advance” of its verification which is the main inspiration for up and coming simulation technologies being introduced today. In its early stages, simulation techniques allowed the management of risk assessments, profiling, data-mining and financial speculations. “By the end of the nineteenth century, these techniques were being applied to quality and process control problems in the field of industrial engineering. By the middle of the twentieth century, the were used to assist in the development of nuclear weapons.” (Bogard, n.d. p.31) The simulation technologies seen today are based on statistical estimation and sampling methods that allows the least amount of data collection to generate models of behaviour.

The first application of simulated technology was used by the military to “improve the accuracy of artillery and aid in logistics and combat preparations.” (Bogard, n.d. p.33). We have seen a rise of simulation training for aviation through the early twentieth century due to the Second World War. Since the inception of manned flight, simulations were recognized as important training protocol due to its reduced costs and its ability to provide efficiency and flexible practice times with minimal risk involved. As airplanes became more complex, so did its simulators and they also started to take into account statistical reasoning. Statistical reasoning controls the deviations created by the simulation, to remain in reasonable bounds so that the user can effectively make corrections. Flight simulation as an example, is capable of training pilots for both routine procedures and emergencies which may or may not include deviations that may need rectifying. Post-Second World War saw an increase in simulation technology that managed selection modelling, ranking and optimization problem solving. Telecommunication models that needed help with call-interceptions and switching, were made easy using simulations. “Models such as these also played key strategic roles in Cold War deterrence, assisting an assessment of technical, military and political capabilities of superpower rivals. Simulations also offered a means to predict and control flows of capital, and to manipulate labor markets and financial transactions.” (Bogard, n.d. p. 34).

In recent times, we have seen a growth of simulation techniques in the health care sector. It is believed that simulation-based learning can “develop health professionals’ knowledge, skills and attitudes” (Lateef, 2010) by also protecting patients from unnecessary harm. As seen by military and aviation simulation-based learning techniques, it will provide a valuable tool to learn objectives and build techniques. It will also mitigate patient tension with health professionals in training and keep ethical violations to a minimal. It helps mitigate errors and maintain a standard of safety by providing “unique opportunities for dynamic, complex, and unanticipated medical situations to be practiced and managed.” (Lateef, 2010). With growing technological advancements, students and health professionals are able to learn procedures and treatment protocols before using them in real-life scenarios. “The simulated environment allows learning and re-learning as often as required to correct mistakes, allowing the trainee to perfect steps and fine-tune skills to optimize clinical outcomes.” This allows individuals to receive realistic exposure before working in their chosen field. Simulations can conduct situations that are hard to come by on a regular basis, therefore making it efficient by not relying on chance encounters.

In a news article published by The New York Times called 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 shifted from “heaps of book learning and lectures, then clinical rotations exposing students to patients” to simulation-based learning that utilizes devices such as virtual-reality goggles and corresponding software designed for this type of learning. A student testimony by Marlene Alfaro in the article addresses the advantages that virtual reality provides. Pappano talks about how simulations allow students to rehearse treatment choices, as well as the ideal ways to converse with a patient in dire circumstances. “Ms. Alfaro sees technology “as a driving force behind the improvement in health care” that could make visits more efficient for her future patients.” (Pappano, 2018). Simulation-based learning and training has introduced new educational applications in many professional sectors. By utilizing evidence-based practices, algorithms, and corresponding protocols, simulation training and learning can be integrated into traditional education programs to develop a set curriculum for further refinement and exploration. “The cost-effectiveness of potentially expensive simulation-based medical education and training should be examined in terms of improvement of clinical competence and its impact on patient safety.” (Lateef, 2010). The underlying purpose of these simulation-based training techniques is to ensure the general public and potential patients that the system is accountable and ethically liable to ensure their wellbeing.

The future of simulation is self-dictated, uncertain from predictions by others and we have seen the rise of technologies that no one could have imagined. It aims to replicate an experience and most recently we have seen the use of Haptic feedback as a way to simulate touch. “Haptic interfaces simulate the feel of objects, their texture, surface resistance, bulk, edges and gaps.” As we have moved past panopticism and simulation surveillance has developed and evolved, it represents a concept far more complicated than the previous panoptic model was capable of explaining. The panopticon was the first concept introduced to familiarize with the inception of surveillance studies. It represented an enclosed system of surveillance that involved unverifiable visibility of authority or control. A relatively simple concept to grasp since we are familiar with some panoptic systems of control today. Religion for example, depends on the unverifiable presence of an immortal being that keeps watch over its people to ensure that they are well-behaved. Without evidence of its presence, individuals continue to follow purely because of their faith, that being well behaved will result in reward. In recent times, we have seen the growth of technology and the rise of post-panopticsm which includes the gamification of different daily activities. A majority of the general public is unaware of the security implications that these new technologies carry and the threats that they might possibly impose. While we see the vast list of positives that simulation-based learning and training provide, it is essential to the growth of this technology to monitor the techniques being used and implemented to ensure that it is not working against the people. The idea of dividuals, derived from the word ‘individuals’ is used to explain a concept of a control society that opposes the panoptic society introduced by Foucault. We have seen the concept shift from individuals being considered the building blocks of society to individuals being broken down into subunits of information and data pools. In summary, we have seen a drastic shift in surveillance models which may be a positive or negative result, depending on unverifiable possibilities.