submitted: august 2016
Doing the right thing; gamification as a means to tuning human behavior
“ Game Over
Save & Continue
Save & Quit ”
– Super Mario Bros.
Keywords: gamification, virtualization, learning, space, reality
This chapter discusses how gamification, the use of game mechanics, game dynamics and game technology within the practice of our everyday lives is both the result of and a driving force in the convergence of physical and virtual worlds, in order to evaluate the promises and risks of gamification.
First, we look at the difference between everyday life and games. We’ll examine what virtualization is, and how human perception structures space in order to try and grasp (virtual) reality. We’ll see how the world that we experience is a map of possible actions, and that our relation to the world is a feedback loop. We examine how in the process of gamification, learningfor individuals and groups is fueled by personalization of this feedback loop to allow for faster learning, and how this gamification in turn powers personal guidance in everyday life contexts.
It is of particular interest to us to carefully analyze how the process of gamification is intertwined with the human perception and construction of space, how this perception and construction of space determine our collective behavior, and how gamification can lead to more freedom and creativity, but also to more monitoring and restrictions (less freedom and less creativity).
If the distinction between everyday life and games would have to be summarized into a single sentence, it would be “everyday life is serious, games are not”. In our daily life we find ourselves in the very serious situation of working to fulfill our basic needs. This not only includes finding food and shelter (which may seem trivial in our western 24/7 economy), but also love, esteem, and self-actualization. Although we’ve greatly optimized our 21th century world to find these things (jobs, housing, transportation, education, etc.) we can’t permit ourselves too many mistakes or failures or we might loose it all, or, less dramatically, end up in a position of stagnation. To say that everyday life is serious is simply to say that a lot is at stake. Our actions are influenced by our goals and fears, more specifically by their anticipated rewards or penalties. And because everyday life is serious, we especially strive to eliminate all risks of huge penalties. We need to succeed, even if optimizing our chances of success limits our actions to (often boring) actions that have a low anticipated penalty on failure and/or a high chance of success. We won’t try new solutions, we can’t easily stop what we’re doing and/or do something else.
By contrast, games are not serious; a game is ‘just a game’. Playing a game could be defined as “the voluntary attempt to overcome unnecessary obstacles” (Suits 54-55). Compared to everyday life, in a game we have the freedom to stop or leave the playing field, start another game with different rules, or experiment with new solutions to the challenges the game poses. We can also optimize the game to be fun to play, so that there is pleasure in the activity of playing the game itself instead of (only) in the anticipated rewards. Although with games there is usually still something at stake (honour and reputation for example), these stakes are not crucial to our immediate wellbeing, and therefore we have within a game the opportunity to fail without grave consequences, possibly even the opportunity to fail beautifully. For a game to be a game, after each ‘Game Over’ there should be a ‘Retry’ option. And exactly because continuing and trying again after failure is possible (it is often even part of the game dynamics), the player isn’t limited to low risk (and low reward) solutions like he is in everyday life, but is instead invited to experiment with new solutions. Games stimulate creativity and freedom.
While being opposites in terms of their seriousness, everyday life and games are of course not unrelated. Humans have always been playing games as part of their daily lives, if only to escape it for a few minutes. But in recent years, everyday life and games have seemed to become increasingly mixed, a process usually identified as the gamification of society, the ‘use of games or game mechanics and/or dynamics in (the support of) the practice of daily life’ (Zicherman & Cunningham). Of course there have been serious elements in the games that humans have been playing for ages. They have not just been playing sports or leisure games such as chess or checkers, but also games that definitely contain serious elements, like pistol duels to settle disputes, or gladiators fighting for their lives. But these older games didn’t really allow for failure, while more recent serious games explicitly do.
Game mechanics include points (quantifiable measurements and allocations of progress), levels (stages of completion with increasing difficulty), challenges (obstacles to overcome), trophies (prizes for winning contests), badges (emblems that prove the user has displayed specific behaviour), achievements (markers for noting that specific goals have been reached) andleaderboards (rankings of users to measure their performance in comparison to others).
Game dynamics are the types of behavioral motivation that can be stimulated with these mechanics, and include rewards (“If I complete this action, I’ll be rewarded with an object with a certain value.”), status (“If I complete this action, others will respect me.”), achievement (“If I keep trying, I’ll achieve this goal (and prove to myself that I can do this).”), self-expression (“My identity is defined by what I do.”), competition (“I want to be the best, I want to be better than X.”), altruism (“I can show I’m part of this community by caring for and giving to others.”).
Recent gamification has lead to the application of serious games in areas as diverse as business (cost reduction, customer relations, productivity, teambuilding), recruitment (motivation, competition), marketing (points, engagement, loyalty, commitment, rewards), entertainment (engagement, participation), education (motivation, engagement, goal tracking, achievements), science (data analysis, data collection), social movements (engagement, cooperation, solving world problems, crowd-everything), health (fitness, sports, medical care, quantified self, patient monitoring) and warfare (drones, training).
In all these cases, game elements (mechanics, dynamics) are used to accomplish serious goals, while at the same time stimulating freedom and creativity like games do. The recent trend of gamification seems to be closely related to a process that is usually described as ‘the virtualization of the human life world’.
This ‘virtualization of the human life world’ is in fact not so much a virtualization in the strict sense of the word; it is instead a movement into a life world that is (partially) computationally mediated instead of ‘directly’ experienced. The concept of the life world is an invention of philosopher Edmund Husserl, and inspired the philosophical discipline of phenomenology, which takes the world as it is self-evidently ‘given’ as the starting point of all our experience. It then examines this experience of (human) life especially in terms of perception and activity (praxis) (Ihde 31-41). In the case of virtualization, we look at the virtuality and reality of our everyday life world as we experience and live it.
To be virtual is ‘being equally real to actuality, but in a different manner’ or ‘the quality of having the attributes of something without sharing its real form’ (Wikipedia “Virtual reality”). In other words, a virtual world is something that looks like and behaves exactly like the world, but isn’t the world ‘as the world really is’. Following this, one can easily see how a computationally mediated world like for example one in a 3D game or Second Life, can be called a virtual world, as it indeed looks and behaves like our every day world, yet clearly isn’t the same world. While this is a correct assessment (Second Life ís a virtual world), contrasting it with the world of every day life in terms of virtuality would be wrong, because as it turns out, our everyday life world is virtual as well.
The difference between these ‘worlds’ seems to be in the degree of computational mediation. If we look at for example Second Life, it is clear that this is in fact a computationally generated world made out of mathematical 3D models, and that if you want to add, modify or delete elements in this world, you’ll need the Second Life 3D editor rather than a shovel. In it’s current state, most of us don’t call Second Life our everyday life world, but rather a new context that is in some way a layer on top of our everyday life (because, when we live in Second Life, we also still need to take care of our physical bodies outside of Second Life; in a sense we are living two lives at once). So how do you determine that Second Life is a computationally mediated world? This is a really hard question, but the most straightforward answer seems to be: you point out which computational devices or elements mediate the life world; in the case of Second Life, you’d need computer hardware, possibly VR headsets, you’d need software and human-computer interaction devices.
To a lesser degree, the same identification of computational mediation is possible in life worlds that contain augmented reality. Augmented reality is the activity of enhancing our everyday life world with computer-generated content tied to specific locations and/or activities (Yuen, Yaoyuneyong & Johnson). This is usually done by projecting computer-generated content within the field of view of a subject, usually either through heads up displays like Google Glass or on smartphone screens or other screens. Mixing our everyday life experience with computationally generated visualizations is often done to provide specific functionality like for example navigation or metadata that is related to the location the user is currently at (for example where to find the best rated pizza nearby) or activities the user is currently performing (like for example travelling from location A to location B). This means that in this case, the subject’s everyday life context is enhanced, instead of replaced with a new contextual layer like in Second Life.
Pointing out computational mediation becomes more difficult with information technologies that have been integrated so tightly into our everyday lives that we almost don’t notice them anymore (C.f. Hillier). This is definitely the case with such trivial things as traffic lights and money, but also with grocery stores, and even mobile phones. They don’t enhance our daily life and aren’t computational contexts on top of it either; they are our everyday life. Money is an especially interesting example: from Linden Dollars (The money of Second Life), to crypto-currencies like Bitcoins, to American Dollars, can we really say one of them is less computationally mediated, or indeed, less virtual than the other?
Even though worlds like Second Life are impressive, the process of computational mediation is having its most significant effects in the parts of everyday life where we don’t even notice this process anymore. It is very tempting to try and identify an aspect of everyday life that is not virtual by looking for an aspect of everyday life that is not computationally mediated, but even if we were to be able to find an aspect of everyday life that is free of computational mediation it could still be something virtual, because computational mediation is just one type of virtualization, and our perception is another one.
3 How we perceive our world as space
In order to understand how gamification (mostly as a part of a process of increasing computational mediation) changes our life world, we have to understand that our life world, as a spatial world in which we live our lives, is always a virtual world. To put it even more general: all space is virtual, because of the way human perception works. And it is exactly the structure of our space that gamification changes, most radically through computational mediation.
Not only more and less ‘computationally mediated’ life worlds (like Second Life, augmented reality and the grocery store) but also life worlds that are seemingly completely ‘directly experienced’ and in no way computationally mediated, like our life world if we would be climbing a mountain in nature, are virtual, because space itself is always mental and virtual. This might seem counterintuitive, so let’s look at the nature of space in human perception in more detail.
In the perception of reality, ‘points of matter’ are constructed at a certain distance (spatial or temporal) from ourselves. We can call these direct or absolute distances. When walking through mountains I can, for example, estimate how far away a particular rock is away from me. In this estimation I will determine the absolute distance between me and the rock. As humans, we are however also capable of calculating distances between two of these points that we have first constructed as points with distances from ourselves; this way, we can construct derived distances. I would for example be able to determine absolute distances between me and the rock, and between me and the ground below the rock. I could then make an estimation of how high this rock is (a derived distance between the rock and the ground), and whether I would be able to jump over this rock or that this rock is too high for me to jump over (a complex derived distance between me and the height of the rock).
What is important here is that space is a set of (projected) distances, and that based on the construction of space by the human mind, the human mind postulates the existence of ‘the real world’. This means that our life world is not the source of our perception, but the result. It also means that our spatial life world is not a kind of 'objective' essence, but that it is mediated by us! This insight has been most famously summarized by philosopher Immanuel Kant in the thesis of the transcendental ideality of space (and time): “Space and time are not things in themselves, or determinations of things in themselves.” (Rohlf) but “Space and time are nothing other than the subjective forms of human sensible intuition.” (Rohlf). In other words (and without going into too much philosophical detail), space has to do with the structure of our perception, rather than the content.
Human perception is representation of the world; it postulates the things in the world as ‘real’ things with ‘apparent physical existence independent of our perception’, and it is exactly in this sense that our perception of reality is always virtual, whether this perception is fueled by input from a computational system or not. Empirical reality could be defined as ‘that which has apparent physical existence’, and this physical existence is exactly the quality that virtual reality systems try very hard to imitate and suggest. And to be absolutely fair, the most important difference between virtual reality systems and ‘the real world’ today is probably that the former do not succeed perfectly in convincing us that the objects we interact with have a physical existence, while the latter does (almost by definition, we might add; the real world is the real world because it has (apparent) physical existence).
Virtuality often has the connotation ‘not-real’ but it is now clear to us that this is only because most virtual reality systems are simply not convincing enough (yet). And, like many works of art and popular culture (from Plato (C.f. Kraut) to The Matrix) have suggested: if we’d live in a perfect (possibly computationally mediated) simulation, we’d have no way of telling if we’d live in a (computationally mediated) simulated world or not. From within our experience, based on perception alone, if this perception is convincing enough, there is simply no way for the subject to determine whether this perception is based on input from or mediated by a computational system or not. If our perception is convincing, we attribute physical existence to the objects that we perceive and they are ‘real’. This implies that ‘reality’ is a property that is based on a kind of judgment or assessment by the subject, that something that is virtual can have (and often has) physical existence, and that virtuality and reality are not opposites.
The fact that everyday life is virtual doesn’t make everyday life unreal, just like the fact that some virtual worlds are computationally mediated doesn’t make these worlds unreal. The reality of those worlds depends solely on our judgment that they are real. Of course, from outside of a computationally mediated virtual reality system, we can point out that it is computationally mediated, but from within this system, this is much more difficult, unless, like a lot of early virtual reality systems, the experiences that we get from them are for example incoherent, incomplete, not seamlessly integrated with other experiences we have, etc.; this way, a negative judgment might be possible (we know ‘this is not real’; or ‘this is a computationally mediated simulation’). But of course we might also be wrong about that!
Our experience of everyday life is a process of representation. The things that we perceive at certain distances from ourselves and each other are objects within space, objects that the mind constructs as real and physically existing objects. This space as a set of distances doesn’t only say something about the world that our mind postulates as the source of our perception, but also about us. In other words, reality is both physical and psychological, and our representation of reality is a spatial map.
It is important to distinguish maps from pictures. Both maps and pictures are copies of something else, adapted to a different (usually smaller) scale. A picture is a representation of something else in which all elements of the original have been copied proportionally, like for example when you would construct a perfect 3D model of a building on a smaller scale. This means that all elements of a scene that is pictured retain their relative sizes and relations to each other, which gives the picture a somewhat objective status. The picture however usually remains a theoretical construct, as in practice it is very hard to create a picture that is identical (except for its scale of course) to the scene that is depicted; there is almost always some kind of subjective factor present in a representation; even a photograph taken with a camera from a very high or distant position isn’t without some perspective skewing.
This is why most representations, including our perception of space, are actually maps. A map is a representation in which proportions are only retained with respect to their (subjective) usefulness or importance. To make a map more useful, proportions are in fact often intentionally changed: more important objects are made visually bigger, and less important items are made visually smaller. In many cases, unimportant items might not be represented at all. The pirate who creates a map to remember where he buried his treasure will surely represent the strange group of trees that serves as the landmark from which it is exactly thirty-seven steps east and fifteen steps south that he’s buried the chest of gold. He will also make sure the location of the chest is marked with a big X, to signify that this is what the map is all about. But he won’t bother to also draw the sun sinking in the sea like it was when he was working hard to put the treasure chest in the ground (unless he has some unstoppable artistic tendencies).
Our perception works similarly: our construction of space is influenced not only by our positional perspective like the position of our body, the direction of our head and eyes, but also, and just as significantly, by our psychological perspective: how we perceive things in space is affected by goals, desires, fears and thoughts. If we have a certain goal in mind, all things in the world will appear either as support or obstacle to reach this goal; if we desire to be with a certain person, all things in the world will remind us of that person, and if we fear a great danger all things will show themselves as either huge risks or safeguards; if we have thought hard about how something works, we will see confirmation of these ideas everywhere, and we’ll have great difficulty seeing the things that contradict our thoughts. All this is evidence that space is a map, and that it is at least as subjective as it is objective (if objectivity and subjectivity were comparable at all).
Like a map, our perception isn’t just our registration of the state of the world, of ‘how things are now’, but it is ultimately a list of things we can do in the world, an array of buttons for us to push. Space is a structure of our options, the actions we can take, and things show themselves in particular as things we can use. Again, our perception tells us something about the world and about ourselves, because how we can use things is dependent on our capabilities. While a ladder might enable an adult human person to climb up, it doesn’t allow a baby to do so. These relations between subjects and things are usually called affordances.
The fact that our perception is a spatial map of things we can do, that space is a structure of our affordances, adds a richer meaning to the term distance: distance is a measure of the anticipated effort required to perform a certain action or to reach a certain goal. Proximity has to do with usefulness, as well as with the reward or peril that we anticipate. To be able to do better in the world, we need to build better maps, which may also be characterized as deep cognitive structures and activation patterns, and therefore we are involved in a continuous learning process of improving our maps (Churchland).
5 Feedback loops
There is a feedback system at work here. Humans are not passive observers of reality: we shape it. The space of our life world is a map of possible actions, and with the actions that we execute, we in turn influence the life world, what we can do next, and so on. Of course our actions influence both the life world itself, as well as how we (and others) perceive it. Humans act in the world and transform it both physically (by constructing buildings, developing infrastructures, and organizing (social) environments) and intellectually (through our belief systems, education programs, politics and laws, media, arts, and advertisements). Physical and intellectual shaping are intrinsically related: physical properties determine our beliefs and vice versa.
Humans have always been doing these kinds of world shaping, developing both themselves and society, and creating institutions, traditions, conventions, regulations and leaders in the process. The relatively recent process of the virtualization (or rather computational mediation) of the life world is a process composed out of human actions as well, and in it we’ve changed our world remarkably. What we have done in this process of computational mediation of the life world is rearrange or reconfigure the spaces that we live in. As computational systems have become more and more efficient, distances have become smaller and, a distance being a measure of anticipated required effort to complete a certain action, actions have become tremendously easier to perform.
Communication techniques as simple as Morse code and as complex as instant messaging have opened ‘worm holes’ in the network of distances between objects and locations of those objects. We have greatly expanded our reach into the universe (at least from the scale of our homes or villages to the scale of our planet), and are now capable of quickly ‘using’ objects that we previously had to undertake long journeys to reach: we can talk to our family at the other side of the planet as though they are sitting next to us, we can order products that are regional specialties of regions far away, and all these actions require less effort than even very primary tasks like talking to our neighbours or buying our daily groceries used to cost in the past.
It is in this sense that our world has become a global village and that we are living in a networked society. Sometimes it seems like we can be at multiple places at the same time, but a better way to put it would be that space isn’t linear but that it has multidimensional, jumps, warps, splits, joints etc. that are determined by our access to or use of it. And if we seem to be at multiple places at the same time, it may be the case that we ourselves are not the simple human beings that we used to be any more.
It has always been difficult to determine where we end and where the world begins; for a blind person, his stick is a very important part of his body, and for a person with glasses, they are a serious improvement to his eyes, allowing him to see further, and with more sharpness and detail. But consequently, and more importantly, these enhancements allow people to do more. We’ve also externalized parts of our memory and thinking to machines in the form of data warehouses and server farms. We have become much closer entangled with the world, and our relationship with other things in the world, including technology, has become much more intimate than before.
The effects of the increasing computational mediation of our life world, the fact that distances have become smaller, actions have become easier to perform, and our reach into the world has simultaneously become more intimate and more widely spread, are that the world has become more personal to us, and it is from this personalization that gamification of our spaces benefits most, because personalization speeds up all kinds of learning and development, both of ourselves and of the world.
It is no wonder that gamification has had the greatest impact in the domain of learning, because personalization is most effective in learning, not only in the traditional domain of education (schools), for example in math games (Eliëns & Ruttkay), but especially outside of it as well, teaching us how (things in) our life world work(s). Excellent examples of gamified learning processes are getting awards for recycling glass or batteries (“Battery man”), receiving collectable rewards in shopping experiences (for example super markets that give away free collectibles with each purchase), or technology devices that contain a ‘walkthrough’ to help us learn use the product by using it instead of shipping with a four inch manual.
Personalized learning works better because learning goals, method and rewards can be adjusted to personal preference (this is of course not possible if everybody gets the same mainstream learning plan). As different people are motivated by different types of things, the learning plan can be dynamically adapted to trigger the correct kind of motivation for every person. Learning using a method that fits personal preferences also makes learning more fun, because it allows every person to learn using a method that they actually like. And if it turns out they don’t like it, or want to change the learning method half way, this is easily possible.
Additionally, learning is most effective with challenges that are within reach, but that are located just outside your usual reach. In general, learning works by trying something new that is only a little bit outside of your comfort zone (if it is too far from your usual behavior, you will overstretch and may sustain an injury), but that is still the accomplishment of something new (if you’ve done the same exercise numerous times before, it will be too easy and you will be bored). Repeatedly trying new things can make the new behavior a regular behavior. If challenges are the same for all ‘students’, for some they will be too hard, for some they will be too easy, for some they will be regular behavior, and only for a few they will be ‘just right’. Personalized challenges make sure that every ‘student’ gets a challenge with the ideal hardness, and can adapt the challenge hardness based on performance results and ‘student’ development to keep it’s hardness optimal even as the ‘student’ is learning (Peerdeman).
Making learning personalized doesn’t mean that learning becomes a solitary process. There is also a social component of learning that can benefit from personalization. Humans are social animals and personalization can actually use social dynamics to improve the learning process, by for example stimulating support (“Alice is stuck at this challenge. Can you help her, Bob?”) and competition (“Alice has completed this challenge. Can you beat her, Bob?”). In the computationally mediated world, social relationships have changed as well; computational mediation allows us to work or learn together or compete with each other even if we’re miles apart. Additionally, the organization, cooperation and communication that is required for learning (in groups) benefits greatly from computational mediation, not just during the gameplay itself, but in meta-learning, the process of reflecting on the gameplay and learning ‘what has been learned’ and ‘how it was learned’ (Kapp).
Most importantly, personalized learning can make sure the learning process fits the individual context of the ‘student’. In addition to our own personal preferences, learning also takes place in a certain practical context. If we learn in the classroom, we are usually not in the same exact situation as when we actually want to apply the learned behaviour in daily practice. Personalized learning can take into account the exact context we are in and suggest challenges either within this context of daily practice, or as a layer on top of it (to make sure we are not punished when we make mistakes in daily life like we normally would be) (Priebatsch).
This way our learning context can as closely as possible match the context of our everyday practice, which makes the learned behaviour more relevant. Personalized learning can also take into account our life flow and present challenges at the moments in our lives when we are most ready to learn, and not when we have enough to deal with already (learning would be inefficient in those situations, except in specific cases where we actually need to learn to act under pressure).
Because of increasing personalization (through computational mediation), any situation and context in our daily life world can be turned into a learning experience. Learning challenges of different kinds can be integrated more directly into our daily lives and this way our daily life can become a non-stop training and learning environment. Through more personalized experience, we learn how things work and how we work. When we develop the world, we also develop ourselves and vice versa. And the tools we use to do this have also been developed by us.
7 Guidance and monitoring – identity, control, responsibility
In this gamification of our everyday life world, it is important to see that our personal goals are ultimately still the same (serious) goals we’ve always had (food, housing, etc.). The serious games we play during everyday life situations are real games that are used in the context of our daily lives and our quests for these serious goals, to improve our daily lives and help solve problems, both those of ourselves and of society. Serious games can help us choose directions, give us guidance and monitor our progress in learning and training; they can help us making decisions and shield us from the dangers of failure by providing built-in levels of protection. This way, self-engineering and social engineering become part of the same process towards Utopia, the ideal (or at least improved) structure of the human life world.
Because modern gamification techniques allow for immersive gaming in the context of everyday life, the learning process of everyday life tasks can be personalized (adapted to personal identity, daily routine, learning speed etc.) while at the same time stimulating social behavior like collaboration and competition. These games are in some sense new rituals, in which humans work, play and live together to improve and solve serious problems. Because these games are highly personalized, lower penalties on failure, improve engagement and lower required effort, improve loyalty and commitment, and as a result improve efficiency of improvement, they can make it easier to do what is really important and learn doing the right thing.
The obvious question is “what is the right thing to do?”, not just because the goals of different ‘players’ might differ or because individual goals might not align with the goals of society as a whole, but also because even if we agree about the relative importance of each individual’s goals and of the goals of society as a whole, we might not be sure about what exactly our own goals, the goals of others and the goals of society as a whole are. How can we align the goals of society and individuals to create a sustainable practical daily life for everyone? The weighing of all these goals in the calculation of game goals, rewards, scores and participation is determined by the question “who is in control?” (i.e. whose goals are important?). In order to be able to deliver personalized guidance and learning experiences, serious games will have to monitor individuals very intimately (especially in domains that have to do with individual well being and health (“Games for health”), and all this data can be used to significantly influence the behavior of these individuals. We might therefore also say that whoever owns, controls or interprets this data is in control.
The issue of control is also important in the practice of measurement. Who determined what is being measured and how it is measured? And more fundamentally: can every activity or thing be measured and represented in points of data? It is here that we run into the risk of datafication, the process of transforming everything into data rather than using data just to measure the world. And even if ‘everything’ (perhaps in practice by definition) could be measured, how do we make sure that what is being measured is in fact that which we want to measure. In the end, there might be a kind of ‘gamepocalypse’ (Schell) looming, which stresses the need for a movement of ‘counter-gamification’, strategies for “disrupt[ing] the processing and exploitation of users’ data”, and disruptive play (Dragona).
It is clear that when everyday life becomes more and more like a game, it is necessary that as a society, we look for rules to govern this game, to make sure that the game is a fair game. Rules of a fair game could for example be (1) every individual decides whether to play or not (freedom to leave the game), (2) failure is possible without grave consequences, (3) there is a ‘Retry’ function, (4) every individual can set their own personal goals as part of or in addition to the game’s overall goals (5) all rules of the game apply to all players. There is work here for philosophers, lawmakers and creators.
For ourselves, as individuals, the question is rather: “who do we want to be?” And how can we use these serious games to become who we want to be? We can use them to become more healthy, fit, social, creative and, ultimately, more free, but we can also use them to offload our responsibility for our lives to third parties and gaming systems. Regardless of whether we ourselves or our gaming systems that monitor our data will be in control, as long as we choose our gaming systems, we will have the responsibility to do the right thing, because freedom and responsibility go together. The impact of games is immense, and games ‘give us nowhere to hide’, but the responsibility for our own lives will always lie with ourselves. There is a need for a narrative and reflection on our choices in the context of games and gamification of our everyday life, and this reflection is part of our ‘project of self’, the necessity to shape and develop our identity through the actions and stories of our life. If not through an epic quest for becoming who we are, then at least by affirming our own responsibility for ourselves and the world, and by acting accordingly.
8 Conclusions – Summary
In the process of gamification, the rise of computational mediation in our everyday lives has greatly impacted the structure of our spaces in our everyday life world. Distances have become smaller, our relationship with the world has become more intimate, and our reach into the world has grown tremendously. Our access to technologies and the world itself has become more personalized, and because space is our perception of the world and how we structure our possible actions within it, the required effort to complete actions in our everyday life has decreased significantly, allowing us to learn faster and as a result act faster. If we are able to use this learning power to help us get better at the tasks in our daily life, we can use gamification as guidance in the process of reaching our serious goals, while at the same time possibly making life a more fun experience.
Gamification can in particular be used to (a) stimulate participation (protect players, lower penalties on failure, increase potential rewards), (b) allow new solutions to arise (stimulate diversity and creativity), (c) support transitions (help changing behaviors or conventions in a gentle way), and (d) align goals of society and individuals (improve ourselves and society and learn doing the right thing).
Ultimately, life is still a serious enterprise. The risks of gamification are in the nature of games as well. If everyday life will become too playful, it’s seriousness maybe lost, and we may forget what is at stake. We should never forget that if serious goals are at stake, not everything will be fun, or we might be very disappointed.
We also have to make sure that every game will be a fair game. This means that characteristics of the game like allowing failure, allowing leaving the game, allowing retrying and allowing individuals to set their own goals should be respected for all players. We should prevent monitoring becoming a totalitarian force that limits our individual freedom by choosing our systems wisely, and we should not forget that we’re all in the game of life together: our life world is a social world, and we might have to develop new rituals as part of our collaborative play.
In the end, the question is: are you gaming, or are you being gamed?
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 Timen Olthof obtained Master degrees in both Philosophy and Computer Science at the Vrije Universiteit Amsterdam. Currently he is working as a Mobile Architect, Consultant and Developer.
 Anton Eliëns is professor in creative technology / new media at Universiteit Twente and the Vrije Universiteit Amsterdam.
 In this chapter we won’t discuss how recent the development of gamification really is. It could be argued that the recent gamification through computational mediation is simply part of a much older process of social engineering and token communities/economies. C.f. Lemov; but also Cosgrave; and Lepper & Greene.
 Here, we won’t go into more philosophical detail about possible subjective and objective factors that play a role in this judgment. For example, we don’t want to argue that there is no objective basis for reality, or that reality is completely determined by the subject as subject, since discussing that would take a few more chapters.
 Usefulness and importance are subjective notions, and it is therefore that the somewhat ‘objective’ or ‘truthful’ status that maps often have can be (ab)used to influence other people in their perception of the world. Maps have to be handled with just as much carefulness as statistics in this regard (Monmonier).
 C.f. “we shape our tools and our tools shape us” (this quote is usually attributed to Marshall McLuhan, although it’s exact origin is unknown.)