“The bystander effect is the somewhat controversial name given to a social psychological phenomenon in cases where individuals do not offer help in an emergency situation when other people are present.” (Listversestaff, 2009)
The discussion around the bystander effect has been a controversial topic in an array of academic articles. However we first stumbled upon this term through a TED talk presented by Ken Brown, The bystander effect is complicated: and here’s why (2015). He references the Kitty Genovese case where she was murdered outside of her apartment, the police report said that “37 who saw murder didn’t call the police” - The New York Times 1964. One of first cases where the bystander effect was first recognised.
Evidence tends to suggest that “individuals intervene less frequently in emergency situations as soon as the number of passive bystanders around increased did not operate.” (Gueguen, Dupre, Georget, Senemeaud, 2015). A part of our natural human nature is blending in, to be one of the many in a crowd. Commonly referred to as being a sheep in society. It makes sense that when people are in a crowd they are more likely to follow what the crowd does. It brings to light the question of “am I doing the correct thing?” which is an insecurity in all of us. One main point stands out from these studies, “that bystanders’ perceived responsibility to act is an important factor of their own willingness to help the victim of an emergency” (Gueguen, Dupre, Georget, Senemeaud 2015). In some cases when there is one or few people, they are more inclined to help because the responsibility is less shared amongst a crowd, more so targeting at individuals. Seemingly “the presence of other people serves to inhibit the impulse to help.” (Fischer, Greitemeryer, Pollozek, Frey, 2006).
However in low risk evaluations in “the bystander condition, 85% of the male participants intervened, whereas in the alone condition only 65% of the participants intervened.” (Fischer, Greitemeryer, Pollozek, Frey, 2006), but “the present study revealed that in the context of highly dangerous emergencies, this bystander effect does not occur.” (Fischer, Greitemeryer, Pollozek, Frey, 2006).
Dangerous situations increase the risk versus the reward factor for helping a victim, studies find that people were more ready to take on that risk for the sake of helping, than those people in low risk situations (Fischer, Greitemeryer, Pollozek, Frey, 2006). So “the decision of helping a person in need is based on the relative weight of costs versus benefits.” (Bommel, Willemvan, Henkelffers, Van Lange, 2012). When it comes down to it, there is evidence suggesting that the more danger the victim is in, the more risk the people in the crowd will take on. When it is a low risk situation people are less inclined to think the responsibility to help is necessary.
Ken Brown in his TED talk furthermore goes on to mention “there is no evidence for the presence of 38 witnesses, or that witnesses observed the murder, or that witnesses remained inactive” (2015). In many studies we can see that the argument is reversed because what is shown is that “Dangerous situations faced in the bystanders are recognized faster and less ambiguously as real emergency situations than harmless situations.” (Fischer, Greitemeryer, Pollozek, Frey, 2006).
All of this shows studies about situations evaluated in real life. Throughout the years however, as technology and social media becomes more advanced, Bommel, Willemvan, Henkelffers and Van Lange make some increasingly relevant points. That “On the one hand, one could argue that the complete visual anonymity and safety of a virtual environment differs in important ways from real-world bystander situations.” (Bommel, Willemvan, Henkelffers, Van Lange, 2012)”. This we believe stands very true, a virtual environment, in particular social media, removes you from the immediate reaction response you would have in real life. “For instance, there is no threat of physical harm by intervening online, thus the potential costs of online-intervention are severely reduced.” Cyber bullying for example, you are protected by your screen at home, it is a place where you can be anonymous; you are not putting yourself in any risk, therefore it is easier to stand out.
“At the same time, in our modern era, real-life and online interaction have become very much entwined. A substantial part of our everyday social interactions, including helping, now takes place online” (Bommel, Willemvan, Henkelffers, Van Lange, 2012)
This poses the question, is our way of ‘helping’ online actually as effective as doing it in real life? What we are trying to address is the fact that trends in particular hashtags on social media, “#bringourgirlsback” or “#prayforparis” may not have any real impact other than making yourself look like a ‘good person’ online. It also seems more and more that people use these easy hashtags as way to acquire social approval, without actually participating practically. When asked if the “#bringbackourgirls” campaign has been a success Hewitt said: “the girls are still missing ... that is the ultimate measure of success and we are not there yet.” (Maeve Shearlaw, 2015). You also see this ‘online bystander effect’ on facebook, with posts saying things like “1 like = 1 prayer,” or “1 share = 10 prayers”. Although it now turned into something comical to reference to, it does prove our point further, that the extension of the bystander effect does exist within social media. Our initial takeaway is that these likes, shares and hashtags majority of time contribute to nothing.
Our findings presented that the presence of bystanders is known to reduce the helping responses, however the bystander inclination is less dominant in more dangerous situations. Also in large crowds, if one person steps out to help, then others will follow. The statement of no one will help is not as bleak as initially thought. (Heene, Wicher, Kainbacher, Fischer, Krueger, Greitemeyer, Vogrincic, Kastenmuller, Frey, 2011). Our approach furthermore attempts to reverse the bystander effect by creating something that cues self-awareness in social settings. (Bommel, Willemvan, Henkelffers, Van Lange, 2012). Ultimately we want to have an artistic comical interpretation of scientific studies.
“A satirical commentary of the bystander effect through the extension of social media”
The goal was to bring awareness to a subconscious act society takes part in. We wanted to present a dramatised, silly, non-serious, exaggerated interpretation of a bystander situation. Using this technology to also represent the involvement and impact social media has had on the bystander effect.
The user holds the iPad over the large detectable image of black boxes and white figure outline, this relates to the whole area giving the sense of a crime scene with a chalk outline of a figure seemingly placed to match the aesthetic of the black boxes and white outline. The black boxes further hold an underlying theme of city blocks, as well as notifications on your phone. When holding the iPad over the image it is then augmented to show the scene of the Auckland library. Strengths of this was that the image was highly detectable by the AR system, this could be replicated again and cut vinyl to give a more clean effect. However the messy chalk look worked in our favour in the end as it almost could have been a real murder chalk outline.
The user experience plays out the scene in the Lorne Street area to provide a familiar location to peak their interest and garner commitment from the user. It is a well known area, having high foot traffic gives in to the idea that individuals are known to become victim to the bystander effect in the Auckland CBD. Locations such as Queen Street and Karangahape Road we believe have this same effect. We modeled using Fusion 360 to represent this location, so far with our play testing people do seem to see it as the library. The only thing about these buildings is that if over done it could diminish the effect as its hard to see the figure with so much else going on in the surrounding area.
The camera on the iPad picks up on the recognisable image and brings up the city scene in AR, along with a tap to start button. Using unity to create this scene, the reason being that Augmented Reality provided a real life context literally. Have the scene take place through a device further exaggerated our point of social media playing a role. Our approach was to display this connection to the public, as social media is now such a huge part of our lives. Through the lens of Augmented Reality, ARcde crosses between our own perception of the environment around us and what is perceived through technology to allow us to see a situation in a different perspective as we would in the real world.
Once tapped it pops up with an enter your name where users can type their name and press enter. The buttons mentioned were a way to add an arcade aesthetic to the scene, as well as clear instruction for user. Done in a similar style of purple and red to match and compliment the AR environment. Using Unity brought about challenges along the way proving to be a timely process, time already being the biggest restraint definity was a risk. Overall the outcome is what we wanted, the use of AR technology turned out to be a great strength in making our point.
The scene starts playing out as small slightly grey transparent figures walk up and down the street imitating pedestrians and bystanders whilst a recognisable arcade wii song from the “mii channel music” plays emulating a light hearted take on the satirical construct that ARcde has created. The colour aesthetic is dual colour with two different shades of purple, the ground being a light purple and all buildings having a darker shade keeping the aesthetic theme of the presentation of the leaderboard. The grey figures are almost meant to blend in and be part of the scene, they actively are doing to help, further playing in our theory that people want to blend in.
A black silhouetted figure walks out of the library's front door and makes his way down the stairs. We wanted the main character to be distinctive amongst the many grey figures. As well as making the black figure specific to no gender or race, this can allow the user to put themselves in their shoes and identify the figure how they see fit. The figure then falls over in a dramatised, fake looking fashion, and cracks it’s head open on the pavement. This is all whilst people walk past the black figure lying on the ground. Approaching this through a satirical commentary helps create a conversation that moves towards a positive outcome. We aimed for it to be cheesy and a little silly. We didn’t want to condemn the audience for witnessing or being apart of such situations. Ensuring the outcome is a comedic take on the serious topic allows the talking points of this project to be lighthearted, helping individuals make conscious decisions to help this. Taking a comedic take on such a serious topic allows ARcde to breakthrough and curate conversation to individuals to promote their conscious decisions to prevent this.
An issue with this is that humor is completely subjective that a minority may not get the punch line when a statement of “#liketosavealife” pops up on screen, along with a like button. Mainly because the point being, that nothing happens at all when you like the scene. As a way to represent the fact that nothing actually happens when you like a good cause on Facebook or other social medias. While the blood is spreading out you have approximately 20 seconds to press the like button. The like symbol pops above his head when you press this button, showing again that you really have no effect.
After the alloted time plays out, a leaderboard pops up and a loser sounding arcade song plays, presenting the top six people who had the most likes. Having the loser sound play further emphasises our point of are you actually doing anything? Gets the user to ask themselves, “why am I losing?”. The board in large font says TOP KILLERS, above that in smaller font subtitled, did your likes really help? To further dramatise our message. We want it to come across as kind of silly take on this situation.
Our approach to this idea was to be over dramatic, exaggerated and not take ourselves too seriously. We had an enormous amount of challenges, not only when coming up with the concept, but during the development stages. Not having any prior knowledge of the programs used (Fusion 360, Unity, Blender). We did however have some knowledge of Adobe software but this wasn’t the main aspect carrying our project. However throughout this project this turned into one of our strengths, as this gave us an outsider approach to how we could shape the outcome. The ability/motivation/drive to learn from what we are doing and constantly looking outside of our own work for existing models and iterations of what has been done within the realm of our project (AR technology, Bystander effect etc) was exceedingly more driving for the final outcome. Though this does mean that our final product was weak in the sense we couldn’t make it look as impressive as practitioners in the field of Augmented Reality do it, we did have a rich field of learning to do and ultimately that was more important to us. Taking this as an opportunity to branch beyond our normal approaches.
We were extremely iterative throughout the first stages of our project, this posed a major threat. We spent the first half of the semester rolling through ideas rather quickly. Deadlines were becoming increasingly crucial. This meant that we had a lack of iterations on our final idea. For us though, those first weeks of exploration proved more useful than initially thought. By the time we came to our final idea, the concept was formulated enough to be carried out rather smoothly. We learnt about what we as individuals didn’t want to focus and produce. This produced many restrictions, however this also allowed us to develop a rich idea that we were all on board with; essentially saving energy for the main event. Time being the biggest restriction, this further shaped the outcome of ARcde, prioritizing the necessities to meet the timeframe required.
We started with an idea of annoyance and anti-design, from this we were thinking of how we could annoy individuals and what small things grind peoples gears. We moved on from this idea as we felt the concept was bleak and was lacking depth. We moved onto the concept of waves, sound and pollution. This was mainly drawn together with our common interest in mixing sounds, photography and the environment.
Through this process the development started with more ideas of how photos tend to pollute our social media feeds. More specifically how similar images are taken of popular areas with no originality (i.e paris Eiffel tower). Idea generation originally focused on the pollution of the ocean, contrasting between the pollution of the physical and virtual space became a point of interest to iterate upon. Furthering the exploration of both originality of sharing content such as photographs to how it relates physically of persons sharing similar photographs of their journey through countries and wonders of the world.
This had us stepping back to investigate about perspective, how one person sees the same thing as another. We thought about tourists taking photos of the same item or object and how this contributed to the idea of unoriginality. Especially in certain locations. We noticed trends on instagram as people in the same location tend to take photos in the exact composition. This lead us to thinking of infographics and peoples reaction to certain spaces.
All this thinking took longer than first anticipation, however it did lead us to our final idea. Not to look back on it as wasted time, reflecting on our journey as part of our process. The rapid iteration cultivated this bystander idea.
The similarities between the need to document your own life through social media and the way people react in different environments brought us to the conclusion of the bystander effect and how this contributes to the reactions of people in the public eye. Things in our society are developing so incredibly fast, we think it is important to address interesting trends and human nature as technology develops.
Technology and methodology
Adobe Photoshop and illustrator was used to prototype, creating textures, texts and stylistic components for the artefact. Fusion 360 to model the scene and blender to explore new processes. Unity was used for the main AR program and animation.
When we finally reached a final verdict, the roles started to form themselves. Gianni took on the responsibility of learning Unity to incorporate AR. Learning everything from scratch was a trial and error experience. Of course never having used this type of program before did limit the possibilities, however this allowed us to think outside of the box as we didn’t know exactly was achievable in the remaining time. It was an intense learning and exploration journey. The main responsibilities was learning Unity which involved, animation, creating buttons and responses of the AR development. Gianni was the main AR visualiser and co-ordinator, incorporating work from Eden and Daniel and combining all the components together.
Gianni also took on the role of developing the back end system of the Like button and leaderboard. This involved learning new skills in programming in both the Python language and C#. The biggest undertaking here was working through it to get the C# scripts to make requests to a Flask server hosted by a Python script. The incorporation of a network aspect elevated the complexity of the challenge as it was no longer a single device based system.
Eden took on the role of the stylistic components and design, as well as 3D modeling the buildings and co-ordinating back and forth with Gianni to get the overall visual aesthetic working to the best of their abilities. Learning Fusion 360, Blender and using previous knowledge of Adobe software. Eden was the main director of the visual outcome, making the design for the UI elements, 3D modeling buildings with detail and the layout of the environment to be cohesive with our theme.
Daniel further took on the role of modeling the roads and background structures for the scene. Learning Fusion 360 to coordinate with Eden on the layout of the environment. Creating main base structures allowed Eden to see some of the main buildings before designing the others. Also creating the final video of our project.
The work flow worked in an iterative circle. Daniel working on road bases, coordinating with Eden to create details and building structures, Eden then coordinating with Gianni on how it should come together, Gianni applying changes and functions. Then back to the beginning again, applying new feedback as we went along. It was interesting because first we envisioned our outcome to project a scene in a box, then we moved on to an approach more logical, the AR system. Without this circle of iteration, it would have taken much longer to reach our final outcome.
Relying on the completion of each other's work under a strict timeline gave us the learning experience of quality control between designing, modeling and visualising the Augmented Reality that ARcde wanted to project to the user at a high level in all elements.
ARcde presents its AR artefact using a square metre mdf board of a chalk outline at a crime scene backed with 2D squares representing the virtual environment created in Unity a 3D game engine. CAD programs such as Fusion 360 and Blender have been utilized to model life-like structures recreating a similar environment of Lorne Street in an effort to help provoke commitment due to the familiarities of the environment. All modeling and stylisation has been imported into Unity creating a platform that can be seen through the lens of an iPad displaying an Augmented Reality to displace the trigger image that is the painted mdf board.
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