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Y.O.L.O. bike is a speculative design project that focuses on the design of the embodiment of autonomous intelligence and its agency, applied to a bike in a futuristic context. Nowadays technologies claim to connect people. The rise of the Internet and our networked society has indeed brought people closer together and made communication easier, but specifically in a virtual way. For example, people using dating app are actually sometimes suffering from the lack of contact in real life. While commuting, people in the train are staring at their mobile phone screens, and are not really open for a talk in the physical world anymore. Also, we noticed that with the rise of autonomous vehicles, people would no longer have to drive and pay attention to the road. They may spend this time to submerge themselves into their online worlds again. And this physical isolation can have negative aspects on humans’ well-being as well. It seems like biking is and will be the only mean of transportation where people are still present and focused on the ride, so we explored it.

Biking is an experience on its own, as people use their body to make the bike move and it all happens in the social context of the city: people pass by each other and can interacting for the sake of the traffic. Technology did not yet have a significant impact on cycling, because people prefer cycling as it is now, autonomous. However, we believe that with all the online data available, we could contribute to the offline cycling experience.

We imagine the future of biking, taking advantage of this context while augmenting the bike experience thanks to smart technologies, in order to make people meet in physical world again. We are introducing you to Y.O.L.O. well-being bike of the future.

RESEARCH

In order to understand the cycling experience, its context and the motivations and frustrations of cyclists, the interviews with cyclists, and observation were conducted. The results showed that cyclists use their bike for school, work, social activities, and groceries. Cycling is preferred as a way of transport, due to the fact that cyclists can be in control of their own pace, which makes them independent. Besides independence, health is one of the core motivations of cyclists to cycle. Cyclists are present in the moment and enjoy their environment during their ride.

Further, through lab research, we have explored what is the most user-friendly and most efficient and least distracting way of feedback. During this lab room research, haptic, visual, and a combination of haptic and visual feedback were tested. The results showed that a combination of visual and haptic feedback was the most preferred.

SEE OUR RESEARCH SET-UP

In order to design the embodiment of autonomous intelligence, different types of the agency were explored: Collectors, Actors and Creators. Collector type of agency only gathers, collects and displays this data while Actors also act on it. Creators type of agency is self-aware and autonomous. We suppose that in a near future, smart objects would mainly be creators. Buy how to apply the creator type of agency on the bike when cycling is something where people like to be in the control and free. What are the features which could make the bike fully autonomous while conserving the bike experience as the users like it? And which additional features are there to enrich the cycling experience? That is why it is interesting to explore how a bike can contribute to its environment and how the environment can contribute to the bike and its owner.

CONCEPT

The Y.O.L.O. bike is the concept we envisioned for future bikes in the year 2050. Y.O.L.O. stands for « Your Online Leads to Offline » and its goal is to leverage your online data to augment your experience of the offline world. In a world of constant online connectivity, the bike focuses on collecting data to analyze the interests of its user, as well as his needs, to create an offline network in which new connections are built more easily. To make the whole experience possible, the bike has to know a lot about its user, that is why the user’s own personal assistant is synchronized with the bike. It is also equipped with a face tracker to understand its user mood. The Y.O.L.O. bike actually extends nowadays small interactions bikers have with other users, and influences them to create new opportunities for friendships, love or professional partnerships… Thanks to Y.O.L.O. bikes, the ride becomes more than just a way to go from A to B, but also a pleasant moment during the day where something else than commuting can happen.

We compare the bike as a pet: Y.O.L.O. is the user’s best companion that aims to bring back the sense of belonging and community through the tangible world. Its behaviors is directly inspired from animals behaviors, especially pets, with their instinct, their personality often depending on their owner, their unpredictable behavior, their sense of loyalty to their community… Exactly the same way you would walk your pet, or ride a horse, the user now have to deal with a complex system that reacts on its surroundings and on your decisions, and from this, will emerge a accomplice relationship. On one side, the cyclist would have his own needs, wishes and his own perception of the environment, and on the other side, the smart bike, like every IoT objects, would be connected to the smart city, other users, and would probably know a lot about its owner based on his personal data. On the other hand, the bike is linked to the other member of its herd, like any animal. That’s why is able to communicate with them in order to regulates the flows, solve issue in the city altogether and make these meetings happen. The Y.O.L.O. bike in this context establishes the partnership between itself and its user and a real dialogue emerges from their collaboration. More than just giving instructions to each other, the smart bike and its users discuss on the good way to go.

VIGNETTES

#1 HERD

The first behavior describes the bike as part of a herd. In nature, a herd is often described as a social group of mammals that helps and protects each other. The herd travels together and acts as a family. The bike sends a request to nearby bikes that communicate it to the users to ask to join the herd. In this herd, users are safe, as they travel together in large groups and they benefit socially. Offline connections are made through an online bike network.

#2 COMPANION

The second behavior describes the bike as a companion. The bike wants to keep the user happy and takes the necessary steps to do so. The bike is not seen as an object, but as an entity which is able to make decisions on its own and can create unique situations due to its creator’s agency traits. The bikes behavior is not adjusted at a repair shop as a piece of software or hardware, instead, the bike and the user resolve problems at a therapist. Just as a human being, a bike grows their own personality and you can’t just change it to your preferred settings.

#3 CONNECTER

The third behavior is about the bike being self-decisive and creating connections. The bike creates connections between users by taking certain actions. An action might include faking a breakdown of the bike and signaling for help, to help create a situation where two people meet. This, of course, makes a situation feel like a coincidence, while in fact, it was all planned by the bike itself. In a developed online community and a sense of being, it’s important to step back to the offline world in which actual connections can be made, through life experiences.

SEE THE SCENARIO

#4 CHARACTER

The fourth behavior describes the bike as a person or pet. A bike is adopted, not bought because a bike can’t just be sold. The bike is part of someone’s life and its characteristics are formed throughout. What this creates, is a bond between a user and its bike that might be different from what you expect. You need time to adjust to your bike and your bike needs time to adjust to you. Bikes aren’t objects anymore, but part of society.

SEE THE SCENARIO

LESSONS LEARNED

We would like to share with the design community the essential takeaways that we have learned through this project. Thinking about the future bike has helped us to bring into focus some aspects of the agency with a specific point of view. It is not that easy to classify a bike as a Collector, an Actor or a Creator. We eventually see it as an IoT object which carries more than one kind of agency. Indeed, we like to think that the different kind of agency are different flavors that can be shifted according to the situation or the context. When a bike becomes a partner, there is a continuous dialogue happening between the bike and its user and the bike moves on a spectrum between collector and creator. That’s why we state that this continuum is affected by the bikes ultimate goal.

Lessons learned 1: Get yourself a herd!
Inspired by nature and animal behaviors, we see significant potential in herd behavior, which describes how individuals in a group can act collectively without centralized direction. It is a behavioral concept that comes from nature, which lately has been used in complex mathematical models and algorithms (Howarth, 2018; Programmable Robot Swarms. 2018). We would like to take the herd behavior augmented with technology in order to spark the feeling of community amongst citizens. To increase safety and the sense of safety. As Hoffer (1995) states: “When people are free to do as they please, they usually imitate each other”. Further, herd behavior describes various social situations in which individuals are strongly influenced by the decisions of others (Asch, 1956). This influence could be turned into strong civic behaviors in the form of mutual assistance and collaborative work towards a common goal. In a world where technology can create distance between people, IoT objects could bring people together using a herd behavior tactics.

Lessons learned 2: Bike knows best what is good for you
We argue that in order to create a partnership between user and bike able to care for its user wellbeing, the bike will have to be equipped with AI in order to be more empathetic. As Rosalind Picard (2000) argued in Affective Computing, emotion is not just an important tool for humans (and other animals), but also for computers and suggests that a truly intelligent system, artificial or otherwise, cannot be implemented without emotional mechanisms. Pamela Pavliscak (2018) argues that for AI and virtual assistants, to make the most positive impact, they’ll need to know how to understand and behave within the framework of our very human emotional cues. When developing algorithms, the machine learning experts need to think about AI in terms of human challenges rather than solely on the technical milestones to serve and augment the human experience. When AI gains ‘empathy,’ and we allow our physiological and emotional states to be observed and understood, the systems can be trained to know how we feel and how to respond appropriately, resolving in better partnership between human and IoT object. Hence our bike will know us much better, behaving ever more like a trusted friend. Moreover, designers should also take into account and design for different personality types. As for example a study of Richter and Salvendy (1995) argues that people interpret software as having human- like personalities, and perform better when presented with interfaced matching their personality: “introverted users performed faster with introverted software interfaces than with the extroverted interfaces”. Lastly, in terms of AI and transportation Ben Bland (2018) mentioned: gradually increasing the empathic capability of the system will support the evolution of the transport experience towards one that is not only safe and comfortable but also delightful.

Lessons learned 3: Digital connection, offline affection
The current tendencies of meeting new people are moving away from the offline real-life contact into the fast-paced online world. As we see the bike as almost the only mean of transportation that will still allow for real-life offline social interaction, the bike would be an ideal tool or partner to help to practice and provide users with those interactions. Returning to the metaphor of a natural object and relation between humans and animals, who have the capability of using their instinct and can have a sense of trustworthiness, we believe the bike should possess the same qualities with meeting new people. In this way, the bike leverages the natural instinct of Mutual assistance: copying the way any entity in a herd would behave. If one bike of the group is having a problem such as accident, technical difficulty, or safety issue (in this case the problem does not necessarily have to be real and genuine) the other members of the community would be asked to help. Allowing bike to act as creator type of agency, in this case, requires the owner to develop a trust that the actions taken on his behalf will be done, with competence and tact.

Lessons learned 4: Who is your bike?
We argue that similarly as humans are not, all the same, the emotionally intelligent machines will develop different personalities and different perceptions of the world through an interaction with the user. Therefore the bike AI system will have to be designed in a way that allows for training. When a person gets himself a pet, he takes on the responsibility of treating him well and training him well, hence when in the future people will get a bike they will have to possess the same sense of responsibility towards the bike’s training and development of their mutual relationship. The ‘training’ or ‘learning’ aspects of the bike’s AI system will be a fundamental part of the experience of owning it. In order to create trust, the learning process has to be more transparent while also being personal.

The project was focused on a bike as an interesting and provocative example, but our findings can be generalized and describe how designers could relate to IoT objects in the future. We see personal assistants seamlessly moving across all the user’s services and devices. The dialogues between the user and the object will, therefore, have to be transparent, trustful and clear. The objects will have to allow users to disagree with their decisions at any moment and be able to take over to balance human and object agency. We agree that the objects do not necessarily have to have lots of anthropomorphic features as Christopher Noessel and Nathan Shedroff argue in their book ‘Make it so’ that autonomy is both powerful and risky to associate with anthropomorphism (human- like appearance). We need to leverage this innate desire to emotionally relate with AI, by making AI better at understanding us. Inspired by our preliminary exploration of the four vignette stories. We see three kinds of agencies (collector, actor, and creator) as a pragmatic spectrum layer on which we would like to propose extension inspired by the trends of social (Wang, Carley, Zeng & Mao, 2007) and affective (emotional) (Picard, 2000) computing. Given this prompt, we thought about emotional and social aspects of dialogues between agentic IoT objects and humans. We propose this tool for analyzing the objects with agencies. Those are just four examples, which are by no means extensive. We stress that this is by no means extensive definition and that much more work is needed.

Asch. E. (1956) Studies of independence and conformity: A majority of one against a unanimous majority. Psychological Monographs, pp. 70-79

Bland, B. (2018). Empathic AI: The Next Generation of Vehicles Will Understand Your Emotions – ReadWrite. Retrieved from https://readwrite.com/2018/01/18/ empathic-ai-next-generation-vehicles-will-understand-emotions/

Cila, N. & Smit, I. & Giaccardi, E. & Krose, B. (2017). Products as Agents: Metaphors for Designing the Products of the IoT Age. 448-459. 10.1145/3025453.3025797.

Farooq, U., & Grudin, J. (2016). Human-computer integration. Interactions, 23(6), 26-32. doi: 10.1145/3001896

Hoffer, E. (1955) The Passionate State of Mind. Harper & Row, New York

Howarth, D. (2018). Studio Drift’s swarm of drones illuminates Miami Beach. Retrieved from https://www.dezeen.com/2017/12/07/studio-drift-franchise- freedom-drone-swarm-performance-art-basel-miami-beach/

Pavliscak, P. (2018). Pamela Pavliscak (Change Sciences) on Emotionally Intelligent Machines | TNW Conference 2018 [Video File]. Retrieved from URL. https://www.youtube.com/watch?v=b7ivN4hVpRo&index=3&list=PL3_sP0zWU T12cEEltp15M7le03mzPU9HF&t=0s

Picard, R. (2000). Affective computing. Cambridge, Mass.: MIT Press

Richter, L. & Salvendy, G. (1995). Effects of personality and task strength on performance in computerized tasks. Ergonomics 38, 2: 281–291. https://doi. org/10.1080/00140139508925104

Shedroff, N. and Noessel, C. (2012). Make it so. Brooklyn, N.Y.: Rosenfeld Media.

Wang, F., Carley, K., Zeng, D., & Mao, W. (2007). Social Computing: From Social Informatics to Social Intelligence. IEEE Intelligent Systems, 22(2), 79-83. doi: 10.1109/mis.2007.41

Wellbeing Google (2018). Retrieved from https://wellbeing.google/