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Editor's Notes

• #2: Good afternoon. Welcome to The 5th International Conference on the Human Side of Service Engineering Me Md. Abul Kalam Siddike, a PhD candidate at the Graduate School of Knowledge Science, Japan Advanced Institute of Science and Technology I under the mentorship of Jim, and in collaboration with Kazuo Iwano, Prof Kazuyoshi Hidaka and Prof Youji Kohda tried to conceptualize wisdom service systems. However, today I would like to talk about ¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­¡­.
• #3: £±£®As we know that wisdom is the highest level decision making performance, acquired by gaining experience that can be applied in complex, conflict situations as well as interacting with other wise people. 2. In this research, we first time introduce and develop the framework of wisdom service systems and showed how appropriately designed cognitive mediators and sociometers harmoniously interact with people. 3. Finally, we concluded the paper with future research directions.
• #5: We human beings have limited life spans and limited cognitive capabilities as well as suffered bounded rationality in case of making decision. In addition, we human beings have to die after certain period of time that creates knowledge burden to our next generation. Futhermore, there is half life of intormation means the information is important in the morning that is not important in the evening. Finally, we are surrounded by data information and knowledge. So, in this situation it is very difficult to make a right decision. Therefore we need wisdom to cope with these situations.
• #7: Technologies are becoming more intelligent to augment people¡¯s capabilities as tools assistants collaborators and coach. Currently these are the technologies are augment people capabilities and in the near future it will help people more and more.
• #8: Traditionaly wisdom is the ability to make the best judgement for the common good. Wisdom is expert knowledge as well as the ability to use knowledge understanding and judgement to achieve a balance between individual and collective human values.
• #12: In this wisdom service systems there are two parts: people/objects and cognitive mediators. Cognitive mediators have the might power to generate insights from trillions of unstructured and structured data, process the data and provide precise recommendations that are termed as artificial wisdom. On the other hand, people have their own wisdom termed as human wisdom that is acquired by sensing the real world environment, using knowledge and experiences. In this way, people and machine collaborate harmoniously and generate win-win value cocreation for indiviuals and the common good.
• #13: This is our proposed wisdom service system process in which people have CMs, equipped with sociometers to help them build better models of the user, themselves, the world and the task at hand. Blue dots indicate the real world people objects and the environments. Yellow dots are metrics observed by socio meters and green dots indicate appropriate options generated my the CMs.
• #14: Tradionally people interact with people and objects of the real world to understand them and their situations, context and cultre. People actuate the situations, context and culture by visiting the real world. But in our proposed wisdom service systems, sociometers (sensors/agents) able to contextualize human communication behavior through the trusted communication channels. In addition, cognitive mediators are also able to observe trillions of unstructured data related to human and machine.
• #18: Finally we propose a step by step iterative wisdom decision process. In the first step, we have to figure out the common good and how we can measure the coomn good of the society, indiviudals, communities and machines. In order to understand social good or