PRE2020 3 Group8: Difference between revisions
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| Machine Learning || Lulof & Edwin | |||
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| User Interface || Morris | |||
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| USE-part || Fanni & Emi | |||
Machine Learning: Lulof & Edwin | Machine Learning: Lulof & Edwin |
Revision as of 20:52, 28 February 2021
Group description
Abstract
A pure software end-user application that supports people in their need to socialize while motivating self-improvement. Anthropomorphism is intentionally used to increase user commitment and experience. Machine learning techniques are used to process user's data and provide feedback, and to facilitate the anthropomorphized interface.
Conceptualized Idea
Hypothetical idea: A webpage/application, that will motivate its users into a more (mentally) healthy way of living life. The user can put in any preferences to be motivated on and set its own goals. Numeric data of the user will be tracked in a communicative way rather than filling in forms, is stored and compared to older data, and reflection of this comparison will be given in a personalized way back to the user.
On this page, the concept of this motivating coaching system will be presented. This system combines specialized monitored and self-measured data from its user with individual and reference knowledge to give its users an overview (and recommendations). The system will keep track of one’s daily life structure, translate and summarize the numerical input into recommendations in a continuous personalized motivating coaching dialogue taking into account the needs and preferences of each user individually.
Members
Name | Student number | Department |
---|---|---|
Edwin Steenkamer | 1006712 | Computer Science |
Emi Kuijers | 1227154 | Psychology & Technology |
Fanni Egresits | 1316400 | Psychology & technology |
Morris Boers | 1253107 | Computer Science |
Lulof Pirée | 1363638 | Computer Science |
Main Task division
Task | Members | |
---|---|---|
Machine Learning | Lulof & Edwin | |
User Interface | Morris | |
USE-part | Fanni & Emi
Machine Learning: Lulof & Edwin User Interface: Morris User-centered design: Emi & Fanni
Logbook See the page logbook_group_8 Problem statement and objectivesProblem Statement Often loneliness is associated with elderly people living unintentionally in social isolation due to unfortunate circumstances. However, the reality is that loneliness is experienced by all ages and almost all humans. [1] Humans are social animals [2] ), and we humans influence each other by merely existing together. Loneliness is seen as a severe public health issue due to its association to increased risk of morbidity and mortality [3]. A study by Luhmann & Hawkley [4] suggests that the prevalence rates of loneliness are highest for young adults (<30 years). Loneliness can best be stated as the perceived discrepancy between the desired amount and the actual perceived amount and quality of social communication and relationships. [5] Both physical, as well as mental health and overall well-being, can suffer from this. With less social relationships, less comparison and facilitation from others will influence a person's behaviour and motivation, leading to a decrease in general motivation. Due to the COVID-19 pandemic restrictions, many people are forced to stay at home [6]. These restrictions also cause personal trainers, dieticians, and other employees that help people engage in a more healthy lifestyle to be unable to work with the normal citizen. However, at this very moment, people must maintain a healthy lifestyle. Exercising and healthy lifestyles increase at the beginning of covid. After the restrictions aimed at minimizing the risk of local transmission of SARS-CoV-2 got stricter, it is more likely that this leads to reductions in physical activity. [7] Therefore, it is necessary to find other ways to externally motivate people to maintain a healthy lifestyle independent of other people's motivation. Besides the external motivation that humans get from other people, we also can motivate ourselves. People have a very complex decision-making process, and not always the rationally right decision is chosen for a particular event or action. Heuristics are used as a mental shortcut to make decisions and are simplifications. These can occasionally lead to systematic flaws and errors, which are deviations from the normative decision-making model, known as biases. One of these biases is overconfidence, a bias during interpreting and assessing information, the second step in the decision-making process. People are often biased in their confidence concerning the hypothesis they have brought in their working memory, believing that they are more correct more often than they actually are. For example, if people would have to report how much they ran during a jog, they will most likely unconsciously overestimate themselves. [8] There is also the psychological phenomenon called planning fallacy, where people underestimate the time it will take to complete a future task. [9] Combining this will optimism bias, which explains our tendency to overestimate the likelihood of experiencing positive events and underestimate the occurrence of negative events. The human mind can sometimes be a dangerous decision-making toolbox to rely on. Using this system, the data gathered from the user will serve as a toolbox. They can be seen as an extended memory that provides the user with statistically true information so decisions will be made taking into account actual statistics, rather than only the estimations and thoughts humans have left of past events. In this way, users will be calibrated towards the truth and rely less on decisions made while possibly be biased.
Needs Two needs arise from the problem statement above. Firstly, to reduce biases in the decision-making process due to falsely remembered memories, people need to be provided with an objective summary of their past events. Secondly, the net amount (both intensity and frequency) of negative emotions and lack of motivation experienced due to a lack of social interaction must be decreased to fill the lack of external motivation.
GoalsTo reach the needs stated above, the software application has two main requirements:
Beyond the scopeThe following features are probably valuable additions to the product, but they are beyond the scope of what can be achieved in one quartile:
User descriptionPrimary Target AudienceThe application will be designed to be used by technology-oriented adults (mainly focusing on minus 30 years), who interact with computers and smartphones on a daily basis. The main target for this system are students who spend most of their time alone in their student accommodation. This can both be due to contemporary COVID-19 pandemic stay-at-home regulations, but also for users who live abroad for a short time, for example. The focus will also be on people who want to improve their daily structure and overall well-being in any way but have no idea what would be best for them. Therefore, the system will provide its user with objective data to discover clear behavioural patterns that might have lead to certain events. Users are more extensively described at the user analysis-section. %refer to user analysis on the wiki. If wiki still unavailable, delete sentence. The application will likely not be suitable for children due to its design constraints, or for elderly people who are not technology-oriented and adapted to new technologies. User requirementsTo engage positive behaviour in people using an AI application, an accessible and practical user-interface is critical. An irresponsive, unintuitive or unfinished interface may discourage users from using the application, let alone be positively nudged by the application. Users need to perceive social engagement and be positively motivated by the system to change its behaviour. Approach, milestones and deliverablesMilestonesThe project milestones are divided into three main parts: Implementing a human-centered design approach, the system's economical value and the software milestones. User-centered DesignTarget User-perspective: Human-Centered design
Potential Ethical Threats
Comparative advantage, product innovation and improving Quality of life of its users
Economical perspectiveEconomical valueIn this section, the preferences of the given users are described that determine the economical value of our product. This can be defined by a survey/questionnaire or by market-research.The economical value of the product is the benefit that the costumers receive from the usage of the AI software. In the case of the specific device we develop, this could be the motivation, joy, health,fun..etc. This value is not an objective characteristic, but rather subjective, since it differs by its user's needs and expectations. Because of this diversity, our proposal is a survey conduction before the start of the program to collect enough information for a fully personalized service. On this way, the economical value to the customers (EVC) can be determined and the market price of the software can be quantified. \\ After the market-research, we plan to create a competitor-analysis which helps us to see which additional tools we need to implement and what the essence and uniqueness our product could be compare to our competitors. This step will also help us to narrow or extend the list of stakeholders we want to approach. This information will enable us to create a value network,a cash-flow for the upcoming semester and to develop a business plan. Stakeholder analysisA stakeholder analysis of an issue consists of finding the equilibrium of different demands from different perspectives. The stakeholder map shows which stakeholders will be considered, moreover, it will help to identify the interests and mechanisms of the stakeholders to influence other stakeholders, key people, competitors and to reduce potential risk. The center is the online platform in the center which connects every stakeholder and provides access to the AI assistant. The main target group is the users, described above. With the marketing, the first targeting would reach the bigger associations, companies or universities, furthermore individuals who personally are interested. The idea is to include specialists, such as dietitians, psychologists and personal trainers. The data analysts are mainly members in our current team who could work in collaboration with the specialist as an exchange in knowledge and expertise. Our team would provide referencing to the specialists by our customers in case the users wish to use the help of physical specialists, e.g. receive a proper diet plan from a dietitian, set a bigger goal for weight loss with a personal trainer or get better help from a psychologist. The help of the specialists could be included in the watch. The collaboration with bigger companies e.g. IT companies where the employees are required to work long with a busy schedule or to do night-shifts would give an opportunity to help to maintain health goals for the employees. Universities could also profit from the services and help the well-being of their students and employees. Business plan and development
Software milestonesStartup
Rough Scattered Prototype
Connected Prototype
Rough Complete Prototype
Literature Review (separate file)Due to bugs in the installation of the LaTeX engine of the wiki, mathematical expressions cannot be shown here. See the following Overleaf file for the literature review, and references: Literature review Overleaf file. OverviewWork-in-progress-pageSee the page WIP group 8 for an actively edited file of notes. User guideTODO... Software documentationTODO... References
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