Added ethical and legal issues

report/report.tex

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     	% This section should contain an introduction to the problem aims and obectives (0.5 page)
 
 		This project is to design and create a new software as a service platform, where users with no experience in machine learning, data analysis could create machine learning models to process their data.
-		In this project the platform will be scoped to image classification, with the ability to be updated later with more model types.
+		In this project, the platform will be scoped to image classification, with the ability to be updated later with more model types.
 		As an easy-to-use platform needs to be able to handle: image uploads, processing, and verification; model creation, management, and expansion; and image classification.
 
 		This report will do a brief analysis of current image classification systems, followed by an overview of the design of the system, and implementation details. The report will finish with analysis of legal, ethical and societal issues, and evaluation of results, and objectives.
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 		\subsection{Project Structure}
 			The report on the project shows the development and designs stages of the project. With each section addressing a part of the design and development process.
 
-			\begin{longtable}{| r | r |} 
-				\hyperref[sec:introduction]{Introduction}                        & The introduction section will do a brief introduction of the project and it's objectives \\
-				\hyperref[sec:lit-tech-review]{Literature and Technical Review} & The Literature and Technical Review section will introduce some current existing projects that are similar to this one, and introduce some technologies that can be used to implement this project \\
+			\begin{longtable}{rp{0.45\textwidth}pr{0.45\textwidth}} 
+				\hyperref[sec:introduction]{Introduction}                       & The introduction section will do a brief introduction of the project and its objectives. \\
+				\hyperref[sec:lit-tech-review]{Literature and Technical Review} & The Literature and Technical Review section will introduce some current existing projects that are similar to this one, and introduce some technologies that can be used to implement this project. \\
+				\hyperref[sec:sanr]{Service Analysis and Requirements}          & This section will analyse the project requirements. The section will define design requirements that the service will need to implement to be able to achieve the goals that were set up. \
+				\hyperref[sec:sdai]{Service Design and Implementation}          & This section discusses transforming the requirements defined in the previous section and implementing them, to obtain a working application. \\
+				\hyprref[sec:lsec]{Legal, Societal, and Ethical Considerations} & This section will cover potential legal societal and ethical issues that might arise from the service and how they are mitigated.\\
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 		\subsection{Conclusion}
-			The technical review of current systems reveal that there are current systems that exist that can perform image classification tasks, but they are not friendly in ways to easy expand currently existing models.
+			The technical review of current systems reveal that there are current systems that exist that can perform image classification tasks, but they are not friendly in ways to easily expand currently existing models.
 
 			The current methods that exist for image classification seem to have reached a classification accuracy and efficiency that make a project like this feasible.
 
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-    \section{Service Analysis and Requirements}
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+    \section{Service Analysis and Requirements} \label{sec:sanr}
 		Understanding the project that is being built is critical in the software deployment process, this section will look into the required parts for the project to work.
 
 		As a SaaS project, there are some required parts that the project needs to have:
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 			Repeated tasks should be sent to the same server to optimize the usage of the resources, as this would improve the efficiency of the service by preventing, for example, reload of data.
 			For example, sending a training workload to a server that more GPU resources available to it while allowing slower GPU servers to run the models for prediction.
 
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 			The service should also keep tract of the space available to it.
 			The service must decide which images, that it manages, to keep and which ones to delete.
 			It should also keep track of other services images, and control the access to them, and guarantee that the server that is closeted to the recourses is that has priority on tasks related to those recourses.
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 			The last kind of data that the service has to keep track of are model definitions and model weights.
 			These can be sizable files, which makes it important for the system to distribute them precisely, allowing the files to be closer to the servers that need them the most.
 
+		\subsection{Conclusion}
+			This section shows that there are requirements that need to be met for the system to work as indented. These requirements range from usability requirements, to system-level resource management requirements.
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+			The service needs to be easy to use by the user, while being able to handle loads from both the website and API requests.
+			The service requires the ability to be able to scale up to the loads that is being provided with and keep track and manage resources that the user or the service created.
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+			It also requires keeping track of computational resources that are available to it, so it does not cause deadlocks. For example, using all of its GPU recourses to train a model while there are classification tasks to be done.
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+			The next section will go thought the process of the implementation of an application that implements a subset of this design requirements, with some limitations that will be explained.
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 	\pagebreak
 
-	\section{Service Design and Implementation}
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+	\section{Service Design and Implementation} \label{sec:sdai}
 
 		This section will discuss the design of the service.
 
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 			During the training process, the TP needs to cache the dataset being use.
 			This is because to create one model, the service might have to generate and train more than one model, during this process, if the dataset is not cached then time is spent reloading the dataset into memory.
 
-	\pagebreak
-    \section{Legal and Ethical Issues}
+		\subsection{Conclusion}
+			This section discussed the design and implementation specifications for the system.
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+			While there were some areas where the requirements were not met completely, due to scope problems, the implementation allows for the missing designed sections to be implemented at a later time.
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+			The implementation follows the requirements with the adjusted scope.
+			The results of the implementation will be tested in a future section.
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 	\pagebreak
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+    \section{Legal, Societal, and Ethical Considerations} \label{sec:lsec}
+		This section will address possible legal, societal, ethical issues that might arise from the deployment of the software being designed.
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+		The Self-Assessment for Governance and Ethics (SAGE) form has addressed, and it is submitted along with the report.
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+		\subsection{Legal Issues}
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+			Legal issues can occur due to the data being stored by the service.
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+			The service collect, the least amount of sensitive information, from the users who directly use the service.
+			That data that is collected while being sensitive is required to be able to authenticate the user, such as name, email, and password.
+			To safeguard that information, the system will be using industry standards to guarantee data security of that data.
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+			Legal issues might occur due to image uploaded images. For example, those images could be copyrighted, or the images could be confidential. The service is designed to provide ways to allow users to host their images without having to host the images itself moving the legal requirement to the management of the data to the user of the system.
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+			\subsubsection{GDPR}
+				The General Data Protection Regulation (GDPR) (GDPR, 2018) is a data protection and privacy law in the European Union and the European Economic Area, that has also been implemented into British law.
+				The main objective of the GDPR is to minimise the data collected by the application for purposes that are not the used in the application, as well as giving users the right to be forgotten.
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+				The application collects only personal data need to authenticate the user, and data that is generated during the normal usage of the application.
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+				All the data that is related to user can be deleted.
+				The system will prevent any new work that is related with the data, that was requested to be deleted.
+				Once the there is no more work that requires the data being done, the system will remove all relevant identifiable references to that data.
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+			\subsection{Social Issues}
+				The web application was designed to be easy to use and there tries to consider all accessibility requirements.
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+				% TODO talk about this
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+				% The service itself could raise issues of taking jobs that are currently done by humans.
+				% This is less problematic as time has shown that the jobs just change, instead of manually classifying the images, the job transforms from the classifying all the images that are needed to maintain and verifying that the data being input to the model is correct.
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+			\subsection{Ethical Issues}
+				While the service itself does not raise any ethical concerns. The data that the service will process could raise ethical complications.
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+				For example, if the service gets acquired by a company that also wants to use the data provided to system for other reasons.
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+	\section{Evaluating the Service}
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+	\pagebreak
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     \section{Results} % TODO change this
 
 		As it was stated during the introduction, this project has multiple objectives.