In today's society, the rapid progression of digitization has led to the automation of various facets of human existence. This transformation has been facilitated by the utilization of algorithms, which are instrumental in driving efficient and effective automated processes. These algorithms have also found widespread adoption in the public sector, where they are employed to streamline and optimize various tasks and operations. The integration of algorithms in the public sector has brought about significant advancements in areas such as predictive policing, social welfare allocation, and healthcare.

However, the use and development of these automated processes were subjected to concerns from the public about privacy, bias, accountability, and transparency. Since these concerns are mainly coming from citizens, their involvement in the process of developing algorithmic systems can potentially be of help.

We explore the potential of participatory AI in marginalized communities as a means of obtaining valuable input from citizens regarding the development of these algorithmic systems employed by the public sector. One Piece of our approach involves hosting discussions in local community centers in marginalized neighborhoods. Our focus is on dilemmas that are relevant to algorithm design and evaluation decisions, and we frame these dilemmas in various ways, including forms that may not directly relate to societal impact, but are understandable for laypeople. Our key findings suggest that involving marginalized citizens can bring valuable perspectives and insights that are otherwise ignored. By incorporating public perspectives into algorithm development, we can promote inclusive decision-making processes and ensure that algorithms align with community values.

ScenWise is an innovative company that specializes in data science revolving around traffic management. ScenWise strives to use the newest and best technologies and practices when it comes to web applications, data science and traffic management. The reason for this is that they provide tools to analyse and visualise a variety of situations that occur in traffic management. One such tool is SmartRoads 1.0, which allows users to analyse traffic data and situations via a web application. Unfortunately SmartRoads 1.0 does not perform as desired. Additionally, ScenWise itself has the problem of not being able to integrate previously made products by student groups into their own existing products. During the research aimed to resolve these problems another issue arose; the software development life cycle of ScenWise is very lacking. Research on the SmartRoads 1.0 performance problem showed that the bottleneck of its performance is due to the front-end. The outdated SmartRoads 1.0 front-end was thus replaced with a new and better SmartRoads 2.0 front-end. The integration problem and development life cycle problem are both addressed in the Longterm evolution (LTE) design found in appendix I. This LTE design contains the architecture migration plan. This plan will transform the current software architecture to a Service-oriented architecture (SOA) providing a solution for the current integration problems. A result of the first steps of this architecture migration plan is the Application Programming Interface (API) Gateway, which has been implemented in the aforementioned SmartRoads 2.0. Next to the migration plan, guidelines for ScenWise to improve their software development life cycle are elaborated in the LTE design. In this report the identified problems, their solutions and executions are explained, discussed and evaluated.

Blockchain is a technology that is in use increasingly. Although owing its common use to the cryptocurrencies there is more to the blockchain technology than just the monetary use. One of these uses is by smaller groups of participants under the control of a central authority, for instance at a company. Such private blockchains use permissioned blockchain consensus algorithms as the participants need the permission of the authority to be able to join the system. This paper will give an overview of the blockchain technology, investigate permissioned and permissionless blockchain, and focus on permissioned blockchains to analyze it in terms of, e.g. trust models between the nodes, incentives, number of nodes & parties involved, and scalability regarding the number of transactions.