<p>Most people would agree that privacy is a civil right, and that we should not be deprived of this civil right for other than legitimate reasons. The difficulty lies instead in how to decide where the legislative boundary should be drawn for the right to privacy, in order to protect the individual from an undue intrusion of his privacy. There are a number of areas where the right to privacy comes in conflict with opposite interests. One of these areas is credit report. In this master thesis the author discusses questions as, what is the meaning of the word privacy, and whether the protection of privacy is sufficient in the legislation concerning credit report? Also a comparative study of the Swedish and the English regulation is performed. The object of this thesis is to analyze to what extent the legislator takes the right to privacy into consideration in the legislation concerning credit report. The author also investigates the possibilities to change the legislation in effort to enhance the protection of privacy. The thesis shows, that today there is a protection of privacy in connection to the processing of personal data, but also points out the need to review this protection and also to extend it to other areas, which are not connected with processing of personal data.</p>

Most people would agree that privacy is a civil right, and that we should not be deprived of this civil right for other than legitimate reasons. The difficulty lies instead in how to decide where the legislative boundary should be drawn for the right to privacy, in order to protect the individual from an undue intrusion of his privacy. There are a number of areas where the right to privacy comes in conflict with opposite interests. One of these areas is credit report. In this master thesis the author discusses questions as, what is the meaning of the word privacy, and whether the protection of privacy is sufficient in the legislation concerning credit report? Also a comparative study of the Swedish and the English regulation is performed. The object of this thesis is to analyze to what extent the legislator takes the right to privacy into consideration in the legislation concerning credit report. The author also investigates the possibilities to change the legislation in effort to enhance the protection of privacy. The thesis shows, that today there is a protection of privacy in connection to the processing of personal data, but also points out the need to review this protection and also to extend it to other areas, which are not connected with processing of personal data.

The field of explainable artificial intelligence (XAI) has gained momentum in recent years following the increased use of AI systems across industries leading to bias, discrimination, and data security concerns. Several conceptual frameworks for how to reach AI systems that are fair, transparent, and understandable have been proposed, as well as a number of technical solutions improving some of these aspects in a research context. However, there is still a lack of studies examining the implementation of these concepts and techniques in practice. This research aims to bridge the gap between prominent theory within the area and practical implementation, exploring the implementation and evaluation of XAI models in the Swedish credit scoring industry, and proposes a three-step framework for the implementation of local explanations in practice. The research methods used consisted of a case study with the model development at UC AB as a subject and an experiment evaluating the consumers' levels of trust and system understanding as well as the usefulness, persuasive power, and usability of the explanation for three different explanation prototypes developed. The framework proposed was validated by the case study and highlighted a number of key challenges and trade-offs present when implementing XAI in practice. Moreover, the evaluation of the XAI prototypes showed that the majority of consumers prefers rulebased explanations, but that preferences for explanations is still dependent on the individual consumer. Recommended future research endeavors include studying a longterm XAI project in which the models can be evaluated by the open market and the combination of different XAI methods in reaching a more personalized explanation for the consumer. / Under senare år har antalet AI implementationer stadigt ökat i flera industrier. Dessa implementationer har visat flera utmaningar kring nuvarande AI system, specifikt gällande diskriminering, otydlighet och datasäkerhet vilket lett till ett intresse för förklarbar artificiell intelligens (XAI). XAI syftar till att utveckla AI system som är rättvisa, transparenta och begripliga. Flera konceptuella ramverk har introducerats för XAI som presenterar etiska såväl som politiska perspektiv och målbilder. Dessutom har tekniska metoder utvecklats som gjort framsteg mot förklarbarhet i forskningskontext. Däremot saknas det fortfarande studier som undersöker implementationer av dessa koncept och tekniker i praktiken. Denna studie syftar till att överbrygga klyftan mellan den senaste teorin inom området och praktiken genom en fallstudie av ett företag i den svenska kreditupplysningsindustrin. Detta genom att föreslå ett ramverk för implementation av lokala förklaringar i praktiken och genom att utveckla tre förklaringsprototyper. Rapporten utvärderar även prototyperna med konsumenter på följande dimensioner: tillit, systemförståelse, användbarhet och övertalningsstyrka. Det föreslagna ramverket validerades genom fallstudien och belyste ett antal utmaningar och avvägningar som förekommer när XAI system utvecklas för användning i praktiken. Utöver detta visar utvärderingen av prototyperna att majoriteten av konsumenter föredrar regelbaserade förklaringar men indikerar även att preferenser mellan konsumenter varierar. Rekommendationer för framtida forskning är dels en längre studie, vari en XAI modell introduceras på och utvärderas av den fria marknaden, dels forskning som kombinerar olika XAI metoder för att generera mer personliga förklaringar för konsumenter.