Background: E-commerce is widespread in today’s shopping routines and conversational commerce (CC) as an expansion, aims at integrating customers and businesses on a whole new level. Through the application of chatbots fueled by artificial intelligence, a more personal and individual way of remote shopping is offered. Purpose: Our research question What potential attributes of AI-fueled CC applications and their possible inherent characteristics are determining the willingness to use them and to what extent, in the context of digital natives living in Sweden and Germany? aims at identifying the demanded attributes of conversational commerce from a consumer perspective. Method: We facilitate a quantitative questionnaire with 118 valid answers to administer a traditional full-profile conjoint analysis. Conclusion: Our results indicate that German digital natives deem a CC application’s behavior as the most important attribute, followed by payment method, personality and communication form (voice or text). The Swedish digital natives however, attach the most importance to the payment method, followed by behavior, communication form and personality. Both have in common that they prefer a rather passive behavior over being actively approached, a personality that is balanced between humor and seriousness and text-based communication over voice. A difference is the Swedish preference for direct in-app payment while German digital natives would select a redirection to a secondary payment provider (e.g. PayPal).

This project includes an implementation of an intelligent voice recognition assistant for Android where functionality on current existing applications on other platforms is compared. Until this day, there has not been any good alternative for Android, so this project aims to implement a voice assistant for the Android platform while describing the difficulties and challenges that lies in this task.

To order pick-up food by using your computer or phone is nothing new. Food delivery companies such as FoodHero and Uber Eats along with many other around the world base their entire company idea around the food order and delivery process. For a company to stand out in such a vast market can sometimes be quite tricky. Sometimes your company needs a niche to stand out in the crowd. This project aims to create such a niche in an order system prototype based on voice-controlled systems and conversation. This prototype allows users to place food orders through only the use of natural speech and a voice assistant. The prototype utilizes products and services from both Amazon and Google to create the order system structure. The ordering system also takes advantage of the serverless architecture that both Amazon and Google provide. The end result of this project is a simple, convenient, and user-friendly prototype

Contemporary society is rapidly changing. The emergence of social inequalities and the use of new technologies to access communicates produce and exchange information among others deeply affects citizens and the complex interactions among citizens businesses and governments. This thesis explores how might technology in the future enable better communication with governments and higher participation of citizens in decision ma ing processes? It showcases a designerly way to approach this question while designing for interactions with an explicit intention of placing value in citizen participation in decision making processes with an aim towards plurality. The design outcomes showcase the possibility of employing technology to achieve greater levels of democratic citizen participation but that which would require major restructuring of government organisations and new ways of working with data.

Today voice recognition is becoming mainstream and nowadays it is also possible to include in individual smartphone apps. However, it has not previously been investigated for which tasks it is preferable from a usability perspective to use voice recognition rather than touch. In order to investigate this, a voice user interface was created for a smartphone radio application, which already had a touch interface. The voice user interface was also tested with users in order to improve its usability. After that, a test was conducted where the participants were asked to perform the same tasks using both the touch and voice interface. The time they took to complete the tasks was measured and the participants rated the experience of completing the task on a scale. Finally, they were asked which interaction method they preferred. For most of the tasks tested, the voice interaction was both faster and got a higher rating. However, it should be noted that in a case where users don’t have specific tasks to perform it might be harder for them to know what a voice controlled app can and cannot do than when they are using touch. Many users also expressed that they were reluctant to use voice commands in public spaces out of fear of appearing strange. These results can be applied to other radio/podcast apps and, to a lesser extent, app for watching TV series and playing music. / Röststyrningen blir vanligare och numera är den också möjligt att använda i individuella appar för smartphones. Det har dock inte tidigare undersökts för vilka uppgifter det ur ett användbarhetsperspektiv är att föredra framför pekskärmsinteraktion. För att undersöka det skapades ett röstinterface för en radiooch podcast applikation som redan hade ett pekskärmsinterface. Röstinterfacet testades också med användare för att förbättra dess användbarhet. Efter det gjordes ett test där deltagarna blev ombedda att utföra samma uppgift med både pekskärm- och röstinterface. Den tid de tog på sig uppmättes och deltagarna betygsatte upplevelsen av att utföra uppgiften på en skala. Slutligen blev de tillfrågade omvilken interaktionsmetod de föredrog. För de flesta av de testade uppgifterna var röstinteraktion snabbare och fick högre betyg. Det ska dock noteras att i fall då användaren inte har specifika uppgifter att utföra kan det vara svårare för dem att veta vad en röststyrd app kan och inte kan göra än när de använder pekskärm. Många användare uttryckte också att de var motvilliga till att använda röstkommandon i allmänna utrymmen av rädsla föratt verka underliga. Dessa resultat kan tillämpas på radio/podcast appar och, i mindre utsträckning, appar för att titta på TV-serier och spela musik.

Software developers and teams typically rely on source code and tasks management tools for their projects. They tend to depend on different platforms such as GitHub, Azure DevOps, Bitbucket, and GitLab for task-tracking, feature-tracking, and bug-tracking to develop and maintain their software repositories. Individually, developers may lose concentration when having to navigate through numerous screens consisting of various platforms to perform daily tasks. Additionally, while in meetings (non-virtual), teams are often separate from their machines and often would have to rely on pure recollection of the tasks and issues related to their work. This can delay the decision-making process and take away valuable focus hours of developers. Although there is usually one person with their laptop to guide the meeting and has access to the source code management tools, this can take a lot of time as they are not familiar with all the developers’ independent works. Therefore, a new tool needs to be introduced to help accelerate individual and team meetings’ productivity. In this paper, we continued the work on Robin, a voice-assistant built to answer questions regarding GitHub issues and source code management. Robin has the ability to answer questions in addition to completing actions on the behalf of the developer. This thesis presents Robin's abilities, architecture, and implementation while also examining its usability through a user study. Our study suggests that some people love the idea of having a conversational agent for software development. However, a lot more research and iterations must be done to fully make Robin give the user experience we imagined. In this thesis, we were able to set the foundation of this idea and the lessons that we learned.

Voice assistant technology on smartphones, smart speakers, or those on the wearable devices is one of the fastest-growing artificial intelligence applications in the market now. However, with the potential ethical issues related to the voice technology, it still has not been extensively covered in major markets such as Indonesia. Therefore, this study aims to explore Indonesians’ perception of voice assistant technology, mainly focusing on whether ethical concerns might play a role in their adoption and use of the technology. Firstly, the picture of the discussion about voice assistants and the possibilities of ethical issues is surrounding the technology in the Indonesian landscape by media is presented using Critical Discourse Analysis (CDA). The findings indicate that educational and informative material has a wider resonance compared to ethical concerns and the downsides received from the technology. Secondly, the study also explored the motivations to adopt and use the technology, focusing on whether ethical concerns might play a role in their perception of the technology, attitude, and experience toward voice assistants through semi-structured interviews. The data, then, was analyzed using the Technology Acceptance Model (TAM). It shows that the users who perceive the voice assistant useful or easy to use still use it to a varying extent. It indicates that TAM variables are not fully explaining the adoption of technology. Adding an ethical framework, we can see that most of the users do not have enough knowledge of the technology they use. It resonates with the portrayal of the subject in media. However, those who are unaware of or neglect the situation to adopt and use the technology still use voice technology influenced by peer pressure, their respect for authority, and other rationalization behavior. Meanwhile, mediation theory explores the influence of the human- technology relationship on the ethical behavior of the users. It also explains that the relation between technology and users is an alterity relationship.

Voice User Interfaces (VUI) are rapidly gaining popularity, revolutionizing user interaction with technology through the widespread adoption in devices such as desktop computers, smartphones, and smart home assistants, thanks to significant advancements in voice recognition and processing technologies. Over a hundred million users now utilize these devices daily, and smart home assistants have been sold in massive numbers, owing to their ease and convenience in controlling a diverse range of smart devices within the home IoT environment through the power of voice, such as controlling lights, heating systems, and setting timers and alarms. VUI enables users to interact with IoT technology and issue a wide range of commands across various services using their voice, bypassing traditional input methods like keyboards or touchscreens. With ease, users can inquire in natural language about the weather, stock market, and online shopping and access various other types of general information.However, as VUI becomes more integrated into our daily lives, it brings to the forefront issues related to security, privacy, and usability. Concerns such as the unauthorized collection of user data, the potential for recording private conversations, and challenges in accurately recognizing and executing commands across diverse accents, leading to misinterpretations and unintended actions, underscore the need for more robust methods to test and evaluate VUI services. In this dissertation, we delve into voice interface testing, evaluation for privacy and security associated with VUI applications, assessment of the proficiency of VUI in handling diverse accents, and investigation into access control in multi-user environments. We first study the privacy violations of the VUI ecosystem. We introduced the definition of the VUI ecosystem, where users must connect the voice apps to corresponding services and mobile apps to function properly. The ecosystem can also involve multiple voice apps developed by the same third-party developers. We explore the prevalence of voice apps with corresponding services in the VUI ecosystem, assessing the landscape of privacy compliance among Alexa voice apps and their companion services. We developed a testing framework for this ecosystem. We present the first study conducted on the Alexa ecosystem, specifically focusing on voice apps with account linking. Our designed framework analyzes both the privacy policies of these voice apps and their companion services or the privacy policies of multiple voice apps published by the same developers. Using machine learning techniques, the framework automatically extracts data types related to data collection and sharing from these privacy policies, allowing for a comprehensive comparison. Next, researchers studied the voice apps' behavior to conduct privacy violation assessments. An interaction approach with voice apps is needed to extract the behavior where pre-defined utterances are input into the simulator to simulate user interaction. The set of pre-defined utterances is extracted from the skill's web page on the skill store. However, the accuracy of the testing analysis depends on the quality of the extracted utterances. An utterance or interaction that was not captured by the extraction process will not be detected, leading to inaccurate privacy assessment. Therefore, we revisited the utterance extraction techniques used by prior works to study the skill's behavior for privacy violations. We focused on analyzing the effectiveness and limitations of existing utterance extraction techniques. We proposed a new technique that improved prior work extraction techniques by utilizing the union of these techniques and human interaction. Our proposed technique makes use of a small set of human interactions to record all missing utterances, then expands that to test a more extensive set of voice apps. We also conducted testing on VUI with various accents to study by designing a testing framework that can evaluate VUI on different accents to assess how well VUI implemented in smart speakers caters to a diverse population. Recruiting individuals with different accents and instructing them to interact with the smart speaker while adhering to specific scripts is difficult. Thus, we proposed a framework known as AudioAcc, which facilitates evaluating VUI performance across diverse accents using YouTube videos. Our framework uses a filtering algorithm to ensure that the extracted spoken words used in constructing these composite commands closely resemble natural speech patterns. Our framework is scalable; we conducted an extensive examination of the VUI performance across a wide range of accents, encompassing both professional and amateur speakers. Additionally, we introduced a new metric called Consistency of Results (COR) to complement the standard Word Error Rate (WER) metric employed for assessing ASR systems. This metric enables developers to investigate and rewrite skill code based on the consistency of results, enhancing overall WER performance. Moreover, we looked into a special case related to the access control of VUI in multi-user environments. We proposed a framework for automated testing to explore the access control weaknesses to determine whether the accessible data is of consequence. We used the framework to assess the effectiveness of voice access control mechanisms within multi-user environments. Thus, we show that the convenience of using voice systems poses privacy risks as the user's sensitive data becomes accessible. We identify two significant flaws within the access control mechanisms proposed by the voice system, which can exploit the user's private data. These findings underscore the need for enhanced privacy safeguards and improved access control systems within online shopping. We also offer recommendations to mitigate risks associated with unauthorized access, shedding light on securing the user's private data within the voice systems. / Computer and Information Science

Les assistants vocaux ont mis au jour une nouvelle manière pour l’humain d’interagir avec les technologies en n’utilisant que la voix. Une technologie qui est également évolutive et interactive grâce à l’intelligence artificielle. Nous verrons que les caractéristiques techniques et logicielles les composant concourent à une collecte massive de renseignements personnels par les entreprises. L’imprécision des politiques de confidentialité, l’absence d’information sur le mode de fonctionnement, l’imperfection du traitement automatique du langage naturel (ci-après le « TALN ») caractérisée par les faux positifs et les difficultés inhérentes à l’exercice par l’individu de certains de ses droits tendent à limiter l’effectivité des différentes lois existantes à l’assistant vocal. En outre, la possibilité pour plusieurs personnes d’interagir avec l’objet ainsi que son absence d’autonomie tendent à compliquer l’application des régimes de responsabilité civile, dont celui résultant du fait des biens. Cette apparition récente de l’assistant vocal n’a pour l’heure pas permis au juge de se prononcer pour faire évoluer les jurisprudences relatives au droit à la vie privée, à la protection des renseignements personnels et à la responsabilité civile. Celles déjà existantes ne semblent plus être adaptées à ce contexte technologique autour de l’assistant vocal, et plus généralement autour de la voix. C’est ainsi que le test de Oakes, permettant de déterminer le caractère raisonnable d’une violation des droits et libertés énoncés dans la Charte canadienne, repris pour être appliqué à la LPRPDE, apparaît comme étant inadapté à ce nouveau contexte technologique. Enfin, le manque de pouvoirs conférés aux autorités compétentes représente un obstacle majeur dans le suivi de l’application des règles de droit. / Voice assistants bring a new way for humans to interact with technology by only using their voice. Scalable and interactive technology thanks to artificial intelligence. We will see that the technical and software characteristics of voice assistants contribute to a massive collection of personal information by companies. The imprecision of confidentiality policies, the absence of information on the mode of operation, the imperfection of the Natural Language Processing characterized by false positives and the difficulties inherent in the exercise by individuals of some of their rights contribute to the mismatch between voice assistants and various existing laws. In addition, the possibility for people to interact with the object as well as its lack of autonomy tend to complicate the application of civil liability regimes, including that resulting from the act of thing. This recent appearance of voice assistants has so far not giving judges the possibility to rule on the right to privacy, protection of personal information and civil liability. Current case law doesn’t seem to be well adapted to the technological context around the voice assistant, and more generally the voice. The Oakes test, which was design to determining the reasonableness of a violation of the rights and freedoms set out in the Canadian Charter, appears to be unsuited to this new context. We will see that the lack of powers conferred on the competent authorities represents a major obstacle in monitoring the application of the rule of law.

Utvecklingen inom fordonsindustrin går mot autonoma fordon, och som effekt av det behöver både säkerhet och samhällets acceptans öka. För att öka säkerheten i autonoma fordon behöver föraren vara situationsmedveten, vilket kan uppnås genom en röstassistent i fordonet. Om säkerheten skulle öka skulle sannolikt även människors tillit och därav samhällets acceptans öka. Studier pekar på att olika egenskaper så som rösttyp hos röstassistenter kan ha en effekt på förares situationsmedvetenhet och tillit. Denna studie ämnar således att undersöka huruvida en feminin eller maskulin röst hos röstassistenter påverkar förares situationsmedvetenhet och upplevda tillit till autonoma fordon. För att ta reda på detta genomfördes en experimentell studie där deltagare befann sig i en bilsimulator av ett autonomt fordon som simulerade körscenarier. Deltagarna var uppdelade i två grupper där varje grupp fick uppleva en typ av röstassistent, antingen med feminin eller maskulin röst. Deltagarna fick uppleva körscenarier där varningssituationer i olika allvarlighetsgrader uppstod, där de fick fatta beslut kring hur de hade hanterat varningssituationen. I samband med körscenarierna utfördes tre olika datainsamlingar bestående av intervju och enkäter. Resultatet av studien påvisar ingen signifikant eller utmärkande skillnad vad gäller upplevd tillit mellan grupper. Resultatet indikerar inte heller någon utmärkande skillnad mellan gruppernas situationsmedvetenhet. Det finns marginell skillnad mellan grupperna, där gruppen som upplevde feminin röst hade både högre upplevd tillit och situationsmedvetenhet. Slutresultatet i denna studie visar att området behöver utforskas vidare för att upptäcka och förstå eventuella effekter av rösttyper hos röstassistenter. / The development in the automotive industry is moving towards autonomous vehicles, and as a consequence the need to increase both safety and societal acceptance is necessary. To increase safety in autonomous vehicles, the driver needs to be situationally aware, which can be achieved through a voice assistant in the vehicle. If safety were to increase, people's trust and therefore society's acceptance would most likely also increase. Studies indicate that different characteristics of voice assistants, such as the type of voice, can have an effect on drivers' situational awareness and trust. Thus, this study aims to investigate whether a feminine or masculine voice in voice assistants affects drivers' situational awareness and perceived trust in autonomous vehicles. An experimental study was conducted in order to investigate this, where participants were situated in a simulator of an autonomous vehicle that simulated driving scenarios. The participants were divided into two groups where each group experienced one of two types of voice assistants, either with a feminine or a masculine voice. The participants had to experience driving scenarios where warning situations of varying degrees of severity arose, where they had to make decisions about how they would have handled the situation. In connection with the driving scenarios, three types of data collections consisting of interviews and questionnaires were carried out. The results of the study show no significant or distinctive difference in terms of perceived trust between groups. The results also don’t indicate any distinctive difference between the groups' situational awareness. There is marginal difference between the groups, with the group experiencing feminine voice having both higher perceived trust and situational awareness. The final result of this study shows that this research area needs to be explored further to discover and understand the possible effects of voice types in voice assistants.