SPAM – A Process Model for Developing Smart Personal Assistants

Information technology capabilities are growing at an impressive pace and increasingly overstrain the cognitive abilities of users. User assistance systems such as online manuals try to help the user in handling these systems. However, there is strong evidence that traditional user assistance systems are not as effective as intended. With the rise of smart personal assistants, such as Amazon’s Alexa, user assistance systems are becoming more sophisticated by offering a higher degree of interaction and intelligence. This study proposes a process model to develop Smart Personal Assistants. Using a design science research approach, we first gather requirements from Smart Personal Assistant designers and theory, and later evaluate the process model with developing an Amazon Alexa Skill for a Smart Home system. This paper contributes to the existing user assistance literature by offering a new process model on how to design Smart Personal Assistants for intelligent systems

AI loyalty: A New Paradigm for Aligning Stakeholder Interests

When we consult with a doctor, lawyer, or financial advisor, we generally assume that they are acting in our best interests. But what should we assume when it is an artificial intelligence (AI) system that is acting on our behalf? Early examples of AI assistants like Alexa, Siri, Google, and Cortana already serve as a key interface between consumers and information on the web, and users routinely rely upon AI-driven systems like these to take automated actions or provide information. Superficially, such systems may appear to be acting according to user interests. However, many AI systems are designed with embedded conflicts of interests, acting in ways that subtly benefit their creators (or funders) at the expense of users. To address this problem, in this paper we introduce the concept of AI loyalty. AI systems are loyal to the degree that they are designed to minimize, and make transparent, conflicts of interest, and to act in ways that prioritize the interests of users. Properly designed, such systems could have considerable functional and competitive - not to mention ethical - advantages relative to those that do not. Loyal AI products hold an obvious appeal for the end-user and could serve to promote the alignment of the long-term interests of AI developers and customers. To this end, we suggest criteria for assessing whether an AI system is sufficiently transparent about conflicts of interest, and acting in a manner that is loyal to the user, and argue that AI loyalty should be considered during the technological design process alongside other important values in AI ethics such as fairness, accountability privacy, and equity. We discuss a range of mechanisms, from pure market forces to strong regulatory frameworks, that could support incorporation of AI loyalty into a variety of future AI systems

Understanding Older Adults' Perceptions and Challenges in Using AI-enabled Everyday Technologies

Artificial intelligence (AI)-enabled everyday technologies could help address age-related challenges like physical impairments and cognitive decline. While recent research studied older adults' experiences with specific AI-enabled products (e.g., conversational agents and assistive robots), it remains unknown how older adults perceive and experience current AI-enabled everyday technologies in general, which could impact their adoption of future AI-enabled products. We conducted a survey study (N=41) and semi-structured interviews (N=15) with older adults to understand their experiences and perceptions of AI. We found that older adults were enthusiastic about learning and using AI-enabled products, but they lacked learning avenues. Additionally, they worried when AI-enabled products outwitted their expectations, intruded on their privacy, or impacted their decision-making skills. Therefore, they held mixed views towards AI-enabled products such as AI, an aid, or an adversary. We conclude with design recommendations that make older adults feel inclusive, secure, and in control of their interactions with AI-enabled products.Comment: The Tenth International Symposium of Chinese CHI (Chinese CHI 2022

The enchanted house:An analysis of the interaction of intelligent personal home assistants (IPHAs) with the private sphere and its legal protection

Abstract In less than five years, Alexa has become a familiar presence in many households, and even those who do not own one have stumbled into it, be it at a friend’s house or in the news. Amazon Alexa and its friend Google Assistant represent an evolution of IoT: they have an advanced ‘intelligence’ based on Cloud computing and Machine Learning; they collect data and process them to profile and understand users, and they are placed inside our home. I refer to them as intelligent personal and home assistants, or IPHAs.  This research applies multidisciplinary resources to explore the phenomenon of IPHAs from two perspectives. From a more socio-technical angle, the research reflects upon what happens to the private sphere and the home once IPHAs enter it. To do so, it looks at theories and concepts borrowed from history, behavioural science, STSs, philosophy, and behavioural design. All these disciplines contribute to highlight different attributes that individuals and society associate with the private sphere and the home. When the functioning of IPHAs is mapped against these attributes it is possible to identify where Alexa and Assistant might have an impact: there is a potential conflict between the privacy expectations and norms existing in the home (as sanctuary of the private sphere) and the marketing interests introduced in the home by IPHAs’ profiling. Because of the voice-interaction, IPHAs are also potentially highly persuasive, can influence and manipulate users and affect their autonomy and control in their daily lives. From the legal perspective, the research explores the application of the GDPR and proposal for e-Privacy Regulation to IPHAs, as legislative tools for the protection of the private sphere in horizontal relationships. The analysis focuses in particular on those provisions whose application to IPHAs is more challenging, based on the technology but also on the sociotechnical analysis above. Special attention is dedicated to the consent of users to the processing, the general principles of the GDPR, attributing the role of controllers or processors to the stakeholders involved, profiling and automated decisions, data protection by design and default, as well as spam and robocalls. For some of the issues, suggestions are offered on how to interpret and apply the legal framework, in order to mitigate undesired effects. This is the case, for instance, of determining whether the owners of IPHAs should be considered controllers vis-à-vis the data of their guests, or of the implications of data protection by design and default on the design of IPHAs. Some questions, however, require a wider debate at societal and political level. This is the case of the behavioural design techniques used to entice users and stimulate them to use the vocal assistants, which present high levels of persuasion and can affect the agency and autonomy of individuals. The research brings forward the necessity to determine where the line should be drawn between acceptable practices and unacceptable ones

Image Classification: A Survey

The Classification of images is a paramount topic in artificial vision systems which have drawn a notable amount of interest over the past years. This field aims to classify an image, which is an input, based on its visual content. Currently, most people relied on hand-crafted features to describe an image in a particular way. Then, using classifiers that are learnable, such as random forest, and decision tree was applied to the extract features to come to a final decision. The problem arises when large numbers of photos are concerned. It becomes a too difficult problem to find features from them. This is one of the reasons that the deep neural network model has been introduced. Owing to the existence of Deep learning, it can become feasible to represent the hierarchical nature of features using a various number of layers and corresponding weight with them. The existing image classification methods have been gradually applied in real-world prob-lems, but then there are various problems in its application processes, such as unsatis-factory effect and extremely low classification accuracy or then and weak adaptive abil-ity. Models using deep learning concepts have robust learning ability, which combines the feature extraction and the process of classification into a whole which then com-pletes an image classification task, which can improve the image classification accuracy effectively. Convolutional Neural Networks are a powerful deep neural network tech-nique. These networks preserve the spatial structure of a problem and were built for object recognition tasks such as classifying an image into respective classes. Neural networks are much known because people are getting a state-of-the-art outcome on complex computer vision and natural language processing tasks. Convolutional neural networks have been extensively used

Digital inclusion - the vision, the challenges and the way forward

This paper considers the vision and aspiration of digital inclusion, and then examines the current reality. It looks beyond the rhetoric to provide an analysis of the status quo, a consideration of some facilitators and challenges to progress and some suggestions for moving forward with renewed energy and commitment. The far-reaching benefits of digital inclusion and the crucial role it plays in enabling full participation in our digital society are considered. At the heart of the vision of universal digital inclusion is the deceptively simple goal to ensure that everyone is able to access and experience the wide-ranging benefits and transformational opportunities and impacts it offers. The reality is a long way from the vision: inequality of access still exists despite many national campaigns and initiatives to reduce it. The benefits and beneficiaries of a digital society are not just the individual but all stakeholders in the wider society. Research evidence has shown that the critical success factors for successful digital participation are (i) appropriate design and (ii) readily available and on-going ICT (Information and Communication Technology) support in the community. Challenges and proven solutions are presented. The proposition of community hubs in local venues to provide user-centred ICT support and learning for older and disabled people is presented. While the challenges to achieve digital inclusion are very considerable, the knowledge of how to achieve it and the technologies which enable it already exist. Harnessing of political will is necessary to make digital inclusion a reality rather than a vision. With the cooperation and commitment of all stakeholders actualisation of the vision of a digitally inclusive society, while challenging, can be achieved and will yield opportunities and rewards that eclipse the cost of implementation