On participatory service provision at the network edge with community home gateways

Edge computing is considered as a technology to enable new types of services which operate at the network edge. There are important use cases in ambient intelligence and the Internet of Things (IoT) for edge computing driven by huge business potentials. Most of today's edge computing platforms, however, consist of proprietary gateways, which are either closed or fairly restricted to deploy any third-party services. In this paper we discuss a participatory edge computing system running on home gateways to serve as an open environment to deploy local services. We present first motivating use cases and review existing approaches and design considerations for the proposed system. Then we show our platform which materializes the principles of an open and participatory edge environment, to lower the entry barriers for service deployment at the network edge. By using containers, our platform can flexibly enable third-party services, and may serve as an infrastructure to support several application domains of ambient intelligence.Peer ReviewedPostprint (author's final draft

ChatGPT Unveiled: Unleashing AI Magic in Online Shopping and Digital Marketing

This research paper explores the use of AI, specifically ChatGPT, in interactive activities within online shopping and digital marketing. The paper examines the potential of AI-powered chatbots to enhance customer engagement, personalization, and marketing effectiveness. Through a literature review, case studies, and user feedback analysis, the research highlights the benefits of AI chatbots in providing real-time assistance, personalized recommendations, and improved customer experiences. The paper also addresses ethical and privacy concerns associated with AI implementation and discusses future research directions. The findings are expected to suggest that AI-powered chatbots have the potential to revolutionize online shopping and digital marketing by offering enhanced customer engagement, optimizing marketing strategies, and addressing customer needs. E-commerce preferences of human-mediated services to technologymediated ones regarding the application of AI in frontline services will be examined

Privacy in crowdsourcing:a systematic review

The advent of crowdsourcing has brought with it multiple privacy challenges. For example, essential monitoring activities, while necessary and unavoidable, also potentially compromise contributor privacy. We conducted an extensive literature review of the research related to the privacy aspects of crowdsourcing. Our investigation revealed interesting gender differences and also differences in terms of individual perceptions. We conclude by suggesting a number of future research directions.</p

Countering Personalized Speech

Social media platforms use personalization algorithms to make content curation decisions for each end user. These personalized recommendation decisions are essentially speech conveying a platform\u27s predictions on content relevance for each end user. Yet, they are causing some of the worst problems on the internet. First, they facilitate the precipitous spread of mis- and disinformation by exploiting the very same biases and insecurities that drive end user engagement with such content. Second, they exacerbate social media addiction and related mental health harms by leveraging users\u27 affective needs to drive engagement to greater and greater heights. Lastly, they erode end user privacy and autonomy as both sources and incentives for data collection. As with any harmful speech, the solution is often counterspeech. Free speech jurisprudence considers counterspeech the most speech-protective weapon to combat false or harmful speech. Thus, to combat problematic recommendation decisions, social media platforms, policymakers, and other stakeholders should embolden end users to use counterspeech to reduce the harmful effects of platform personalization. One way to implement this solution is through end user personalization inputs. These inputs reflect end user expression about a platform\u27s recommendation decisions. However, industry-standard personalization inputs are failing to provide effective countermeasures against problematic recommendation decisions. On most, if not all, major social media platforms, the existing inputs confer limited ex post control over the platform\u27s recommendation decisions. In order for end user personalization to achieve the promise of counterspeech, I make several proposals along key regulatory modalities, including revising the architecture of personalization inputs to confer robust ex ante capabilities that filter by content type and characteristics

Panel: IS has outgrown the need for reference discipline theories, or has it?

In the decade since the creation of wireless handheld devices, mobile commerce (m-commerce) has become a ubiquitous channel for accessing information and conducting business. Mobile users can now access information anytime and anywhere. Mobile advertising, retailing, and gambling are popular, and gradually the competition among mobile services providers turns fierce. Hence, some services providers adopt personalization technologies to customize content for their users. This paper explores the opportunities and challenges of the use of personalization technologies in m-commerce. Although the effectiveness of personalization on the web is well-examined, there is little work on personalization in mobile services. The debates regarding the effectiveness of personalization and technological limitations and privacy concerns motivate us to conduct focus groups with mobile users, and explore the opportunities and challenges of personalized mobile services. The focus groups findings illustrate that mobile users are very concerned about their privacy and spam. We then extract a list of personal information from the focus groups findings. This list of personal information is highly related to mobile users’ privacy concerns. We conduct an online survey to gain a better understanding of which piece of information mobile users are more willing to share with services providers and we perform a multi-dimensional scale analysis