Digitalization is a socio-technical phenomenon that shapes our lives as individuals, economies, and societies. The perceived complexity of technologies continues to increase, and technology convergence makes a clear separation between technologies impossible. A good example of this is the Internet of Things (IoT) with its embedded Artificial Intelligence (AI). Furthermore, a separation of the social and the technical component has become near enough impossible, for which there is increasing awareness in the Information Systems (IS) community. Overall, emerging technologies such as AI or IoT are becoming less understandable and transparent, which is evident for instance when AI is described in terms of a black box. This opacity undermines humans trust in emerging technologies, which, however, is crucial for both its usage and spread, especially as emerging technologies start to perform tasks that bear high risks for humans, such as autonomous driving. Critical perspectives on emerging technologies are often discussed in terms of ethics, including such aspects as the responsibility for decisions made by algorithms, the limited data privacy, and the moral values that are encoded in technology. In sum, the varied opportunities that come with digitalization are accompanied by significant challenges. Research on the negative ramifications of AI is crucial if we are to foster a human-centered technological development that is not simply driven by opportunities but by utility for humanity. As the IS community is positioned at the intersection of the technological and the social context, it plays a central role in finding answers to the question as to how the advantages outweigh the challenges that come with emerging technologies. Challenges are examined under the label of dark side of IS, a research area which receives considerably less attention in existing literature than the positive aspects (Gimpel & Schmied, 2019). With its focus on challenges, this dissertation aims to counterbalance this. Since the remit of IS research is the entire information system, rather than merely the technology, humanistic and instrumental goals ought to be considered in equal measure. This dissertation follows calls for research for a healthy distribution along the so-called socio-technical continuum (Sarker et al., 2019), that broadens its focus to include the social as well as the technical, rather than looking at one or the other. With that in mind, this dissertation aims to advance knowledge on IS with regard to opportunities, and in particular with a focus on challenges of two emerging technologies, IoT and AI, along the socio-technical continuum. This dissertation provides novel insights for individuals to better understand opportunities, but in particular possible negative side effects. It guides organizations on how to address these challenges and suggests not only the necessity of further research along the socio-technical continuum but also several ideas on where to take this future research. Chapter 2 contributes to research on opportunities and challenges of IoT. Section 2.1 identifies and structures opportunities that IoT devices provide for retail commerce customers. By conducting a structured literature review, affordances are identified, and by examining a sample of 337 IoT devices, completeness and parsimony are validated. Section 2.2 takes a close look at the ethical challenges posed by IoT, also known as IoT ethics. Based on a structured literature review, it first identifies and structures IoT ethics, then provides detailed guidance for further research in this important and yet under-appreciated field of study. Together, these two research articles underline that IoT has the potential to radically transform our lives, but they also illustrate the urgent need for further research on possible ethical issues that are associated with IoTs specific features. Chapter 3 contributes to research on AI along the socio-technical continuum. Section 3.1 examines algorithms underlying AI. Through a structured literature review and semi-structured interviews analyzed with a qualitative content analysis, this section identifies, structures and communicates concerns about algorithmic decision-making and is supposed to improve offers and services. Section 3.2 takes a deep dive into the concept of moral agency in AI to discuss whether responsibility in human-computer interaction can be grasped better with the concept of agency. In section 3.3, data from an online experiment with a self-developed AI system is used to examine the role of a users domain-specific expertise in trusting and following suggestions from AI decision support systems. Finally, section 3.4 draws on design science research to present a framework for ethical software development that considers ethical issues from the beginning of the design and development process. By looking at the multiple facets of this topic, these four research articles ought to guide practitioners in deciding which challenges to consider during product development. With a view to subsequent steps, they also offer first ideas on how these challenges could be addressed. Furthermore, the articles offer a basis for further, solution-oriented research on AIs challenges and encourage users to form their own, informed, opinions.