An ongoing conversation in the Information Systems literature addresses the concern, "How can we conduct research that makes a difference?" A shortage of high-impact research will, over time, challenge the identity and weaken the viability of IS as an academic discipline. This paper presents the systematic high-impact research model (SHIR), an approach to conducting high-impact research. SHIR embodies the insight gained from three streams of high-impact research programs spanning more than 50 years. The SHIR framework rests on the proposition that IS researchers can produce higher-impact contributions by developing long-term research programs around major real-world issues, as opposed to ad hoc projects addressing a small piece of a large problem. These persistent research programs focus on addressing the entirety of an issue, by leveraging multidisciplinary, multiuniversity research centers that employ a breadth of research methods and large-scale projects. To function effectively, SHIR programs must be sustained by academic and practitioner partnerships, research centers, and outreach activities. We argue that SHIR research programs increase the likelihood of high impact research.

AI is a phenomenon that does not only manifest itself as a disruptive technology, but also entails a paradigmatic shift with conceivably unprecedented and unforeseeable consequences for society and the human condition. This technology with its components Big Data and Machine Learning/algorithms has evoked critical reactions because of ethical concerns that follow on the backwash of its ubiquitous and ever more expanding use. Whose voices are presently raised and what contributions can actually be expected from the information systems (IS) discipline – an academic field that is prone to scrutinize phenomena that emerge when the social and technological system interact? By reviewing a systematically defined selection of the latest IS research literature and analyzing the critical perspectives, this study displays current themes in the IS discipline concerning critique of AI. The accumulation and clustering of the results can provide an answer to the question of what themes appear in the critique of AI in the IS discipline and whether a critical standpoint towards detrimental effects of AI use in society is formed. Social critique, which has no longstanding tradition in IS research, would be necessary to succeed in offering a well-informed and science-based guidance on how to face AI as a society and with the human condition as a focal point.

Majoriteten av jordens befolkning har profiler på något av den handfull av sociala nätverk som dominerar Internet. Samtidigt som dessa tjänster växer i dominans och användarantal upplevs det ofta att användarupplevelsen blir allt sämre. Kritik har bland annat riktats mot hur de låter desinformation spridas och hur de monetäriserar användardata för att sälja målstyrd reklam. Enshittification är ett fenomen som definierades av techjournalisten och -kritikern Cory Doctorow för att beskriva hur dessa plattformar aktivt gör upplevelsen sämre för användarna. Enshittification gör gällande att användare stannar på plattformar som exploaterar dem på grund av höga omställningskostnader, såväl ekonomiska som sociala, trots en uppenbar försämring av den digitala miljön. Forskningsarbetet som presenteras här är en teoriutvecklande kritisk studie av enshittification och hur det manifesteras inom sociala medieplattformar. Studiens syfte är att grunda fenomenet och etablera en dialog kring enshittification i en IS-kontext. Den erbjuder insikter i enshittifications underliggande orsaker och dess konsekvenser för användarna, men även i hur man kan motverka fenomenet. Studien argumenterar även för att kritisk teori behövs inom IS för att kunna analysera sådana här fenomen och relaterade sociala aspekter inom informationsteknik. / A majority of the world’s population today resides on social media. At the same time a small group of platforms dominate the social media landscape. While these services have experienced great growth both in terms of registered users and market dominance, they’ve also been heavily criticized for the way the user experience seems to have deteriorated over time, particularly in respect to how disinformation is spreading throughout the networks and the way these services monetize their users’ personal data. Enshittification is a phenomenon, coined by the tech journalist and -critic Cory Doctorow, that describes the way these platforms actively work to make the user experience worse. The phenomenon asserts that people will keep using services that exploit them due to high switching costs—of either personal or economic nature, or both—even though the user experience deteriorates. This study offers a grounding theory of enshittification as a phenomenon, along with a critical perspective of its manifestation in social networks. Its purpose is to create a definition of the phenomenon and to establish a dialogue within the research field of information systems. The study also offers greater insight into the underpinnings of enshittification and its consequences for the end users, along with a critical reflection over possible mitigation strategies. It also argues that critical theory is needed in the field of IS research in order to be able to analyze phenomenons like enshittification and similar social aspects that manifest themselves within information technology.