We present the main messages of a European Expert Round Table (ERT) on the unintended side effects (unseens) of the digital transition. Seventeen experts provided 42 propositions from ten different perspectives as input for the ERT. A full-day ERT deliberated communalities and relationships among these unseens and provided suggestions on (i) what the major unseens are; (ii) how rebound effects of digital transitioning may become the subject of overarching research; and (iii) what unseens should become subjects of transdisciplinary theory and practice processes for developing socially robust orientations. With respect to the latter, the experts suggested that the “ownership, economic value, use and access of data” and, related to this, algorithmic decision-making call for transdisciplinary processes that may provide guidelines for key stakeholder groups on how the responsible use of digital data can be developed. A cluster-based content analysis of the propositions, the discussion and inputs of the ERT, and a theoretical analysis of major changes to levels of human systems and the human–environment relationship resulted in the following greater picture: The digital transition calls for redefining economy, labor, democracy, and humanity. Artificial Intelligence (AI)-based machines may take over major domains of human labor, reorganize supply chains, induce platform economics, and reshape the participation of economic actors in the value chain. (Digital) Knowledge and data supplement capital, labor, and natural resources as major economic variables. Digital data and technologies lead to a post-fuel industry (post-) capitalism. Traditional democratic processes can be (intentionally or unintentionally) altered by digital technologies. The unseens in this field call for special attention, research and management. Related to the conditions of ontogenetic and phylogenetic development (humanity), the ubiquitous, global, increasingly AI-shaped interlinkage of almost every human personal, social, and economic activity and the exposure to indirect, digital, artificial, fragmented, electronically mediated data affect behavioral, cognitive, psycho-neuro-endocrinological processes on the level of the individual and thus social relations (of groups and families) and culture, and thereby, the essential quality and character of the human being (i.e., humanity). The findings suggest a need for a new field of research, i.e., focusing on sustainable digital societies and environments, in which the identification, analysis, and management of vulnerabilities and unseens emerging in the sociotechnical digital transition play an important role.

In relation to the fourth industrial revolution, traditional manufacturing methods cannot serve the flexibility demands related to mass customization and small series production. Rapid tooling provided by generative manufacturing has been suggested recently in the context of metal forming. Due to the high loads applied during processes to such tooling, a purposeful mechanical description of the additively manufactured (AM) materials is crucial. Until now, a comprehensive characterization approach for AM polymers is required to allow a sophisticated layout of rapid tooling. In detail, information on compressive and flexural mechanical properties of solid infilled materials made by additive manufacturing are sparsely available. These elementary mechanical properties are evaluated in the present study. They result from material specimens additively manufactured in the fused filament fabrication (FFF) process. The design of the experiments reveals significant influences of the polymer and the layer height on the resulting flexural and compressive strength and modulus as well as density, hardness, and surface roughness. As a case study, these findings are applied to a cup drawing operation based on the strongest and weakest material and parameter combination. The obtained data and results are intended to guide future applications of direct polymer additive tooling. The presented case study illustrates such an application and shows the range of manufacturing quality achievable within the materials and user settings for 3D printing.