Unintended Side Effects of the Digital Transition: European Scientists’ Messages from a Proposition-Based Expert Round Table

Abstract

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.

1. Scope and Goals

1.1. Digitalization as a Main Driver of Human Socio-Cultural Evolution

The digital revolution comprises one of the major transitions of human development. We may consider it to be as critical as the mastery of fire, the development of language, or the first Industrial Revolution [1]. Whereas the latter was characterized by the extension of human activity and economics by supplementing organic (photosynthesis-based) energy in plants with the use of energy from fossil fuel (i.e., starting with coal), the main technological essence of the Digital Revolution is the exponential increase in the speed and amounts of storage, processing, retrieval, and communication of digital data. Thus, the empowerment, extension, and substitution of human physical power are followed by an empowerment of cognitive or mental power. Digitalization (used synonymously with digitization) is the representation of discrete or analog (real-world) objects or processes in the form of digital symbols. The major roots of digitalization are found in the history of the invention of place-value numbers and the number zero, about 2600 years ago [2,3,4]; binary numbers 500 years ago; the first programmable computer invented by Babbage (1791–1871) [5], followed by Boole’s (1815–1864) symbolic logic; and—as a key entrance to technological implementation—Zuse’s programmable, digital computer in 1941. We may consider the year 2002 as the start of the Digital Age, if we refer to the criterion provided by Hilbert [6] that the majority of human-produced information has, by now, been stored digitally. Given the World Wide Web, distributed and pervasive computing inventions such as Nelson’s hypertext leading to the internet played an important role [7].

Digital technologies are machines that master digital representation, computing, and adapting (learning) related to environmental information. We do not deal with the history of technology in detail. Yet we want to mention that the history of Moore’s law, with a doubling of the density of transistors (defined as the numbers of transistors per circuit) and thus the doubling of storage capacities, has not yet come to an end [8,9], although there are strong arguments that the present technology will reach its physical boundaries [10]. However, there are new computing technologies such as quantum computers that will open new doors to algorithmic complexity, encryption, and machine learning [11,12] and cell-based biocomputers that may lead to the perspective of hybrid biotechnological systems [4,13].

Digital technologies are operating on and changing all levels of human systems. There are programmed, cancer-fighting nanorobots that destroy (marked) tumor cells [14]. Brainwaves may be read by computers to steer cars. Individuals immerse themselves in virtual gaming worlds. Human bonds are forged and maintained 24/7, as people scattered all across the globe Skype keep relations with friends and family. Virtual companies play important roles in pharmaceutical developments [15]. Countries such as Estonia utilize digital technology for managing all public services. The global internet and its social networking platforms has become a primary communication system among humans and is building something like the mind of the human species. Digital technologies are all-purpose technologies and transform processes and life in all domains of the planet.

1.2. The Rush for a Better Society by Digitalization

All of the European countries have high expectations with respect to digital transitioning. However, Europe’s 2017 Digital Progress Report for EU countries [16] documents a high level of variance in the integration of digital technologies, with Scandinavian countries and several smaller countries at the top and Romania and Bulgaria scoring lowest. This assessment is based on a Digital Economy and Society Index including connectivity, digital skills, internet use and the use of digital technology in business and public services. Almost every country has developed something like a national Digital Agenda [17] or Digital Strategy [18]. The aims are to boost economic progress, the supply of health care, connected and autonomous mobility, efficient energy and resource use, wealth and (international) competitiveness, and so on, as well as a comprehensive digital public service with a focus on strengthening democracy.

Yet, presumably, any large-scale technology transition is linked to beneficial—but also unfavorable and unwanted—changes for almost all actors included or concerned. The three decades of discussion about the productivity paradox, starting with Solow’s 1987 statement [19] that we cannot see productivity increase caused by computers, have been modified by Brynjolfsson and colleagues’ sophisticated business-systems transition analysis [20,21,22] and have culminated in recent meta-analyses [23,24] that reveal that digital technology is the trigger and catalyst for a fundamental societal transition and economic growth. This transition is linked to synchronous and delayed positive and negative changes on sociocultural and material-biophysical levels. We may argue that this is a key matter for sustainability science, in particular if we consider the anticipation of critical unintended side effects (unseens) of technology innovation on various domains of society as the art of sustainability learning [25]. In this context, the anticipation of unseens may be considered a critical factor in sustainability learning. Therefore, we approach sustainability from a systemic perspective when conceiving sustainable development as an (i) ongoing transdisciplinary inquiry on (ii) managing systemic limits (i.e., for avoiding hard landings) in the frame of (iii) inter- and intragenerational (global) justice [26,27].

1.3. Identifying Unintended Side Effects of Digital Transitioning as Objectives of Proposition-Based Expert Round Tables (ERTs) on Sustainable Digital Environments

Please note that unseens are not the barriers that harm development. In decision-theoretic terms, an unseen is a positive or negative impact that results from an action A on a system B that was not intended by the decision maker (or by those who were involved in the planning or realization of an action). Thus, in general, we distinguish between intended impacts and unintended impacts of an action. Unintended impacts are usually unanticipated. Harvesting crops in (early) agriculture may serve as an example. The goal and intention of ancient farmers was to grow as much of a crop as possible on arable land. The unseen was the consequential reduction of nutrients and, thereby, of the harvest. This unseen was compensated (mitigated) by the invention of fertilizing or other means (such slash and burn agriculture which may be conceived as adaptation). We want to note that unseens may affect the same system as that of the intended impacts or a different system (which may not be in the primary interest of the decision maker).

Unanticipated barriers in the course of implementing a technology are not conceived as unseen. If, for instance, unexpected high costs or public concerns prevent the implementation of a technology (such as GMOs as food in some European countries), these negative aspects are conceived as potentially unknown (or unanticipated) costs for implementing a technology (i.e., making a decision A).

Additionally, the goal of these Expert Round Table (ERT) was (launched by the first author) to increase awareness among the science community that the digital transitioning (including the digital divide) is a core issues of sustainable science. Based on this, the identification of unseens was conceived as a step for preparing science for transdisciplinary processes. A transdisciplinary process [28,29,30], is a knowledge-integration-based, real-world, problem-oriented discourse including representatives from all key stakeholder groups that is intended to generate socially robust orientations on critical issues of sustainable development [28,29]. For instance, the facilitation of the adaptation and/or the mitigation process for those who cannot benefit from the desired advantages of digital transitioning may become the subject of a transdisciplinary process related to the Digital Revolution.

The goals of the European ERT, as well as those of a previous Japanese ERT [31] that took place in February 2017 [32], read as follows:

• Goal 1: Identify positive or negative unsee(ns) that are linked to digital transitioning;
• Goal 2: Reflect on the way(s) in which the unsee(ns) can best become subjects of science in an overarching way;
• Goal 3: Project (from the science perspective) which unsee(ns) might become subjects of transdisciplinary processes (i.e., science–practice discourses that relate different types of knowledge in order to efficaciously master complex, relevant societal challenges).

The present paper presents and classifies the unseens and compares them with those from a Japanese ERT which took place in February 2017 and develops a bigger picture on sensitive domains which are not yet well understood and which ask for further research policy means. The propositions of Appendix A address the above goals and a basic pillar of this paper. Before we present the method of proposition-based (Science) ERT, and findings of the European ERT, we briefly summarize the main findings of the Japanese ERT.

1.4. Main Findings, Unseens, and Conclusions of the Japanese 2017 ERT

The Japanese ERT followed the same Goals 1–3 as presented above. The outcomes were published by Sugiyama et al. [31] and are summarized to some extent in Appendix B. The main digital-technology innovations identified were automatization, Big Data, artificial intelligence (AI), conversational software, and digital biotechnology (including biocomputers). Globalized networking and ubiquitous availability in all domains of life were identified as unique selling points of digital technologies.

Three issues that are less frequently discussed may be of special interest. The first is that culture (and religion) matters in the use and acknowledgement of digital technology. The experts argued that the Japanese (given a Shinto and Buddhism cosmology) prefer embodied, humanoid robots, whereas Christian principles of resurrection and salvation allow for the appreciation of nonhumanoid robots. The second refers to concerns related to endogenous black-swan—like threats that endanger financial, military, and other large-scale digital systems. Third, several propositions provided by Scholz and Sugiyama refer to biotech. Scholz [4], who also provided propositions to the Japanese ERT, conceives deoxyribonucleic acid (DNA) and GMO as genetically modified organisms (GMO) (quaternary number-based) entities and operations. In this context, critical impacts from directed evolution become unseens from digital technology. But, in addition, reduced conceptions of evolution due to the preponderance of the digital theory of molecular genetics (this is elaborated in Appendix B) were identified as inner-science unseens. In the context of biotechnology, special attention was also given to biocomputers, which include living cells which are conceived as cognitive systems [33] and decision-makers [34] rather than as mere electrochemical processes. Concerns were raised about the kind of governance that would be necessary for these types of bionic entities.

2. Theory: Approaching a Classification of Unintended Side Effects (Unseens)

2.1. Defining Human Systems, Environmental Systems, and the Digital Environment

The digital transition is a genuine human-made issue. For investigating and analyzing unseens, we take a decision-making perspective. As a point of departure, a (digital) technology is considered as a means (i.e., decision alternative, A_D, also denoted as a digital, D, technology innovation) that is invented, established, or used by a decision maker (i.e., a human individual, a company, or a government, denoted by H) to acquire some positive outcome (i.e., some positive utility payoff) from an intended change in the environment, E. Unseens are nonperceived or unanticipated (negative) side effects. From a system-theoretic perspective, the management of digital technologies calls for a symbiotic coevolutive connection with all human systems, in particular the social, economic, and political processes [35].

The digital environment E_D comprises all human-made processes that rely on digitally represented information. The (discrete) digital nature and computational (processing-based) nature are essential. Following the Human-Environment System (HES) framework [25], the cell (including its self-creating programs and its capability to decide) is considered the basic unit of life. The definition of the human individual and of its environment follows this definition. According to HES, the human environment, E, complements (the atoms of) all living cells of an individual that emerged from the zygote and their interactions. The HES framework distinguishes between the material-biophysical layer, H_m (the “body”), which is inextricably coupled with a social-epistemic-cultural layer H_s (the “mind”), and there is a hierarchy of human systems above and below the human individual. The (main) levels above the individual are the (human) group, organization (commercial and non-commercial), institutions (organizations which are established by societies), societies (the major subdivision of human species [36]), and the human species. According to the cell-based definition, a company (as one type of organization) consists of the activities of the living cells of all owners and employees assigned to this company. Similarly, other human systems may be defined. Below the human system, we distinguish the organ, tissues, cell systems, and the single cell. The forthcoming analysis of expert’s views on unseens and the discussion of the results refers to the presented complementarities and the hierarchy postulate of the HES framework as presented in this section (see [25,37]).

The environment, E, of a human system consists of—simplified—all the atoms of the universe minus the atoms of the cells which make the human system, H. We distinguish between a (living) biotic (cell-based) and an abiotic environment (see Figure 1). As there are biocomputers that include living cells [4,13], the digital environment may also be distinguished by a (traditional) abiotic digital environment, $E_{m-\mathit{abio}-\mathit{digi}}$, and a biotic one that includes both a material one, $E_{m-\mathit{bio}-\mathit{digi}}$, and (if we consider the cell as a cognitive system [33,38]) a social–epistemic–cognitive level, $E_{m-bio-digi},$ as well, In this context, it is essential that digital technologies allowed to monitor (and even to visualize) nanostructures, e.g., the genetic code. This opens the floor to new horizons. Against this background—as technology may be conceived as “idea, volition, or knowledge” [39]—the genetic modification of organisms (GMO) has been seen as part of the digital environment and denoted as one of the major threats to human development [4,40].

The paper focuses on unseens related to societally relevant impacts. However, the science system itself will also be subjected to fundamental changes through digitalization (see also Section 1.4 and Appendix B.1). Bruno Latour’s work on the sociology of science revealed that computerization changed life in the biological research laboratory in a most fundamental manner [41]. He stated that the change in scientific work (tending to become more fragmented) is even greater than the shift from experimentation to simulation. There are also fundamental changes in modeling caused by digitalization. Some scientist stress that the shift from analytic mathematical theory-based modeling to computational, discrete mathematics is linked to different types of validation errors (e.g., round-off or truncation errors). This has affected, for instance, climate research (where continuous functions of time and space are transferred to discrete points) [42]. From a philosophy of science perspective, it is of interest that different notions of meaning that are assigned to mathematical theorems (which partly represent natural laws in a nomothetical manner) and to algorithms (which are mostly conceived as descriptive tools) [42,43]. Moreover, mathematics itself has been fundamentally affected by the invention of the computer; there is a shift to computer-based or automated theorem proving in mathematics [44,45], as indicated by the question, “How can we believe in a machine-checked proof?” [46]. Referring to Figure 1, this establishes a new relationship between the individual mathematician’s mind and (a formerly) written (chalk-and-blackboard, technology-based) mathematical theorem whose verification is now mediated by a machine-based computational layer (as a specific form of the digital curtain) and does not only rely on the mathematical expert.

2.2. Innovations in the World of Digital Technologies

The smart and connected world in which services, products, and people are somehow embedded in broader systems, is reshaping society. Emergent domains such as Web 3.0, Industry 4.0, Government 3.0 (Refer to Gov3.0 project: http://www.gov30.eu/), or even Life 3.0, which discusses the implications of artificial intelligence on the future of life on Earth, are changing the role of digital technologies and the data on designing and rethinking human systems. For example, in the industry sector, the pervasiveness of digitization has been reshaping products toward a layered architecture that includes devices, networks, services, and contents [47].

Digital products share three main elements: physical components, smart components (sensors, microprocessors, data storage etc.), and connectivity components (especially the networks that provide communication within the system, see [48]). The same is happening in the public sector, where new possibilities for innovating governance have been created by the growth in data, computational power, and social media [49], as well as by the digital city governance concept where cities require smart and connected public services (and their related design and development), smart decision-making processes, integrated public policies, and new governance structures.

From a data-driven perspective, we can distinguish between the storage, retrieval, processing (the algorithmic part), and transmission (the network part) of digital data. Storage, often resulting in Big Data, can use decentralized, centralized, and partially networked storage units including cloud storage. The encryption and access to its code is a key to data security. Multiauthority cloud-storage systems are seen as overcoming the mono-emperorship that has been linked to a central data-control authority.

Another critical issue of storage at the interface to retrieval is the longevity of data. The history of Information and Communication Technologies (ICT) is full of variants of unfulfilled expectations with respect to overcoming the aging effects of storage media such as magnetic tapes, optical CDs, and semiconductor transistors, and other developed technologies all have critically low lifetimes. Robust, potentially long-term storage systems that demonstrate the same level of performance as papyrus scripts that are hundreds of years old are not yet in sight. How Big Data may be reliably retained is, as yet, unanswered.

With respect to retrieval, the potential for hacking and the vulnerability of economic, medical, and infrastructure data is also an unsolved problem.

Table 1. Main operations and technologies related to digital data and technology innovation that may cause unseens.

Operation of Digital Data	Main Question and Factors (See Bullet Points) with Respect to Impacts and Unseens
Storage	Who is hosting whose data, and how, where, and using what technology? This includes useens related to ○ Big Data cloud storage [50,51] ○ Multiauthority cloud-storage systems ○ (Big) Data ownership [52] ○ Potentials and limits of encryption [53] ○ Longevity of data
Retrieval	Who has access to what data under what constraints at what speeds and what search algorithms under what security barriers or access architecture? Here, the following issues are of interest: ○ The economic status of data (data as public good, private good, club good, etc.) ○ Legal regulation of retrieval/use of data (what regulations of access to data govern the system?) ○ Retrieval architectures ○ Hacking, cyberattacks
Processing	For what purpose is data processed—by whom and with what algorithms? What processes in what systems are affected by the processing? ○ Artificial intelligence: What mental operations (e.g., calculating, writing, rule-based causal inference, etc.) are substituted by what digital algorithms? ○ Self-organizing ○ (Types of) parallel processing ○ Cloud computing
Transmission	○ Digital Networks: Electronic Product Code for digital data ○ IOT: RFID-based ubiquitous networked sensing

describes important factors related to the main operations related to digital data and technology innovation that may cause unseens.

2.3. New Types of Digitalized Environments

Digital technology and the above-mentioned sub-components are general-purpose technologies. This is best expressed by terms such as pervasive computing [54], distributed systems, networks, systems of systems, or the Internet of (Every-)Thing (IoT). A key issue of technology transitioning is that the new technology induces a fundamental restructuring of social, production, business, and other processes. It was not the steam engine itself but the adjustment of production by transmission belts, energy, insertion in vehicles, etc. that led to trains, new types of workers, and technological knowledge that transformed human life and Earth. These developments, in turn, led to new environments such as industrial cities, new forms of education at institutes of technology, new forms of poverty, and capital as a key variable of economic systems. We can find the same kinds of developments in the digital transition.

3. Procedure/Methods/Data Sampling

3.1. Invitation, Procedure, Sampling of Data, Methods of Data Anylysis

After the Japanese ERT in Tokyo (19 February 2017), the organizers of the European ERT (Scholz, Parycek, and Steiner) defined a tentative list of perspectives and potential contributors who should participate in the ERT. The initial plan was to include representatives from economics and industry, and experts in biogenetics, cyberwarfare, and integrated world systems. Based on a phone chain, the scientists presented in

Table 2. Perspectives and (scientific) experts who wrote propositions for unseens. Perspectives 6 and 7 (marked with *) were not represented at the ERT ¹ (participating experts are marked with ⁺, the country of primary institutional association is shown in parentheses).

No.	Perspective	Experts (Country)
1	Industrial change	G. Schuh + (D) & J. Prote (D)
2	Economic change	E. Bartelsman (NL)
3	Environmental systems	M. Höjer (S) & L. Hilty (CH)
4	Social & neuropsychology	S. Diefenbach (D) & C. Montag + (D)
5	Genetics	L. Franke (NL)
6	Big Data analytics	P. Parycek (A) & G. Viale Pereira (A)
7 *	Cybersecurity & warfare	R. Hill + (CH/GB)
8 *	Ethics & the Digital	C. Kirchner + (F) & G. Dowes + (F)
9	Global social change	D. Helbing + (CH) & S. Klauser (CH)
10	Sustainable development	A. Grunwald (D) & O. Renn (D)

¹ The ERT was moderated by R. W. Scholz (A) and P. Parycek (A); K. Fritsche (D) and A. Reichel (D) participated as discussants.

made commitments to participate in the ERT.

Finally, 17 European science experts working in 8 different European countries provided 42 propositions (see Appendix A) on the 10 perspectives. The scientists were asked to focus on unseens. Some proposals had to be rewritten several times, as the experts were focusing only on the phenomena related to digital transitioning. Based on this, a “Workbook for Preparing the European Round Table Structuring Research on Sustainable Digital Environments” was created (see Supplementary Materials 1). This 43-page workbook included all propositions and a glossary with referenced definitions including the following key terms: digital revolution, transition, and transformation; sustainability/sustainable development; transdisciplinarity; and unseens. All participants received the workbook a week before the ERT was to convene.

The one-day ERT took place in Bonn on 19 September 2017. Eleven of the authors of the propositions, the first author as moderator, two invited discussants (see Table 2, and five representatives of the German Ministry of Education and Research (BMBF) joined the ERT. After a brief presentation of the background and general message, each set of proposals (accessible to participants in the workbook) was discussed for 30–40 min to develop a deeper understanding on a specific perspective message. The experts had been informed of the highlights of the Japanese ERT by mail before the ERT in Bonn and via the pinboard. The main steps of this proposition-based ERT is presented in Figure 2.

In the course of the ERT, the participating science experts were asked to provide suggestions/inputs by key words (key topics) to four (living) pinboards (see Supplementary Materials II). 1: Priority list of unseens: Most urgent rebounds/unseens/digital threats calling for special treatment (see Goal 1 of the ERT above); 2: Blind spots and overarching layers: What has not yet been sufficiently discussed in the propositions of the Tokyo and the European ERTs? 3: Overarching conceptual layers: This topic referred explicitly to Goal 2, i.e., on the question of how unseens may become the best subjects of research. 4: Candidates for Td Processes: What key stakeholders of what domain of digital transitioning are interested in a transdisciplinary process?

3.2. Data Analysis

3.2.1. Main Messages

Right after the workshop, (i) main conclusions were elaborated in the final discussion. These conclusions and others developed throughout the entire workshop were summarized by two authors (Reichel and Scholz) and sent to all participants of the ERT (see Box 1) for any corrections and supplementations.

3.2.2. Classifying Unseens

For (ii) classifying unseens, the essence was extracted from the proposals. Appendix C presents short labels for identified unseens, the main technology innovation related to each one, the primary intended change of this technology innovation, and a brief description of the properties of each unseen. This table was constructed by two participants of the ERT (Scholz and Viale Pereira) with a face validity check by two other scientists (Clemens Fischer and Reiner Czichos). Several propositions were skipped (such as transdisciplinarity; see A.10.4), as they did not deal with an unseen. Some propositions were merged since they dealt with the same issue. Thus, from the 42 propositions, 30 different unseens were extracted.

For classifying the extracted unseens ($A_{i,k}=Ai,k)$, a bottom-up strategy was chosen. Based on the description of the identified unseens in the propositions (see Appendix A), 34 salient issues (main issues; $I_n$) were identified by two authors (Scholz and Viale Pereira). A salient issue is defined here as the main aspect that characterizes a proposition.

Three authors (Scholz, Steiner, Viale Pereira) provided ratings on the question, to what degree are the (potentially negative) impacts addressed by or related to the item (e.g., $I_1$: Loss of democracy) in the proposition (e.g., A.5.1, DNA-based discrimination) in individual sessions? The ratings were presented on a three-level scale ranging from “not at all” (=0) to “some significant extent” (=1) to “very much” (=2). The raters received instructions on how to cope with ambiguities. Supplementary Information 3 provides some insight into the ambiguities of the ratings.

In order to mitigate subjective-rater bias, the 1088 ratings on 34 × 32 pairs of items and propositions by the three authors were adjusted in the following manner: The squared difference secures ensures that the main features are affecting the grouping/clustering of the data. For stressing contrasts, Ward’s method was chosen [55,56]. To avoid being biased by the set of propositions, the raters were instructed never to rate two relationships between propositions and ratings in a row. The mean of the ratings of the three raters was taken as input for the Life Cycle Assesment (LCA).

4. Results

4.1. Unseens Discussed in the European ERT

For structuring the 31 unseens from the 42 propositions of the European ERT (see Appendix C), a hierarchical CLA [56] was applied based on mean judgments of three raters.

Figure 3 presents six main clusters (the interested reader should look at the propositions in Appendix A). First, clusters C1 and C2 (belonging to one supercluster) include the propositions on the dark side of digital transitioning on the societal level, C1 Cybernetics and warfare, and on the level of the individual (see the propositions of Hill and Kirchner/Dowes), C2 Psychoneurological sensitivity (Montag and Diefenbach).

The second supercluster includes four subclusters, C2–C4. The Smart factory, labor market, and justice cluster (C2) has roots in the Industrial change (Schuh and Prote) and Economic change (Bartelsman) perspectives (see Appendix A).

Cluster C4, Economic change and rebounds, includes digital innovation of business and finance (addressed by Schuh and Prote), New finance (i.e., financial systems, emerging from Global Societal Change; Helbing & Klauser), and Environmental rebounds (per Höjer and Hilty’s Environmental systems perspective; see Appendix A).

The Ethics cluster, C5, is rooted in propositions provided in the Genetics (Franke), Ethics and the digital (Kirchner & Dowes), and Sustainable development (Grunwald and Renn) perspectives (for the perspectives, see Appendix A).

Finally, there is a multirooted Governance cluster C6 that refers to propositions on Big Data analytics (Parycek and Viale Pereira) that stress cybersocial systems and resilience governance, digital-based democracy (referring to Helbing and Klauser), and manipulated democracy (referring to Renn and Grunwald’s proposals) as one root and a renewal of the economic (Schuh and Prote) and capitalist system (Helbing and Klauser) as a second root.

Figure 4 presents clusters of the items used in rating the 31 unseens used for classifying the clusters. These clusters can be interpreted as main properties used to describe, characterize, and appraise the unseens. Thus, Figure 3 presents common aspects that are inherent in clusters of unseens, whereas Figure 4 presents common aspects in the concepts used in the science expert’s items for judging similarities. The latter may help to provide a bigger picture or even to approach a thick description [57] of the sociotechnical dimensions of digital transitioning as they are seen by European science experts.

Here, we may distinguish three superclusters (with high distance) and seven clusters on a lower level. $C_{i}1$ (the index $i$ refers to item) denotes the digital democratic renewal, which supplements the lower sub-cluster of $C_{i}1$, i.e., the digital economic renewal. These two changes may be seen in relation to redefining humanity due to the power of the digital, both sub-clusters of $C_{i}1$. Finally, we have to acknowledge that A personal and resilient society (sub-cluster of $C_{i}2$) calls for protecting the losers.

4.2. Results from the Living Pinboards

The results from the pinboards are an interfacial element between the Propositions (that were written and available before the ERT) and the Main messages that were composed directly after the ERT. The inputs of the experts were put on “keyword buttons” that were grouped by a collective grouping dialogue among all (N = 10) experts who participated in this final activity of the ERT.

With respect to 1: Priority list of unseens, the pinboard had four clusters including the keywords (N = 8 experts provided input to this pinboard):

• The role of data/knowledge in economics, data ownership, value of data, data economy, rules of using data, methods of aggregation, and transparency of global infrastructure (N = 4)
• Ethical questions, redefining humanity in the coupled human–digital tech age, the digital reality shift, human autonomy vs. autonomous technology, save human autonomy, externalization of control (N = 4)
• Urban/regional structures, future of urban life effects of productivity, energy, and climate (N = 2)
• Experiments, fasten interdisciplinary research

Inputs to 2: Blind spots and overarching layers were provided by N = 6 experts. The grouping included the following topics:

• Normative reference frame, normativity, timing of tech development, understanding between digital and analog
• Who decides on facts and truth
• Changing the demands (more critical)
• Power distribution

Inputs to 3: Blind spots and overarching layers (for cross- and interdisciplinary research) were provided by N = 8 experts. Here, N = 6 experts provided inputs with the following groups:

• Data theory and governance, making data computable, making data understandable, data = past—losing future, data algorithm human interaction
• Power of algorithm, algorithmification
• Power distributions, compare scenarios, the purpose of decision-making
• Time relations, use of time, space, and resources
• New modernization theory, tetrahedron of digital age, level of system organization

No single input was provided to Pinboard 4 (see Supplementary Material 2), i.e., on the question of which stakeholders would be interested in a transdisciplinary process on which topics.

4.3. Main Messages Constructed Directly after the ERT

Based on a preliminary analysis of 42 propositions on 10 perspectives, a one-day ERT in Bonn on 19 September 2017, with 11 experts representing eight perspectives, the inputs to the Living pinboard, and continuous interaction based on the goals of the workshop, the first author and André Reichel (a participating discussant of the ERT) composed the following 10 messages. The list of Main Conclusions (MCs) was sent out on 3 October 2018. All 11 participating proposal writers were asked to provide feedback within one week. Based on written and oral feedback by 7 experts, the final version shown below was composed on 17 October 2018.

Data ownership (see Box 1, MC 1) and, with somewhat minor importance, the relationship to The nature of algorithms (MC2) were placed at the top, due particularly to the dynamics of the discussion and the inputs to the living pinboards. The tremendous changes of a globally Networked, AI-driven, adaptive industry and economy were addressed in MC3.

The DNA personality (MC4), access to the most personal data, DNA (including the option to change this code by nano-engineering) played a special role in this discussion.

MC5, the different Speeds of transitioning, and MC6, Change of human–environment transitioning, stress the new stage of human evolution and the severe challenges of adaptation that human systems have to face related to the digital transformation. The multiple negative Rebounds or unseens, MC7, are an important issue here.

The last three issues dealt with the cross-disciplinary, overarching nature of digital transitioning. These deal with the question of whether MC8, AI, is a means or ends and MC9, whether Innovation is not good per se, and our need for a thorough, interdisciplinary understanding of the Digital Age.

Box 1. Main conclusions (MCs), highlights, messages, hot spots, and lessons of the ERT on Sustainable Digital Environments.

MC1: Data ownership: The most essential point involves data, their ownership, and their value. This may induce a new form of data economy where disembodied data might come to be seen as a new economic entity of the quality of capital, labor, or natural resources.

(We should note that the discussion stressed that we are currently facing a data oligarchy which is far from data democracy. Further, Some ERT members stated that digital data and systems such as Google may be considered as public good.)

 

MC2: The nature of algorithms and control systems and their unseens: The role of algorithms in different types of computers (including) biocomputers and control systems (which may include human decision-making in different manners) is essential. The type of algorithm (e.g., how an autonomous car functions and how it is directed) will strongly affect individual and social behavior and may cause unseens.

 

MC3: Networked, AI-driven, adaptive digital industry: Global industry becomes a computer-networked, AI-driven, data-based, IT security-sensitive system that can adapt flexibly to consumer (market demands) needs. The emergence of digital (blockchain, sharing-economy, bitcoin-like) economies of different kinds may become an even more substantial basic layer than the energy ([58]; yet the energy rebounds described by O’Deyer and Malone [58] are of high importance, the last year Blockchain energy consumption was equivalent to the energy consumption of Ireland) transportation, or analog communication layer for the Industrial Age.

 

MC4: The DNA personality: Data from the genetic sector are the most sensitive. Correlations between (tremendously cheap) DNA profiles and disease prevalence for health insurance or DNA-based intelligence properties for employment can be considered a starting point. The challenge is who will have access to such data, what ethical rules will be applied to handle the data meaningfully, and by what national or global rule systems/conventions this might be governed.

 

MC5: Speeds of transitioning: Different speeds of revolution: We are facing two transitions: (1) The digital, which is a fast (techno-social) one with severe impacts to society; and (2) a slow one to a sustainable form of living (proposed by Grunwald and Renn, sustainable transitioning or the “grand revolution”).

 

MC 6: Change of human-environment transitioning: The relationship between humans (i.e., human systems such as the individual, groups, companies) and their natural, technical, and social environments will change in the Digital Age. The digital world will function as a kind of moderator (i.e., a digital curtain). This causes what has been called reality shift (this idea emerged already in the Japanese ERT; [31]). This means that the (partly biased, individually shaped) digital curtain is providing a new disturbance variable and distractor for sharing common experiences and knowledge. Socio-materialism (or socio-data-materialism) emerges from the imbrication of the social (policy making) and the material (data inputs) that become entangled within time as people imbricate their agencies towards data-driven decision making process.

 

MC 7: Efficiency rebounds: Automatization by digital means is providing more-efficient resource management. This, in turn, may provide an increase of material flows, especially when material consumption of digital technologies (finite precious and rare earth metals) and the ecological side effects of material extraction are taken into account. Given the decreasing resilience of ecosystems, this calls for strategies and incentives to avoid negative environmental rebound effects and circular economy initiatives for digital technologies.

 

MC 8: AI, means or ends: There was a dispute during the European ERT on the topic of whether data/evidence-based, simulation-based, automated decision-making based on digital worlds might become real and in what domains this might take place. The question is whether computer algorithms might include context, complexity, human values (instead of current human opinions), etc. in a manner similar to humans, who have a biological organismic nature. In order to better understand the potentials and limitations within AI development, it appears to be important to understand AI not as a singular phenomenon but as being embedded in a hybrid environment of digital representations and algorithms and human agents constituting a new coupled cyber-social world of AI—just as there is no singular human individual but always a close network of human individuals and their social as well as cultural environment that makes them human in the first place. Furthermore, there is a strong need to develop digital environmental literacy in the sense that science and society discuss whether AI-driven decisions are conceived as a means or as an autonomously operating servant of smart/sustainable decision-making.

 

MC 9: Innovation is not positive per se: The question that any technology innovation is positive has been doubted. Human will, needs, and prospects are essential to consider. In addition, the terms “intended” and “unintended” have to be considered in this context (who intends what).

 

MC 10: Conceptual understanding of the Digital Age: If the double transformation of digitalization and increased sustainability pressures is to be taken seriously, existing modernization theories of how societies are structured and react to rapid change (such as Beck’s risk society, White’s network theory, or system theories from Luhmann) need a new conceptual foundation. New approaches must take into account the interconnection and co-evolution of human individuals (bodies and minds), technology, society, economy, politics, and culture.

5. Discussion

The discussion first refers to the propositions as a major element of the ERT. The clusters of unseens are first assigned to levels of human systems (Section 5.1). Then (Section 5.2), based on the CLA, we sketch salient overall changes and features in view of the European ERT (Section 5.2). We then (Section 5.3) turn to prospective action and refer to the messages of the living pinboard and the major conclusions identified directly after the ERT. Section 5.4 reflect on the strengths and weaknesses of the presented method of Proposition-based ERT. We end with some considerations on whether the digital transitioning is a stage of technology development (such as the invention of the automobile) or is of more fundamental nature.

5.1. Unseens on Different Levels of Human Systems

There is much concern and literature on certain unseens such as the loss of privacy or the loss of full employment by the digital transitioning. The former is a key issue of the individual, whereas the latter is a matter of economy and thus (also) of primary interest on the level of society. We will subsequently discuss what unseens have been identified by the European science experts above the level of the individual and then deal with levels above the individual.

5.1.1. The Human Individual

The loss of privacy and the finding of means of protecting privacy have been addressed in a couple of propositions (governmental means [A.6.2 and A.6.3], A.7.5 and A.10.2). The arguments cumulate in the statement that “mass surveillance violates the human right to privacy and it is form of cyberattack” (A.7.4). In addition, the benevolent and malignant, nudging based on personal Big Data as well as the coping with individually tailored fake news (see A.10.2), i.e., knowing whose information you may trust and believe in is a new challenge in the individual’s life, are included in the propositions.

From a psychological perspective, unseens of digital technologies were assigned to the psychoneurological sensitivity (see Figure 3; Cluster C2) of the human individual. Humans show limits in multitasking (e.g., solving a challenging problem when simultaneously responding to the e-mail alert). The spreading practice of being ubiquitously accessibility at any times for different issues is one reason of the fragmentation of life (A.4.2). This often results in loss of efficacy and efficiency and affects well-being.

The new digital etiquette (A.4.2) with others and the environment is increasingly patchy, disintegrated, virtual, and indirect interaction that does not allow for an empathic trust building or reliable judgment on the partners intention and preferences. This may be also relevant for the interaction between policy makers. For instance, some politicians switch from personal, empathy, mutual trust building- and partnership-based verbal (e.g., telephone-based) interaction or physical interaction to twitter short notice. The personal relationships (see Appendix A.4; [59]) resulting from a virtually shaped interaction factually differs from those when interaction with the human personal.

There is an evolutionary new form (e.g., two-dimensional screen-based pictures vs. a complex, co-evolutionary developing environment such as a complex tropical forest), density, artificial, and increasingly virtual (and thus evolutionary unknown) information. We may take from anthropology and human history that human is a highly adaptive species that may adapt to physically and socially highly different environments. If the digital environment does not meet the primal emotional needs (see A.4.4) human health and well-being may be endangered. Addiction, epigenetic and other measurable biophysical effects may result as unseens [4,59]. Interdisciplinary research and monitoring on health impacts of e-sports [60] seem to be necessary. Interdisciplinary research on monitoring and transdisciplinary processes including key actors on health impacts of e-sports seem to be necessary.

The access to the genetic code provides another critical unseen. Assessing an individual’s DNA costs just about US$30. And there is increasing knowledge to judge the risk for certain diseases based on the DNA data and a most recent paper in Nature Reviews Genetics confirms the concerns expressed in MC6 (Box 1). Some countries (such as Switzerland or The Netherlands) are going to prepare laws which allow or even demand health, life, or disability insurances to ask for DNA and adapt insurance costs to the DNA profile (A.5.1). Genetic privacy, perhaps the highest-level privacy, seems to be in conflict with severe economic and other interests. Given that the 193 countries that are members of the United Nations (and inner country federal state laws) differ essentially, this case shows that global regulations are needed to protect the individual. The importance of this issue is stressed by a recent review. Large scale studies including more than one million subjects show that “20% of the 50% heritability of intelligence” can be predicted by genome-wide polygenetic scores.

5.1.2. Human Groups

Small groups build a primary evolutionary entity which forms the individual personality of humans [61]. Group norms, goals, hierarchy structures, decision rules, rewarding and penalizing behavior, rules for being a member etc. [25,62,63] and the identification and differentiation of groups have been an essential part of socialization in all cultures. Internet groups show similarities and differences [64] which may be beneficial and negative for certain type of people and for different purposes. Diversity of information and expertise among group members has been identified as a crucial ingredient of collective intelligence.

There is a basic interpersonal need to belong to a group whose members share interests, values, etc. On the digital web, there is a large scale of online groups, chat rooms, etc. which allow to build virtual groups or well-organized digital heterogeneous communities across the world [65]. Critical unseens may emerge from overcoming loneliness, (different forms of honest, positive). This may lead to self-disclosure [66] which is misused when personal data are transmitted by others to the public.

5.1.3. Organizations (Companies)

The propositions just focused on commercial organizations (i.e., companies) ranging from industry, via various forms of Internet companies, to financial institutions. Unseens for noncommercial organizations have not been considered.

Much focus has been given to changes related to production. The governmental German Industrie 4.0 initiative promotes the aggregation and synchronizing of data and processes on different levels of manufacturing and production (A.1.1). This increases efficiency along the supply chain. Yet, allows for new risks of industrial espionage and data security. The factor knowledge and data become a new critical entity also on the business level (A.2.1). A new, digitalized and networked supply, for instance, may endanger valuable technical know-how of small and medium sized industry. Thus, in order to become negatively affected by the digital transformation, the given case SMEs should develop strategies that help to decide what digital technologies should be introduced when to keep the viability of the enterprise. This vulnerability assessment is factually subject of a recent method that has been applied already to many companies [40].

5.1.4. Institutions (Governmental Organizations)

Public services are becoming digital. There is a trend on automated decision making based on Big Data of the residents and the cities. The “war against drugs,” terrorism, etc. promotes the storage of large personal and economic data from residents, companies, political actors, etc. Following the European democratic principles, unseens may emerge from various sources: (i) Often, the roles, actors, and data owners are not clearly defined (A.6.1); (ii) data may become accessible to semi-public organizations or other countries whose legal regulation and data are collected; and (iii) data security may be questionable given the large number of public servants working on data to establish resilience digital data governance models (A.6.3). Viale Pereira and Parycek (Appendix A.6) stress that not only a responsible use of public data but also the relations of the citizens to algorithms may cause problems and ask for regulations.

5.1.5. Societies (Nation States)

Digitalization will change the main components of society (i) economic system; (ii) political and legal system; (iii) the social and cultural system; (iv) scientific and educational system [25,67,68].

Platform economics (A.1.4), global customer driven production (A.1.3), knowledge economy (A.2.1), home offices and new forms of freelancing (A.3.3), AI driven machines (A.7.5, see also MC8), crypotoeconomics (A.9.2, targeting a decentralized economy without political structure, legal system, geographic location [69]) and the increasing role of (digitalizable) knowledge (A.2.1), virtual products etc. will generate new economic structures, agents, and processes.

Strong impacts have been expected in the fields of public governance (see Section 5.1.4) and politics. In politics, unseens are related to Big Data analytics-based nudging (A.10.2) that calls for careful attention.

Culture has only been addressed by digital etiquette (A.4.5) on the level of the individual. But, the behavioral change on the level of the individual and small group is transforming interpersonal communication, trust formation, etc. as components of societal culture will fundamentally change [70].

The unseens with respect to the scientific and educational system have been addressed in the context of ethics (A.8.2). Digital representations and digital technology fundamentally change the whole scientific system. This goes beyond the world wide web-based real-time interaction among scientists, measurements etc.

5.1.6. Human Species

Many of the identified unseens address the level of the human species. This relates to

• the fundamental redefinition of human labor which asks for new forms of higher knowledge resulting in a new form of digital divide including a potential loss of what is conceived traditionally as labor (A.1.2, A.2.3 and A.10.3)
• the emergence of (digital) knowledge economy (A.2.1) when (digital) knowledge (and data; i.e., digitalized labor; A.2.2) supplement capital, labor, in this context also surveillance economics in which personal data are of economic value may taken as example [71], as suggested by one of the reviewers of this paper, digital technology may be conceived as an affordance to which any economic transaction has to adapt
• new forms of property rights are required to avoid economic imbalance as both the self-learning AI machine and the data provider contribute to new knowledge and economic values (A.2.4)
• efficiency rebounds result by hedonistic, amenity value driven demands ( A.3.1 and A.8.3)
• digital (intentionally resilient) public governance [72] and democratic capitalism (A.9.3) which may, however (in a critically long transition period (A.6.1 and A.6.2)) be endangered by deceptive, antidemocratic and self-enrichment oriented cyberattacks, and
• cyberwar on all levels of human systems, ranging from the individual to global networks of people and countries (A.7.2)

Admittedly, this set of examples rather refers to the darks side of possible developments. And they are in contrast to the often positive, sometimes enthusiastically optimistic visions expressed in many propositions. But this, vulnerability shaped view on unseens may be conceived as an important means of resilience management. We may also incorporate the proposition of the first author presented at the Japanese ERT on various vulnerabilities related to directed evolution (of plants, animals, and humans) by the mastery of genetic engineering (see B.5.2; this has been expressed by a European participant). Finally, the change of the science system by using digital technology for recording data, communication among scientists, fighting plagiarism and fraud in data fabrication, automated scientific discovery (e.g., by AI-program-based planning of sequential experiments), computerized mathematical proofs causation (see A.8.2) has been mentioned and discussed. Yet, naturally, the before-mentioned issues are incomplete, also as certain perspective were missing at the European ERT.

5.2. Developing a Bigger Picture on Major Unseens

The development of a bigger picture is done when summarizing the major communalities among the unseens (Section 5.2.1) and when relating the major conclusions (see Box 1) of the European ERT (Section 5.2.2).

5.2.1. Clusters of Unseens and Common Patterns in Ways of Evaluating Unseens

Both, the middle clusters of Figure 3 Smart factory, labor market and justice (C3) and Economic change and rebounds (C4) indicate that the ERT considered production and economy as an important domain if not as kernel of the digital revolution. However, as indicated in the label of C4, besides changing the economic and the financial systems (which may include specific unseens), environmental rebounds build another sub-cluster. Cybernetics and warfare (C1), which include unseens related to data security (as the concept of war requires some redefinition; A.7.1), are related with regard to content. The ambiguous, double-edged sword nature of the digital transitioning, which is characteristic for any technology innovation, is ubiquitously visible.

The neuropsychological sensitivity (C2) has been mentioned on the level of the human individual and (small) group. But technology has been a key factor of the cultural evolution all along the history of humankind, human life will look like different after the digital transitioning than before. Certain domains of the mind and the body will be trained and developed in a more pronounced way.

Finally a proper digital technology-based society asks for new forms of governance (C5) and ethics (C6). Ethical dilemmas linked to learning machines (A.8.5) may call for new ways of looking at humankind.

5.2.2. Overarching Aspects of Interdisciplinary Research (Goal 2)

The clustering of the main properties used to classify the unseens provides quite a comprised picture. We may conclude that the power of the digital, based on digitech and digitech knowledge is promoting (i) a renewal of the economic system and (ii) launching a digital democratic system. There is concern with respect to (iii) protecting the losers of the digital transformation, particularly approaching a personal and societal resilient society in a fundamental process of (iv) redefining humankind that calls for basic philosophical, ethical, and epistemological questions of general interest. The identified as subjects may well serve as overarching aspects for restructuring research (Goal 2).

5.3. Additional Results and Follow-Up Activities from the Proposition-Based Science ERT Discussion

The above discussion much focused the proposition. They were individually prepared by the experts when relying to their perspectives and disciplines. But what new outputs and perspectives emerged from the interaction among the science experts. What has additional views developed across the perspectives (see Section 4.2 and Section 4.3). What topics for transdisciplinary processes have been identified? (Goal 3)

When referring to what has been discussed before, the following additional issues emerged from the ERT:

The economic value, ownership, access and use of data including data theory and governance, has been discussed in depth (MC1). This discussion has been related to control systems, transparency, and ethics of algorithms that govern data processing in an increasingly automatized, AI-driven digital world (MC2). Thus, in terms of Table 1, the understanding, praxis, and management of the basic elements of digital technology, the storing, retrieving, and transmitting digital data and the processing—i.e., the application of algorithms (see also A2.1, A6.1, A6.4 and A8.3) raised special concerns. In this context the discussion on how to deal with DNA data (MC4) raised special concern. We may think that this issue may become a global learning field for rethinking how privacy may have to be reconsidered.

Somewhat surprisingly, as transdisciplinarity processes were demanded in A10.4 and during the process, there have been no direct inputs on topics that may become subject of transdisciplinary processes (Pinboard 4). Yet right after the ERT the idea emerged that private, commercial, and public agents may be interested to reduce the vulnerability and to increase the resilience of the global digital world. This may include the identification of loopholes in the global legal system, weaknesses in the implementing executive control of legal regulations (such as the Amendment of the European Data Protection Regulation [73]), to focus critical issues such as privacy by design, to identify (ongoing potential) deficient behavior of actors (and to develop strategies to cope with this) by relating the knowledge of key representatives from key stakeholder groups with that of scientists working on sustainability and digital environments (SDE). The objective of the transdisciplinary process (which is under planning by the Institute of Advanced Sustainability Studies, IASS Potsdam Berlin, and right refers to MC1) include of self-declaration of key stakeholders on responsible data use and the draft of ethics principles from a practitioner and a scientist perspective.

Two—more theoretical—insights not yet included and the proposition (discussed above) deserve mentioning. One is on different speeds of change of technological, socio-cultural, and biotic-genetic systems. We think that this issue asks for a thorough reflection, in particular when proper means of mitigation, adaptation, and interventions (as not any innovation is positive per se; MC9) are targeted. Another refers to the new evolutionary dimension of AI, which alters the human–environment relationship, introduces socio-digital/material systems. And thereby calls for a thorough, reflexive understanding of the Digital age (MC 6, MC 8, MC 10.).

Finally, the European proposition-based science ERT on SDE has been considered that the seminal way to structure the changes and unseens from different disciplines. Thus, the initiators of the Japanese and the European ERT will launch further ERT to support a resilient digital transitioning.

5.4. How Do the Japanese and the European ERT Differ and Complement Each Other?

The Japanese ERT also focused on the potential unseens of the economic transition, such as platform lock-in by the oligopoly of platform providers (B.1.1) and AI-induced underemployment (B.7.1) or low-capability franchise workers, which can result in a new stratum of the poor in a society. Although some participants had backgrounds in political science, the changes to democratic systems (though mentioned in one proposition referring to Internet monopolies; B.4.1) have not been in the foreground as much as they were in the European ERT.

Much attention has been given to risk management (B.3.2 and B.6.1), in particular to black-swan risks, e.g., new systems of digital risk resulting from the interconnectedness of an IoT world. Here, the threat that one monopolitical enterprise may stockpile all intelligence has been seen as a potential unseen (B.4.1)

With respect to the individual, the imperialistic spread of US-Western culture by the Internet (B.2.2), i.e., the reality shift caused by individually shaped, biased information channels that are not corrected by “evolutionary feedback loops” (B.1.2), have been named in a pronounced manner. Finally, biotechnological governance (B.5.1 and B.7.2) based on the management and engineering of DNA and biocomputers as a new form of cognitive, hybrid decision-makers (see 1.4 above, B.5.1, and Appendix B.1) was mentioned.

The cultural differences have been presented earlier in 1.4. One of the Japanese experts stressed that the apocalyptic concerns shared by many Western authors about technological singularity, where a future superintelligence substitutes for and suspends humankind, is not shared by many Japanese. In line with this difference, in Japan there is a much stronger desire among experts and the public “to co-inhabit with AI and robots” [31] than there is in Western cultures. The role of religion and worldview, here, that of Shintoism and Confucian thinking regarding the preference for humanoid robots, has been explained in 1.6 as the differing understandings of the role of academic knowledge in transdisciplinary processes. Transdisciplinary processes have also been recommended by the Japanese ERT. Yet, whereas in Europe transdisciplinary processes generally include both representatives from key stakeholder groups (e.g., of people concerned) and representatives from different scientific disciplines on an equal footing, according to Confucian thinking and practical order, those who are expected to know (i.e., academia) should take the lead.

5.5. Constraints of the Method of Proposition-Based Expert Round Tables

Round tables are a common means of looking at one and the same issue from different perspectives. A round table, such as panel discussions, allows a certain set of invited people to exchange, discuss, supplement, explore, examine, question and to (gently) verify certain views on an issue. From a methodological point of view, we used the ERTs as a means of triangulation for better understanding and ranking unseens and the ways in which science and transdisciplinary processes may serve to deal with them properly. We should note that not only the content has to be triangulated. This has been done in the present case by perspectives. In order to develop socially robust orientations, Triangulation should also refer to disciplines (and the included modes of validation; this has been), worldviews, philosophy of science perspectives, and other issues. The exceptional broad scope of disciplines (including natural, engineering, social sciences and humanities) has been promoted by the choice of the perspectives.

But the presented ERT went beyond an ad-hoc single meeting round table as it included elements a Delphi-like multistage process [74]. Experts were asked to present (proposition on the) the most important unseens from their own perspective and the initial input was evaluated and adjusted in form and content after feedback of the organizers of the ERT. All experts gained in-depth insight into other experts’ views and referred to a set of definitions of key terms that were included in a jointly shared and produced workbook that included the propositions. After a full day of listening to each other, the main impact factors and features of unseens, missing knowledge about them, and suggestions what issue may be better understood by science were discussed (see above the living pinboard technique). And, based on an in-depth cluster analysis, the main domains of society and common features of the ERT were identified. A preliminary analysis using these methods was also used as input for formulating main conclusions which much resemble the aspiration of policy Delphis to obtain reliable orientations [75] before decisions are taken.

If we think about the critical, biasing, artefactual side of the chosen methodology attention has been paid to questions such as: Are proper goals and questions to be answered by the (right things) properly addressed? Is the set of perspectives addressed by the right experts well chosen? What experts, with what expertise, cosmology (including philosophy of science perspective) or with what self-conception as scientist (e.g., public good vs. advocacy) are chosen? We will just answer the last question. In autumn 2017, the discussion on Europe was not formed by a single special event (such as the Facebook-Cambridge Analytica case, March 2018) that affected the ERT. There, public media at that time were much shaped by discussions on deliberate computer attacks and nudging of citizens in the course of elections.

6. Conclusions

Taking ten different perspectives, seventeen European science experts provided forty-two propositions on unintended side effects (unseens) of the digital transition. Based on this carefully deliberated and written input, a full-day exchange about features, sources, critical developments, intersecting issues, and potential transdisciplinary processes was achieved. The written inputs, the round-table discussion, and the follow-up content analysis (based on cluster analysis) resulted in an interactive, structured (Delphi-like method) method, which we call a proposition-based expert round table. The application of the method allows for the following conclusions.

Digital technology, conceived both as the knowledge about and the physical manifestations of digital technologies, induce, first, a most fundamental renewal of the industrial and (capitalist) economic system. The intangible, potentially non-scarce, and (principally) ubiquitously accessible asset “digital data and knowledge” is supplementing capital, labor, and natural resources and altering processes and restructures of the supply chain (e.g., by IoT based production and platform economics). Likewise, second, (an infrastructure-like) digital public service and democratic system are developing. We should note that inner science unseens (such as dealt with in Appendix B.1) have not been subject of the European ERT.

Like any technological transition, the Digital Revolution is a double-edged sword. Thus, special attention has to be paid to unseens. The European ERT argues that, third, protecting the losers of the digital transformation is a major challenge on the pathway to sustainability; losers here refer to people, companies, and other human systems that cannot (sufficiently) adapt to digital economic processes. Here, individuals and human groups that show sensitivities with respect to critical issues (e.g., internet addiction in various forms) are one example that requires more attention. But in addition, the subtle, individually biased, or even manipulated information and nudging processes that endanger the very foundations of democratic processes call for better understanding and counter-strategies. Thus, ownership, economic value, use, and access to digital data are key steps on the way to a personally and societally resilient digital society. The (market) value of personal DNA data may play a special role in the future (see Box 1, MC4). What route will be taken here much depends on the decisions (and behavior) of policy makers, industrialists, and individuals.

The process of substituting cognitive processes with AI-based digital technologies is presumably the most fundamental transition in sociocultural human evolution. This is indicated by the landmark idioms redefining labor, democracy, or humankind. The natural, technical, social, and humanity sciences are challenged to contribute to a better understanding of fundamental questions referring to data governance and potential, and the limits of algorithmification; the essence of digitally shaped biotechnological systems and engineering as well as bionic systems; various forms of vulnerabilities of natural and human systems; and the roles of religion, ethics, and culture as prerequisites for understanding and forming the Digital Age. These issues, on the one hand, call for integrated, cross-disciplinary, and interdisciplinary research supported by the frame of sociotechnological vulnerability and resilience analysis. On the other hand, societal-sustainability learning may be supported by transdisciplinary processes in regard to certain complex unseens whose understanding and management call for utilizing experiential expertise from practice and sound, high-quality scientific knowledge from different fields of science. We are convinced that science-expert roundtables such as the European and the preceding Japanese one may help pave the road to a more sustainable future.