Cutting-edge technologies sustainability assessment towards EC Digital
Decade 2030 Compass objectives
EGILS GINTERS
Riga Technical University,
Riga, LV-1658
LATVIA
Abstract—In 2022, the EC Digital Decade 2030 Compass identified seven cutting-edge digital technologies, the
development of which will receive special attention in the coming years. Digital technologies are a specific type of
technology that is critical to the existence of today's society. Failures in technological development can have fatal
consequences, so assessing the sustainability of digital technologies is a very important task.
The aim of the study is to assess the sustainability and potential risks of development of the proposed cutting-edge
digital technologies.
Two-level Integrated Acceptance and Sustainability Assessment Model (IASAM) is used to assess sustainability,
where digital technology acceptance and sustainability assessment is first performed using system dynamics
simulation and Skype reference line modulation to calculate the sustainability index. Subsequently, Bayesian acyclic
networks are used to assess potential risks. The simulation results indicate the potential sustainability risks of some of
the digital technologies and industries mentioned in the EC Digital Decade 2030 Compass.
The article can be useful for digital sustainability researchers, investors and new digital technology developers.
Keywords—Digital technology, systems sustainability, system dynamics simulation, IASAM model, sustainability
risks assessment, Digital Decade 2030.
Received: April 21, 2021. Revised: February 8, 2022. Accepted: March 10, 2022. Published: April 6, 2022.
1. Introduction
HE European Commission's (EC) Digital Decade 2030
report set out basic guidelines for the further development
of digital technologies [1]. The guidelines form a multi-level
pyramid (see Fig. 1), the highest level of which defines
activities aimed at the development of democracy, which
contain a high proportion of the digital component.
For example, the priority of human resources, solidarity and
inclusion, freedom of choice, e-participation, safety and
security, and Sustainability as well. These democracy-
building activities are based on a heterogeneous set of digital
services, such as artificial intelligence, data governance, data
spaces, online platforms, cybersecurity and media pluralism.
In turn, these digital services will be provided by the
purposeful development of specific cutting-edge technologies.
Document [1] identifies seven digital technologies: Digital
Twins , High-Performance Computing , Digital
Wallet , Quantum Computing , Microelectronics
, Blockchain and 5G Communication .
Fig. 1 EC 2030 Digital Decade (Digital Compass) ([1] modified by
authors)
The specific concept is contradictory and ambiguous. For
example, in 2021 Augmented and Virtual Reality (AR/VR)
combined use with Robotics (RPA) were promoted as the top
emerging technologies [2]. At present, the above technologies
are no longer mentioned in the Digital Compass 2030
guidelines. Have the goals been achieved then? Of course not.
It is not clear by what criteria Artificial Intelligence (AI) is
included in Digital Compass 2030 at a higher level of
hierarchy than Digital Twins. It should be the opposite, as AI
usually serves as a component of Digital Twins rather than the
other way around. Why is Digital Twins included in this
T
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pyramid at all, because from a modelling point of view this is
traditional method, rather than technology, has been used for
decades? The essence of Digital Twins is to test the possible
follow-up using asynchronously or synchronously modelling
or simulation of a problem. That is, it is a daily practice in
making any important decisions. Perhaps that the reason for
the inclusion of Digital Twins in the Digital Decade 2030
pyramid is the ignorance of model-based decision-making
approach at the level of policy crafters [3].
Why are both High-Performance Computing and Quantum
Computing emphasized as supported technologies? Perhaps
that the aim is to accelerate the development of Quantum
Computing, which has been waiting on the Gartner curve [4]
for more than a decade without real success.
Another important problem is the incomparability of the
nominated cutting-edge technologies. It is not possible to build
a pyramid of regular size, including blocks of different sizes
on one level, at least the ancient Egyptians did not.
The authors [5], based on the Dijkstra hierarchical layers
approach, identified the features of the core digital technology,
and in particular:
1) Self-sufficiency - the technology is considered to be used
independently.
2) Problem-orientation - the technology has a specific
problem-oriented use.
3) Integrability - the technology can be used to create other
technologies, complementing the newly created goal
technology with a set of attributes belonging to the
underlying technology.
The above classification is necessary to identify groups of
core technologies that could be more or less comparable to
identify hidden and unanticipated factors influences, which
will significantly affect the risks of further development of
cutting-edge technologies [5].
Based on the above criteria, 5G Communication, Digital
Wallet and also Blockchain technologies can be considered to
meet the characteristics of a digital core technology. However,
the use of Digital Twins, High-Performance Computing and
Quantum Computing is too general. Microelectronics is the
basement of any digital technology. Microchip is part of any
digital device, but it is not self-sufficient. Microelectronics can
be considered an industry, but its nomination for cutting-edge
technology could be challenging.
According to the hierarchical model of Digital Decade 2030
Compass (see Fig. 1), sustainability of technologies is at the
same time a precondition for the sustainability of the
development of democracy in society. Despite the fact that the
conceptual model of Digital Decade 2030 is debatable, the aim
of the article is to assess the sustainability of the cutting-edge
technologies included in it, in order to understand the
reliability of the digital development directions set by the EC.
Using the system dynamics simulation-based IASAM
methodology [6], the sustainability forecasts of the
technologies included in the first level of the conceptual
Digital Compass 2030 model will be assessed, but the
potential risks of sustainability development will be predicted
later.
The results of the study may be useful for researchers of
sustainability, policy makers, as well as technology developers
and investors who want to assess their future prospects a
priori.
2. Sustainability Development and Risks
Assessment of Cutting-Edge Technologies
The global dominant approach to sustainability assessment
is based on the Triple Bottom Line (TBL) model, which
identifies the potential impact of a product / technology on
society, business and the environment. There are more than a
hundred different sustainability assessment methods, mainly
used to assess a variety of large projects with significant
environmental impacts [5]. These methods are based on
labour-intensive surveys of third parties / experts, usually
ignore technology acceptance and adoption phases, and are
difficult to adapt to assess the sustainability of other projects.
Because engineers and investors need faster and cheaper
sustainability prediction that provide self-assessment
capabilities, the authors [6] have developed and validated the
IASAM model, which is based on systems dynamics
simulation and Roger diffusion theory. Sustainability is
assumed to be characterized by the interaction of four impact
streams, which is modulated by the Skype reference curve.
The sustainability index of technology is measured in
skype units, which provides good perception and interpretation
possibilities:
(1)
where:
1) – technology acceptance flow, which
characterizes the society's desire to use the goal
technology.
2) – management factors flow, which
describes the resources available for technology
development, implementation and maintenance.
3) – quality flow, which characterizes the
essence and specifics of technology.
4) – external factors flow, representing
market position, political factors, competitive aspects
and other relevant parameters that may affect the
sustainability of the technology / project / product.
The peculiarity of the IASAM method is the assessment of
the sustainability index by analysing the impact of technology
on society. Studies [5] have shown that the inclusion of the
business and environmental pillars in the model is not useful
in assessing the sustainability of digital technologies. This
does not mean that digital technology has no impact on
business or the environment. Of course, such effects do exist,
but their importance is insignificant compared to the impact of
digital technology on society. The impact of digital technology
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on the other two pillars is implicitly respected in the IASAM
model.
Respecting the paradigm set out in the EC 2030 Digital
Decade Compass [1] and the objections mentioned in the
previous section, seven cutting-edge technologies
, were evaluated by IASAM implementing a
self-assessment of sustainability (see Table I).
2.1 Initial Conditions
During the self-assessment, it is assumed that all four
impact streams that determine the sustainability index have the
same weight. All factors that determine each flow of influence
have the same weight. The result of the evaluation is a trend
towards sustainability, which is a comparative perspective for
the development of each technology in the future. The result
of the flow estimation in absolute values is done according to
the Likert 7-point scale. The interpretation of the value of the
sustainability index is performed in accordance with the
breakdown of sustainability groups set by the IASAM.
Sustainability self-assessment reliability is not statistically
validated.
2.2 Results
I. Cutting-edge technologies sustainability index (skypes)
Item
Management
(% of max)
Quality
(% of max)
Domain
(% of max)
Acceptance
(% of max)
Sustainability
index
(skypes)
– 5G
Communication
80
68
76
89
0.78
–
Blockchain
84
73
74
74
0.76
–
Microelectronics
79
57
90
58
0.70
– Quantum
Computing
67
46
75
49
0.59
– Digital
Wallet
84
74
73
79
0.77
– High-
Performance
Computing
82
61
86
66
0.73
– Digital
Twins
82
73
86
76
0.79
A comparative graphical representation is shown in Fig. 2
and Fig. 3.
Fig. 2 Cutting-edge technologies sustainability development
assessment
Fig. 3 Comparative representation of influencing flows
Assessing the risks to the sustainability development of
technology is very important.
Digital technologies are a specific type of technology with a
high stochastic component and are determined by
unanticipated and hidden factors. This means that the
sustainability forecast requires a risk adjustment
: . (2)
The authors [5] have developed a Bayesian network model
for assessing the risks to the sustainability of digital core
technologies in the BayesFusion [7] GeNIe environment,
which identifies the following main groups of hidden and
unanticipated factors
that determine uncertainty of
digital core technology:
(3)
where
- determined and systematic impacts;
-
unexpected stochastic externalities;
- the age dynamics
factor;
- technology self-development possibilities;
- unexpected use;
- unanticipated consequences;
-
dual-use possibilities; and
- emerging incentives.
In the factor interaction model (see Fig. 4), it is assumed
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that the correction of the sustainability forecast and at the
same time the total uncertainty attribute
of the
technology corresponds to
.
The influence of the network of factors
on
uncertainty attribute
is characterized by (4):
(4)
Fig. 4 Bayesian network of digital technology sustainability
assessment risks
Based on (4) and [7], it is possible to perform cutting-edge
digital technologies unanticipated risks self-assessment
(see Table II), which practically reflects the reliability
of sustainability forecast .
II. Reliability of cutting-edge technologies sustainability forecast
Item
Evidence
Sustainability risks
– 5G
Communication
H
M
H
L
L
M
M
H-46%
M-8%
L-46%
–
Blockchain
M
H
M
L
H
M
L
H-46%
M-8%
L-46%
–
Microelectronics
M
L
L
L
L
L
H
H-8%
M-8%
L-84%
– Quantum
Computing
M
M
L
L
L
H
L
H-46%
M-46%
L-8%
– Digital
Wallet
H
L
H
L
H
L
H
H-8%
M-8%
L-84%
– High-Performance
Computing
H
L
L
M
L
M
L
H-46%
M-8%
L-46%
– Digital
Twins
M
H
L
M
L
L
L
H-8%
M-8%
L-84%
(H – high, M – medium, L – low)
3. Interpretation of the Results and
Risks of Sustainability Assessments
The interpretation of the results is based on belonging to a
certain group of sustainability index intervals. The IASAM
assessment methodology identifies four groups of
sustainability indices (see Table I):
1) [0-0.25[- corresponds to a low level of sustainability and
shows that the development of technology, according to
the IASAM criteria, is unpromising.
2) [0.25-0.5[- identifies questionable prospects for
technology development, with technology acceptance
being a particular concern.
3) [0.5-0.75[- shows that the technology under assessment
meets the IASAM sustainability criteria well enough,
however, during the development of the technology,
careful monitoring of impact factors must be performed.
4) [0.75 - 1] - determines the prospects for good
development of the technology, however, it would be
useful to repeat sometimes sustainability assessment.
Based on the grouping of the above indices, it can be stated
that none of the technologies mentioned in Digital Compass
2030 are expected to fail. On the other hand, the sustainability
prospects of none of these technologies are so excellent. The
success of the sustainability development of 5G
Communication, Digital Twins, Blockchain and Digital Wallet
is not in doubt. On the other hand, the prospects for the
successful development of High-Performance Computing and
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Microelectronics may be hampered. Quantum Computing's
development prospects are in great doubt.
The analysis of impact flows shows that there is no
technology that has received the best or worst ratings in the
evaluation of all flows. Each of the technologies has different
advantages and disadvantages that determine their overall
sustainability rating. The architecture of any technology
consists of logical and physical structures, where the logical
structure consists of methodology, guidelines, algorithms,
rules, etc., but the physical structure is the environment for the
implementation of the logical structure, that is, hardware,
software, etc. [8]. In assessing digital technology, both sides of
the architecture must be considered equally important.
Quantum Computing received the lowest value in the
management flow assessment. This is not surprising, as
theoretical advances still dominate and there is still a long way
to go before an industrial solution can be found. Lack of
adequate quality management and service staff can be a
problem. Is there a legitimate expectation today to make a
fundamental breakthrough in the development of technology
that has been on the Gartner curve [4] for many years? No
such justification has yet been found.
Quality flow leaders are Blockchain, Digital Wallet and
Digital Twins. These technologies have long been known and
tested in various applications. Quantum Computing, on the
other hand, has unanswered questions about hardware,
infrastructure, and the choice of specific methodologies, and,
of course, the potential costs of the technology are debatable.
The challenges of Microelectronics development are related to
the significant expansion of the industry, which can lead to a
shortage of qualified personnel and infrastructure. Production
costs in the EU will be significantly higher, followed by
higher final product prices. Delays in the development of 5G
Communication are related to infrastructure development
problems, as the subscriber's distance to the connection point
must be less than in previous technologies. In addition,
communication equipment is more expensive.
The socio-political and market factors that determine the
Domain flow are very favourable for the development of
Microelectronics and High-Performance Computing, as the
market niche is quite wide, while the sustainability of Digital
Wallet is successfully influenced by a strong political lobby.
One might ask here why Digital Twins are so highly rated? It
is a non-objectionable technology that benefits all industries,
at least for as long as real AI use is not significantly
represented in decision-making tasks.
The flow of Acceptance in technology sustainability
assessment is fundamentally important in a democratic
society, because nothing can / should happen without public
acceptance and against the public interest. It is a stream that is
often ignored by project developers and evaluators. In this
case it is considered that all four impact flows of sustainability
factors are equally important. The potentially high costs of
Quantum Computing will be difficult to explain to the society,
as no obvious and rapid benefits are expected within a
reasonable timeframe. Will the society accept more expensive
household appliances and other electronic products if they will
be built using EU-made chips? This is a very challenging issue
for the development of Microelectronics. In turn, respecting
the heritability of technology, the society will successfully
accept 5G Communications, which has already proven its
viability. Various theories of conspiracy and even an objective
increase in electromagnetic pollution is unlikely to affect the
society opinion. Digital Twins will not have a direct impact on
the citizens in the near future, but Digital Wallet technologies
in various basic forms have been used successfully for several
years. Blockchain acceptance is a bit more problematic
because the technology increases security but consumes the
time and effort of the citizens. Will the society be prepared to
pay with the increased security? It depends on how sensibly
and proportionately this technology will be introduced.
The above sustainability assessment of Digital Compass
2030 cutting-edge technologies is subjective and shows
possible sustainability development trends of technologies.
Theoretically, this subjectivity can be reduced by selecting a
set of experts who could repeat the assessment. Traditional
statistical processing tests can then be performed to assess the
reliability of the results. Unfortunately, the subjectivity factor
will not go away, because who will be the independent experts
in this case and who will set up this set of experts? Will they
be competent and experienced enough digital technology
professionals, politicians or business people? What will be the
proportions and weight of these groups in decision-making?
These are questions for which the authors do not yet have a
reasoned answer.
Development risk assessment (see Table II) can be
considered as a partial validation of the sustainability forecast.
In fact, the risks to the sustainability of technology are related
to the impact of society and the external environment. The
results of Bayesian modelling show that the development of
Microelectronics, Digital Wallet and Digital Twins have green
light and their sustainability is not threatened.
In turn, monitoring the development of sustainability is
necessary for 5G Communication and Blockchain
technologies, because the subjective attitude of the society will
be ambiguous and polarized. However, these risks are not
critical and do not jeopardize the success of these
technologies.
This is difficult to explain, but similar risks are associated
with the further development of High-Performance
Computing.
Unfortunately, the development of Quantum Computing is
the riskiest from a sustainability perspective. The assessment
does not suggest that development will fail, but the risks of
unexpected results are quite high.
4. Conclusion
Today, we live in a digital society in which every activity,
from the provision of living conditions such as utilities,
electrification, transport, healthcare and others, is based on a
variety of digital technologies.
Digital technologies are a specific type of technology that is
characterized by a set of interacting attributes that distinguish
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them from other types of technology. While Performance,
Complexity, and Reliability are common to most modern
technologies, the attributes of Pervasiveness, Evolutionism,
and Uncertainty are special and characterize the stochastic and
unpredictable effects of digital technology.
The impact of digital technologies on society is critical.
Changes in the functionality of digital technologies, thanks to
artificial intelligence as well as automatic self-diagnostics and
reconfiguration, and prototyping capabilities, can be lightning-
fast. This means that even small mistakes can have
unpredictable consequences. Digital core technologies are an
integral part of almost any other technology, so the balanced
development of digital technologies that contribute to society's
progress is important to society. This means that digital
technologies must be sustainable.
In order to determine the sustainability of digital
technology, acceptance must first be assessed, followed by an
analysis of the quality of the technology and the flows of
internal and external socio-economic factors. The flows
interaction characterizes the digital technology sustainability
index, which is measured in skype units according to the
IASAM system dynamics model. The above approach allows
for a self-assessment of the sustainability of new and existing
digital technologies and for identifying the future prospects of
each technology.
Digital technologies are characterized by Uncertainty,
which is a critical attribute to the successful development of
technology and poses significant risks to its sustainability.
Uncertainty is mainly determined by the interaction of hidden
and unanticipated factors described by the IASAM Bayesian
acyclic network. The impact of potential risks determines the
reliability of the technology's sustainability forecast.
The EC Digital Decade 2030 Compass identifies seven
cutting-edge digital technologies / industries that will receive
special attention. The selection of emerging technologies is
debatable, so the authors performed a sustainability
assessment and risk calculation of the nominated items.
The results of the self-assessment confirmed the
sustainability of the EC Digital Decade 2030 Compass
cutting-edge digital technologies, but identified some
technologies whose development prospects could be
problematic.
This study serves as an example of the use of the IASAM
methodology, the results of which could be of interest to
technology promoters and digital policy crafters.
Further research will focus on the development of the
Bayesian model of unanticipated risk factors, specifying the
interactions between the factors and the intensities of their
effects.
Acknowledgment
The article publication is funded by LZP-2020/2-0397
“Latent Impacts on Digital Technologies Sustainability
Development Assessment (LIASAM)”.
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