Notat og høringssvar om hvidbogen om kunstig intelligens

Udenrigsministeriet
Asiatisk Plads 2
DK-1448 København K
Telefon +45 33 92 00 00
Telefax +45 32 54 05 33
E-mail: um@um.dk
http://www.um.dk
Girokonto 3 00 18 06
Medlemmerne af Folketingets Europaudvalg
Bilag Sagsnummer Kontor
3 2020-1125 EKN 18. juni 2020
NOTAT
Høringssvar til hvidbogen om kunstig intelligens
Til underretning for Folketingets Europaudvalg vedlægges Erhvervsmi-
nisteriets notat, høringssvar samt bilag vedrørende regeringens hørings-
svar om hvidbogen om kunstig intelligens.
Jeppe Kofod
Europaudvalget 2020
(Omtryk - 18-06-2020 - Notat tilføjet) KOM (2020) 0065 Bilag 5
Offentligt


NOTAT
Annex: Specific comments from the Danish Government on the white
paper on artificial intelligence
Specific comments
An ecosystem of trust: Regulatory framework for AI
The overall aim must be to create a regulatory framework where trustwor-
thy, ethical, safe and secure AI goes hand in hand with the ability to provide
innovative solutions. This regulatory exercise must also include stocktak-
ing of existing legislation in order to make sure that existing legislation is
up to date and is able to address specific issues related to AI. A stocktaking
process should also ensure that potential new legislation does not overlap
with existing requirements.
The General Data Protection Regulation (GDPR) has illustrated how the
EU has been able to set global standards. However, the subsequent demand
for guidance on how to adhere to the new standards showed the importance
of legal clarity and user centric guidance. Therefore, clear and operable
regulation is a precondition and must be factored in from the outset when
establishing a regulatory framework for AI.
The scope for a new EU regulatory framework for AI
Where certain situations related to serious risks to individuals or to society
stemming from the use of AI are not best tackled by existing legislation,
the Danish Government finds it appropriate to address such risks in a new
risk-based regulatory framework at the European level, while taking into
consideration Member States’ competences in specific sectors. This regu-
latory framework should address serious risks in relation to transgressions
of fundamental rights such as discriminating decision-making as well as
risks of infliction of injuries, especially where these may be irreversible.
Certain AI applications can be applied in critical sectors, which may in-
volve serious risks of societal or individual significance, thereby catego-
rising such application as high-risk. At the same time, it is important to
consider that AI is also being developed and applied in critical sectors for
the benefit of health, welfare and public services. Therefore, it is essential
to find the right balance in the risk-based regulatory framework between
minimizing risks and facilitating the development and uptake of new solu-
tions for societal challenges.
Defining high-risk AI
It is crucial that the definition of high-risk AI is clearly limited to applica-
tions, which can actually cause serious risks, as it is imperative that un-
problematic applications of the technology are not unnecessarily limited to
Europaudvalget 2020
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the detriment of innovation, the development of new business models as
well as the creation of future jobs. Therefore, essential building blocks for
this new framework have to be a clear and targeted definition of high-risk
AI and provide businesses and public authorities with proper guidance on
how high-risk AI is defined in practice.
Firstly, such a definition should entail a clear definition of AI itself. The
definition of AI will need to be sufficiently flexible in order to accommo-
date technical developments, while being precise enough to provide the
necessary legal certainty. However, there is a need to elaborate further on
the definition set out in the white paper, as it is still uncertain which kinds
of AI is covered. The properties of AI as currently defined ranges from
statistical models to neural networks, whereas in our view, the former
should not be covered by the definition AI.
Secondly, the aim must be to identify the AI applications, which constitute
serious risks and determine how serious risks are defined. Such an identi-
fication should result in making the category of high-risk AI the exception
rather than the rule. With this in mind, the two cumulative criteria set out
in the white paper constitutes a good starting point, as an exhaustive list of
sectors combined with the application itself could provide the necessary
predictability and delimitation. However, this will furthermore depend on
the elaboration of the two criteria. The exhaustive list of sectors must cover
a limited set of sectors and the definition of application should be clarified.
This list should also be accompanied by clear guidance, as the term "appli-
cation" could cover many different aspects such as the process as well as
the end purpose. In order to bring clarity and cover the actual high-risk AI,
we would give greater weight to the end purpose of the application, as this
would characterize the potential outcome and thereby the risk more pre-
cisely.
In continuation hereof, applying the two cumulative criteria could never-
theless bring about different grey zones as well as overlook nuances with
respect to serious risk. Therefore, greater emphasis should be put on a-
built-in risk assessment, which for example should assess both individual
and societal risks as well as assessing the probability of the actual risk.
However, such a risk assessment should not in itself create legal uncer-
tainty or bureaucracy.
Furthermore, the role of human oversight already incorporated in the ap-
plication should be taken into account in the risk assessment. There should
be a difference in terms of adhering to a stricter regulatory framework,
when an application takes autonomous decisions compared to the situation
where the application constitutes a support tool for humans in the decision-
making process.
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Lastly, we are wary of the exceptional instances, where the use of an AI
application for certain purposes is to be considered as high-risk irrespective
of the sector, as such an approach could undermine the legal certainty.
There could be certain applications with a horizontal nature where such an
exceptional category would make sense, but it must be composed of an
exhaustive and limited list of specific applications.
Requirements for high-risk AI
The key features set out in the white paper are a good basis for identifying
the relevant requirements for high-risk AI. An essential element of the fu-
ture discussion is the operationalization of them. In this context, it is im-
portant to build on the existing work concerning the guidelines for trust-
worthy AI and take into account the experiences stemming from their feed-
back process. As stated by the Commission, one of the key results of the
feedback process is that a number of the requirements are already reflected
in existing legal or regulatory regimes. As the requirements should com-
plement, but not overlap with existing legislation, such results must be
taken into account, especially as it is likely that high-risk AI applications
are also covered by sector-specific legislation.
In order to not unnecessarily hamper innovation and future solutions within
the area of high-risk AI, any new requirements imposed must be propor-
tionate, technology neutral and be able to address the specific risks associ-
ated with the AI application.
Furthermore, the Commission should incorporate, to the utmost extent pos-
sible, technical standards on AI as well as data technology in general, since
standards have proven to be a flexible way to regulate a field including
rapid technological developments. ISO/IEC and CEN/CENELEC as well
as the IEEE are currently working on different aspects of standardization
of AI and ethics/trust.
 Training data
As AI is only as useful, as the data, which it is trained upon, it is essential
to set tangible data requirements for the development and use of high-risk
AI. These should be easy to interpret, and therefore it is necessary to elab-
orate as to what constitutes “sufficiently representative” training data with
regards to dimensions of gender, ethnicity and other possible grounds for
bias or discrimination as well as those of privacy and safety. Such require-
ments should not inhibit the innovation of AI, which does not touch upon
these dimensions.
 Data and record-keeping
An essential part of AI oversight is the ability to review the decisions taken.
A complete transparency requirement might not be technically possible
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and could in some cases be a de facto hindrance for innovation. Instead, it
should be required that certain information about the AI model such as
records regarding the data used for training as well as the techniques used
for developing the system is stored. These obtainable inputs will enable
explanation of the output performed by the model and thereby enhance the
transparency.
In terms of storing significant characteristics of datasets, it is vital that
these characteristics rely on existing standards prevalent in the market in
order to avoid imposing potential transition costs on authorities and busi-
nesses who are already using common metadata standards when describing
data.
As to not create unnecessary burdens, it is important to establish strict re-
taining limits as well as what specific information is necessary in order to
explain the AI’s output. At the same time, this requirement should not lead
to a situation, where developers and deployers of high-risk AI are required
to publish data as well as algorithms. The objective should be to give the
competent authorities, if needed, the adequate insight in order to verify
whether applicable rules and requirements are complied with.
Furthermore, it is essential to take into account the requirements already
set out in the GDPR as well as to specify how developers and deployers of
AI are able to collect, store and use data for AI and still be GDPR-compli-
ant. In this aspect, it should be considered, if GDPR is a sufficient legal
framework in order to avoid creating new legislative burdens.
 Information to be provided
Proactive information related to the AI system’s capabilities and limita-
tions is essential, as such information could raise the understanding of the
system as well as how it should be deployed. It could furthermore help in
cases concerning liability, for example if a system is utilised in a way,
which contradicts its capabilities and limitations, which the deployer was
made aware of in advance. However, as to not lay unnecessary burdens
upon developers, it is important to establish what specific information is
needed in order to explain the system’s capabilities as well as limitations.
When it comes to a requirement about informing users about the interaction
with an AI system, it is unclear whether such a requirement in practice will
empower citizens. The GDPR already sets out requirements, when per-
sonal data are obtained, concerning the existence of automated decision-
making. Furthermore, despite this requirement, the deployer or developer
of the AI – including public authorities - will still be responsible for the
output and citizens will still be able to challenge the output. Lastly, another
5
potential requirement for high-risk AI involves human oversight, which
seems to overlap with this particular requirement. Transparency should be
our point of departure in order to promote trust, but the aim should be to
enhance transparency by giving citizens a meaningful choice and/or giving
the possibility for the output to be put to the test.
 Robustness and accuracy
For AI to be trustworthy, it requires both robustness and accuracy of the
application. However, in our view, both aspects require further elaboration,
also in terms of the specific definitions of robustness and accuracy. One of
the most important questions in terms of establishing such new require-
ments is whether AI must be more precise than humans, for example
should autonomous vehicles be more precise than humans driving tradi-
tional ones? In order to minimise risks, but without hindering innovation,
it is essential to find the proper balance in this question.
The issue of security is partly covered by the requirements on robustness
and accuracy. Given the importance of cybersecurity in relation to AI and
other data-based technologies, the item should be elaborated. Denmark
supports a horizontal approach to cybersecurity, where existing legislation
regarding cybersecurity would be updated, if necessary, in order to address
potential risks in relation to AI – instead of establishing a sectorial ap-
proach for AI in relation to cybersecurity.
 Human oversight
When categorised as high-risk AI, there must be a requirement to have an
appropriate involvement of human oversight in the specific AI application.
One example could be when applying AI to diagnose patients or to choose
medical treatment. In such cases, human oversight must be required. For
example, a doctor must have the final say in the beforementioned matters,
thereby making the AI application a support tool for the doctor in order to
qualify the decision-making process.
As the AI applications within the category of high-risk AI may be a diverse
group, there will not be one size fits all-model in terms of human oversight,
meaning that human oversight could manifest itself in different forms. The
appropriate involvement of human oversight - type as well as degree –
should be proportionate and take into account the specificities of the AI
application in question. In such determination, it would be useful to bring
into play the results from the build-in-risk assessment used for establishing
whether the AI application in question was high-risk or not.
 Specific requirements for certain particular AI applications used
for remote biometric identification
Usage of technology for remote biometric identification calls for a very
cautious approach, as it must neither result in general surveillance of our
6
citizens nor erode fundamental rights as well as existing EU and national
legislation. At the same time, we acknowledge that certain, but strictly lim-
ited cases may justify its deployment for example in terms of the preven-
tion, investigation and prosecution of crimes. However, it is important that
we strike the right balance between conflicting considerations. We need to
find the right balance between fundamental rights and the prevention, in-
vestigation and prosecution of crimes. Biometric remote identification
must always have a clear purpose, be proportionate, allowed for a strictly
limited period as well as subject to adequate safeguards. As to whether
further guidelines and regulations are needed in this respect, we will re-
serve the right to form our position, once such a potential proposal has been
presented by the Commission.
Certification and control of high-risk AI
An efficient governance structure must strike the balance between the need
for a uniform application of the requirements and the need for avoiding
unreasonable burdens for developers and deployers of AI. An overarching
European governance structure should play a key role in facilitating the
implementation of the regulatory framework, as this is important to ensure
a consistent and harmonized application of the requirements related to AI.
Especially the responsibility of guidance as well as capacity to assist de-
velopers and deployers covered by the regulatory framework should be
clearly defined from the beginning.
The specific conformity assessment should be entrusted to notified bodies
designated by the Member States. This would increase assessment capac-
ity, as developers and deployers would have access to at least 27 different
notified bodies in order to obtain the conformity assessment. Furthermore,
sufficient capacity to certify AI products and services needs to be ensured
before entry into force of the regulatory framework.
Important considerations for the set-up of a conformity assessment should
be to avoid lengthy, burdensome processes as well as duplication with
other conformity assessments and tests in other fields such as medical de-
vices. Additionally, some specificities of the requirements are not relevant
for all types of AI products and services. The conformity assessment
should be able to take into consideration the different aspects of different
AI applications, focusing on those, which are relevant for the application
in question. Also, it could be considered if a conformity assessment could
be divided into different steps or similarly where an AI application in its
testing stage would not be obliged to go through a conformity assessment,
thereby giving room to innovate as well as minimizing the pressure on the
notified bodies.
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It should be the responsibility of the developer or deployer of AI to assess
whether their applications are required to be certified. As grey areas are
unavoidable due to the continuous development of the technology, it is es-
sential to develop practical guidance tools in order to reduce legal uncer-
tainty. A practical tool could for example involve an algorithm assessment
tool, where developers and deployers could get immediate guidance on
whether they are subject to the requirements or not.
As AI is a fast-evolving technology with an algorithm, which is not always
static, recertification must be a requirement, if the AI application has been
significantly modified. In order to avoid a situation, where developers and
deployers find themselves in continuous conformity assessments, it should
be explored how to stipulate benchmarks for when recertification is needed
and whether the developer or deployer, which has already been assessed
could be able to have specific aspects assessed based on their prior assess-
ment.
Concerning SMEs, a conformity assessment could be a burdensome and
lengthy process. However, once a conformity assessment is in place and a
SME’s AI is categorized as high-risk, the SME would for the most part be
requested to deliver a fully-fledged certification from buyers and users who
would otherwise turn to other certified providers. Therefore, an outright
exception for SMEs would not solve the issue. Instead, SMEs should be
given priority at the notified bodies and when establishing the Digital In-
novation Hubs, SMEs should be given assistance with their potential con-
formity assessment.
In order to ensure that the different requirements are complied with over
time and ensure consistent application of the requirements, compliance
must be monitored and controlled by the existing competent national au-
thorities, part of a market surveillance scheme. In our view, such control
does not call for a new enforcement setup, as AI is just one technology out
of many and would at the same time be controlled in connection with other
areas such as competition, product safety etc. However, there could be a
potential competency gap of the existing national authorities, which must
be addressed in order to be fully equipped to enforce the new requirements
related to high-risk AI.
Voluntary labelling for AI applications outside the high-risk category
As the general objective should be to enhance trustworthy AI - not only for
the AI which poses serious risks – the Danish Government strongly sup-
ports a European voluntary labelling scheme. In this regard, the Danish
Government will bring concrete experiences from the recent work with de-
8
veloping a Danish prototype of a data ethics seal as well as from the pri-
vately established Danish labelling scheme for IT security and data ethics
which is planned to launch by the end of 2020.
A European labelling scheme should promote human-centric and ethical
AI and data use in Europe by making it visible for consumers which com-
panies, products and services to trust and thus empower consumers to make
the ethical choice. A Danish study from 2019 showed that over 80 percent
of citizens would avoid shopping at places, if they suspected that their data
was not being processed responsible. At the same time, 65 percent of citi-
zens stated that their choice would be influenced by a labeling scheme. A
labelling scheme would therefore be a practical way of enhancing trust-
worthy AI for citizens as well as creating a push for making this a compet-
itive advantage for companies.
Scope of a European labelling scheme
The Danish Government supports the idea for a European labelling scheme
to target AI specifically. At the same time, we would underline the need
for the labelling scheme to cover broader issues in the digital economy
which citizens are concerned about in order to secure the relevance of the
labelling scheme, which should be demand-driven. Such issues would en-
compass for example the usage and storage of data, tackling cybersecurity
as well as ensuring unbiased decision-making processes, all of which are
essential parts of AI. The Danish study from 2019 also showed that citizens
do not differentiate between IT security and data ethics when using online
services. Based on these insights, we would advocate for a European label-
ling scheme, which both incorporates IT security as well as data ethics into
the scheme's criteria, in order to make the scheme relevant for citizens and
to avoid confusion.
Furthermore, it must be ensured that the scheme is not inconsistence with
corresponding regulation and requirements, for example the GDPR. How-
ever, the scheme should not be limited to the processing of personal data
or guaranteeing GDPR compliance and the scheme should therefore be an
addition to these.
Criteria for the scheme
The European labelling scheme should be rooted in a set of common crite-
ria based on the ethical guidelines for trustworthy AI. As a successful la-
belling scheme is based on a broad market uptake, there should be a differ-
ence between the very strict requirements for high-risk AI and the require-
ments in the labelling scheme, which would cover all other AI, even though
the requirements should be based on the same foundation. Such differenti-
ation should aim at not requiring all developers and deployers of AI to ad-
here de facto to the regulatory framework of high-risk AI.
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The criteria could require that data ethics are anchored at the managerial
level of an organization, for example by requiring that businesses’ internal
policies for data ethics are included in their annual non-financial reporting.
The criteria should also address and be anchored at the technical level such
as fulfilling certain cybersecurity standards and ensuring that the use of
algorithms is explainable, transparent and unbiased.
As the category of AI outside the high-risk category would cover a diverse
group of developers and deployers of AI, it could be worth to consider a
differentiation of criteria, depending on a risk profiling. In the Danish pro-
totype, companies are categorized into four groups based on their organi-
zational complexity and data complexity. In order to obtain the data ethics
seal, each group is required to adhere to a set of different criteria, which
also vary in strictness. We would recommend for the European labelling
scheme to follow a similar approach.
Furthermore, it will be challenging for many developers and deployers in
the target group such as SMEs to comply with all the criteria. For this rea-
son, it could be considered to use a progressive disclosure model when
rolling out the labelling scheme, meaning that the applicants will not be
asked to comply with all the criteria at once. This strategy has multiple
purposes such as reducing complexity for the applicants, making it easier
to get started and thus increases the chance of buy-in, and giving the feeling
of progression by providing the applicants with the most relevant criteria
for its risk profile first and then increase the complexity-level progres-
sively.
Furthermore, the model and criteria should be flexible to reflect future
technological development and be revised continuously. In order to secure
trust in the labelling scheme, it should be voluntary to apply for the label,
but when first awarded, the criteria should be legally binding.
Governance of the scheme
An efficient governance structure for the scheme could be based on the set-
up for the EU cybersecurity certification framework. This entails giving an
EU agency the responsibility to provide the common criteria and certifica-
tion scheme for the label. An advisory group, which could be the high-level
expert group on AI could provide recommendations for drafting the com-
mon criteria and the Member States, should be responsible for appointing
national conformity assessment bodies. An alternative model could be to
anchor the governance of the labelling scheme in an advisory board and a
secretariat constructed by industry bodies.
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Adjustments to existing EU legislation related to AI
The Danish Government supports a horizontal approach towards AI and
thus supports that the Commission also focuses on adjusting existing leg-
islation to address specific issues in relation to AI.
In this respect, the Danish Government welcomes a revision of the General
Product Safety Directive (GPSD) in order to ensure a set of minimum
standards for product safety in regard to AI embedded into consumer prod-
ucts. These should be complemented by updates to the existing sector spe-
cific legislation to address the specific needs pertaining to different cate-
gories of products. However, it is important that the sector specific regula-
tion is aligned with the general requirements in the GPSD in order to avoid
conflicting demands.
The Danish Government also supports the Commission’s proposed provi-
sions in relation to product safety in order to support responsible innova-
tion in AI technology, including a focus on the life cycle of products, qual-
ity of data, transparency and cooperation among economic operators and
public authorities. Additionally, the regulatory framework for product
safety should also address possible changes in consumer behaviour, when
interacting with products embedded with AI technology and ensure that
existing safety requirements - such as physical or mechanical means to de-
activate a product - is not compromised. Finally, updates to the regulation
must also address resilience towards external threats and be aligned with
existing legislation concerning cybersecurity.
Furthermore, it is essential to analyse whether and to what extent the cur-
rent legal framework on liability is still fitting in order to protect users in
the area of AI. The Danish Government supports that individuals having
suffered harm caused with the involvement of AI systems need to enjoy
the same level of protection as individuals having suffered harm caused by
other technologies, whilst technological innovation should be allowed to
continue to develop. In this respect, the Danish Government welcomes that
all options to ensure this objective should be carefully assessed, including
possible amendments to the Product Liability Directive and possible fur-
ther specific targeted rules in the specific area of AI.
Overall, it is important that the adjustments of existing legislation are
drafted as clear as possible – both regarding the scope, definitions and al-
location of responsibilities, but also that they take other Union or national
legislation into consideration. A common and clear European regulatory
framework will increase consumer protection and benefit European com-
panies.
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An ecosystem of excellence
The Danish Government supports the Commission’s ambitious focus on
research concerning AI and recognizes the importance of international co-
operation among research centres with expertise in AI. For research initia-
tives to accelerate the innovation of AI, these must be coupled by adjusting
our framework conditions at the European level. Therefore, the Danish
Government further supports initiatives to make data, investment and test-
ing facilities available across the EU with the aim of making the technol-
ogy accessible for both the private as well as the public sector. In this re-
spect, effective coordination across fields, programmes, the Commission
and the Member States is essential in order to achieve the common objec-
tives in terms of AI.
Revising the Coordinated Plan
As AI is undergoing rapid development – both in terms of the technology
itself, but also due to initiatives set out in the Digital package as well as the
context with COVID-19 - the Danish Government looks positively at re-
visiting the Coordinated Plan with an aim to review the impact of its initi-
atives and based on such a review, adapt where necessary. The overall ob-
jective of the Coordinated Plan must still be to foster closer cooperation
and coordinating common priorities and initiatives within AI.
If Europe truly wants to be a front-runner in the global digital economy,
we need to be ambitious in our priorities as well as maximizing efforts
through closer cooperation which the Coordinated Plan caters for. At the
same time, the Coordinated Plan should utilize and build upon existing
well-functioning structures, institutions and clusters of expertise and ca-
pacities in order to improve the impact of the plan. This must be taken into
account when revisiting the plan.
With regards to the energy sector, the Danish Government strongly sup-
ports the focus on how digitalization, access to data and emerging technol-
ogies can support our efforts to meet the EU’s climate neutrality targets by
2050. In our view, the Coordinated Plan could to a greater extent become
an enabler of accelerating the twin transition towards a green and digital
economy which must be the backbone of the EU’s recovery plan for a more
sustainable and resilient Europe. For instance, by establishing testing and
experimentation facilities that focus on developing and using solutions that
paves the way towards a carbon-neutral and circular economy.
Furthermore, the Danish Government suggests that a review of the Coor-
dinated Plan builds on the experiences obtained from the existing plan with
respect to the security implications related to AI. The review should also
include considerations on the security implications of AI in other critical
functions in society beyond transport, security and energy.
12
Focusing efforts on the research and innovation community
The proposed creation of reference testing centres for AI under the Digital
Europe programme should focus on providing a competitive advantage for
Europe by ensuring that the testing centres are relevant for a variety of
public and private sectors, applications and initiatives. It is important that
the selection of testing centres follows an open, transparent and inclusive
process and that the test centres commit to involve both SMEs as well as
start-ups in order to foster the entire ecosystem.
Testing centres should have a flexible set-up and not apply a one-size fits
all model, as AI can be used in many different settings. It is important that
the testing centres build upon and strengthen existing capabilities in Mem-
ber States and have a strong connection to existing AI ecosystems in order
to avoid duplication. Furthermore, the testing centres should be obliged to
develop and support responsible and trustworthy AI as well as having a
strong focus on promoting carbon-neutral and circular solutions across sec-
tors. We further believe that Denmark has several well-suited candidates
that could participate in the set-up of testing centres for the benefit of all
of Europe.
Furthermore, research and innovation actions under Horizon Europe will
be an important element in Europe’s approach to AI. Denmark fully sup-
ports the proposed AI and Robotics intervention area of cluster 4 (Digital
and Industry) and notes that it is of particular importance to ensure effi-
cient, cross-cutting coordination with other clusters in Horizon Europe, as
well as with efforts from other relevant EU programmes.
Skills
The Danish Government recognizes that there is a great need for a larger
digitally qualified workforce, while emphasizing Member States’ compe-
tences in this area. Fully harnessing the potential of AI requires investing
in people's digital competences and skills. The Danish Government recog-
nizes the importance of a continuous focus on the intake of students in
higher education programmes in information technology, including AI.
Here, the Digital Europe Programme will be an important element, as it
aims to develop world-leading masters programmes in AI. As the focus in
the Digital Europe Programme is based on the broad uptake of digital tech-
nologies in the economy, the activities should have a sufficiently broad
scope in order to meet the demand from businesses and public sectors.
Furthermore, there is a need for safe and secure use and handling of data
on all levels with a specific focus on cyber and information security skills
as part of the overall effort to empower individuals and investing in digital
skills for citizens and SMEs.
13
Focus on SMEs
It is important that the European Digital Innovation Hubs under the Digital
Europe Programme ensure broad uptake of digital technologies by busi-
nesses and especially SMEs. The Danish Government is currently taking
steps to integrate the Digital Innovation Hubs in the existing Danish struc-
tures for decentralized business promotion. Modalities and framework for
the hubs must be drafted in such a way that the hubs can contribute effec-
tively to accelerate the digital transformation and have a real added value
for European businesses and public authorities. Therefore, no hindrance
should be introduced for the utilization of existing structures which already
meet the needs of businesses and public authorities and which can carry
out the tasks.
As AI is a technology of horizontal nature with importance for a wide range
of sectors, the Danish Government supports the initiative that at least one
European Digital Innovation Hub under the Digital Europe Programme has
a degree of specialization in AI. Such a specialization requirement will still
cater for a flexible framework, which enables Member States to build upon
existing national structure and institutions, as the hubs should build on lo-
cal strengths available as well as the future needs of the local economy.
Partnership with the private sector
The Danish Government supports the Commission’s ambition to establish
a public-private partnership in AI, data and robotics and acknowledges the
importance of building strong ties between public and private institutions
in the research and development of AI solutions.
To this end and based on national experiences within data ethics and AI,
the Danish Government has established a national cluster organization for
digital technologies in accordance with the national smart specialization
strategy 2020-2023. The cluster organization aims at promoting innovation
in companies developing AI solutions by strengthening collaboration be-
tween the private and public sector.
Promoting the adoption of AI by the public sector
The Danish Government supports the proposal to initiate sector dialogues,
giving priority to healthcare, rural administrations and public service oper-
ators as set out in the white paper, which seems to resonate with the areas
incorporated in the existing Coordinated Plan, thereby strengthening exist-
ing efforts. However, we suggest that AI systems intended for green, cli-
mate-positive purposes are also added to the priority list.
It is important that a new action plan on AI aimed at the public sector al-
lows for both a top-down approach to identify critical functions in society
14
that must be given priority to ensure the strategic autonomy of EU member
states, as well as a bottom-up approach, for example an explorative ap-
proach that presents local authorities, such as municipalities and regions
with a high degree of self-determination to experiment with AI solutions
within the realm of the law.
Regarding the “Adopt AI programme”, Denmark proposes that the pro-
gramme not only focuses on the aspect of the public sector procuring AI
systems, but also includes the aspect of the public sector developing AI
systems.
A programme focusing on public development and testing of AI solutions
could support the “Adopt AI programme” by incentivising local authorities
to develop AI solutions for application in prioritised areas holding a poten-
tial to heighten the quality and capacity of the public sector through up-
scaling of the technology, but where experience is needed before a wider
uptake is possible. Such a programme could draw inspiration from the Dan-
ish “signature projects”, a joint public sector effort to test AI within the
prioritised areas of healthcare, public administration and employment.
Securing access to data and computing infrastructures
Ensuring access to computing infrastructure as well as high-quality data
across different sectors should be highly prioritized, as access to data is a
precondition for the development and wider uptake of AI. Therefore, it is
of utmost importance that the initiatives set out in the Commission’s Data
Strategy complement the initiatives set out in the white paper on AI. This
especially revolves around the development of data spaces, where stand-
ardisation is a key driver in establishing useful and well-functioning data
spaces, cf. the Danish Government’s response to the Data Strategy.
International aspects
Alongside the EU’s priorities to develop and deploy trustworthy AI, the
Danish Government supports the Commission’s continuous efforts to pro-
mote the ethical use of AI through international cooperation in order to
make this the international norm.


NOTAT
The Danish Government’s response to the public consultation on the
white paper “On Artificial Intelligence – A European approach to ex-
cellence and trust”
General comments
The Danish Government welcomes the European Commission’s (Commis-
sion) white paper on artificial intelligence (AI) and supports the ambition
for a European approach to promote the development and uptake of AI in
a responsible and trustworthy manner. AI is one of the pivotal technologies
that can underpin the EU's competitiveness, prosperity, strategic autonomy
and climate-neutral transition as well as public administration and welfare.
Its vast potential has furthermore become evident by the current COVID-
19 crisis which has highlighted the technology’s contribution to tackling
the pandemic. At the same time, the increasing application of AI and its
potential to solve the challenges of tomorrow has reinforced the important
objective of ensuring trustworthy, ethical, safe and secure application of
AI.
In certain situations, the usage of AI may involve serious risks to individ-
uals and society which must be addressed in a proportionate and risk-based
regulatory framework at the European level. A European framework must
be clear and operable in order to ensure trust among citizens and increase
the protection in society as well as ensuring legal certainty for business and
public authorities. The aim should be to pave the way towards a true Single
Market for AI, where developers and deployers of AI are able to innovate
and scale up across the EU.
AI will likewise be one of the key enablers for rebooting the European
economy after COVID-19. Therefore, a strengthened focus on fostering AI
ecosystems and capacities in the EU is needed in order to improve Europe’s
future competitiveness and resilience as well as for achieving the objec-
tives set out in the European Green Deal. The EU must continue to strate-
gically build on its strengths and reduce its weaknesses in order to improve
its abilities to develop and deploy responsible, ethical, safe and secure AI,
thereby making this a trademark for the EU.
It is important to have in mind that certain usage of AI in sectors critical
for our society can involve risks of societal significance. Consequently, a
strengthened focus on fostering AI ecosystems and capacities in the EU
should also seek to reduce technological dependency on third country de-
liveries in key value chains and infrastructure of critical importance for our
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society and security, thereby strengthening the EU’s autonomy as well as
enabling the EU to define the European way on digitalisation.
The overarching aim must be to ensure that AI and the digital economy in
the EU is characterized by a high degree of trust, safety and security as
well as a strong competitiveness based on framework conditions which
promote innovation, are technology neutral and do not create unnecessary
burdens and barriers.
The Danish Government is looking forward to the further discussions and
work on the initiatives announced in the white paper and will form a posi-
tion on the specific legislative initiatives, as these are presented by the
Commission. It should be noted that the Danish Government finds it im-
portant that the coming discussions does not in any way prejudge the ne-
gotiations on the future Multiannual Financial Framework nor fail to re-
spect the common understandings on the Digital Europe Programme and
the Horizon Europe Programme reached between the European Parliament
and the Council.
Specific remarks to the different elements in the white paper can be found
in the attached document “Annex: Specific comments from the Danish
Government’s on the white paper on artificial intelligence”.


ERHVERVSMINISTEREN
ERHVERVSMINISTERIET
Slotsholmsgade 10-12
1216 København K
Tlf. 33 92 33 50
Fax. 33 12 37 78
CVR-nr. 10092485
EAN nr. 5798000026001
em@em.dk
www.em.dk
s
Notat
Til Folketingets Europaudvalg
Europa-Kommissionen har igangsat en høring af sin meddelelse ”Om kun-
stig intelligens: En Europæisk tilgang til ekspertise og tillid” (COM (2020)
65, som blev offentliggjort d. 19. februar 2020. Formålet med høringen er
at indsamle reaktioner fra interessenter inden Kommissionen fortsætter
med det arbejde, der skal munde ud i regulering for kunstig intelligens.
Regeringen har udarbejdet et samlet dansk høringssvar, der består af ved-
lagte svar med generelle kommentarer samt et svar med konkrete kommen-
tarer til de enkelte elementer.
Fra dansk side bydes meddelelsen velkommen med et fokus på, at kunstig
intelligens og Europas digitale økonomi kendetegnes ved tillid og sikker-
hed, mens tilgangen også skal fremme innovation og konkurrencedygtig-
hed. Det anerkendes, at kunstig intelligens kan medføre seriøse risici for
både brugerne og samfundet generelt, hvorfor der ses positivt på en risiko-
baseret tilgang til teknologien, der giver mulighed for at stille særlige krav om
f.eks. datakvalitet og menneskeligt tilsyn til AI-løsninger i højrisikogruppen.
Potentialet af kunstig intelligens er blevet mere synligt i krisen COVID-19,
hvor teknologien viser potentiale til at bekæmpe sygdommen såvel som til
at løse morgendagens udfordringer. Men den øgede brug af kunstig intelli-
gens viser også, at der er behov for at sikre, at brugen er tillidsvækkende,
etisk og sikker.
Regeringen understreger, at kunstig intelligens sandsynligvis bliver en af
de drivende kræfter for genopretning af den europæiske økonomi efter CO-
VID-19, hvorfor der er behov for et øget fokus på at fostre økosystemer og
kapaciteter inden for teknologien. Dette vil øge Europas fremtidige kon-
kurrenceevne og gøre økonomien mere modstandsdygtig mod chok som
COVID-19, samt bidrage til at opnå målene i Europas Grønne Pagt.
Regeringen gør opmærksom på, at brugen af kunstig intelligens i sam-
fundskritiske sektorer kan medføre væsentlige risici. Derfor skal der i styr-
kelsen af AI-økosystemer – og kapaciteter også søges efter at reducere den
europæiske teknologiske afhængighed af AI-løsninger fra tredjestater.
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Regeringen ser desuden frem til de kommende drøftelser, der skal udfylde
tilgangen i hvidbogen.