From the SelectedWorks of Yueh-Hsuan Weng

Winter December 10, 2019

Natural Law and its Implications for AI
GovernanceYueh-Hsuan Weng, Tohoku University
Takashi Izumo, Asahi University

Available at: https://works.bepress.com/weng_yueh_hsuan/118/

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Natural Law and its Implications for AI Governance1

Natural Law and its Implications for AI
GovernanceYueh-Hsuan Weng and Takashi Izumo*
With the recent emergences of AI technologies, our societies are facing regulatory challenges in terms of their design, manufacture, sale and use. In addition to the existing norms,
many new ‘AI laws’ will be needed for early stage AI governance. However, when it comes
to AI, there is a significant gap between hard laws and soft laws. Although we have witnessed the development of soft law from both public institutions and organisations like the
EU and the IEEE in recent years, hard law has been less forthcoming. Answering the question of why this gap exists and whether or not ‘natural law’ can narrow is the chief purposeof this paper. To do so we will draw on two supplemental principles from the natural law
tradition.

I. Introduction
When it comes to effectively governing emerging AI
technologies in the short run, a critical issue relates
to the establishing relevant norms. Drafting hard law
to regulate unknown new technologies is difficult
when the public believe that the ‘law shall always fallbehind the technology’.1 Furthermore, regulators
usually have a tendency to over-regulate emerging
technologies because of their lack of knowledge in aparticular technological field. One famous example
is the UK’s 1861 Locomotive Act or ‘Red Flag Laws’,
which is now regarded as an excessively stringent
regulation of what was then an emerging technology; the steam engine powered vehicles.2 In addition,
when we take a legal viewpoint we can easily analyse
conflicts between existing AI laws, but it is more difficult to imagine legal issues emerging from futurelaws for technologies which do not, as of yet, exist.

On the other hand, soft law for AI governance,such as ethical principles or legislative guidelines,
has become much more prominent in recent years.
Let us take Europe as an example. In 2014 the EU introduced guidelines for regulating robotics, the socalled FP7 Robolaw Project.3 In 2016 the EU Parliament published the Draft Report with Recommendations to the Commission on Civil Law Rules on Robotics4 and in 2019 the AI HLEG, an expert group set
up by the EU Commission, published the Ethics
Guidelines for Trustworthy Artificial Intelligence(AI).5 There have also been many soft law initiatives
outside of Europe, such as the IEEE’s Ethically
Aligned Design (v1, v2, and e1),6 the Future of Life’s
Asilomar 23 AI Principles,7 and the Japanese Society
for Artificial Intelligence’s Ethical Guidelines.8
In terms of the regime of positive law, there is aclear distinction between hard law and soft law. For
example, Abbot and Snidal define soft law as any law*

Yueh-Hsuan Weng. Assistant Professor, FRIS, Tohoku University,
Japan. Visiting Scientist, RIKEN-AIP, Japan.; Dr. jur. Takashi,
Izumo. Associate Professor, Faculty of Law, Asahi University,
Japan. For correspondence: <y.weng@srd.mech.tohoku.ac.jp>

4Mady Delvaux-Stehres et al, ‘Recommendations to the Commission on Civil Law Rules on Robotics, European Parliament’ (2016)
Draft Report

51Mark Fenwick, Wulf Kaal and Erik Vermeulen, ‘Regulation
Tomorrow: What Happens When Technology Is Faster than the
Law?’ (2017) 6 American University Business Law Review 3

The AI HLEG, ‘The Ethics Guidelines for Trustworthy Artificial
Intelligence’ (2019) European Commission

6

The IEEE A/IS Initiative, ‘Ethically Aligned Design (EAD)’<https://ethicsinaction.ieee.org> accessed 5 September 20197

Future of Life Institute, ‘Asilomar 23 AI Principles’ <https://futureoflife.org/ai-principles> accessed 5 September 20198

The Japanese Society for Artificial Intelligence, ‘The JSAI Ethical
Guidelines’ <http://www.ai-elsi.org/wp-content/uploads/2017/05/JSAI-Ethical-Guidelines-1.pdf> accessed 5 September 2019

2

3

Red Flag Laws were regulations made by the UK Parliament for
the use of steam engine powered vehicles on public highways in
the 19th century. < https://www.legislation.gov.uk/ukpga/Vict/24-25/70/contents> accessed 05 September 2019.
Erica Palmerini et al, ‘Guidelines for Regulating Robotics’ (2014)
EU FP7 RoboLaw Project2

Natural Law and its Implications for AI Governancethat lacks one or more of the three critical featuresof hard law: obligation, precision, and delegation.9
These soft laws are not only created in a flexible way,
but are also difficult to be implemented. With thisdefinition in mind, we can define soft laws in AI governance (‘AI soft laws’) as laws that meet the following three criteria: (1) Not formally binding (ie in regard to robot developers, vendors, users or otherstakeholders) (2) Not precise, so that the judgmentof the norm implementation is left to each party, and(3) Merely private, so that no third party has the authority to monitor implementation. In other words,
AI soft laws is a set of weakened rules that help theparties to self-regulate their research and commercial
activity on. However, the relative weakness of soft
law makes it difficult to handle conflict between different values and norms. When testing for the realworld, it is sometimes not clear on how to decide thehierarchy between current existing hard laws and auniversal moral principle from AI ethics without ameta guiding principle. If we cannot ensure a corresponding rise in hard law to an explosion in soft law
in this area, are there any other alternative way tocover the gap of AI soft laws in real governance asmentioned above?

II. Applying Natural Law as a Regulator
in Early-Stage AI GovernanceThe classification of hard law and soft law is straightforward to modern governance system based on positive law. However, a boundary distinguished from‘hard’ and ‘soft’ seems not clear to the other perspective called ‘natural law’ which is a kind of moral theory in defining legal authority in relation to different
norms. As an alternative solution to above mentioned
gap of governance in AI soft laws, we propose to consider natural law as a regulator in early-stage AI governance. In other words, we assume that the natural
law traditions can be used as supplementary principles for soft laws in dealing with some difficult situations like to handle conflict between different values and norms. But sometimes it can also be ambiguous and difficult for the layman to understand what
the concept of natural law is. Hence, at the beginningwe want to clarify the exact scope of natural law andits connection with the context of AI soft laws.
As the concept of natural law itself has evolved
over a long history, it is hard to find a uniformed de-Delphi 3|2019

finition that can be applied to all natural law theories. Thus, in this study, we will focus only on several jurists and philosophers who had particular influence in the early-modern period and classify the concept of natural law according to their writings as
mentioned below. The first criterion comes from afundamental distinction between the fact and morality, ie between the being and ought-to-be. There aresome laws that were regarded as a part of natural law
in the 17th and 18th century but should be excluded
from our study because they are treated by economists or natural scientists today. Such laws can be
subdivided to the laws that are applied also today
and the others that are false according to modern science. An example of the former laws is the law ofsupply and demand. Christian Thomasius (1655 1728), who is called ‘Father of German enlightenment’ (in German: Vater der deutschen Aufklärung),10 found that the price of merchandise depends on its supply and demand.11 This idea was formulated independently by Alfred Marchall in the 19th
century as so-called supply and demand.12 In otherwords, his concept of natural law was not restricted
to the so-called human morality, but it included also
economic analysis. By contrast, Thomasius had afalse prejudice and called it natural law by statingthat humans are permitted to eat meat because of his
belief that no other animal apart from human beings
would have sense.13 This prejudice derived, as henamed explicitly in another place,14 from the thoughtof the famous French philosopher Rene Descartes(1596 - 1650) that a dog, a cat, or a bird has no spirit

9Kenneth Abbott and Duncan Snidal, ‘Hard and Soft Law inInternational Governance’ (2000) 54 International Organisation
3, 421 - 422

10 About the question of how the name of ‘Father of German Englitenment’ (in German: Vater der deutschen Aufklärung) was
given to Thomasius, see Markus Meumann, Diskursive Formationen zwischen Esoterik, Pietismus und Aufklärung: Halle um
1700, in Monika Neugebauer-Wölk (ed), Aufklärung und Esoterik:Rezeption - Integration - Konfrontation (Walter de Gruyter 2009)78
11 Christian Thomasius, De aequitate cerebrina: l. 2. C. de rescind.
vendit. et ejus usu practico (Johann Christian Hendel 1749) 52
12 The Law of Supply and Demand ‘states that in a free market theforces of supply and demand generally push the price toward thelevel at which quantity supplied and quantity demanded areequal’. W. Baumol et al, Microeconomics: Principles and Policy(11th edn, Cengage Learning 2008) 66
13 Christian Thomasius, Institutiones jurisprudentiae divinae (7thedn, Christoph Salfeld 1730) 184
14 ibid 8

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Natural Law and its Implications for AI Governance3

Table 1. Source: Authors' elaboration. The traditional concept of ‘natural law’ can be classified asfollows:
World

Modern discipline

Subject

Strength

Natural world in the narrow
sense

Natural Science

Factual rules of physical entities

Neither hard nor soft because these laws cannot be
violatedSocial world concerned withfacts

Sociology and economics

Factual rules of human society

Normally inviolable but social customs are changeable

Social world concerned withmorality

Jurisprudence

Moral rules of human society
which can be sued in court

Normally hard but sometimes soft

Policy Making

Interdisciplinary field of discussions on moral rules ofhuman society

From hard to soft
Hard: eg official guideline
Soft: eg recommendation

EthicsMoral rules of human society
which cannot be sued in
court

Soft

Theology

Conscience = moral rules ofhuman society which is controlled by God

Religiously hard but secularly soft

Religious world

and thus are merely ‘automata’.15 Today this theory
has been denied by biologists and is often criticisedin the context of animal rights.16 These laws, or ‘natural law developed with the concern of facts’, will be
excluded from discussion in this paper regardless ofthe question of whether they are true or false, because they are controlled by natural force. In otherwords, we have no choice whether or not to follow
natural science.
If the context world of natural law is one which isdeveloped with a concern for morality, then weshould refer not to natural science but to jurisprudence and ethical norms. Furthermore, jurisprudence and ethical norms should be distinguishedfrom each other in regard to the existing problems
we described in the early stages of AI governance.

15 Norman Smith, New Studies in the Philosophy of Descartes(Macmillan 1952) 136, 140
16 Tom Regan and Peter Singer, Animal Rights and Human Obligations (2nd edn, Prentice Hall 1989) 13-19
17 For example, in Summa theologiae, Part 1-2, Question 87, art 1,
Thomas von Aquin wrote that there are three sorts of punishment,
ie punishment from oneself, from other people, and from God.

Hence, the scope of natural law traditions we will investigate in this paper will tentatively exclude its connection with hard law. However, the concept of natural law we will investigate, namely the one at thelevel of ethical norms, should be further sub-classified into three groups, (1) conscience, or people’s inner voice, (2) legislative policy and (3) ethics in the
narrow sense.
First of all, the conscience can be regarded as one
recognition method of natural law given the assumption that God will punish a person who committed acrime against his or her conscience, even if a court
overlooked the crime.17 The assumption that God is
omniscient and omnipotent is useful when it is notclear whether a Christian committed a crime. One of
the merits of this belief is the restraint of sanctions
ie the church entrusts ambiguous cases to God. Therefore religious natural law, which is ordered by God,is indeed ethical because when it is violated it is notpunished in this world, but in the background. On
these grounds we should also exclude the consciencein this paper.
Finally, it is clear that legislative policy, and ethics
in the narrow sense remain as the subject of our study.

4Natural Law and its Implications for AI Governance

Legislative policy is different from ethics in the narrow sense in that it is suggests policies which are enforceable in future. In other words, natural law includes some rules which should be incorporated into positive laws by legislation even if not everyone
agrees on doing so18 (one pertinent example is thequestion of whether or not old people should return
their car licenses once their driving skills deteriorate).
By contrast there is no such enforceable obligationin the case of ethics in the narrow sense (eg people
should return greeting to each other).

III. How Natural Law Can Support AI
Soft Laws?
From a natural law viewpoint, the concept of AI soft
law at the very least should include legislative policy (eg the draft report from European Parliament)
and ethics in the narrow sense (eg the Future of Life’s
Asilomar 23 AI Principles). However, some AI softlaws like the IEEE’s ‘Ethically Aligned Design’ have
dual characteristics in that they are not merely an
ethical guideline, but also include law and policy sections for legislators to use in developing laws related to AI governance. The question, then, is how natural law can support AI soft law in the early stage AI
governance? To answer this, we found two supplemental principles from the natural law tradition,
namely, shareability and complementarity. First, theconcept of shareability means that natural law mustbe acceptable to all nations as a common rule regardless of their cultural background. This feature was
required by Hugo Grotius by stating that international customary law that he called ius gentium has alsohigh shareability but only natural law is perfectly
shareable and can be accepted to all nations.19 Specifically, AI soft law must become acceptable to all parties and stakeholders. Secondly, complementarity is
the notion that multiple rules should support eachother because it is impossible for a single rule to regulate everything flawlessly. This second requirement
was suggested also by Grotius, and he wrote that
there are multi kinds of law in this world, namely,
natural law, international customary law, which wascalled jus gentium, civil law, and divine law, which
God revelated. Grotius believed that if a rule of natural law is contrary to another rule of civil law, thenthe latter should be applied, in other words, in his
legal system, natural law is regularly soft whereas

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civil law is a sort of hard law. In the context of AI
governance, this concept requires us to create a situation where AI soft laws does not violate hard law
and does not disturb private business among citizens.

1. Shareability: A Universal Principle anda Golden RuleIn regard to shareability, we immediately face theproblem that it is difficult to find a common rulethat can be accepted by all reasonable persons regardless of their cultural background. And indeed it
seems, at first glance, that this is also true when it
comes to human-robot co-existence. However, if welook to legal history, there was a rule that was globally accepted, ie Golden Rule (hereinafter the GR).20
Thomas Hobbes, one of the fathers of modern natural law theory, argued that every conclusion of natural law can be intuitively drawn from the GR.21 He
believed that natural law must be understood by all
humans without difficultly and must consist of asimple normative proposition. In short, the GR, according to Hobbes, is a law based on human nature,
which by definition all humans have in common regardless of intellectual ability or cultural background.
The GR has at least two different forms, ie ‘treat
others as you would like others to treat you’ (positiveform) and ‘do not treat others in ways that you would
not like to be treated’ (negative form). Its existence
is not merely limited in Western traditions, but the
GR also plays an important role in Eastern societies,
such as Confucian from ancient China.22 Scholars
have argued for a long time about the difficult question of whether the GR, especially in the positive

18 Takashi Izumo, Die Gesetzgebungslehre im Bereich des Privatrechts bei Christian Thomasius (Peter Lang Verlag 2016) 54-58
19 Hugo Grotius, De jure belli ac pacis (Joan Blaeu 1660) 7
20 In regard to the popularity of the GR, see Harry J Gensler, Ethics
and the Golden Rule (Rout 2013) 34 seqq
21 Thomas Hobbes, Leviathan: Reprinted from the Edition of 1651
(Oxford University Press 1929) 121
22

Fumihiko Takahashi, ‘The Confucian Golden Rule: Chu Hsi's
Neo-Confucian Interpretation and the Critical Arguments by
Japanese Confucianists in the Seventeenth and Eighteenth Centuries’, in B. Sharon Byrd, Joachim Hruschka und Jan C. Joerden(eds), Jahrbuch für Recht und Ethik, Band 8 (2000), Themenschwerpunkt: Die Entstehung und Entwickliung der Moralwissenschaften im 17. und 18. Jahrhundert (Duncker & Humblot
2000) 315 seqq

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form, really leads to shareable conclusions. Thomasius convincingly argued that everyone must agree
to the following negative form of GR: ‘You ought not
to harm others because you do not want to be harmed’(in original Latin: Quod tibi non vis fieri, alteri ne feceris; translated in English by T. Izumo).23 In otherwords, he believed that the prohibition of harm is auniversal rule for human beings.
Surprisingly this old wisdom is consistent withthe following key principle within the ‘Ethics Guidelines for Trustworthy Artificial Intelligence’: namely‘Develop, deploy and use AI systems in a way thatadheres to the ethical principles of: respect for human autonomy, prevention of harm, fairness and explicability’.24
The GR also partially coincides with the first ruleof Asimov’s ‘Three Laws of Robotics’. This first rulesays that ‘a robot may not injure a human being or,
through inaction, allow a human being to come toharm’. Connected with the GR, the first law needs tobe extended and to be rewritten as follows: A robot
may injure neither human beings nor other entities
nor, through inaction, allow them to come to harm.
This extended version of the first rule is a minimum
rule of AI and robot regulation and it mandates that
AI and robots ought to maintain the safety of humans and human property (thus indirectly also thesafety of AI and robots themselves as human property). In order to satisfy this order, various measures
must be taken. These can be divided into threegroups, ie damage prevention (eg setting of fire inprohibited areas), damage containment (eg firefighting equipment) and damage compensation (eg fire
insurance).

23 Christian Thomasius, Fundamenta juris naturae et gentium (4thedn, Christoph Salfeld 1718) 183-184
24 European Commission, Ethics Guidelines for Trustworthy AI<https://ec.europa.eu/futurium/en/ai-alliance-consultation> accessed 16 August 201925 Yueh-Hsuan Weng, ‘Robot Law 1.0: On Social System Design for
Artificial Intelligence’ in Woodrow Barfield, Ugo Pagallo et al(eds), Research Handbook of Law and Artificial Intelligence(Edward Elgar Publishing 2018)
26 Theo Jacobs, Gurvinder Singh Virk, ‘ISO 13482 – The New
safety Standard for Service Robots’, ISR/Robotik 2014; 41stInternational Symposium on Robotics, 2014
27 New JIS as Safety Standards for Robot Services Established, see
https://www.meti.go.jp/english/press/2019/0520_003.html
28 Yueh-Hsuan Weng, Yusuke Sugahara, Kenji Hashimoto, Atsuo
Takanishi, ‘Intersection of “Tokku” Special Zone, Robots, and theLaw: A Case Study on Legal Impacts to Humanoid Robots’ (2015)
7 International Journal of Social Robotics 5, 841-857

Natural Law and its Implications for AI Governance5

2. Complementarity: Harmonisation ofMultiple Norms in GovernanceNew regulations for ensuring the safety of human-robot interactions will be needed when service robots
that perform close interactions with humans become
more popular in our society. However, current safety
regulations for industrial robots, based on the ‘human-robot separation’ safety policy, contradict theoriginal purpose of service robots.25 Although the firstAI soft law to ensure the safety of service robots has
emerged in the form of the 2014 ISO 13482,26 the law
is not sufficient to regulate tasks involving more complex daily human-robot interactions. Therefore, theJapanese Ministry of Trade and Economy (METI) developed another new standard in July 2019 (JIS Y1001)
which aims to act as supplemental measure with a focus on requirements for safe management and operations of robot service providers.27 From this, we cansee a trend that the type and content of AI soft laws
is going to keep growing. More importantly, the larger issue is about the harmonisation of multiple norms
in governance or as we call it: ‘complementarity’.
At present in this very early stage of human-robot
co-existence, we do not yet have ‘AI hard laws’. However, we do have hard laws which already impact theAI field including civil law, criminal law, data protection law. These can be labelled ‘non-AI hard laws’.
Problems arise in norm complementarity when theimplementation of the GR conflicts with these nonAI hard laws. How should we address this?
As mentioned before, the GR is a universal moral
principle from the natural law tradition and future
AI legislation should respect the GR. Therefore, conflicts between the GR and AI hard laws should not
happen. The GR can be regarded as a kind of meta
rule for both AI hard law and soft law, but it does notmean that the GR has the same moral force of constraint on non-AI hard laws. Because those currently existing hard laws have their own values, AI governance might not be their priority. The importanceof solving this norm conflict in the near future isabout a unique regulatory sandbox or ‘Tokku’ for intelligent robots and safety critical autonomous systems. The ‘Tokku’ special zone for robotics empiricaltesting and development (RT special zone) originated in Japan, which is not only a shock buffer for
emerging technology and society, but also a deregulation system for AI’s last mile testing into the realworld.28 Hence, conflicts between the GR and non-

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Natural Law and its Implications for AI Governance

AI hard laws are more likely to happen during testing scenarios inside the special zone. One alternative
solution for the potential conflicts between the GR
and non-AI hard laws is to reserve some core value
issues in legislative process as an upper meta rule forthe early stage transition period.29
Even if we ensure no conflict with current existing hard laws, some original rules or so called ‘expedient measures’ may come up during the process ofrule implementation in governance. In regard to AI
soft law a top-down institutional approach should also be avoided and a societal consensus should besought. For example, even if no hard law enforces
self-driving car owners to buy property damage liability insurance, it should not be forbidden for parking lot owners to provide the clause that self-drivingcars are not insured in their lots. If such a clause becomes popular in a community, then the insurance
would function as a kind of soft law. In this situation,
the concept of ‘complementarity’ is required for thevalidity of AI soft laws.
Such complementarity was required in early-modern natural law theories because natural law could
not cover all political or economic issues and it wasnecessary to mandate legislators in each country to
make appropriate but not exhaustive positive laws.30
However, there are still several fields where the roleof hard law would become so important that soft law
would not have space to be applied. In addition, theliability immunity clause that exempts the responsibility of robot developers and vendors should only
be restricted by hard law, as in the case of product liability in the United States. Otherwise it might cause
unfair outcomes for robot users.
There are also some overlaps between shareability and complementarity in Roman law, where theprinciple of complementarity can be a supportive
tool in the implementation of the GR. Here the mostimportant principle is that humans should be treated as free and equal by nature. Justinian the First,
who was an Eastern Roman emperor and reigned
from 527 to 565, confirmed that humans are free by
nature and the slavery has been artificially introduced.31 This contradicts the Aristotelian believe that
there are inferior people who suitable for slavery by
their own nature.32 The Justinian claim can be easily justified by the GR, ie the explanation of Aristotle
is not shareable because it cannot be accepted by thepeople who are regarded as inferior. No one thinksthat he or she should serve others as a slave because

Delphi 3|2019he or she wants to be served by others as slaves. In
addition, this natural law satisfies the requirementof the complementarity because natural freedom canbe restricted by positive laws and natural equality
can be changed too. For example, in ancient Rome,
Roman citizens enjoyed more freedom than foreigners in several fields.33 Ulpian, who was one of themost famous Roman jurists, explained it clearly as
follows: ‘The jus civile is that which neither wholly
diverges from the jus naturale and jus gentium nor
follows the same in every particular. And so whenever to common law we add anything or take anythingaway from it, we make a law special to ourselves, thatis, jus civile, civil law’.34 This overlaying of multi-rules
is applicable to modern society too. One possible application is that we will distinguish the professional
residents who are involved with robotics from theothers and restrict the freedom of the latter group (egby setting up restricted areas) or give more freedom
to the former (eg by giving permission to develop
some technologies that are normally prohibited).

IV. Conclusion
The ‘Regulation of the Unknown’ is a kind of general problem for regulators when they are faced withemerging technologies like AI and robotics. It reflects
the importance of the role of soft laws in AI governance at its initial stage. In this paper, we investigated the connection between the natural law tradition
and AI soft laws with a focus on two supplemental

29 Yueh-Hsuan Weng, ‘Beyond Robot Ethics: On a Legislative
Consortium for Social Robotics, Advanced Robotics’ (2010) 24
Advanced Robotics 13, 1919-1926
30 For example, Hugo Grotius and Samuel von Pufendorf thoughtthat price control should be left to the judgment of each legislator
or judge even though natural law requests it in several cases.
Grotius (n 19) vol 2, cap 12, § 26, 237; Samuel von Pufendorf,
De jure naturae et gentium, vol 5, cap 3, § 9 (Adam Junghans
1672) 630
31 Rolf Knütel et al, Corpus Iuris Civilis: Die Institutionen: Text undÜbersetzung (4th edn, C.F. Müller 2013) 5-6
32 For an overview of Aristotle’s defense of the slavery in ancient
Greek see Fred Miller, ‘Aristotle’s Political Theory’ in The Stanford
Encyclopedia of Philosophy (First published Wed Jul 1, 1998;
substantive revision Tue Nov 7, 2017) <https://plato.stanford.edu/entries/aristotle-politics/> accessed 23 August 2019.
33 Max Kaser, Rolf Knütel and Sebastian Lohsse, Römisches Privatrecht: Ein Studienbuch (21th edn, C.H. Beck 2017) 94
34 D 1.1.6 pr (‘D’ is the abbreviation of ‘Digesta’, ‘pr’ is ‘principium’) translated by Alan Watson, The Digest of Justinian, vol 1(University of Pennsylvania Press 1998) 2

Delphi 3|2019principles: shareability and complementarity. We
found that the shareability principle is important foreasing value conflicts between different AI soft laws
when they are applied to the same target. On the other hand, the complementarity principle can help tosolve conflicts between different kinds of norms in

Natural Law and its Implications for AI Governance7

terms of AI governance. Finally, we demonstrated thefeasibility of natural law to be a policy tool to support AI governance in the early stage (for example todeal with potential conflicts happening in special
zone deregulation systems for testing safety critical
AI and autonomous products).