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Microsoft Japan

2023

AI Data Symposium
What will happen to the intellectual property of datawith the advent of generative AI
While generative AI is attracting attention, on December 22, 2023, the AI Data
Consortium held a symposium on AI by prominent researchers and experts in Japan.

In addition to the basics of generative AI and the current state of system development, a panel discussion was heldwith speakers after explaining policies related to AI and data, regulatory trends and legal issues surrounding AI.

Director of the AI Data Consortium /Director of AI Data Consortium /Professor, Faculty of Law,

Digital Agency

Attorney at TMI

Director of AI Data Consortium /Professor, The University of Tokyo

Microsoft Japan, National Technology Ofﬁcer

Waseda University

Planning Ofﬁcer, International Data Strategy

Associates

Partner, PwC Consulting LLC

Toshiya Watanabe

Kenzaburo Tamaru

Tatsuhiro Ueno

Maiko Meguro

Yuto Noro

Takuya Fujikawa*Honoriﬁcs omitted

Director of AI Data Consortium / Professor Toshiya Watanabe, The University of Tokyo

Purpose of the AI Data Symposium

The AI Data Consortium was established in 2019 and focuses on the utilization of AI data. The organization is developing alearning data infrastructure for AI and is exploring new ways to deliver data through a platform called AIDC Data Cloud. We arealso utilizing limited data provided based on the Unfair Competition Prevention Act
and introducing a simple contract preparation system.

The consortium is also actively working on issues from the perspectives of AI data

legislation, governance, and intellectual property rights, and will host a symposium
on AI data utilization to address these issues. Here, we will hear the opinions ofexperts on a wide range of topics, including generative AI, copyright, international
trends, and personal information protection.

Under the leadership of Chairman Ken Sakamura, the consortium aims to harness
the full potential of AI and solve related challenges.

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2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

Generative AI and
Copyright

Generative AI and
Changing system development

Speakers

Speakers
General Incorporated Association
Director of AI Data Consortium
Microsoft Japan,
National Technology Ofﬁce

Kenzaburo Tamaru

Data transformers enable self-supervised learningwith less sample.

Professor, Faculty of Law,
Waseda University

Tatsuhiro Ueno

The reduction in the cost of extremely large
data storage and computational resources
required to train the large-scale model that

Microsoft is mainly in charge of data

forms the basis of this large-scale model

The debate on AI and copyright can be

infrastructure in the AI Data Consortium.

has greatly contributed to the progress ofdivided into two main issues: the possibility of

They introduce in detail the background toresearch and development of large-scale

copyright infringement through information

generative AI and how system development

models.

analysis, and the presence or absence ofis about to change. AI's capabilities, such as

Microsoft's Azure OpenAI provides a

copyright protection for AI products.

object recognition, speech recognition,

service that allows users to use their data

First, there is the issue of copyrightmachine reading comprehension, andin a completely closed environment,

infringement in information analysis. The

machine translation, have been achieved asallowing them to use AI with a focus onquestion is whether the act of collecting

equal to human quality on benchmark fromt r a n s p a r e n c y, f a i r n e s s , a n d p r i v a c ycontent from the Internet without permission

2016 to 2019. However, the quality ofprotection. When dealing with intellectualis at risk of copyright infringement in both

Japanese in natural language processing isproperty, it is common for data to be

the learning and output stages. In particular, if

not sufﬁcient compared to English andstored and processed across multiple

the AI uses text, images, etc. on the Internet

other Western languages.

countries and regions. These variations in

to learn, the question arises whether it may

Generative AI has been widely featured inwhere computational resources are hosted

infringe the copyright of these contents. Of

the media in recent years.

and international regulations are inﬂuencing

course, in the case of private use, permission

However, it is by no means a new area ofthese challenges.

is not required to use the copyrighted work

research. It is well known that SCIgen, an

As an example of change made by generativeof others, but in the case of organizations

automatic paper generation program

AI, Microsoft Security using Sentinel and log

and companies, it is a problem because it

published in 2005, passed peer review inmonitoring. With the advent of generative

does not fall under private use.

academic journals. In addition, Microsoft

AI, operations can now be directed in natural

Next, there is the issue whether the AI

Research has conducted a research projectla ngua ge, a n d t h e u s e r i n t e r fa c e h a s

product is copyrighted.This is because it isin 2016 that studies Rembrandt's paintingschanged signiﬁcantly. For example,based

generally believed that content createdand generates images in the same painting

on the natural language instruction

entirely autonomously by AI is notstyle. AI-generated technology has"Summarize it in PowerPoint format", it iscopyrightable. However, there is also the idea

improved signiﬁcantly today, resulting in a

now possible to visualize the ﬂow of thethat if a human makes a creative

quality that makes it very difﬁcult to

attack and create a summary. In the past,

contribution, such as trial and error to input

distinguish between real subjects andreport creation was done manually based

prompts, in the process of generating

generated images.

on research and analysis, but generative AI

content by AI, the AI product should be

The difference between conventional AI

is about to change the way user interfaces

recognized as a copyrighted work. In someand AI using large-scale modeling that has

are conducted.

countries, such as the United Kingdom, there

been attracting attention in recent years is

are also legislative precedents that grantthat conventional AI focuses on a speciﬁc

copyright to content generated entirely bydomain and learns to improve accuracy,

AI, even without human creative involvement.

while generative AI can be used in a wider

Regarding the use of copyrighted works forvariety of ﬁelds. With the advent of data

AI learning,in Japan, Article 30-4, Item 2 oftransformers, automated research on

the Copyright Act permits the use oflabeling and data organization is

copyrighted works for information analysis

accelerating. GPT has evolved andimproved its performance due to thei n v e n t i o n o f Tr a n s f o r m e r s a n d o t h e r

under certain conditions. This provision was
Microsoft Sentinel now uses generative AI tovisualize monitoring and create summaries.

introduced in 2009 as Article 47-7 of the
Copyright Act and amended in 2018.

inventions, as well as the increase in the

Currently, this provision allows information

number of parameters.

analysis as long as it does not unduly harm

In the past, a speciﬁc model was used tothe interests of the copyright holder.

deal with a speciﬁc problem, but now it isJapan was the ﬁrst country in the world topossible to respond to multiple problems

introduce copyright restrictions forusing a large-scale model as a base.

information analysis. Subsequently, many

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AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

countries, including the United Kingdom,of music are not subject to copyright

However, if this is the case, this is a risk in theGermany, Switzerland, and Singapore,protection. Ideas and methods of expression

use of AI, so there is a lot of discussion.

introduced similar provisions. The EU has

are important for creators, but copyrightmade it mandatory for member states toprotection is a strong monopoly for a long

introduce information analysis provisions

period of 70 years after the death of theby 2021. While it is necessary to beauthor, and if copyright infringement is

careful about strict comparisons,recognized, there is a risk of criminal penalties,

internationally, Japan's regulations areincluding imprisonment, as well as injunctions

considered to be relatively extensive.

and damages, so abstract styles and ideas are

In particular, Japan's regulations has thenot protected by copyright law. This is anfeature that the subject is not limited to theundisputed principle around the world.

research institutes, and that it is not uniformly

Regarding AI, even if the AI that comprehensively

prohibited to use it for commercial purposes.

analyzes works created by speciﬁc authors

In the EU, there is a provision that the rightgenerates a new work in the style of Ghibli,

holder can refuse analysis only for commercial

Banksy, or Beatles, it is common to think thatuse, but there is no such provision in Japan. In

it does not constitute copyright infringement

This issue is not new, and has been discussed

addition, in Japan, there is no restriction thatunless the creative essence of the originalat the Intellectual Property Headquarters in

information can be analyzed only for legallywork does not exist. On the other hand, if an2016 and through the revision of the law inaccessed content. As a result, this provision

AI product outputs a speciﬁc representation

Heisei 30. And if there is a risk of copyright

may also apply to the analysis of copyrighted

of the learning source work as it is, such as

infringement by AI, it can extend to users

works accessed in breach of contract orEver ﬁlter, an app that processes images in

who use AI, AI service providers, and AI

bypassing technical measures, as well as

the style of anime directed by Makoto

development companies. For example,

information obtained from illegal sources.

Shinkai, which was once a problem, it isrecently, AI services such as DALL-E3 haveclearly copyright infringement.

taken measures not to be able to input the

Article 30-4, Item 2 of the Copyright Act

n a m e o f a s p e c i ﬁ c c h a r a c t e r, s u c h a s

regulates the use of copyrighted works for

Pikachu, if someone tries to output it.

learning, but if learning is carried out withIn the United States, there is no clear provision

the intention of outputting content thatfor information analysis, and in the event of aconstitutes copyright infringement, thislawsuit, the court will decide. In fact, litigation

provision does not apply because it does not

has begun, so it is expected that discussions

constitute non-enjoyment use as deﬁned inon the copyright of AI learning will proceed in

the main paragraph of the same article.

the United States in the future.

However, in addition to Article 30-4, Item 2

There are various opinions regarding the

In Japan, the Copyright Act permits the use of
copyrighted works for information analysis undercertain conditions.

of the Copyright Act, Article 47-5, Paragraphinterpretation of the information analysis

1, Item 2 was also stipulated in the revision

provisions in Japan's copyright law. Inof the law in Heisei 30. Article 47-5,

particular, the proviso that it does not

In addition, under Japan regulations,Paragraph 1 also targets search engines, forunduly harm the interests of the copyrightcreating and providing datasets to others

example, and permits minor output such as

holder is the focus of the discussion.

for information analysis and selling

displaying a snippet of text or a thumbnail of

However, regardless of the interpretation ofanalyzed datasets may also be subject toan image as a search result under certain

the information analysis provisions, that is,

this provision. It can be said that thisconditions, so I think there is room for thisregardless of whether or not copyright ismakes it possible to take advantage of theprovision to be applied to generative AI that

extended, it is possible and useful to have a

beneﬁts of information analysis.

has a purpose of enjoyment.

data provision contract for the purpose of

However, there are criticisms of such a

In this way, for the debate about AI andinformation analysis. Already, we are seeing

broad provision, and there is an opinion thatcopyright, careful consideration is required,contracts with publishers and newspapers

the copyright law needs to be revised.

distinguishing between both learning phases

to provide digital data suitable for analysis.

However, this provision is only for theand output phases. Personally, I believe that it

As such, it is important for data owners tolearning stage and does not allow up to theis important to prevent infringement at thefacilitate data delivery agreements. On top

output stage, so this point should not be

output stage, but that freedom at the learningof that, it is necessary to take measures at

misunderstood. In other words, if generative

stage should be maintained, but we mustthe output stage, which can be said not only

AI outputs something similar to the creative

continue to pay attention to international

for infringement of rights such as copyright

representation of the content it learns from,trends and ﬁnd the right balance.

infringement, portrait infringement, andsuch output may infringe copyright.

As for AI and copyright, the problem is thatpublicity infringement, but also for various

Of course, in copyright law, there is a principle

whenever AI learns someone else's work andillegal and harmful information. With regard

called the "dichotomy of ideas andoutputs something that co-exists with thatto the freedom of the learning stage, I thinkexpressions." This protects only concrete"creative expression", it is a copyright

we should maintain this to the last, and thenexpressions, not the ideas themselves. For

infringement. If the AI is said to be relying on aconcentrate our wisdom and technologicalexample, data from newspaper articles, thework that it has learned in the past, the output

ingenuity to prevent illegal and harmfulstyle of illustrations, and the expressive style

is considered to be a copyright infringement.

information at the output stage.

If AI outputs "creative expressions" of works learnedin the past, it may constitute copyright infringement.

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2023

AI Data Symposium

AI Development and Utilization
and Data GovernanceSpeakers
Digital Agency
Planning Ofﬁcer,
International Data Strategy

Maiko Meguro

Data governance for artiﬁcial intelligence (AI)can be broadly divided into two categories:"data issues in the formulation of policies
and rules related to the development anduse of AI" and "data governance related toall stages of AI development and use."
The former includes speciﬁc examples as
AI strategy in 2022, the summary of issues(provisional) issued at the AI Strategy
Meeting, and economic measures in Japan.
These address speciﬁc data issues andprovide draft guidelines for businesses.
The latter includes strategic documents
and relevant laws and regulations (e.g.,
intellectual property laws, limited availability
data, privacy laws, etc.) that are relevant to
the overall data strategy.
Internationally, the Government of Japan has
taken the lead in Data Free Flow with Trust(DFFT), which is international initiatives. Thisis an initiative to accept the reality that datacrosses borders, regardless of differences inlegal systems such as privacy, security, andintellectual property, and to constructively
discuss principles for building trust between
countries, speciﬁc legal systems, speciﬁc
international guidelines, and speciﬁc policies.
In terms of speciﬁc domestic policies, the AI
strategy in 2022 shows an awareness of the
problem that although data is accumulated
in each ﬁeld, it is not being used as
effectively as in other countries. In addition,at the AI Strategy Meeting (May 26, 2023),
the emphasis was similarly on enhancing theWhat will happen to the intellectual property of datawith the advent of generative AI

business use of generative AI.

The Data Strategy Action Plan has two

As mentioned above, various discussions

main goals: "Develop and open high-quality

and initiatives are taking place in AI dataand easy-to-use data" and "Develop tools

governance both in Japan and overseas,

and mechanisms that enable the use andand each of them is collaborating tolinkage of the data with conﬁdence." In

improve the environment for better data

addition, it is important not only to develop

utilization. It is believed that discussions onand collaborate with domestic data

data governance should proceed from

infrastructure, but also to collaborate

various perspectives, such as policies andinternationally.

rules related to data, and AI development

In 2023, the G7 Hiroshima Summit was held,

and use in the future.

where discussions were held on issues

Next, I will explain the "Action Plan for the

related to international data governance andDevelopment and Collaboration ofdata utilization. DFFT is deﬁned as "reliable

Public-Private Data in the Age of AI"

and free ﬂow of data" and relates to theannounced by the Digital Agency of

cross-border ﬂow of international data. This

Japan on December 20, 2023. This action

concept was proposed by Prime Ministerplan focuses on the theory of data

Abe at the Davos Summit in January 2019

governance at all stages involved in theand agreed upon at the G20 Osaka Summit

development and use of AI.

in June 2019. The cross-border data

The development of data governance has

problem is complicated by differences ingone through three stages. The ﬁrst focus

privacy, security, and intellectual property

will be on core data for the realization of alegislation from country to country. While

digital society, and "Comprehensive Data

data localization legislation is on the rise, theStrategy(June 2021)." Next, after theneed for country-speciﬁc placement of data

establishment of the Digital Agency

centers and country-speciﬁc management(September 2021), based on this strategy,of data collection and processing can

Data Free Flow with Trust (t DFFT). Throughoverturn the fundamental assumptions ofthe "Priority Plan for the Realization of acloud technologies.

Digital Society (June 2023)," we are

At the 2019 Davos Forum, Prime Minister

proceeding with speciﬁc implementations

Abe said that personal data, intellectual

and initiatives in priority areas. However,property, and data related to national

these efforts are still in the middle stage,security should be protected, but impersonaland in response to the rapid development

and anonymous data such as healthcare,of generative AI technology, the G7 Gunma

industry, and transportation should be freely

Takasaki Digital and Technology Ministers'

circulated. The G20 Osaka Leaders'Meeting agreed to establish an Institutional

Declaration in 2019 highlighted DFFT and

Arrangement for Partnership (IAP) on DFFT.

declared that "continuing to address issues

In the "Action Plan Background" section, itr e l a t e d t o p r i v a c y, d a t a p r o t e c t i o n ,describes how to respond to the rapid

intellectual property rights and security candevelopment of generative AI technology.

promote the free ﬂow of data andConverting the massive amount of data

strengthen consumer and business trust."

held by the government into a format that

Expertise in different areas, such as

can be used by AI is a time-consuming andprivacy, security, data protection, andlabor-intensive task. The Digital Agency

intellectual property, inﬂuences the ﬂow ofplans to open up the data held by thedata, and how to coordinate and facilitate

government and promote the use of pastthem can be challenging. In particular,

administrative data.

AI-related developments and advances incloud technology are rapidly advancing andavailable data and building a data linkage

are widely incorporated into our daily lives,

platform, which is a prerequisite for AI.

but discussions on international governanceIn addition, the Comprehensive Economic

among governments and governments

Stimulus Plan (2023) focuses on AI, andhave not kept up.

speciﬁc initiatives related to AI and data

AI developers and the research community

governance are being promoted in manyare calling for steps to ensure the data

areas, such as "responding to risks,"

quality of AI training. Contains disinforma-"promoting the use of A(I, mainly generativeAI)," and "strengthening AI development
capabilities." The Digital Agency is making
concrete efforts to verify the technology
and improve the usage environment for the

The Digital Agency is planning to open up the data
held by the government and others and convert it
into AI training data.

tion or information that infringes intellectual property rights can lead to legal consequences later on. Against this background,the introduction of "rating tags" to indicate

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2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

the safety of data has been proposed, but
the setting of standards requires international discussion. Even if it is technicallypossible, if appropriate evaluation criteria
are not determined, there is a risk that the

can identify a speciﬁc individual by the

AI and Issues in the
Personal Information
Protection Law

international ﬂow of data will stagnate.

Speakers

In addition, there are various stages of AI

Attorney at TMI Associates

development and service provision, withdifferent regulatory trigger points. Howev-

Yuto Noro

description contained in the information, or
information that includes an individual
identiﬁcation code."
The ﬁrst point of contention is theapplicability of personal information in
AI. In the debate on whether this AI is
personal information, the factor (1) is
important, and it is said that it may not

er, if regulations are concentrated at a spe-be personal information because it is not

ciﬁc stage, it will be inefﬁcient when viewed

related to the individual in the ﬁrst place.

from the perspective of the entire life

Here, if AI is deﬁned as an algorithm andcycle. In addition, it is difﬁcult to talk abouta parameter, the Personal Information

AI and applications in data governanceI thought it would be useful to check theProtection Commission explains that it

discussions, and discussions on individual

relationship between AI and the Personal

does not fall under personal information

regulations such as privacy, security, andInformation Protection Act in order tobecause it does not fall under (1) as far

intellectual property are not shared from a

consider how to establish regulations for AI

as the correspondence between theholistic perspective.

in the future, so I would like to talk about

speciﬁc individual is excluded, regarding

Under these circumstances, the Japanthe theme of "AI and the Personal

the latter "parameter".

government is looking for ways to connect

Information Protection Act" today.

The second point of contention is the

it to international governance discussions.

Today, I would like to ﬁrst talk about theapplicability of input and output data to

At the 2023 G7 Gunma Takasaki Digitalextent to which Japan's Personal

personal information. A variety of things

and Technology Ministers' Meeting, it wasInformation Protection Law can affect AI

can be input and output data, so it is aacknowledged that it is difﬁcult forin regulation. I will explain that this law

case-by-case decision. On top of that, we

experts from different ﬁelds to discuss

does not directly regulate AI, but indirectlybelieve that input and output data thatwith each other, and that there are gaps inregulates it through AI input and output

includes (1) and (2) fall under the categoryinternational governance. Therefore, it isdata. Next, I would like to talk about theof personal information.

proposed to gather evidence on speciﬁc

extent to which Japan's Personal

To illustrate these issues, let's take AI as an

issues and barriers to the reality ofInformation Protection Law regulates AI at

example of disease prediction AI in the

cross-border data access, and to look forthis time. This law regulates AI at each

medical ﬁeld, where it inputs patient

the way to use the concrete way tostage of acquisition, use, and provision of

information and outputs problematic

eliminate gaps, not abstract rules.

personal information, but there are

symptoms as images. In this case, while the

However, since many projects tend to bepractical countermeasures for all of them,

AI itself is considered not to fall under thet e m p o r a r y, a n a p p r o a c h t o s e t u p a

and I plan to explain that the regulations

category of personal information, thesepermanent secretariat for governance andare not so strict as to impede the use of

inputs and outputs meet the requirements

to solve the individual problem is

AI at this time.

of (1) and (2) and may fall under theimportant. Also, the establishment of an

category of personal information.

international system for the realization of

1.Applicability of AI and personal

Next, we will explain what is "personal

Data Free Flow with Trust (DFFT) at the

information

information" and what is not evaluated assummit level was also approved, and it

First, I would like to discuss the issue of the"personal information" at the learning andwas decided to place it in the OECD. It isapplicability of AI and personal information

use stage of AI in a diagram in accordance

believed that this will make it easier toin order to conﬁrm the extent to whichwith the process of AI learning and use.

advance discussions with developed

Japan's Personal Information Protection

countries that have similar values.

Law can affect AI. Here, I would like to

The Japan government aims to back up these

explain two issues, the ﬁrst of which is the

movements and build large projects andapplicability of AI to personal information. I

organizations to come up with a wide range

think it raises an uncomfortable questionof solutions with a wide range of experts.

about whether AI itself personal
information is, but in other words, it can be
explained as a debate about whether AI
algorithms and parameters containpersonal information. The second is the"applicability of personal information in
input and output data," which is the issue[Figure] "Personal information" at the stage oflearning and using AI.

of whether the input data and output data
The International Framework for the Implementationof the DFFT (IAP) was approved by the OECD in
December 2023

are personal information.

First, in the [Learning Stage], the "raw data"

There are two elements to the deﬁnition ofis processed to create a "training dataset".

personal information: (1)Information about

This The "training dataset" is input to thea living individual" and "(2) Information that"training program" to generate the trained

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2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

model, and the "trained model" is output.

regulates AI itself, so it is possible to ban

there was a concern that conversational AI

Next, in the [Usage Stage], the user inputs

algorithms that adversely affect society as

would violate the regulations for obtaining"Input Data" to the "Trained Model" output

a whole. We believe that the EU's AI Bill will

special care-required personal information.

in the [Learning Stage], and the "AI Product"

serve as a reference when considering

However, during the debate on the personalis output.

regulations on AI in Japan.

information protection law surrounding
generative AI in recent times, this point was

The above is the process of learning andusing AI that is generally assumed but

2.Regulation of AI and the acquisition ofraised again, and the discussion deepened.

based on the discussion of the applicability

personal information

What is important in considering this issueof personal information earlier, it can be

Next, in order to discuss the extent tois the "Summary of Alerts to OpenAI"

organized as follows, ﬁrst, the items in thewhich Japan's Personal Information

published by the Personal Information

red frame in the ﬁgure, "raw data", "learning

Protection Law regulates AI at this time, I

Committee on June 2, Reiwa 5. In thedataset", "input data", and "AI product" arewill explain from the regulation of AI and theoutline of this warning, based on thethe input and output data I mentioned

acquisition of personal information. Here,premise that OpenAI physically acquires

earlier. It may fall under the category of

the regulation of the acquisition of personal

special care-required personal information

personal information. On the other hand,

information at each of the data input andfrom users and third parties without thethe item in the black frame is "Learning

output stages is an issue. There are twoconsent of the user, a certain amount of

Program" and the "trained model" is the AI

regulations on the acquisition of personal

prior. If you take action after the fact, you

i t s e l f t h a t I m e n t i o n e d e a r l i e r, a n d i n

information that can be problematic in any

can understand that it is a legal

principle it is not personal information. Asof these situations. The ﬁrst is thearrangement that prescriptively evaluates

shown in these ﬁgures, the Act on theprohibition of unauthorized acquisition ofthat you have not acquired personalProtection of Personal Information does not

personal information as stipulated in Article

information in the ﬁrst place. In the outline

cover the AI itself, which is enclosed in a

20, Paragraph 1 of the Personal Informationof this alert, it is required to take measures

black frame, but the peripheral part of theProtection Law. This prohibition stipulates

such as taking necessary measures to

AI surrounded by a red frame, that is, thethat personal information must not be

prevent the above information from being

data input to the AI and the data output.

obtained by unauthorized means. The

included in the information to be collected

Based on the discussion so far, if weanother is a regulation on the acquisition of

as a preemptive response, and as asummarize the relationship between AI andspecial care-required personal information

follow-up response, if it is discovered that

the Personal Information Protection Act, it

stipulated in Article 20, Paragraph 2 of thethe above information is included, it iscan be explained that this law does not

Personal Information Protection Law. As arequired to delete it as soon as possible. If

directly regulate AI, but indirectly regulates

general rule, this regulation stipulates that

the Personal Information Protection

AI through input and output data.

special care-required personal information

Commission is able to take these preventive

This is due to the EU's data protection

must not be acquired without the consent

measures and take follow-up measures, itlaw, the GDPR (General Data Protectionof the individual.

can be understood that it has not acquired

Regulation) also regulates personal data,

As a situation where these regulations are

personal information in the ﬁrst place andso like the Personal Information

problematic for the acquisition of personal

is not subject to the acquisition regulations

Protection Law, it does not directly

information, we will ﬁrst introduce "Case 1:

related to special care-required personal

regulate the AI itself, but inputs it to the

Situations where the regulation of theinformation. Such an interpretation is

AI. It is considered to be restricting theacquisition of personal information at thetheoretically questionable, but at least as andata to be output. And recently, the EU's

data entry stage is a problem". In this case, if

administrative interpretation, it can be

AI bill, which has been politically agreed,

the AI training data contains illegally obtained

understood that such a legal arrangement

allows for direct regulation of the AI

information or special care-required personalis made so as not to interfere with practice.

itself, which is enclosed in a black frame

information, the problem is that these two

Although this interpretation is anin the diagram that was not covered byregulations will be violated.

interpretation of the regulations regarding

the GDPR. I think the background to thisThis problem has not arisen recently as a

the acquisition of special care-requiredis that the existing GDPR did not directly

problem with generative AI, but has existed

personal information, I think the same canregulate the dangers posed by AI as longas a problem that is difﬁcult to solve since

be said about the interpretation regarding

as it covered personal data.

the 27th revision of the Personal

the prohibition of unauthorized acquisition.

As a result of that the EU's AI bill regulates

Information Protection Law established new

AI itself, we have been able to apply

regulations for the acquisition of special

regulations to various areas that could notcare-required personal information. For

be covered by the existing GDPR. For

example, in conversational AI, there is a

example, the existing GDPR is a law thatpossibility that a third party's special

targets personal data, and its rules are built

care-required personal information willaround the protection of individuals in theinevitably be included in the input data ofbackground, but if AI adversely affects

the AI, but in that case, it is practicallysociety as a whole or a part of it, it is

difﬁcult to obtain consent for the special

difﬁcult to regulate it because it is notcare-required personal information from alinked to the protection of individuals. On

third party, and it does not necessarily fall

the other hand, the EU's AI bill directly

under the exception of the regulation, so

Case 1: Situations where restrictions on theacquisition of personal information at the data entry
stage are problematic.

6

2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

Next, we will introduce "Case 2: A situation(Guidelines on the Act on the Protection of

information, and the person is notiﬁed, or it

where the regulation of the acquisition of

Personal Information (General Rules) 3-1-1

is publicized.

personal information at the data output（※1）. This interpretation was added to the

There is a debate about whether thestage becomes a problem". In this case, it

guidelines based on consideration at the

purpose of use should be for the generalis assumed that illegally obtained informa-time of the revision of the Personal

purpose of "development/research andtion or special care-required personal

Information Protection Law in Reiwa 2.

development of new products andinformation is included in the AI productPrior to that, there was an interpretation

services" or whether it is necessary to haveinstead of the training data. For example,

that in order to specify the purpose of use,

a speciﬁc purpose of use at the level of "AI

when using ChatGPT, a third party's per-it was necessary to specify the ﬁnal

learning" to the extent of specifying thesonal information has been output for

purpose of use of personal information, so

purpose of use in this case. The view thatsome reason.

it was not necessary to specify in detail theneeds to be concretized is that AI learning

In this case, there is an argument that theprocess leading up to the ﬁnal purpose ofcannot be reasonably predicted oruser who has acquired the AI product willuse. However, in the case of analysis of

assumed for general purposes, and that AI

be subject to the regulation on theindividual behavior monitoring, it islearning should be speciﬁed until theacquisition of special care-required

necessary to explain not only the ﬁnal

learning of AI. The basis for this view is apersonal information and the prohibition of

purpose of use but also the analysis of thespeciﬁc interpretation of the purpose ofunauthorized acquisition. However, as inprocess, which has been added in theuse when analyzing information such as

Case 1, if precautionary measures areinterpretation based on the consideration

behavior and interests about the person

taken in advance and immediate deletion isat the time of the revision of the Personalmentioned earlier, but there are doubts as

taken after the fact, it may be interpreted

Information Protection Law in Reiwa 2. In

to whether this interpretation will bethat the above information was not

addition, Article 18, Paragraph 1 of theapplied to AI learning in the ﬁrst place. The

acquired in the ﬁrst place.

Personal Information Protection Act

view that it is not necessary to specify the

If this is the case, it will be possible tos tip ula te s th a t, i n p r i n c i p l e , p e r s o n a lpurpose of use is understood that it does

comply with the rules of the Personal

information must be handled within the

not need to specify the speciﬁc technical

Information Protection Law in both Cases

scope necessary to achieve the speciﬁed

method of information analysis when

1 and 2, so I think it can be said that the

purpose of use, and these regulations are

specifying the purpose of use, so it is not

Personal Information Protection Law is notestablished for the identiﬁcation of

mandatory to mention AI. The rationale fora regulation that hinders the use of AI inpersonal information and the handling

this view is No. 28 of the Guidelines for thethe context of AI and the acquisition ofwithin that scope.

General Rules in the Result of the Call for

personal information.

Another usage regulation is the prohibition

Opinions published by the Personalof improper use. Article 19 of the Personal

Information Protection Commission on

Information Protection Law stipulates that

August 2, 2021. In this regard, if you read

personal information must not be used in a

the privacy policies of some companies,

manner that may encourage or induce

you will ﬁnd that some AI development

illegal or unjust acts. This provision is a

startups specify "AI learning", but there areprohibition added by the amendment to thenot many that specify to that extent as an

Personal Information Protection Law inoverall trend. I have the impression that

Reiwa 2, and broadly prohibits thethere are many descriptions of the purpose

improper use of personal information, butof use with a granularity.

Case 2: Situations where restrictions on theacquisition of personal information at the data output
stage are problematic.

it may be applied in situations where AI isused.
One example of the use of personal
information where these regulations can be

3.Regulation of the use of AI andproblematic is "Case 3: A situation where

personal information

the regulation of the use of personal

Next, I will explain the regulations on theinformation at the AI learning stage is ause of AI and personal information. One ofproblem". In this scenario, it is assumed

the problematic usage regulations is thethat the use of personal information for AI

regulation of the speciﬁcation of the

training is not included in the existing

purpose of use and the handling within that

purpose of use. In this case, the use ofscope. First of all, Article 17, Paragraph 1

personal information for AI learning will beof the Personal Information Protection Act

handled outside the scope of the existing

stipulates that the purpose of use must be

purpose of use of personal information, so

Another example is "Case 4: A situation

speciﬁed as much as possible. In particular,

it is necessary to change the purpose ofwhere the regulation of the use of personal

when analyzing information such asuse in order not to violate the Personal

information at the stage of using AI

behavior and interests related to the

Information Protection Law. Therefore, in

becomes a problem." In this situation, it isindividual, it is understood that the purpose

practice, I think it is necessary the purpose

assumed that the purpose of use does notof use must be speciﬁed to the extent thatof use is changed so that AI learning is

include analysis of behavior and interests

the person can predict and assume

included in the purpose of use of personal

related to the person using AI. In this case,

Case 3: Situations where the regulation of the use of
personal information at the AI learning stage
becomes a problem.

7

2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

since there is a possibility of violating the

For example, the EU's AI Bill sets out a list

exception, this regulation does not apply.

Personal Information Protection Law asof cases where the use of AI is prohibited

Here are two examples. The ﬁrst is "Case 5:

handling personal information outside thefor unacceptable risks, and it is conceivable

A situation where the applicability of thescope of the purpose of use, it is requiredthat it will be something like that list.

provision of personal data is questionable."to change the purpose of use so that theIn this scenario, the user inputs a prompt

analysis of the behavior and interests of

into the AI and the AI product outputs it,

the person using AI is included in the

but it is assumed that the AI vendor

purpose of use of the individual, and tohandles the user's prompt only for the

notify or announce it to the person. As in

purpose of outputting the response result.

Case 3, it is possible to comply with the

In principle, the consent of the user isrules of the Personal Information

required to provide personal data to the AI

Protection Law by notifying or announcing

v e n d o r, b u t i f t h e A I v e n d o r i s n o t

to the person, so I think it can be said that

supposed to handle personal data, thethe Personal Information Protection Law
does not impede the use of AI even in thecase of the use of AI and personal

Case 4: Situations where the regulation of the use of
personal information at the stage of using AI
becomes a problem.

information.

cloud exception will apply. In this regard,
according to the "Warning on the Use ofGenerative AI Services" published by the
Personal Information Protection

In this case, the so-called proﬁling is being

4.Regulation of the provision of AI andCommission, if an AI vendor treats theperformed and there is also an interesting

personal data

user's prompt only for the purpose ofquestion as to whether it is subject to the

Finally, we will explain the regulations on the

outputting response results, it can beprohibition of improper use depending on

provision of AI and personal information.

understood that it does not fall under thethe manner in which it is done. Proﬁling

There are two regulations on the provisioncategory of "provision" of personal data, as

generally refers to the automated analysis

of personal information that can bewith the cloud exception, and is not subjectof private aspects of an individual. Whether

problematic here. The ﬁrst is the general

to regulations regarding the provision of

to establish proﬁling regulations in Japan's

regulation of personal data on third parties

personal data. However, in other cases, it is

Personal Information Protection Law has

stipulated in Article 27, Paragraph 1 of theunclear under what circumstances the use

been discussed since around the 27th

Personal Information Protection Law. Whenof AI vendors' services is exempt from therevision, but at this time there are noproviding personal data to a third party, inprovision regulations. For example, if the AI

proﬁling regulations themselves. Then, as

principle, the consent of the person is

is ﬁne-tuned on the user side, it may not be

for whether proﬁling falls under therequired. However, if the AI vendor does

applicable if the AI vendor handles theprohibition of inappropriate use, No. 57 of

not handle personal data, it can beuser's prompt only for the purpose of

the Guidelines for the General Rules in theconsidered as a so-called cloud exception,

outputting the response result, and it may

Results of the Call for Opinions, which wasand there is an interpretation that it does

not be interpreted in the same way as aannounced by the Personal Information

not mean that the personal information iscloud exception. It has been suggested that

Protection Commission on August 2, 2021,“provided” to the AI vendor in the ﬁrst

the cloud exception may be considered in

may be subject to the prohibition ofplace. (Q&A: 7-53 regarding the "Guidelines

the future in the review based on the

inappropriate use depending on theon the Act on the Protection of Personal

three-year review provision by the Personal

individual case. In general, I think it isInformation", Caution regarding the use ofInformation Committee, which I mentioned

reasonable to interpret that it may apply

generated AI services, etc. (1) (2). Even if it

earlier.

depending on the individual case, but at

is understood that personal data is being

this point it is not clear in what speciﬁc

provided, there is an exception in the case

cases it falls under the prohibition ofof outsourcing the handling of personal

inappropriate use.

data (Article 27, Paragraph 5, Item 1 of theIt has been suggested that the relationship

Personal Information Protection Act). The

between the prohibition of inappropriate

other is the regulation of the provision ofuse and generative AI may be the subject

personal information to third parties inof future consideration in the examination

foreign countries stipulated in Article 28 ofbased on the three-year review regulations

the Personal Information Protection Law.

of the Personal Information Protection

When providing personal data to a third

Commission (Personal Information

party in a foreign country, in principle, it isProtection Committee, "Examination basednecessary to obtain consent after providing

on the so-called three-year review

certain information to the person. In theprovisions of the Personal Informationcase of provision to a third party in a

The second is "Case 6: Situations where theProtection Law" (November 15, Reiwa 5), p.

foreign country, the entrustment of theoutsourcing of the handling of personal

3) ）. If, as a result of this study, the use ofcollection of personal data is not excepted.

data and the standards for thegenerative AI that falls under the category

Of course, even if personal data is provided

establishment of systems are problematic."of inappropriate use is clariﬁed in

to a third party in a foreign country, if theThis is also a scene where the user inputs a

guidelines, Q&A, etc., it may be possible torecipient meets the standards for systemprompt into the AI and the AI productcreate a new regulation on generative AI.

development equivalent to Japan law, as an

outputs it, but it is assumed that the AI

Case 5: Situations where the applicability of theprovision of personal data becomes an issue.

8

2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

vendor will use not only the user's prompt
response, but also the prompt itself as
machine learning data. In this case,according to the "Warning on the Use ofgenerative AI Services", it cannot be

Japan's Generative AI Utilization
Status and AI Regulatory
Trends in Each Country

interpreted in the same way as theso-called cloud exception, and it must be
understood that personal data is provided
to AI vendors.
There is a possibility that it can beinterpreted as falling under the

Speakers
General Incorporated Association
Director of AI Data Consortium
Partner, PwC Consulting LLC

Takuya Fujikawa

consignment of the handling of personal

About half of companies feel that generative AI isinferior to competitors and is more aware of the threat

The survey results are classiﬁed into ﬁveclusters: 12% are "indifferent," 34% are

data, and it may be possible to organize it"interested but not taking action," 22% are

as not requiring the consent of the person.

PwC's "Fact-ﬁnding Survey on Generative"promoting projects but postponing

However, in the case of foreign AI vendors,

AI Autumn 2023" is available on the web,governance," 18% are "using it for internal

regulations regarding the provision ofand if you are interested, you can search

operations and focusing on governance,"

personal data to third parties in foreignfor "PwC Generative AI Fact-ﬁnding

and 14% are "company-wide support inside

countries apply, so in principle, consent

Survey 2023 Autumn" and download theand outside the company." In particular, theafter providing information to the person is

PDF ﬁle. This data is a valuable source oftechnology and telecommunications

required. However, even if this regulation is

information for understanding how Japan

industries are leading the way, and theapplied, there is an exception if thecompanies perceive generative AI and

automotive industry is also making positive

provider meets the standards for system

what strategies they are taking.

moves. The retail industry tends to be

development equivalent to Japan law. This

According to the survey, awareness ofinterested but not take actions.

point will be judged on an individual basis,

generative AI among managers of large

Comparing the Spring and Fall Surveys, theand it will be necessary to consider

companies in Japan has risen to 96%, 73%

Technology Industry, while the industry andcontracts with AI vendors. If this contract

have used it, and 87% are considering

telecommunications continue to bemeets the standards for the establishment

introducing it. The survey, which waspioneers, the healthcare and automotiveof the system, it will be possible to comply

conducted in October 2023 and released

industries are gaining momentum. The

with the rules of the Personal Informationin December, surveyed 1,000 people inﬁnancial industry is slowing down.

Protection Law, so I think it can be said

section managers and above who belong

In terms of use cases, the technologythat the Personal Information Protection

to companies and organizations in Japan

industry is developing applications and

Law is not a regulation that hinders the usewith sales of 50 billion yen or more.

automated programming, the telecommuni-of AI even in the case of the provision of AI

Expectations are high for generative AI

cations industry is providing services forand personal information.

that aims to improve efﬁciency, and 12%

call centers, the healthcare industry is

Thank you for your time.

of companies are already providing it asimproving the efﬁciency of doctors' ofﬁce

Thank you very much for listening.

an external service.

work, and the automotive industry is sup-On the other hand, about half of the

porting vehicle design. PwC is looking atcompanies feel that we are relatively

emerging trends such as automated CAD

inferior to other competing companies

generation, using generative AI for design

about generative AI, and their motivation

defect checking in the construction indus-

to aim for the ﬁrst time in the market hastry, landscape design generation in the real

been conﬁrmed. The amount ofestate industry, and product packaging andinvestment varies from several million

advertising production in the retail industry.

yen to billions of yen or more, with 24%

Regarding generative AI legislation in major

investing hundreds of millions of yen or

countries, the EU and China have adopted

more. Also, with 43% of companies

a strict hard-law model, and the EUplanning to implement generative AI by

regulations are particularly strict. The EU

M a r c h 2 0 2 4 a n d 5 8 % b y S e p t e m b e r,aims to provide robust protection for civil

companies with large investment budgets

rights under the GDPR, and ﬁnes forare more risk-conscious and using tools

violations can reach up to 7% of sales. This

like conversational generative AI isis also important for non-EU companies, as

becoming increasingly important.

it can affect all companies that provide

While each company has its own

services to EU citizens.

departments leading AI governance, it

In China, the National Internet Information

typically involves departments such as

Ofﬁce (CAC) has enforced the AI Algorithm

i n f o r m a t i o n s y s t e m s , s e c u r i t y, l e g a l ,Regulation. This has a notiﬁcation system,

and business. The key is for various

and severe ﬁnes can be imposed in thedepartments within a company to work

event of a violation. Thus, state-led digital

together to build governance.

strategies for AI technologies are being

Case 6: Situations where the outsourcing of thehandling of personal data and the standards for theestablishment of systems become problematic.

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AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

strengthened.
The U.S. has previously adopted a soft-law
type of regulation, but with a new executive
order, there are signs of a shift to a hard-law
model. This could make AI developers
obliged to test and report.
Japan has relatively loose regulations andregulations based on guidelines have been
the mainstream, but with the sharing of the

AI regulation is divided into two types: "hard law"with strict laws and "soft law" with no penalties.

new "Draft Guidelines for AI Business
Operators", regulations may be strengthened

Japan companies need to take into accountin the future. Japan companies need tothe international business development, andunderstand overseas regulations before

to understand and adapt the regulations ofdeveloping their business in the global

each country. This is especially true in themarket, so they are required to consider

EU, where there are strict regulations, suchmeasures in advance.

as speciﬁc obligations imposed on

The EU's AI Regulation sets strict regulations

providers and users regarding AI systems.

on prohibited and high-risk AI systems, and

The G7 Leaders' Statement on the

it includes many areas such as biometrics

Hiroshima AI Process calls for organizations

services, critical infrastructure, anddeveloping AI systems to apply an

personnel evaluation.

international code of conduct, which

In the EU, providers and users are obliged

includes risk checks and strengthening

to perform quality control, technicalsecurity measures.

documentation, conformity assessment,"Improving user literacy" is also taken up

and post-market monitoring.

due to Japan's strong demand, and it issaid that users are also responsible.
In PwC's view, companies need to build theirown rules with international rules in mind in
addition to Japan's guidelines. In the future,
it is expected that individual guidelines foreach industry will be required, and it isspeculated that EU regulations will move inSince the strength and weakness of regulations on
AI in major global countries are different, it isnecessary to be careful in business development.

a more harmonized direction. China is also
moving toward international cooperation
while continuing to operate under theleadership of the state.

In line with these developments, Japan

In closing, it is stated that it is important tocompanies operating globally need to grasp

immediately develop a governance systeminternational regulatory trends and establish

in order to promote innovation in generative

an appropriate governance system. In

AI. Preparations for stringent regulations

addition, it is expected that more detailed

need to start now, and consideration isindustry-speciﬁc guidelines will be required inrequired to establish global standards.

the future. This will enable companies to drive
innovation while effectively managing risk.
The E U h as t h e st r i cte s t re gula tions ,followed by China. While these countries
have adopted a hard-law type of regulation,
Japan has so far promoted a soft-law typeof regulation, that is, regulation with loose
guidelines. However, in Japan, new "Draft
Guidelines for AI Operators" has been
submitted, suggesting that this could

It is expected that each country will develop agovernance system and consider the establishmentof global standards.

increase the severity of regulations.
In the U.S., there have been signs of a shift toa hard-law model due to a recent executive
order, although the country has adopted aloose regulation through guidelines. Thismeans that AI developers may be obliged totest and report.

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AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

Di s c ussi on

Panel discussion by speakers
The panel covered specialized topics related

multiple tracks to advance the discussion.

of this will ultimately converge. However, heto data governance, personal data

And he emphasized that it is necessary topointed out that Japan's theoreticalprotection, intellectual property rights, cloudcreate a form that satisﬁes everyone while

framework that copyright does not need totechnologies, and international data ﬂows.

he wants to make the domestic regulatory

extend to uses that no one enjoys in the

The main focus is on cross-border data

environment the standard overseas.

ﬁrst place is attracting attention from othertransfers, the relationship between machine

Mr. Ueno pointed out that if the output ofcountries, and that it may converge in thatlearning and copyright, data security andmachine learning is common to the creative

direction in the future.

privacy issues, and international data

expression of the original work, it may be a

Mr. Noro said that if we are complying withgovernance approaches.

copyright infringement. Therefore, he said

the law, we should not be overly afraid of

Mr. Meguro explained that through thethat the liberalization of machine learning

ﬂaming because of the vague fear, about aOECD project, countries will cross borders

should be maintained, but consideration

business that involves new technologies. In

in anticipation of the cloud, and will work

should be given to ensuring that the output

areas where new technologies such as AI

with engineers and the ﬁeld to solve

result is not the same as the creative

are involved, even if the law is complied

problems. In addition, the OECD has nearly

expression of the learning source work. Mr.

with, there is a potential possibility that it

40 member countries, and while policy

Watanabe pointed out that there are many

will be ﬂamed at some point, but thecoordination is required, the data topics

opinions that "I don't want to be learned,"question is whether the business should

are wide-ranging, he mentioned that someand explained that many of them are notalways be shut down due to concerns

topics are appropriate to use IAP, while

copyrighted works, and that measures areabout that possibility. He said that theothers can be narrowed down by

required to prevent them from becomingsupervisory authorities are also paying

frameworks such as bilateral and trilateral.

technically copyright infringement.

attention to whether or not new businesses

We believe that challenging topics also

He Mr. Ueno pointed out that the copyrightthat are born every day can gain therequire a rethinking of the scope of theholder cannot refuse to study for theunderstanding of the public, but as long as

project. Furthermore, he indicated that the

non-proﬁt research purpose in the EU andthey comply with the law, they do notissue of cross-border data transfer will lead

the UK, but rather that the EU and the UK

always take measures to stop the businessto multilateral and multilateral discussions.

have more freedom to study for non-proﬁteven if a ﬁre breaks out.

In addition, in response to a question fromresearch purposes. He said that even if

On the other hand, as a practical matter, in

Mr. Watanabe about security of database,

there is a strong concern about his work

companies

Ms. Meguro acknowledged that information

being AI-learned at the moment, he hopes

Mr. Noro points out that when promoting

related to security is basically unshakeable

that as time goes by, generative AI will

AI-related businesses, it is also importantand that it is difﬁcult to separate it, but hebecome commonplace, and there will be noto consider reducing the risk of ﬂaming

believes that the government needs tomore concerns about AI learning itself.

as much as possible in practice. As aseparate the frame that should deal with

Mr. Ueno introduced Japan's ﬁrst provisioncountermeasure against ﬂaming, hedata discussions, the frame that should be

for information analysis and said that withemphasized the user's point of view anddiscussed by isolating only security, andthe growing awareness of the newsaid that it is necessary to consider boththe issue that should be discussed in terms

knowledge that big data analysis can

the law and social acceptability, and thatof technical protection and should use

provide, it is unclear how the understanding

it is important to proceed with business

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2023

AI Data Symposium

What will happen to the intellectual property of datawith the advent of generative AI

with consideration not only of the law but

providers have trouble setting prices andteam is transforming through the use ofalso of social acceptability, especially in

expressed the need for value-based

generative AI, within Microsoft. He showed

areas where new technologies such as AI

pricing.

the idea that the method of creating system

are involved.

Mr. Tamaru and Mr. Watanabe explained

services using generative AI is not an

Mr. Noro also pointed out that Japan's

about the data exchange platform "Dataextension of the past, but a completely new

Personal Information Protection Law does

Cloud" developed by the AI Data Consortium.

line. He also said that young engineers andnot currently pose a major obstacle toThis allows the data provider to set the

R&D are bringing in new ideas, and that he

AI-related businesses. For example, whenterms of the transaction and transact while

feels that it is fresh and good when it

handling personal information in anprotecting the limited offer data. However,

becomes a product. On the other hand, he

AI-related business, while it may bethey shared the issue that the existence of

said that he was surprised by the highpossible to request deletion of data input

this trading platform is not sufﬁciently

usage of ChatGPT in the senior community,and output data to AI, it is difﬁcult torecognized.

and when he saw how it was used, he felt

request deletion of the AI itself on the

Mr. Fujikawa stated that his mission is tothat he had to come up with new ideas

premise that AI itself is not a personalbring together companies to solve common

when creating things.

information.

problems and promote the distribution and

The discussion highlighted the complexity

He also explained that the provision of

sharing of data. He also aims to bringof data governance and its impact on

personal data to AI providers can rely on

together companies in the same industry tosociety and business, as well as the needso-called cloud exceptions, which may notsolve major industry issues and social

for international collaboration andbe subject to their regulations. However,problems.

standardization. The discussion addressed

M r. N o r o e x p l a i n e d t h a t i f A I u s e r

Regarding the use of AI data, he explained

the new challenges associated withcompanies are making adjustments in thethat although it would be ideal to form atechnological advances and exploredform of ﬁnetuning, they may not be able tocommunity that crosses industries, itapproaches to solving these problems

rely on so-called cloud exceptions, so it isshould start small and within the same

within an international framework.

necessary to be careful.

industry. Regarding AI governance, he

Recognizing the importance of ensuring theTamaru pointed out that there is a big

pointed out that the framework of thefree ﬂow and reliability of data (DFFT), we

difference in the way companies in Japan

industry may not be necessary, but also

are committed to building new mechanisms

and the United States handle data. In

said that it is necessary to create guidelines

and partnerships for international data

Tamaru's experience, U.S. companies

within the industry because people in thegovernance. It also discusses in depth theprovide data unless it's a trade secret, whilesame industry are using AI for similar use

interpretation of copyright law and theJapan companies rarely provide data. He

cases, and that such efforts should be

handling of personal information in relation

said that this is affecting AI development incarried out in a manner that is not boundto AI, and it explores how these issues

Japan, and expressed a sense of crisis thatby the industry.

should be incorporated into international

there is less data speciﬁc to Japan than in

Finally, Mr. Tamaru said that the development

data governance frameworks.

other countries and regions.
M r. Ta m a r u a l s o p o i n t e d o u t t h a t t h eperception of the value of data is changing,and there is a shift from disposable toutilized. He cited the establishment of the
AI Data Consortium and explained thatefforts are underway to make data trading
more open and fairer. On the other hand,
he said that one of the reasons why
companies do not want to provide data isthat they see their data as monetary value,
and that it is necessary to build an
ecosystem that returns the value of data.
Mr. Watanabe emphasized the importanceof creating a data ecosystem and utilizing
AI. He said that in order to increase thedelivery of valuable data, technical options
are needed. He also pointed out that data

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For inquiries, please use the following information.
■Internet Homepage: https://aidata.or.jp/■Secretariat: info@aidata.or.jp

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