October 29, 2024 • 36 mins
Welcome to "AI or Not," the podcast where we explore the intersection of digital transformation and real-world wisdom, hosted by the accomplished Pamela Isom. With over 25 years of experience guiding leaders in corporate, public, and private sectors, Pamela, the CEO and Founder of IsAdvice & Consulting LLC, is a veteran in successfully navigating the complex realms of artificial intelligence, innovation, cyber issues, governance, data management, and ethical decision-making.
Ever wonder how a career in e-commerce can lead to becoming a leading advocate for data privacy? Join us as we chat with Kohei Kurihara, the co-founder and CEO of Privacy by Design Lab, who shares his unique entrepreneurial journey. From his beginnings at a major Japanese e-commerce company to launching a manga and anime crowdfunding platform, Kohei navigates us through his pivot to international marketing and his impactful work with blockchain organizations. Gain insights into his realization of data categorization's crucial role in innovation and how this inspired him to create a privacy-focused community, culminating in the Privacy by Design Conference.
In the latter part of the episode, we unravel the complex world of data transfer and privacy governance, spotlighting TikTok as a case study. Explore the multifaceted challenges of international data protection and the implications for national security. Kohei emphasizes the significance of data categorization, understanding data lineage, and ensuring governance to prevent misuse. We also discuss Japan's AI guidelines, which promote transparency, privacy protection, and human-centric design. Exciting AI innovations that prioritize privacy and data minimization are paving the way for more accurate and trustworthy user interactions, making this episode a must-listen for anyone navigating the digital landscape.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Pamela Isom (00:00):
This podcast is for informational purposes only.
Personal views and opinionsexpressed by our podcast guests
are their own and not legaladvice, neither health tax, nor
professional nor officialstatements by their
organizations.
Guest views may not be those ofthe host views may not be those
(00:32):
of the host.
Hello and welcome to AI or Not,the podcast where business
leaders from around the globeshare wisdom and insights that
are needed now to address issuesand guide success in your
artificial intelligence anddigital transformation journey.
My name is Pamela Isom and I'myour podcast host, and we have
yet another special guest withus today Kohei Kurihara.
Kohei is co-founder and chiefexecutive officer of Privacy by
(00:58):
Design.
We met recently, where I was aguest on his podcast, and we
have remained in contact.
Kohei, welcome to AI or Not.
Kohei Kurihara (01:11):
Yeah, thank you for coming, Mira.
That's a privilege to join yourchannel, so thank you again.
Pamela Isom (01:18):
Yeah, and so the first thing I want to know is
can you please tell me a littlebit more about yourself?
You have a very interestingjourney.
You have your entrepreneur withPrivacy by Design Lab.
You have an interesting careerat large.
So tell me more about yourself,your career, how you got to
(01:39):
where you are today, how did youget going with entrepreneurship
and why privacy by design labssure.
Kohei Kurihara (01:48):
Thank you for the questions.
So back to my history.
I started my own company from2014, when I was in a 24 at the
moment.
I created my previous careerfrom the largest Japanese
e-commerce company and I startedmy first business with four of
(02:09):
the cargos from differentcountries.
My first project was the mangaand anime creators platform,
which is supporting theirfundraising.
We call this the crowdfundingplatform for them because a lot
of the manga creators or animecreators have been challenged to
(02:33):
make their own funds to makecontent deliveries, so we're
gonna help them through ourplatform.
But actually the first projectwas not going successfully due
to some of the business failures.
So I have to reconsider our ownopportunities, how we can help
(02:55):
the other people who is tryingto create new things.
So I changed.
My business is just onlyfocusing on the creators, but
also some of the interestingperson just want to sell them by
the products cross borders, soI do focus on the marketing
(03:18):
channel to deliver the productsand businesses to the
international opportunities.
So that's my brief history.
And I was lucky to be a part ofthe new initiative from the
United States in 2017, which isblockchain organizations.
(03:40):
So they work for the nonprofitactions and they support some
American governments or publicsectors to encourage them to
start using the new technology.
President, to make a communityand engage with the Japanese
(04:11):
regulators to encourage them tostart using the blockchain.
And I'm trying to reach some ofthe community leaders in the
international market, such assome regulators in Singapore,
regulators in Europe.
I talked with them how we cancreate a new environment to
start using the blockchain inthe future.
(04:31):
But I realized through theconversation with them the
blockchain is the infrastructure, but the infrastructure is less
than important from the societyBecause the infrastructure
itself is not working so well.
They need more information anddata to make it effective.
(04:55):
But I realize at this time also, there is no specific
taxonomies to define the dataitself, so that's more important
.
To make an innovation in oursocieties, we have to categorize
(05:16):
each of the data.
What kind of data set isimportant to create innovation?
This is the opportunity where Istarted to work on the privacy
and data protection part.
I came back from the UNESCO 2019.
After talking with someexecutives, I came back with new
(05:39):
ideas to create aninternational collaboration
community and I came back toJapan and talked with some of
the colleagues ideas to createinternational collaboration
community and I came back toJapan and talked with some of
the curriculum and gathered thefour members.
Let's get started thegrassroots approach and we
created a company from 2000,training during the COVID and we
(06:04):
started community-basedcommunication with the
regulators, business persons,several organizations and we
tried to engage withinternational practitioners as
well.
Then, finally, we had startedour main business the Privacy by
(06:24):
Design Conference.
We organized an annual and thefirst edition was 2021.
We invited regulators andbusiness persons, cp
organization to gather and havea dialogue to create a better
society in the privacy world.
So that's a brief story of mycareers.
Pamela Isom (06:47):
Well, that's pretty interesting.
So there's a couple of thingsthat I want to reiterate from
what you just said.
So one I appreciate the factthat you learned from your
experiences and didn't stop, butbrought that forward.
So if I think aboutentrepreneurship, I believe that
that's what it's all about.
So I heard you say you startedoriginally focusing on content
(07:11):
and content development and thenyou expanded it to the
marketing side of the house andfocus more on marketing, and
then which is where you aretoday and then you morphed into
a privacy by design lab.
I'm also interested to know tosee that you focus on community.
(07:32):
So that international community, I think, is really good, and I
appreciate that, because wehonestly need more of that.
So the reason why I liketalking to you and the reason
why I was honored to have you asa guest is because it's really
important for businesses tounderstand, not just within
their local domains, but at aglobal perspective, what are the
(07:53):
regulations?
How do we make sure that ourproducts are going to be
effective as they are applied ata global scale?
And so conversations like thisare very helpful, but it's
really nice to know that youhave a focus on communities and
a community orientation that isat an international scale.
I heard you say that a coupleof times when you were going
(08:16):
over your background.
So thank you very much and Iappreciate your business and I
appreciate understanding yourgrowth and your trajectory, so
thank you very much for that.
One question I have for you,really, that I want to discuss.
It's not a question, but I'dlike to just discuss more around
the AI guidelines for business.
(08:37):
I think it's version 1.0, theJapanese government has compiled
AI guidelines for business.
Can we talk some more aboutthat?
I'd like to know more about howthat's impacting you and what
are things that I should beaware of, for instance, as a
small business owner here in theUnited States.
Let's talk some more about that.
Kohei Kurihara (09:00):
Sure, that guideline has been released in
this April.
Before the publishing of thisguideline, the Japanese
government has made some actions, just like the Hiroshima AI
process, which is very famous.
In last year in the G7gathering and also they have
(09:22):
been discussing a lot of thingswith the different community,
which is just like theindustrial community, scientific
community.
There is a bunch of the workinggroup has been organized of the
japanese government, thefinally, the door discussion has
been consolidated as the oneguideline then just published.
So that's a short history howit works and this is a very big
(09:47):
impact to the industry people,because in last year we have
talked a lot about how we canuse the AI itself.
They didn't talk about a lot ofthe things, especially for the
privacy copyrights.
They just care about it, butthe business side is in almost
(10:10):
the actions.
But from this year theatmosphere is becoming changed
to focus on the privacycopyrights, fundamental rights.
I think those importantdialogue has been started this
moment and this is veryimportant.
(10:31):
The government has been releasedthis kind of guidelines and
included some of the veryimportant concepts.
So the Japanese government istrying to give more freedom for
the business side to use AI tocreate new innovations From this
year.
They tried to change a bit toregulate some parts of the AI
(10:55):
usage, but they are starting tobe more open, more voluntary for
the enterprises to comply withthe principle of using personal
information for AI use.
So this is a little bitdifferent from the perspective,
(11:16):
such as in Europe, the UnitedStates.
The government is trying tobalance between the regulation
and businesses at this moment.
So the guideline has been acomparison.
Once the company wants to usethe AI technology, that's a good
(11:36):
navigation, even for the smallcompany.
They are trying to pick up somepoints and leverage their own
principle.
So this is a very importantnotice in the market of the AI
in this year.
Pamela Isom (11:51):
So you're saying that what's different about it
or what's advancing about it isthere's more focus on innovation
and using AI because theculture sees it as valuable.
But did I hear you say that nowthey're starting to introduce
(12:13):
more around privacy and theregulations but at the same time
, still promote the use of AIfor innovation?
Kohei Kurihara (12:25):
Yeah, okay, actually, there is a very few
companies compared to theWestern regions to invest in AI
because the amount of investmenthas been very small in our
country at this moment.
So once we put very strictregulations for the enterprise
(12:49):
side, the fields become moreconservative to use to invest
new technology.
So that's a Japanese mentality.
So the government side is alsopaying attention to how they can
pick up the new innovations,not just regulate it.
That's why the government triedto look for the best efforts to
(13:14):
create innovation through theAI opportunities.
Pamela Isom (13:20):
Okay, yeah, that makes a whole lot of sense, and
I know that culture iseverything, so it takes time to
really start to mold and allowculture to adapt to innovations.
But I was reading that Japan isexperiencing aging populations,
(13:41):
that projections show missionworker deficits by 2040, and
that AI is intended to boostproductivity.
I believe that the caution thatthe regulators are introducing
is global, so that makes a lotof sense, because you want the
(14:02):
AI solutions to not introduceprivacy, risk and other types of
risk.
I think that that makes a wholelot of sense and it's nice to
see, actually, that there is afocus on using AI to boost
productivity.
So that's really good to seeand that blends in with what's
happening in Western culture aswell, so I think it's great that
(14:26):
you point that out.
So, within that AI guidelinesfor business, I saw categories
around human-centric design,safety, fairness, privacy
protection and transparency.
I'd like to talk some more aboutprivacy protection and
accountability.
So I've been involved innumerous discussions with folks,
(14:47):
and one of the discussions thatI've been having that I'd like
to continue even in thisdiscussion, is around data
categorization.
So I believe that in order forus to protect the information,
we have to categorize it.
So we have to understand thedata and we have to
categorizeize data so that wecan protect it, and particularly
(15:09):
around one's privacy.
Now I'd like to get moreinsights on that from the
(15:36):
standpoint of privacy protectionand data categorization and
then maybe talk.
Well, first give me yourperspective that.
Am I on the right track?
Do you want to add to what I'msaying?
I personally believe thatcategorization is everything
when it comes to privacyprotection, but what's your
thoughts?
Kohei Kurihara (15:56):
yeah, I totally agree that your opinions.
The categorization might be thevery important to protect the
information, especially becausea lot of the enterprises
requirement at this moment whatkind of the information could be
the personal personallyidentifiable.
(16:16):
That means it directs you thecoverage of the regulations
whether your business model orbusiness data can be complied or
not.
So that's critical for thebusiness side.
But also it's very difficult todefine this kind of data, these
(16:37):
kind of categories, and thereis some of the difference in a
context in between.
Like Europe and GDPR has beenlike the special category data.
Those data is not always samelevels of the protection in a
different region, even in ourcountries.
(16:58):
Or this data is under the GDPRcould be the special category,
but in our regulation this isthe same level of the protection
or not.
So that's some gaps in thedifferent regions.
The problem is how we canharmonize the different level of
(17:19):
the personal identifiable andhow we can be harmonized actions
in a different region.
So that's why I'm now payingattention to the cross-border
deals.
So we have a different level ofgranularities to the
perceptions of the personalidentifiable information.
(17:42):
But we need to protect thefundamental rights, how we can
cooperate together.
So that's a very importantcontext for us in the privacy
and data protection communityright now.
Pamela Isom (17:55):
Is the protection of the fundamental rights and
the PII.
Well, you mentioned both.
So protection of thefundamental rights and you said
that there are differences whenit comes to the geographic
locations, so, for instance,categorization of PII in one
nation may be different than inanother.
Can we talk some more aboutthat?
(18:18):
What are some examples of howit might be different?
I'm trying to understand moreabout what we mean.
Kohei Kurihara (18:27):
I mean the difference is the kind of the
threshold.
It means what is the level ofthe data has to be, the more
stronger, more weaker, securelevel of the deed, of the
personal information.
Of course we have thisdifference, just like the ISO.
(18:50):
This kind of standardization isa good difference, okay, but
under the regulation it's notalways sticking to the level of
the international standards.
So in this case we arestruggling.
Oh, iso has the level of thesecurity assurance, but in these
(19:11):
regulations might not be out ofthe scope and how they can deal
with it.
That's very important.
So we have some standards, butthis standard is not always
applicable to each localregulation.
So that's the challenge from myperspective.
Pamela Isom (19:31):
Got it.
So what you're saying is thereneeds to be some consistency
because, for instance, theindividual's personal
information in the United Statesmight be categorized as
personal, sensitive information,but in another nation it may
not necessarily be consideredsensitive information.
It may be personal, but it maynot be categorized as sensitive,
(19:53):
and I think a lot of times ithas to do with context, and that
is true.
I study on the variouscategories and I know that there
are differences.
There's overlap as well, but Iknow that there are differences.
Sometimes gender is notconsidered personal information
in some nations, where in theUnited States it is a part of
(20:17):
that categorization of personalinformation.
So I understand what you'resaying there.
I'd like to talk some more aboutdata transfer and data
localization.
So if I think about thesituation with TikTok and the
whole concept of what's going onthere, in that we need data
(20:37):
that resides in the UnitedStates to be managed by the
United States and governed bythe United States, or at least
governed by allied resources,there's this whole discussion
around transference of data anduse of data at a global scale.
(20:57):
Does that touch, in yourperspective, on data transfer
mechanisms and areas that weneed to improve from a privacy
perspective, does that alsotouch on categorization of data
and what do you see as theconnection?
Kohei Kurihara (21:17):
There is a bunch of issues that still exist and
especially for the datatransferring, as I mentioned in
the last part, we have adifferent level of data
protection in each category andbesides that, we see some of the
different issues.
That's a business perspective.
As I mentioned, tiktok, theyhave a lot of presence in the
(21:37):
United States, this woman butthe business perspective oh,
this company is originally fromChina.
Oh, this company is originallyfrom China.
It actually is verycontroversial in the level of
national security.
The internal business has cometo the more secure level of the
(21:59):
requirements.
It's not just one singlecompany, it's a kind of the
international movement.
At this moment there is asimilar case between Japan and
South Korea, the largestJapanese messaging app.
Their ownership share the halfpercentage is the South Korean
(22:21):
company, the half in theJapanese.
So in this case the SouthKorean company side has some
control of the data management.
It's not easy to free controlof the data administrations,
even the big company you imagineany platform company who got a
(22:44):
lot of the share in your country, but their ownership is a
different country.
In this case they can easilysneak in the accessing of
information for the nationalsecurity purposes as well.
That's a problem that happensactually from the business side.
(23:07):
That's a problem that happensactually from the business side.
That's the different layers ofthe systematic issues of the
data protection and privacy.
But the finally consider to thedata categorization as well.
If this data is very sensitive,this data is transferred to the
(23:29):
third country for the nationalsecurity purposes, just like
religious data or just likegenders or many other things.
Any infringement of thedemocratic decisions, such as
(23:49):
the election, the voting, thatactually happens in some
countries in a control by theother parties for the democratic
process that the thing isactually happens.
With the data transfer issue,we try to solve the problem
(24:12):
through the internationaldialogues, so that's very
important so that makes me thinkabout governance and
accountability.
Pamela Isom (24:19):
So I often always talk about governance and
putting the structures in placeto guide safety of the
information, protection of ourprivacy, and to just be there to
provide those guardrails.
And that has everything to dowith the data sets that are used
(24:40):
for AI and the AI models inthemselves.
So I think it's important tomaintain an inventory of the AI
models so that we know what ourmodels are used for.
But more important, which issomething that I always
mentioned, is understanding thatdata, the data lineage and the
data provenance, so that we know, should you even have access to
(25:04):
the data to begin with, whoshould have access and I think
that's what's happening with thewhole TikTok situation is who
should have access and, if so,who is going to be accountable
if there is an invasion ofprivacy or if data is misused.
But what we're trying to do inthat particular governance
(25:24):
perspective and governance atlarge is prevent things from
happening to begin with, becauseit is going to be hard to track
the lineage and the provenance,and it's going to be hard
because of the proliferation ofthe data.
So you bring about some reallygood points.
I'll go back to the guidelines,the Japan's AI guidelines for
(25:45):
business, version 1.0.
So we talked aboutaccountability.
We talked about transparencysome in that you want to know
who has the information Privacyprotection which is what you
specialize in and safety.
And then the human-centricdesign.
You know, I associate that withprivacy, in that we are looking
(26:06):
at ensuring that our privacy isprotected and that our privacy
is respected, and earlier youmentioned human rights, and so I
think that the human centricdesign is so important.
And then fairness.
So I am going to review somemore about that, but I think
that's a pretty important pieceof work that could potentially
(26:28):
scale internationally.
So the last thing I want to dois go into AI innovations.
Is there an AI innovation thatyou're excited about that you
want to share with us today?
I know you have a lot going onin the privacy lab.
Can you tell us how you'reusing AI and are there any AI
(26:50):
innovations that just reallyexcite you?
Kohei Kurihara (26:55):
Yeah, my point is the privacy is essential to
protect the fundamental rights.
Then also, the privacy is a newinducement for the users to
provide more accuracies of theinformation Under the guidelines
they mentioned that it's veryimportant to protect fundamental
(27:17):
rights because the user wantsto take a willingness to provide
more information and the AI cansqueeze the more accurate
information, the accuratefeedback.
So that's very important.
Even you got a lot of the data.
This data is in garbage.
The garbage out.
It's a processes of theinformations.
(27:39):
So if you want to have aproductivity the competitiveness
AI you should be moretransparent.
You should be more accountableto protect the privacy.
The competitiveness AI youshould be more transparent.
You should be more accountableto protect the privacy, the
copyrights, the fundamentalrights for the users.
Users can be your safety.
Users can be trusted to providemore good information for the
(28:02):
AI.
That could be thecompetitiveness in the future.
That's why I'm very excited tohave a new AI solution to
protect the privacy rights.
So that's very important.
And also I think AI will be anew step, which means small
(28:24):
amounts of the data, the dataminimization, but to create a
better feedback for the users,because the data itself is
becoming more similar to how theuser is behaving on the
internet.
So you don't have to store toomuch of the data, you just need
minimum data.
(28:44):
But the user wants to givefeedback.
Feedback is much more importantthan the data in the data.
You just need minimum data, butthe user wants to give feedback
.
Feedback is much more importantthan the data in the future.
So in this case, some of the AIis training to be more clever
with the small amounts of thedata.
I think it's a very biginnovation in the future because
(29:07):
a lot of the data set isnecessary.
They need more electricity, thepower to consume it, and that's
a big cost for the businessside as well.
So how we can minimize thesecosts and give them a great
feedback.
So I think it's acompetitiveness for the future.
So the privacy is the factorsto direct those new AI
(29:37):
technology and thecost-effectiveness
competitiveness as a businessperspective.
That's why I'm excited thefuture AI can create those kind
of elements to produce the moreeffective future.
Pamela Isom (29:51):
That's just a really great way to think about.
It is because I look a lot oftimes at sustainability and what
are some things that we can bedoing from a sustainability
perspective when it comes to AI.
And you just mentionedsomething really cool because
you talked about the feedback,which I hadn't talked about with
my clients yet.
I talked about other things,but not the feedback loop and
(30:14):
the fact that the instantfeedback will require us to
store less data, which couldultimately end up adding to
sustainability.
So that was really that's agreat innovation and I hadn't
really thought about it, hadn'teven had that discussion with my
clients and I hadn't reallythought about it, hadn't even
had that discussion with myclients.
So I appreciate you bringingthat up because that's a great
way to think about it.
And I do have discussionsaround the competitive advantage
(30:38):
, because the more the solutionsare sustainable and not adding
to energy consumption, thegreater your competitive
advantage is, so that we do have.
But I love the concept of thereal-time feedback, which means
less storage, which, when wethink about these sustainability
(30:59):
concepts, we don't think aboutstorage.
We think more about processingpower and speed and how it's
burning energy and consumingenergy.
So that's a great way to thinkabout it.
You also mentioned dataminimization, which still goes
to.
Do you need all thisinformation?
(31:19):
Do you need to be storing allthis information?
Because that's what businessesare doing today they're storing
too much information, more thanwhat is really needed, and then
that ultimately can get us intotrouble, especially if we don't
have good archive anddecommissioning programs and
processes in place.
So you brought up some reallygood points, but I love how you
(31:41):
tied that to not only protectingprivacy but sustainability.
So those are great innovations.
That's just great.
Okay, so I wanna know from youdo you have any words of wisdom
outside of what you've alreadyshared?
Do you have any words of wisdomor experiences that you've
(32:03):
already shared?
Do you have any words of wisdomor experiences that you'd like
to share with the listeners?
Kohei Kurihara (32:08):
Yeah, I would say Azana, I'm working on the
privacy by design.
The part of the by design isbecoming very important because,
for example, the AI isrepresenting the machine is the
part of the society.
They can create more innovativethings, just like then chat,
(32:33):
gpt.
We don't have to make an accordfrom scratch.
They can be like a basic codeor some kind of thing, because
they memorize a very importantamount of the information.
On the other side, thedevelopers on the business side
have to embrace the concept bydesign.
(32:56):
That's very important becauseall things become automatic.
So the creators, business sides,engineers have a liability of
producing a specific service,engineering.
So that's a similar concept ofthe automobile.
They have a lot ofresponsibility to manufacturers,
(33:20):
to those businesses, to themarket, because they have been a
very huge responsibility,responsibility to manufacturers,
to those businesses, to themarket, because they have been a
very huge responsibility forthe fundamental resources for
all the humans who drive in thecars.
If making any problems, justlike cars have some wrong system
(33:40):
, the drivers might be dead insome accidents.
The AI has the powers If thesesystems could be integrated in
the physical products so theautomotive car is an example
they might be making a kill todrivers if it makes a wrong.
(34:04):
So the thing is, ai is not justfor the software.
The software will be migratedto the hard things in the future
, so all the person whoconcerned with the processing of
the producing AI has to take aresponsibility.
So the by design approachignapproach is fundamental.
The same things of all theindustry have been worked
(34:26):
through.
So that's why I'm going to tryto deliver my message that
by-design is important.
Of course, privacy, of coursesecurity or other things to
protect fundamental rights.
Pamela Isom (34:40):
So that's great.
That's really good insight.
So your emphasis is on bydesign, because you're saying
that we want to integrate someof the principles up front and
at the onset rather than waitinguntil the end and privacy by
design.
I often say equity by designbecause I think we should build
in equitable solutions andsustainability.
(35:02):
I think we should be thinkingabout that in the onset rather
than wait until the software hasmade it all the way through the
life cycle and now we come backand try to retrofit.
So by design is very popularand very needed, so I agree with
that.
But I do think and agree withyou that it's about the life
cycle and looking at the entirelife cycle.
(35:24):
I heard you say that and thatAI is not just about the
software but integratingfundamental principles up front
or, as you said, by design.
I really want to thank you.
I hope I caught everything thatyou were saying.
Did I miss anything when Isummarized it there?
Did I get it?
Yeah, that's pretty good.
(35:46):
So I really want to thank youfor being with me and talking to
me.
I really appreciate you.
I had a great time when I wason your show and we had a good
dialogue and it's reallyinteresting this conversation
today because of the fact thatyou are a privacy person but an
innovator, and the innovationreally came out in this
(36:08):
discussion, which is how I am aswell.
I believe in balancing theinnovation and the risk, so
balance the two and payattention to both by design.
So I appreciate the fact thatyou have brought that up and I
hope that we can have moredialogue.
This has been a greatdiscussion and so thank you so
(36:30):
much for being here, and if youneed to get in touch with me,
you know how.
This podcast is for informational purposes only.
Personal views and opinionsexpressed by our podcast guests
are their own and not legaladvice, neither health tax, nor
professional nor officialstatements by their
organizations.
Guest views may not be those ofthe host views may not be those
(00:32):
of the host.
Hello and welcome to AI or Not,the podcast where business
leaders from around the globeshare wisdom and insights that
are needed now to address issuesand guide success in your
artificial intelligence anddigital transformation journey.
My name is Pamela Isom and I'myour podcast host, and we have
yet another special guest withus today Kohei Kurihara.
Kohei is co-founder and chiefexecutive officer of Privacy by
(00:58):
Design.
We met recently, where I was aguest on his podcast, and we
have remained in contact.
Kohei, welcome to AI or Not.
Kohei Kurihara (01:11):
Yeah, thank you for coming, Mira.
That's a privilege to join yourchannel, so thank you again.
Pamela Isom (01:18):
Yeah, and so the first thing I want to know is
can you please tell me a littlebit more about yourself?
You have a very interestingjourney.
You have your entrepreneur withPrivacy by Design Lab.
You have an interesting careerat large.
So tell me more about yourself,your career, how you got to
(01:39):
where you are today, how did youget going with entrepreneurship
and why privacy by design labssure.
Kohei Kurihara (01:48):
Thank you for the questions.
So back to my history.
I started my own company from2014, when I was in a 24 at the
moment.
I created my previous careerfrom the largest Japanese
e-commerce company and I startedmy first business with four of
(02:09):
the cargos from differentcountries.
My first project was the mangaand anime creators platform,
which is supporting theirfundraising.
We call this the crowdfundingplatform for them because a lot
of the manga creators or animecreators have been challenged to
(02:33):
make their own funds to makecontent deliveries, so we're
gonna help them through ourplatform.
But actually the first projectwas not going successfully due
to some of the business failures.
So I have to reconsider our ownopportunities, how we can help
(02:55):
the other people who is tryingto create new things.
So I changed.
My business is just onlyfocusing on the creators, but
also some of the interestingperson just want to sell them by
the products cross borders, soI do focus on the marketing
(03:18):
channel to deliver the productsand businesses to the
international opportunities.
So that's my brief history.
And I was lucky to be a part ofthe new initiative from the
United States in 2017, which isblockchain organizations.
(03:40):
So they work for the nonprofitactions and they support some
American governments or publicsectors to encourage them to
start using the new technology.
President, to make a communityand engage with the Japanese
(04:11):
regulators to encourage them tostart using the blockchain.
And I'm trying to reach some ofthe community leaders in the
international market, such assome regulators in Singapore,
regulators in Europe.
I talked with them how we cancreate a new environment to
start using the blockchain inthe future.
(04:31):
But I realized through theconversation with them the
blockchain is the infrastructure, but the infrastructure is less
than important from the societyBecause the infrastructure
itself is not working so well.
They need more information anddata to make it effective.
(04:55):
But I realize at this time also, there is no specific
taxonomies to define the dataitself, so that's more important
.
To make an innovation in oursocieties, we have to categorize
(05:16):
each of the data.
What kind of data set isimportant to create innovation?
This is the opportunity where Istarted to work on the privacy
and data protection part.
I came back from the UNESCO 2019.
After talking with someexecutives, I came back with new
(05:39):
ideas to create aninternational collaboration
community and I came back toJapan and talked with some of
the colleagues ideas to createinternational collaboration
community and I came back toJapan and talked with some of
the curriculum and gathered thefour members.
Let's get started thegrassroots approach and we
created a company from 2000,training during the COVID and we
(06:04):
started community-basedcommunication with the
regulators, business persons,several organizations and we
tried to engage withinternational practitioners as
well.
Then, finally, we had startedour main business the Privacy by
(06:24):
Design Conference.
We organized an annual and thefirst edition was 2021.
We invited regulators andbusiness persons, cp
organization to gather and havea dialogue to create a better
society in the privacy world.
So that's a brief story of mycareers.
Pamela Isom (06:47):
Well, that's pretty interesting.
So there's a couple of thingsthat I want to reiterate from
what you just said.
So one I appreciate the factthat you learned from your
experiences and didn't stop, butbrought that forward.
So if I think aboutentrepreneurship, I believe that
that's what it's all about.
So I heard you say you startedoriginally focusing on content
(07:11):
and content development and thenyou expanded it to the
marketing side of the house andfocus more on marketing, and
then which is where you aretoday and then you morphed into
a privacy by design lab.
I'm also interested to know tosee that you focus on community.
(07:32):
So that international community, I think, is really good, and I
appreciate that, because wehonestly need more of that.
So the reason why I liketalking to you and the reason
why I was honored to have you asa guest is because it's really
important for businesses tounderstand, not just within
their local domains, but at aglobal perspective, what are the
(07:53):
regulations?
How do we make sure that ourproducts are going to be
effective as they are applied ata global scale?
And so conversations like thisare very helpful, but it's
really nice to know that youhave a focus on communities and
a community orientation that isat an international scale.
I heard you say that a coupleof times when you were going
(08:16):
over your background.
So thank you very much and Iappreciate your business and I
appreciate understanding yourgrowth and your trajectory, so
thank you very much for that.
One question I have for you,really, that I want to discuss.
It's not a question, but I'dlike to just discuss more around
the AI guidelines for business.
(08:37):
I think it's version 1.0, theJapanese government has compiled
AI guidelines for business.
Can we talk some more aboutthat?
I'd like to know more about howthat's impacting you and what
are things that I should beaware of, for instance, as a
small business owner here in theUnited States.
Let's talk some more about that.
Kohei Kurihara (09:00):
Sure, that guideline has been released in
this April.
Before the publishing of thisguideline, the Japanese
government has made some actions, just like the Hiroshima AI
process, which is very famous.
In last year in the G7gathering and also they have
(09:22):
been discussing a lot of thingswith the different community,
which is just like theindustrial community, scientific
community.
There is a bunch of the workinggroup has been organized of the
japanese government, thefinally, the door discussion has
been consolidated as the oneguideline then just published.
So that's a short history howit works and this is a very big
(09:47):
impact to the industry people,because in last year we have
talked a lot about how we canuse the AI itself.
They didn't talk about a lot ofthe things, especially for the
privacy copyrights.
They just care about it, butthe business side is in almost
(10:10):
the actions.
But from this year theatmosphere is becoming changed
to focus on the privacycopyrights, fundamental rights.
I think those importantdialogue has been started this
moment and this is veryimportant.
(10:31):
The government has been releasedthis kind of guidelines and
included some of the veryimportant concepts.
So the Japanese government istrying to give more freedom for
the business side to use AI tocreate new innovations From this
year.
They tried to change a bit toregulate some parts of the AI
(10:55):
usage, but they are starting tobe more open, more voluntary for
the enterprises to comply withthe principle of using personal
information for AI use.
So this is a little bitdifferent from the perspective,
(11:16):
such as in Europe, the UnitedStates.
The government is trying tobalance between the regulation
and businesses at this moment.
So the guideline has been acomparison.
Once the company wants to usethe AI technology, that's a good
(11:36):
navigation, even for the smallcompany.
They are trying to pick up somepoints and leverage their own
principle.
So this is a very importantnotice in the market of the AI
in this year.
Pamela Isom (11:51):
So you're saying that what's different about it
or what's advancing about it isthere's more focus on innovation
and using AI because theculture sees it as valuable.
But did I hear you say that nowthey're starting to introduce
(12:13):
more around privacy and theregulations but at the same time
, still promote the use of AIfor innovation?
Kohei Kurihara (12:25):
Yeah, okay, actually, there is a very few
companies compared to theWestern regions to invest in AI
because the amount of investmenthas been very small in our
country at this moment.
So once we put very strictregulations for the enterprise
(12:49):
side, the fields become moreconservative to use to invest
new technology.
So that's a Japanese mentality.
So the government side is alsopaying attention to how they can
pick up the new innovations,not just regulate it.
That's why the government triedto look for the best efforts to
(13:14):
create innovation through theAI opportunities.
Pamela Isom (13:20):
Okay, yeah, that makes a whole lot of sense, and
I know that culture iseverything, so it takes time to
really start to mold and allowculture to adapt to innovations.
But I was reading that Japan isexperiencing aging populations,
(13:41):
that projections show missionworker deficits by 2040, and
that AI is intended to boostproductivity.
I believe that the caution thatthe regulators are introducing
is global, so that makes a lotof sense, because you want the
(14:02):
AI solutions to not introduceprivacy, risk and other types of
risk.
I think that that makes a wholelot of sense and it's nice to
see, actually, that there is afocus on using AI to boost
productivity.
So that's really good to seeand that blends in with what's
happening in Western culture aswell, so I think it's great that
(14:26):
you point that out.
So, within that AI guidelinesfor business, I saw categories
around human-centric design,safety, fairness, privacy
protection and transparency.
I'd like to talk some more aboutprivacy protection and
accountability.
So I've been involved innumerous discussions with folks,
(14:47):
and one of the discussions thatI've been having that I'd like
to continue even in thisdiscussion, is around data
categorization.
So I believe that in order forus to protect the information,
we have to categorize it.
So we have to understand thedata and we have to
categorizeize data so that wecan protect it, and particularly
(15:09):
around one's privacy.
Now I'd like to get moreinsights on that from the
(15:36):
standpoint of privacy protectionand data categorization and
then maybe talk.
Well, first give me yourperspective that.
Am I on the right track?
Do you want to add to what I'msaying?
I personally believe thatcategorization is everything
when it comes to privacyprotection, but what's your
thoughts?
Kohei Kurihara (15:56):
yeah, I totally agree that your opinions.
The categorization might be thevery important to protect the
information, especially becausea lot of the enterprises
requirement at this moment whatkind of the information could be
the personal personallyidentifiable.
(16:16):
That means it directs you thecoverage of the regulations
whether your business model orbusiness data can be complied or
not.
So that's critical for thebusiness side.
But also it's very difficult todefine this kind of data, these
(16:37):
kind of categories, and thereis some of the difference in a
context in between.
Like Europe and GDPR has beenlike the special category data.
Those data is not always samelevels of the protection in a
different region, even in ourcountries.
(16:58):
Or this data is under the GDPRcould be the special category,
but in our regulation this isthe same level of the protection
or not.
So that's some gaps in thedifferent regions.
The problem is how we canharmonize the different level of
(17:19):
the personal identifiable andhow we can be harmonized actions
in a different region.
So that's why I'm now payingattention to the cross-border
deals.
So we have a different level ofgranularities to the
perceptions of the personalidentifiable information.
(17:42):
But we need to protect thefundamental rights, how we can
cooperate together.
So that's a very importantcontext for us in the privacy
and data protection communityright now.
Pamela Isom (17:55):
Is the protection of the fundamental rights and
the PII.
Well, you mentioned both.
So protection of thefundamental rights and you said
that there are differences whenit comes to the geographic
locations, so, for instance,categorization of PII in one
nation may be different than inanother.
Can we talk some more aboutthat?
(18:18):
What are some examples of howit might be different?
I'm trying to understand moreabout what we mean.
Kohei Kurihara (18:27):
I mean the difference is the kind of the
threshold.
It means what is the level ofthe data has to be, the more
stronger, more weaker, securelevel of the deed, of the
personal information.
Of course we have thisdifference, just like the ISO.
(18:50):
This kind of standardization isa good difference, okay, but
under the regulation it's notalways sticking to the level of
the international standards.
So in this case we arestruggling.
Oh, iso has the level of thesecurity assurance, but in these
(19:11):
regulations might not be out ofthe scope and how they can deal
with it.
That's very important.
So we have some standards, butthis standard is not always
applicable to each localregulation.
So that's the challenge from myperspective.
Pamela Isom (19:31):
Got it.
So what you're saying is thereneeds to be some consistency
because, for instance, theindividual's personal
information in the United Statesmight be categorized as
personal, sensitive information,but in another nation it may
not necessarily be consideredsensitive information.
It may be personal, but it maynot be categorized as sensitive,
(19:53):
and I think a lot of times ithas to do with context, and that
is true.
I study on the variouscategories and I know that there
are differences.
There's overlap as well, but Iknow that there are differences.
Sometimes gender is notconsidered personal information
in some nations, where in theUnited States it is a part of
(20:17):
that categorization of personalinformation.
So I understand what you'resaying there.
I'd like to talk some more aboutdata transfer and data
localization.
So if I think about thesituation with TikTok and the
whole concept of what's going onthere, in that we need data
(20:37):
that resides in the UnitedStates to be managed by the
United States and governed bythe United States, or at least
governed by allied resources,there's this whole discussion
around transference of data anduse of data at a global scale.
(20:57):
Does that touch, in yourperspective, on data transfer
mechanisms and areas that weneed to improve from a privacy
perspective, does that alsotouch on categorization of data
and what do you see as theconnection?
Kohei Kurihara (21:17):
There is a bunch of issues that still exist and
especially for the datatransferring, as I mentioned in
the last part, we have adifferent level of data
protection in each category andbesides that, we see some of the
different issues.
That's a business perspective.
As I mentioned, tiktok, theyhave a lot of presence in the
(21:37):
United States, this woman butthe business perspective oh,
this company is originally fromChina.
Oh, this company is originallyfrom China.
It actually is verycontroversial in the level of
national security.
The internal business has cometo the more secure level of the
(21:59):
requirements.
It's not just one singlecompany, it's a kind of the
international movement.
At this moment there is asimilar case between Japan and
South Korea, the largestJapanese messaging app.
Their ownership share the halfpercentage is the South Korean
(22:21):
company, the half in theJapanese.
So in this case the SouthKorean company side has some
control of the data management.
It's not easy to free controlof the data administrations,
even the big company you imagineany platform company who got a
(22:44):
lot of the share in your country, but their ownership is a
different country.
In this case they can easilysneak in the accessing of
information for the nationalsecurity purposes as well.
That's a problem that happensactually from the business side.
(23:07):
That's a problem that happensactually from the business side.
That's the different layers ofthe systematic issues of the
data protection and privacy.
But the finally consider to thedata categorization as well.
If this data is very sensitive,this data is transferred to the
(23:29):
third country for the nationalsecurity purposes, just like
religious data or just likegenders or many other things.
Any infringement of thedemocratic decisions, such as
(23:49):
the election, the voting, thatactually happens in some
countries in a control by theother parties for the democratic
process that the thing isactually happens.
With the data transfer issue,we try to solve the problem
(24:12):
through the internationaldialogues, so that's very
important so that makes me thinkabout governance and
accountability.
Pamela Isom (24:19):
So I often always talk about governance and
putting the structures in placeto guide safety of the
information, protection of ourprivacy, and to just be there to
provide those guardrails.
And that has everything to dowith the data sets that are used
(24:40):
for AI and the AI models inthemselves.
So I think it's important tomaintain an inventory of the AI
models so that we know what ourmodels are used for.
But more important, which issomething that I always
mentioned, is understanding thatdata, the data lineage and the
data provenance, so that we know, should you even have access to
(25:04):
the data to begin with, whoshould have access and I think
that's what's happening with thewhole TikTok situation is who
should have access and, if so,who is going to be accountable
if there is an invasion ofprivacy or if data is misused.
But what we're trying to do inthat particular governance
(25:24):
perspective and governance atlarge is prevent things from
happening to begin with, becauseit is going to be hard to track
the lineage and the provenance,and it's going to be hard
because of the proliferation ofthe data.
So you bring about some reallygood points.
I'll go back to the guidelines,the Japan's AI guidelines for
(25:45):
business, version 1.0.
So we talked aboutaccountability.
We talked about transparencysome in that you want to know
who has the information Privacyprotection which is what you
specialize in and safety.
And then the human-centricdesign.
You know, I associate that withprivacy, in that we are looking
(26:06):
at ensuring that our privacy isprotected and that our privacy
is respected, and earlier youmentioned human rights, and so I
think that the human centricdesign is so important.
And then fairness.
So I am going to review somemore about that, but I think
that's a pretty important pieceof work that could potentially
(26:28):
scale internationally.
So the last thing I want to dois go into AI innovations.
Is there an AI innovation thatyou're excited about that you
want to share with us today?
I know you have a lot going onin the privacy lab.
Can you tell us how you'reusing AI and are there any AI
(26:50):
innovations that just reallyexcite you?
Kohei Kurihara (26:55):
Yeah, my point is the privacy is essential to
protect the fundamental rights.
Then also, the privacy is a newinducement for the users to
provide more accuracies of theinformation Under the guidelines
they mentioned that it's veryimportant to protect fundamental
(27:17):
rights because the user wantsto take a willingness to provide
more information and the AI cansqueeze the more accurate
information, the accuratefeedback.
So that's very important.
Even you got a lot of the data.
This data is in garbage.
The garbage out.
It's a processes of theinformations.
(27:39):
So if you want to have aproductivity the competitiveness
AI you should be moretransparent.
You should be more accountableto protect the privacy.
The competitiveness AI youshould be more transparent.
You should be more accountableto protect the privacy, the
copyrights, the fundamentalrights for the users.
Users can be your safety.
Users can be trusted to providemore good information for the
(28:02):
AI.
That could be thecompetitiveness in the future.
That's why I'm very excited tohave a new AI solution to
protect the privacy rights.
So that's very important.
And also I think AI will be anew step, which means small
(28:24):
amounts of the data, the dataminimization, but to create a
better feedback for the users,because the data itself is
becoming more similar to how theuser is behaving on the
internet.
So you don't have to store toomuch of the data, you just need
minimum data.
(28:44):
But the user wants to givefeedback.
Feedback is much more importantthan the data in the data.
You just need minimum data, butthe user wants to give feedback
.
Feedback is much more importantthan the data in the future.
So in this case, some of the AIis training to be more clever
with the small amounts of thedata.
I think it's a very biginnovation in the future because
(29:07):
a lot of the data set isnecessary.
They need more electricity, thepower to consume it, and that's
a big cost for the businessside as well.
So how we can minimize thesecosts and give them a great
feedback.
So I think it's acompetitiveness for the future.
So the privacy is the factorsto direct those new AI
(29:37):
technology and thecost-effectiveness
competitiveness as a businessperspective.
That's why I'm excited thefuture AI can create those kind
of elements to produce the moreeffective future.
Pamela Isom (29:51):
That's just a really great way to think about.
It is because I look a lot oftimes at sustainability and what
are some things that we can bedoing from a sustainability
perspective when it comes to AI.
And you just mentionedsomething really cool because
you talked about the feedback,which I hadn't talked about with
my clients yet.
I talked about other things,but not the feedback loop and
(30:14):
the fact that the instantfeedback will require us to
store less data, which couldultimately end up adding to
sustainability.
So that was really that's agreat innovation and I hadn't
really thought about it, hadn'teven had that discussion with my
clients and I hadn't reallythought about it, hadn't even
had that discussion with myclients.
So I appreciate you bringingthat up because that's a great
way to think about it.
And I do have discussionsaround the competitive advantage
(30:38):
, because the more the solutionsare sustainable and not adding
to energy consumption, thegreater your competitive
advantage is, so that we do have.
But I love the concept of thereal-time feedback, which means
less storage, which, when wethink about these sustainability
(30:59):
concepts, we don't think aboutstorage.
We think more about processingpower and speed and how it's
burning energy and consumingenergy.
So that's a great way to thinkabout it.
You also mentioned dataminimization, which still goes
to.
Do you need all thisinformation?
(31:19):
Do you need to be storing allthis information?
Because that's what businessesare doing today they're storing
too much information, more thanwhat is really needed, and then
that ultimately can get us intotrouble, especially if we don't
have good archive anddecommissioning programs and
processes in place.
So you brought up some reallygood points, but I love how you
(31:41):
tied that to not only protectingprivacy but sustainability.
So those are great innovations.
That's just great.
Okay, so I wanna know from youdo you have any words of wisdom
outside of what you've alreadyshared?
Do you have any words of wisdomor experiences that you've
(32:03):
already shared?
Do you have any words of wisdomor experiences that you'd like
to share with the listeners?
Kohei Kurihara (32:08):
Yeah, I would say Azana, I'm working on the
privacy by design.
The part of the by design isbecoming very important because,
for example, the AI isrepresenting the machine is the
part of the society.
They can create more innovativethings, just like then chat,
(32:33):
gpt.
We don't have to make an accordfrom scratch.
They can be like a basic codeor some kind of thing, because
they memorize a very importantamount of the information.
On the other side, thedevelopers on the business side
have to embrace the concept bydesign.
(32:56):
That's very important becauseall things become automatic.
So the creators, business sides,engineers have a liability of
producing a specific service,engineering.
So that's a similar concept ofthe automobile.
They have a lot ofresponsibility to manufacturers,
(33:20):
to those businesses, to themarket, because they have been a
very huge responsibility,responsibility to manufacturers,
to those businesses, to themarket, because they have been a
very huge responsibility forthe fundamental resources for
all the humans who drive in thecars.
If making any problems, justlike cars have some wrong system
(33:40):
, the drivers might be dead insome accidents.
The AI has the powers If thesesystems could be integrated in
the physical products so theautomotive car is an example
they might be making a kill todrivers if it makes a wrong.
(34:04):
So the thing is, ai is not justfor the software.
The software will be migratedto the hard things in the future
, so all the person whoconcerned with the processing of
the producing AI has to take aresponsibility.
So the by design approachignapproach is fundamental.
The same things of all theindustry have been worked
(34:26):
through.
So that's why I'm going to tryto deliver my message that
by-design is important.
Of course, privacy, of coursesecurity or other things to
protect fundamental rights.
Pamela Isom (34:40):
So that's great.
That's really good insight.
So your emphasis is on bydesign, because you're saying
that we want to integrate someof the principles up front and
at the onset rather than waitinguntil the end and privacy by
design.
I often say equity by designbecause I think we should build
in equitable solutions andsustainability.
(35:02):
I think we should be thinkingabout that in the onset rather
than wait until the software hasmade it all the way through the
life cycle and now we come backand try to retrofit.
So by design is very popularand very needed, so I agree with
that.
But I do think and agree withyou that it's about the life
cycle and looking at the entirelife cycle.
(35:24):
I heard you say that and thatAI is not just about the
software but integratingfundamental principles up front
or, as you said, by design.
I really want to thank you.
I hope I caught everything thatyou were saying.
Did I miss anything when Isummarized it there?
Did I get it?
Yeah, that's pretty good.
(35:46):
So I really want to thank youfor being with me and talking to
me.
I really appreciate you.
I had a great time when I wason your show and we had a good
dialogue and it's reallyinteresting this conversation
today because of the fact thatyou are a privacy person but an
innovator, and the innovationreally came out in this
(36:08):
discussion, which is how I am aswell.
I believe in balancing theinnovation and the risk, so
balance the two and payattention to both by design.
So I appreciate the fact thatyou have brought that up and I
hope that we can have moredialogue.
This has been a greatdiscussion and so thank you so
(36:30):
much for being here, and if youneed to get in touch with me,
you know how.
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Introducing… Aubrey O’Day Diddy’s former protege, television personality, platinum selling music artist, Danity Kane alum Aubrey O’Day joins veteran journalists Amy Robach and TJ Holmes to provide a unique perspective on the trial that has captivated the attention of the nation. Join them throughout the trial as they discuss, debate, and dissect every detail, every aspect of the proceedings. Aubrey will offer her opinions and expertise, as only she is qualified to do given her first-hand knowledge. From her days on Making the Band, as she emerged as the breakout star, the truth of the situation would be the opposite of the glitz and glamour. Listen throughout every minute of the trial, for this exclusive coverage. Amy Robach and TJ Holmes present Aubrey O’Day, Covering the Diddy Trial, an iHeartRadio podcast.
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Karoline Borega married a man of honor – a respected Colorado Springs Police officer. She knew there would be sacrifices to accommodate her husband’s career. But she had no idea that he was using his badge to fool everyone. This season, we expose a man who swore two sacred oaths—one to his badge, one to his bride—and broke them both. We follow Karoline as she questions everything she thought she knew about her partner of over 20 years. And make sure to check out Seasons 1-3 of Betrayal, along with Betrayal Weekly Season 1.
Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.