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new way to immerse yourself in learning with InfoSec

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. Now let's begin the show Today

2:20

on CyberWork . I'm very excited to welcome

2:23

Debbie Reynolds , the data diva herself

2:25

to discuss data privacy . Now Debbie

2:27

developed a love of learning about data privacy

2:29

ever since working in library science , and

2:31

she took it through to legal technologies and now

2:33

runs her own data privacy consultancy

2:36

and hosts a long-running podcast , the

2:38

Data Diva Talks Privacy Podcast

2:40

. We talk about data privacy in all its

2:42

complex , nerdy and sometimes frustrating permutations

2:45

how GDPR helped bring Debbie

2:47

to even greater attention , how AI

2:49

has added even more layers of complexity

2:51

to this puzzle . And Debbie gives some great

2:53

advice for listeners ready to dip their toes into

2:55

the waters of a data privacy practitioner

2:58

career . That's all today on CyberWork

3:00

. Hello

3:06

and welcome to this week's episode of the CyberWork

3:08

podcast . My guests are a cross section

3:10

of cybersecurity industry thought leaders , and

3:12

our goal is to help you learn about cybersecurity

3:14

trends and how those trends affect the work

3:16

of infosec professionals , and

3:18

leave you with some tips and advice for breaking in or

3:21

moving up the ladder in the cybersecurity industry

3:23

. My guest today I'm very excited about this

3:25

is Debbie Reynolds . She's known as the

3:27

data diva . She's a leading expert in data

3:30

privacy and emerging technology . With

3:32

over 20 years in ad tech , fintech

3:34

, legal tech and AI . She delves

3:36

into smart cities , iot and data

3:38

privacy . She's a sought-after

3:40

keynote speaker , and Debbie has addressed

3:42

companies like Coca-Cola , paypal and Uber

3:45

. Her insights appear in the New York

3:47

Times and Wired , and

3:49

she is also the host of the number one podcast

3:52

, the Data Diva Talks Privacy Podcast

3:54

, which I love . I've listened to about half a dozen episodes

3:56

already . I'd highly recommend it . She's recognized

3:59

globally as a top data privacy

4:01

expert as well . Her leadership roles include

4:03

the US Department of Commerce's IoT

4:05

Advisory Board membership and the chair

4:08

of the IEEE Committee on

4:10

Cybersecurity for Human Centricity

4:12

, which is influencing the future of data privacy

4:14

and emerging technology . So no

4:16

guesses in terms of what we're gonna be talking about today . It's gonna be

4:19

data privacy all the way , but I'm looking forward

4:21

to learning more about Debbie and her journey

4:23

and how she got here . So , debbie , thank you so much for

4:25

joining me and welcome to CyberWork .

4:27

Thank you so much for having me on the show . I'm excited

4:29

to chat with you today ?

4:39

Oh , my pleasure . Yeah , like I said , I've been listening to your podcast for a while now and I'm

4:41

even , as someone who's not completely steeped in data privacy myself , it seems like I get at least

4:44

one really cool insight in every episode . So , yeah , I really appreciate it . So

4:46

yeah , debbie , to help our listeners get to know

4:48

you a little better where did you first get

4:50

interested in , like computers and technology

4:52

and security and privacy

4:54

was was there ? Was there an initial spark ? Was there a moment

4:57

when you said this is what I want to do with my life

4:59

, or what got you excited about it ?

5:01

yeah , well , it is quite

5:03

a pernicious journey . Uh , it wasn't

5:05

a straight line , I would say . Um

5:08

, I was actually a philosophy major in college

5:10

. I thought I was gonna actually become

5:12

a lawyer , uh , and I actually

5:15

my mother was diagnosed with cancer

5:17

when I was in my senior

5:19

year of college and so I

5:22

decided I want I need to do something

5:24

where I can be spend

5:26

more time with her . So I

5:28

started doing , you know

5:30

, back then it's called desktop publishing , like

5:32

now . It's like graphic design and different

5:34

things like that . And

5:36

I had a friend that had another friend

5:38

that was a

5:41

head of a university library and they wanted

5:43

to create databases

5:46

of books and so they asked me to

5:48

help out and I did and I fell

5:50

in love with data . So that

5:53

was kind of the beginning of my data journey . So

5:55

this was back in the day when

5:57

libraries had card catalogs

5:59

and they were trying to create

6:02

databases of books and you know

6:04

, you see how rapidly and differently you

6:06

know library science is now as it

6:08

was back then . But then

6:10

, during that time also , I

6:12

read a book called the Rights of Privacy and

6:15

Caroline Kennedy was a co . The Rights of Privacy and Caroline Kennedy

6:17

was a co-author of that book and the

6:19

book shocked me . Actually

6:21

it was a book my mother had and

6:23

she was very interested in it

6:26

and her interest made me interested

6:28

and

6:36

it was all about what's private and what isn't in the US . And I was , you know

6:38

, very shocked because I think in the US we think , you know , we're the land of the free , the

6:40

home of the brave , but we don't know that privacy is not like

6:42

a constitutional right . And

6:44

that book talks about those legal , you

6:47

know , areas , those gray areas

6:49

where people's privacy , you know , may be taken

6:51

advantage of . So that was around the time of

6:53

just , you know , like the early internet

6:56

, right , 1995 . And

6:58

so as I worked more and

7:00

started getting more in depth into technology

7:03

and more stuff started getting into digital

7:05

systems , I started to see , you

7:08

know , the problems with putting

7:10

people's personal data in these systems

7:12

or how the data was shared and different things like

7:14

that . And so I

7:16

, as I I was doing this work , I was working a lot

7:18

of multinational companies that were doing

7:21

data moves and data

7:23

transfers around the world , and in

7:25

order to do that you have to know , like , the laws

7:27

for different jurisdictions

7:29

, and back then that wasn't even a job

7:31

, right , it was just something you just had to know . But

7:34

as

7:37

the European Union started to

7:39

re-examine their

7:41

data protection regulations

7:43

, I started getting calls from companies

7:46

that knew me and they started asking me hey

7:48

, can you come talk to me about privacy ? And

7:50

so one of the first big companies they asked me

7:52

to come talk with them was mcdonald's corporation

7:55

. So I went to their corporate

7:57

legal department and talked to all their legal

7:59

folks around the world around

8:01

privacy , and this is before the

8:03

big chain and the general data

8:05

protection regulation came into play in

8:08

europe . And I was like , hey , this is even though

8:10

this is europe . This is going to be a huge , big deal and

8:12

this is why it is and this is how it's going to change

8:15

. You know your work , and it actually

8:17

did . And so , like nobody

8:19

in the US talked about that around that time

8:21

, right , this is before it came out . And

8:24

then I just kept talking about , hey , this is important

8:26

. You know , I felt like I was like Paul

8:29

Revere , like , oh , the British are coming . You

8:31

, the British are coming . You know , you need

8:33

to pay attention . And eventually , by

8:35

the time the regulation

8:37

went into full effect , I got a call from PBS

8:40

and they asked me to be on TV to talk about

8:42

germ data protection regulation

8:44

. It's funny because people still

8:47

contact me about that interview , so I made

8:49

some predictions that actually came true . It's pretty

8:51

funny , but yeah , so that's what

8:53

I decided . Well , maybe I should just do privacy

8:56

.

8:56

Yeah , absolutely . I

8:59

love that . So it sounds

9:01

like the sort of the roots

9:03

of the Data Diva experience came

9:05

from GDPR happening and a lot of people

9:07

not in Europe or companies

9:09

that were partly in Europe and partly

9:12

in the US were like help us understand

9:14

what the heck's going on here . Is that accurate

9:16

?

9:17

Yeah , absolutely Absolutely . So

9:19

it's fortuitous . You know , I'm like it's

9:22

so funny because what ? So ? The

9:24

GDPR went into full effect in

9:27

May 25th of 2018 . That's when

9:29

I was on PBS . But two

9:31

years before that , the law was passed and

9:33

I thought , you know , the

9:36

day that passed became a law

9:38

, quote-unquote , but not enforceable . I

9:40

thought , okay , I'm gonna wake up and today

9:43

everyone's gonna care about data protection and

9:45

like there was nothing on the news , there was

9:47

nothing , like nobody cared , right

9:49

. So I thought , oh god . So I thought

9:51

, well , I just need to talk about this a lot

9:53

. There even weren't things

9:55

written about it , right ? Uh , when

9:57

I was telling people about people like , oh , can you give

9:59

me a summary ? like there is no summary , you

10:02

know so I started doing like writing a lot

10:05

in that time period about it , just so

10:07

that there'll be some information that people can

10:09

look back on .

10:10

Yeah , yeah yeah , yeah , I

10:12

, I remember that that era . It's

10:14

funny . Yeah , yeahs don't really become laws

10:17

until they become enforceable , and I know that on

10:20

your show you talk about you know , if

10:22

you give your guests one wish , or

10:24

you know , king for a day , queen for a day , whatever

10:26

, in terms of making changes , and I over here

10:28

talk about having a magic gavel and stuff . So we'll

10:30

talk later about what kind of enforceable

10:34

things that we want to get

10:36

into with regarding the data privacy . But to

10:38

start with here I want to talk a little more about

10:40

your career . So I like to

10:42

look around . I

10:44

guess maybe this is an invasion of privacy , but I look at

10:46

your LinkedIn profile , your experiences , to get a

10:48

sense of what your history is

10:50

like and it gives me a sense of

10:53

you know , your employment story and

10:55

your your cyber history and stuff like that

10:57

. So I mean , you've , you know , uh

11:00

, done a lot of stuff uh

11:02

in you . You told us a little bit

11:04

about that in terms of library , science and so forth

11:06

, but you spent a good portion of your earlier career

11:08

working in law and specifically legal technology

11:11

. Uh , and I've had one other guest on who's

11:13

a law cyber person on the show in the past

11:15

and it's . I think it's not

11:17

a common path , but it's an interesting one . So

11:20

could you talk about how

11:22

a pivot like this from

11:24

the legal tech area I guess that was probably privacy related

11:26

too but like how did that sort of turn

11:29

into this complete world of data privacy

11:31

?

11:32

Yeah , well , I think people misunderstand

11:35

that part of my history . I've

11:37

always been a data person and I've always

11:39

done consulting around data

11:41

projects , but I have had situations

11:44

where I've worked

11:47

with companies that were involved in

11:49

legal stuff . But that was not , that

11:51

was not the whole entire , the whole

11:54

enchilada of what I worked on

11:56

, right ? So you know I was still working

11:58

. You know I'm still working like an ad tech

12:00

. You know people just call me up . I've

12:03

been very fortunate that people have called me up all

12:05

types of wacky things that they want to do with

12:09

data , and so I've been able to

12:11

. You know , for me , I think , if people

12:13

see , oh well , she's done some stuff in

12:15

legal tech , but I was never always

12:17

in legal tech Like I was in all

12:19

these other types of tech spaces . But

12:22

for me , to me , that's the

12:24

reason why my work

12:26

is so unique , because I traverse

12:29

all these different industries . I think people

12:31

just didn't know that I knew all . You know people

12:33

in business intelligence

12:35

, people in ad tech , people in you

12:37

know , pharma , all this other type of stuff

12:39

. Just because you

12:47

know , when you think of legal , a lot of legal issues

12:49

around data is around litigation , and

12:56

so companies have bigger data problems than litigation , so I work with them

12:58

on all those different things . So before litigation , you know people need to have better governance

13:00

of everything you know within their corporation

13:02

and a lot of my talking

13:04

with people over the years about privacy

13:07

is about how much bigger it

13:09

is than any one industry .

13:11

Yeah , yeah . Now I

13:13

want to sort of break apart how

13:15

you acquired this sort of tool , belt

13:17

of private , because I know it sounds like you . You

13:20

know you learned as as needed on the job and

13:22

so forth , but for a lot of our , our , our listeners

13:24

, they're trying to figure out you know where their

13:26

opportunity is , is going to come from . And

13:28

one of our past guests , chris Stevens , is , is

13:31

our InfoSec skills author

13:33

for privacy and sort

13:35

of privacy certifications . You

13:38

know the seven of them or whatever . And I'm

13:40

wondering if you can talk a little bit

13:42

about the combination of

13:45

how you sort of like came to learn , like

13:47

the different privacy regulation

13:51

structures around the world , the governance

13:53

. How did you sort of put all that together

13:55

? I mean , I know it was kind of on the job and

13:57

as you were going , but like , well , what are the different

13:59

pieces of this toolbox that sort of add

14:02

up to the whole ?

14:03

Yeah , actually it wasn't on the job . Privacy

14:06

is my own personal interest . So

14:09

, these are things that I was interested in

14:11

back then . As I said , when I read that book

14:13

in 1995 , I just

14:15

kept seeing , just in general

14:18

, how more data was being created

14:20

, more data was being collected , seeing

14:23

kind of the gaps , and that's what I talk a lot

14:25

about on my show . So I talk about the gaps in

14:27

privacy , the gaps in regulation

14:29

. You know how data plays within

14:32

data spaces , and so

14:34

what happened is my personal

14:36

interests converged with my professional

14:38

life . So you

14:40

know , like I see things , like people say , well

14:43

, let's put chips in pets

14:45

. And I thought , oh , this is bad , because

14:48

people are going to put chips in people at some

14:50

point . Right . And so for me

14:52

, I didn't ever think

14:54

that my personal interest in

14:56

privacy would turn into a business . But

14:59

it is because people will start saying

15:02

, well , we want to do this . Well , you know

15:04

. Like an example , let's say someone said

15:06

, ok , we have some data in France

15:08

and we want to transfer the

15:11

FTP over to the US , and I'm

15:13

like , well , you can't do that , yeah

15:16

. And they're like , well , why't do that ? And

15:18

they're like , well , why

15:21

? I'm like because they have , you know , this type of data can't be transferred because of you know

15:23

these blocking standards and those are things you know . That was not something that that

15:26

was . It was not a job requirement or anything

15:28

. That was what I brought my knowledge

15:30

that I had , just because that's something that

15:32

interests me . So for me

15:34

it's just been many years of reading , researching

15:38

, because I guess I'm you know , I'm

15:40

personally interested in privacy

15:42

. You know , I want you know what are people doing

15:44

with my data . So I think my , you

15:46

know , I think my motivation for

15:49

being interested in privacy is , is

15:51

personal . Yeah , Right

15:53

, I'm like well what , what you know , what are you doing

15:55

? And so I , when

15:57

I had a chance to get involved whether

16:00

it was , you know , this IOT advisory

16:02

board , you know I raised my

16:04

hand . I said , hey , I want to , you know change

16:07

. You know how can I use my skills

16:09

to change the

16:11

way that things are happening in the world ? And

16:13

so that's what I decided . I'm like well , I

16:16

can go in any direction . Right , I

16:19

can take off a career like a cult and

16:22

move into any type of data space , because I've

16:24

built data systems for over 30 years .

16:27

Can you talk about building data

16:29

systems Like what does that process

16:31

look like on sort of a practical day-to-day

16:33

level ?

16:34

Yeah , so I guess my early career

16:37

in library science

16:39

literally creating the

16:41

technology that's capturing particular

16:43

data types , whether that be text

16:46

or , you know , barcodes or different

16:48

things that we're using around

16:50

that . Eventually

16:52

technology got to

16:55

a place where people wanted more descriptive information

16:57

around data . That was put

16:59

in Because you know , when you think of like

17:01

libraries and catalogs

17:04

, it basically would tell you you know here's

17:06

a book and here where it is and here's

17:08

the title you know . Eventually people want to

17:10

know more , right ?

17:11

So what's the ?

17:12

description of the book , what's in the

17:14

book ? You know what books

17:16

you know cross-reference the same information

17:18

, so I think you know my background

17:21

in . That really helped me

17:23

, especially as other companies

17:25

were coming to the challenge where

17:27

they couldn't manage

17:30

the data that they had manually

17:33

right , so there were just not enough paper . There were not had manually

17:35

right , so there were just not enough paper . There were not enough

17:37

people right . As we see more

17:39

digitization , especially

17:41

with the commercial internet , where people were

17:44

you know , microsoft Office

17:46

, different things like that People were authoring

17:49

things more rapidly . There's

17:51

more data in different forms . It

17:54

was just difficult to be able to try

17:56

to manage . I think if

17:58

it were not for the internet , we'd still be in a very

18:01

paper world . Especially

18:03

, we're seeing this escalation again

18:05

with artificial intelligence , where

18:08

there's going to be even more data created

18:10

.

18:12

It's even harder to source where it's

18:14

coming from , with ai , I imagine yeah , exactly

18:16

so .

18:16

It's creating more data challenges

18:18

that we're having just because the the volume

18:21

and the the

18:23

the speed in which this data

18:25

is being collected . So for me it was like

18:27

, okay , so we don't have the right tool , let's

18:29

build it . Let's build a new tool

18:31

or let's go . You know is another

18:34

, another industry using a

18:36

tool in a different way that we can learn

18:38

from . So , you know , it's just

18:40

it's kind of a race , a race

18:43

to try to keep up with the

18:45

demands of what people really want

18:47

and what those technologies end

18:49

up being used .

18:51

Yeah , now , like I said

18:53

, I really enjoy the Data Diva

18:55

Talks privacy podcast here and

18:57

I encourage our listeners to go

18:59

check it out and check out some episodes . It

19:03

obviously comes from a place of real passion for

19:05

you . Like you said here , you

19:07

got into data privacy because you

19:09

have this very vested interest in understanding

19:11

what our data is being used for

19:13

and you know each episode

19:16

. It feels like you know you're asking the guests

19:18

what is the thing you know , what

19:20

is the data privacy issue

19:23

that you're most worried about right now ? So I'll turn

19:25

the question back to you , debbie what

19:27

is the number one data privacy issue

19:30

for you at the moment ? What's the thing that , if

19:32

not , keeps you up at night , keeps you kind of thinking about

19:34

it at the moment ?

19:35

what's the thing that , uh , if not keeps you up at night , keeps

19:37

you kind of thinking about it . Yeah well , let's see my big issue

19:39

. I guess I'm gonna blend it with ai . I guess

19:42

, uh and this is a concern I've had

19:44

for many years and so I've seen it

19:46

play out now uh , probably

19:48

worse than I even imagined . So I

19:51

feel like people are abdicating their human

19:53

judgment technology where

19:56

we're saying , oh , we don't need humans

19:58

, we'll just have robots that you know

20:00

fold clothes and you know pick

20:02

up eggs and stuff like that .

20:05

We're going to save so much money this way ?

20:06

Yeah , so it's like , yeah , but

20:08

you're trying to use technology to make bad

20:11

decisions and then you're trying to advocate your

20:13

, your responsibility as a

20:15

human for that right . So we're seeing

20:17

a lot of bias in hiring

20:19

algorithms . We're seeing a lot of problems

20:22

with , you know , these tools spitting

20:24

out information that's not correct , things

20:26

that are harmful people . Um

20:28

, you know , we're seeing just an over

20:30

data collection , just too much data . There

20:33

was a expose

20:35

in the New York Times recently

20:38

about cars collecting people

20:40

don't even know like your car

20:43

is collecting data that's going to these secret

20:45

data brokers to get it sold to

20:47

insurance companies without their knowledge . And one

20:49

of my friends who was a data expert

20:52

didn't know this . His insurance went up 30%

20:54

and they were like you know , I didn't get any tickets . Expert , didn't know this , and his insurance went up 30% . And they were like

20:56

you know , I didn't get any tickets , I didn't do anything

20:59

. You know there was nothing in my

21:01

quote unquote driving

21:03

record that was wrong . They were like well , you

21:05

know , you drove through this neighborhood

21:08

five times , or you

21:10

, you know , we think you took these

21:12

trips , these number

21:14

of trips in your car , or , um

21:16

, you , you , you broke

21:19

, you did like a fast stop

21:21

, a hard break .

21:23

Uh , you know they're tracking the

21:26

, the actual drive it , you're driving style

21:28

and they're like you're too dangerous , wow exactly

21:31

so mean to me that's problematic

21:33

.

21:34

Right , right I'm like

21:37

maybe I did a hard stop because someone

21:39

a kid ran into my

21:41

pathway and I wouldn't hit the kid Right

21:43

. A

21:47

lot of context , a lot of possibilities

21:49

for context here have with people using

21:51

technology . I see to me

21:53

AI should be more of a low-level , low-risk

21:56

, low-stakes tool as a

21:58

helper to people . It shouldn't be making

22:00

decisions about people .

22:07

I agree completely . Yeah , no , there's a lot of space for it , especially in terms of crunching numbers

22:09

or , you know , gathering , you know data from large sets and stuff like

22:11

that it's perfect for . But yeah

22:13

, doing things like that and you

22:16

know , also sort of replacing sort of human

22:19

judgment , you know , and allowing sort of decision-making

22:21

, is pretty wild . Now can you

22:23

you know , obviously you're a person

22:26

, a forefront can you speak to support

22:28

anyone else who is currently working

22:30

or talking in this space

22:32

, who is saying especially interesting

22:35

things about the confluence of AI and privacy right

22:37

now , that you'd like to shout out ?

22:39

Yeah , wow , there are so many different

22:41

people . One person I think that

22:43

you would love to chat with . His

22:45

name is Stephen Lawton , so

22:48

he's a writer . He's

22:50

a technologist in cybersecurity

22:52

. He traverses a lot of different

22:54

areas . He does a lot of writing for publications

22:58

like Dark Reading Bloomberg . He's

23:02

a great person to talk to because he knows

23:04

so much about computers and computing

23:06

. He talks about the cyber

23:09

risk and cyber insurance , so

23:12

he goes the

23:14

gambit , I think , around technology . He

23:16

has a deep , deep knowledge of just

23:19

tech and cyber in general , and

23:21

so he's a . He's a great fan

23:23

and he's been on the show as well .

23:25

he's amazing and well , um

23:27

, let's talk about the show here . Like I

23:29

said , I've been uh excited

23:31

about about it for a while now and you've got

23:33

what almost 200 episodes on there , something

23:35

like that , or over 200 ?

23:36

Yeah almost 200 . Amazing

23:39

200 in about I don't

23:41

know 10 weeks or something .

23:42

So when did you start it ? In 2018

23:45

?

23:47

2019 , I think , or

23:50

2020 ?

23:51

No , I've been 2020 , I think , wow okay

23:53

, that's an incredible pace

23:55

of work there . So , um , well

23:58

, let's tell our our guests , uh

24:00

specifically about the type of people that

24:02

you speak , uh speak to and I think

24:05

, because you know you look at a list of

24:07

175 , whatever uh

24:09

past guests and you get a little overwhelmed what

24:11

is there like one or two episodes that you think

24:14

our listeners should start with ? That really gives like

24:16

a good idea of like what makes the show great

24:18

yeah , oh , wow , that's such a

24:20

great question .

24:21

Uh , first of all , we're really happy

24:23

and proud that people really love the podcast

24:26

. I think we have last time I checked we've had

24:28

over 170 000

24:31

downloads of those

24:33

podcasts . Uh , we have listeners

24:35

in over 112 countries

24:37

. Um , the guests

24:40

run the gamut , um , so they're

24:42

not . I think the reason why people really like

24:44

the podcast is that it's not just privacy

24:46

people . Uh , because privacy

24:49

is such a horizontal issue

24:51

that impacts like almost any type of

24:53

company or any type of profession

24:56

. I'm able to bring on people

24:58

from all different areas

25:00

. So there may I may have lawyers

25:02

. I have cyber people . I have people in , like

25:04

you know , biometrics identity

25:08

. You know

25:10

, just , you know anyone in a data space

25:12

that wants to talk with me about privacy

25:14

. You know we've had , you know , people like

25:16

Cameron Carey , who's

25:18

part of the Brookings Institute , who's probably

25:20

one of the biggest you know

25:23

people in the US on privacy

25:25

. We had Johnny Ryan , who's an advocate

25:27

in Ireland . He works

25:29

on a lot of those real-time bidding at

25:32

tech cases . He's been on . I

25:36

mean , we've had a ton of VIPs . Probably

25:38

one of the coolest

25:40

episodes that I've done recently is

25:43

with a guy named Jesse

25:46

Taylor . So Jesse Taylor

25:48

, he's actually the inventor of

25:50

the App Store , really

25:52

, wow , yeah , yeah . So he

25:54

has a story in the show where

25:57

he he had a meeting

25:59

with Steve jobs . They introduced the

26:01

the app store concept to

26:03

him , uh , and then they

26:05

Apple bought it and so that's how the app

26:07

store started , with Apple , uh

26:09

. So his episode is amazing because

26:12

he talks about his trajectory

26:15

in tech , you know , inventing

26:17

the app store and then now he's working on

26:19

identity , right , ok , try

26:21

to solve a lot of identity

26:23

problems . So he has like a really cool

26:26

technology and a really cool way

26:28

that he thinks about stuff . So for

26:30

geeky tech people who are really

26:32

interested in that , you would really love that .

26:34

So it was one of my favorites oh , it's

26:37

awesome and I think also people love hearing

26:39

the firsts of things

26:41

like that , or or where things started . I

26:43

think one of my my past guests was , uh

26:45

, the first person to hack an iphone . I

26:48

think it was like the first , first iphone that

26:50

came out and they were part of the team that , uh

26:52

, hacked the first iphone . So everyone wants to

26:54

hear that story for sure . But so

26:57

I want to move into sort of the work

26:59

portion of our show , cyber Work here , because

27:02

you're giving us

27:04

lots of awesome knowledge here about data privacy

27:06

and I wanted to ask you

27:08

specifically about the role of

27:10

, say , a data privacy officer . You

27:14

know you learned your skills

27:16

over a long period of time . You were

27:18

doing other work , you were doing it

27:20

as kind of like a thing that

27:22

excited you and you gathered the skill

27:24

set over , you know , over time

27:26

. But for people who are just trying to get into this

27:29

space now , do you have any recommendations

27:31

for common educational

27:33

requirements , qualifications , degrees

27:35

or certifications or extracurricular learning that

27:38

would sort of get you up to speed

27:40

to do this type of work ? Like , where would you start

27:42

?

27:43

Yeah , that's a great question . First

27:46

of all , I would say start with self-learning

27:48

. So before you , spend any money on it

27:50

you know , look into it , look

27:52

into what's being written , follow people

27:54

who are talking about things that you're interested

27:57

in . You know there was a lot of

27:59

. You know , back in the olden times

28:01

you had to go to the library , but now you have the

28:03

Internet , so go on the Internet . You

28:06

know , I tell people they're interested in privacy stuff

28:08

. Put like a Google alert

28:10

for yourself for these things you're

28:12

interested in , so that you can get like a reading

28:15

list every day without having to go out and search

28:17

for things to see . Like , is this

28:19

something I'm interested in ? Like , do I really want

28:21

to go into this area ? Um

28:23

, also , I think , especially for people who

28:25

are young in their career , who aren't established

28:27

and they are not known , I recommend

28:30

that they try to decide

28:32

maybe get some type of certifications

28:34

, maybe a variety of them

28:36

. So , for privacy people

28:38

, you know , I tell people anyone

28:41

who's in a data job can , can

28:43

add privacy to their toolkit

28:45

. Right , so , you know , get a

28:47

certification and read a book . You know

28:49

there's something you know privacy

28:51

is something that all companies

28:54

have to deal with at some

28:56

level . So having just a little bit

28:58

of knowledge may give you that leg up where

29:00

you're invited to be on a

29:03

team within your company or you

29:05

can volunteer . There's no one in

29:07

your company say , hey , I'm really interested in learning about

29:09

this . You'd be surprised how companies may

29:12

invest in you . And you know , I

29:14

I do . I don't have certifications

29:16

because I think people

29:19

kind of know me already yeah

29:22

, yeah , yeah , no , what , what I am and

29:24

what what I can do . Um , but for

29:26

people who are not as well known

29:28

, I think those certifications help because

29:30

it it really demonstrates maybe

29:32

a future employer that you have

29:34

taken time there to be

29:36

able to get those things . Then I also you

29:38

know as much as I love

29:40

privacy . Because there's so much AI

29:43

out there , I highly recommend people

29:45

start to learn stuff about AI too . So

29:48

whether that be like I tell people , if

29:51

you read one article

29:53

let's say you spend 10 minutes a day for 30

29:55

days to learn something new about

29:57

AI , you'll probably know more than anybody

29:59

around you . Right

30:01

, right , we're at the beginning of the

30:03

beginning around what AI

30:05

will be in the workplace . So anything that you

30:07

can do to read on your own , you

30:10

know a couple of . There are a couple of different

30:12

places that have free

30:14

certification classes that you could

30:16

take in AI . You know just the basics

30:19

and , again , having the

30:21

basics will make you better than most people

30:23

. Most people don't , you know , unless they're data

30:25

geeky people like me Just

30:27

doing it for fun . Yeah Right , yeah Right

30:29

, you'll probably know more than other people . That'll

30:32

give you a huge leg up and

30:34

it helps you differentiate yourself . I

30:36

think too right , yeah , you say , hey , I'm

30:39

a cyber person , but then I also have

30:41

this , you know , interest in privacy and

30:43

those things can come together . You

30:45

can probably be , maybe , maybe the translator

30:47

between those legal and technical people

30:50

within organizations . So I highly

30:52

recommend people kind of diversify a bit

30:54

. You know , maybe , maybe not . I

30:57

wouldn't . I would not recommend people go into

30:59

debt to be able to do that there

31:01

are so many free resources out

31:03

there but just a little bit . You know , even

31:05

if you took one , even if you

31:07

took one little class

31:10

or something , you know that'll be better

31:12

than nothing . Or

31:15

if you read one article a day , that'd be better than nothing . Or if you read one article a day , that'll

31:17

be better than nothing . So I'll say , you know , I highly recommend self-learning . You know

31:20

, I'm a self-taught person . I

31:22

was . I did not go to school for

31:24

technology . My first computer , you

31:26

know , back in the day , when computers came with books , you

31:28

know I would read the whole book or I would

31:30

, you know , learn as much as I could

31:33

. And that's how I ended up in technology

31:35

, because I was interested

31:37

and I could prove

31:39

that I was capable of doing

31:41

things . And so myself , my

31:43

journey a lot , is around self learning

31:45

.

31:46

Yeah , that's , yeah , that's awesome advice

31:48

. I want to ask

31:51

a little bit . You mentioned already about differentiating

31:54

yourself from other people , especially at entry

31:57

level position , sort of floating

31:59

you to the top of the resume pile and so forth

32:01

and I , like you said , I think having

32:04

these kinds of like niche skills

32:06

, certain aspects of privacy or

32:08

or things in addition to your cyber skills

32:11

, is probably a really great way . Now you

32:13

run Debbie Reynolds Consulting . You're

32:15

a , you're a consultant for companies . Is

32:17

consulting uh something

32:20

that you can , uh someone new

32:22

can do to get their job in the door ? You

32:24

know their foot in the door , like if you wanted to uh

32:27

volunteer your time , say , for some local

32:29

organization that needs to know

32:31

you know what their privacy requirements

32:34

are and stuff like that . Is that something that companies

32:37

or you know places in general would

32:39

be willing to entrust to

32:41

, like a newcomer who's trying to get their feet wet ?

32:44

Yeah , I highly recommend . That's one of the

32:46

top things . When people contact

32:48

me , like how do I get my foot in the door ? No

32:51

, or for some people , some people

32:53

say , you know , I went to this school

32:55

, I got a degree , I've maybe got a

32:57

certification , but no one will hire me because

32:59

I don't have any experience , right , and I tell

33:02

them , like , do you have family members that have

33:04

to have businesses ? Do you have like a local

33:06

business that you can go to and say , hey

33:08

, you know here's privacy

33:10

thing , it's a big deal . Maybe I volunteer

33:12

or you do it like for just a nominal

33:14

fee , not a ton . You know , maybe

33:22

just help them with their website privacy policy . All that is

33:24

experience and you don't have . You can put that on your resume , right , absolutely , I was the

33:26

data privacy officer for blah , blah , blah , whatever

33:28

, whatever that is , and they don't need to know

33:30

that you didn't get paid for it , right , it's

33:33

still experience , right , that you can put

33:35

it on your resume and it's something

33:37

that you can do at your own pace , right , because a

33:39

lot of companies , especially the smaller companies

33:41

, they don't know what to do and they'll be happy

33:44

to talk with you because a lot of them

33:46

think , well , I need a lawyer to do this

33:48

, so you actually don't right Most of

33:50

these . I'm not a lawyer . A lot

33:52

of people who do this work are not lawyers

33:54

. A lot of us are tech people , data

34:02

people who are , who have a background in governance and know what you should and shouldn't do

34:04

with data and that's really all that . Privacy is like you can do or you can't do this

34:06

with data or the things you need

34:08

to look at . So I

34:10

highly recommend people do that and that's

34:12

been something that's been very beneficial

34:15

to people who've actually taken that

34:17

track . So you know , even

34:19

let let's say , for instance , you have

34:21

a job , maybe you're a cyber

34:23

, you know , see if

34:25

there are projects in the company

34:27

around privacy that you can say

34:29

can I , can I be a part of this

34:31

project ? Can I help do this ? You

34:34

know you may be able to . You

34:37

know I've had people say well , you know , can

34:39

you ? I'll be your

34:41

data privacy officer , but you know

34:43

I'll just . Maybe you just

34:45

get a new title or something . Yeah , that

34:48

says privacy .

34:49

Negotiate extra responsibilities and yeah

34:51

.

34:51

Yeah , exactly , so there are ways to be

34:53

able to get in . I would say , you

34:56

know , to me it's a wide path

34:58

, so I think you know . I

35:01

think in the future it's going to become even more

35:03

important , especially as things

35:05

with AI come about . Yeah

35:07

, because a lot of lawyers don't you know they

35:09

weren't , they didn't , they're not

35:11

experts in tech or they're not experts

35:14

in data . So having people who are experts

35:16

in data and also know the privacy

35:19

part , I think really

35:21

can elevate someone's career .

35:23

Yeah , that's really good advice too . A

35:26

portion of our listenership is also people who are

35:28

trying to transition into

35:30

cyber-related roles

35:32

, maybe after having another career , maybe

35:34

in their 30s or their 40s , and I think that's

35:36

a you know , if you're already at a company like

35:38

a really good starting place is to

35:40

you know , on your next job evaluation

35:42

, ask for more responsibility , say

35:45

, is anyone doing data privacy for this

35:47

company ? Can I do that in addition to what

35:49

I do , or can I get a few things taken off

35:51

my plate in order to concentrate

35:53

more on this ? You know , I think there's a lot of

35:55

talk about professional development and companies

35:57

want you to be , you know , constantly

35:59

growing . I think that's such a great piece of

36:01

advice in terms of that .

36:03

And one thing I will add that you should really

36:05

know about kind of the job market

36:08

and in

36:10

privacy right now . So

36:12

much so when I was interested

36:14

in privacy in the US , there were like hardly

36:16

any lawyers doing it . It was just all

36:19

data people like me , right , Right . But

36:21

over the years , as the regulations

36:23

came about , there are more lawyers now in

36:25

privacy . Some people think of it as like a

36:27

lawyer-only job and it isn't

36:29

so . There's a lot of people like me who are in

36:32

privacy , but then also , you

36:35

know , it's employers

36:40

. Now they're looking for

36:42

more of the people who understand

36:45

privacy , who understand

36:47

data . All right

36:49

, Because at some point you

36:52

know , unless you're a super big company , it's always

36:54

changing . Once you know what the regulation

36:56

is , you know you need to

36:58

figure out how to change your operation

37:01

, how you work , and so what

37:03

we're seeing is more emphasis

37:06

on companies trying

37:08

to recruit more data people in

37:11

privacy . So people who understand

37:13

the data part of

37:16

how companies work

37:18

because they have to . Companies are struggling

37:20

really with operational change , not like

37:23

the regulation , so , uh

37:25

, so to me it's like a very good area to

37:27

put yourself in , is a good way to differentiate

37:30

yourself .

37:31

Yeah , I love that . Um , yeah , that that reminded

37:34

me of , of , uh , something I was going

37:36

to ask . Oh , this is so . This is kind of a a

37:38

sideways question here . Uh

37:45

, but you know , like I said , um , in learning about , you know , possible new career tracks , if you're

37:47

just , you know , fresh out of school or not even out

37:49

of school or not , didn't go to school , you

37:52

know , or whatever you're thinking

37:54

like data privacy , this is it , this is my career

37:57

track , and you're all excited , can you talk

37:59

about ? Is there a certain aspect of the

38:01

job that is you

38:03

know that people should be warned of ? You know , in the sense

38:05

that , like , this is , this part of it is is

38:08

way more boring than you're expecting , or this part

38:10

is , you know , makes you want to pull

38:12

your hair out because you know people are not going to

38:14

, you know , take your

38:16

advice , or whatever . Are there certain sort

38:18

of undersides of data privacy that

38:20

is , as long as you know them coming in

38:22

? Uh , you know , you got to be ready for them oh

38:25

, that's a good question .

38:26

So underside I will say if you don't

38:28

like , reading like this is not like the

38:30

job for you yeah , there's lots of reading

38:32

. You're constantly researching , I imagine , right

38:34

constantly , constantly , like I

38:37

do several hours of research every

38:39

day . Wow , so's

38:41

just the only way you can keep up

38:43

. The

38:46

European Union has the AI

38:48

Act that came out . That's like

38:50

500 pages , even

38:52

though it's in Europe . It's going to be like

38:55

the GDPR was , where

38:57

it's going to be very influential for

38:59

different jurisdictions . If you learn that

39:01

, then in the future , when

39:03

more laws come out , you'll start

39:06

to see shades of that that

39:08

regulation there . So

39:10

learn on reading that understanding that

39:13

will help you navigate what that future

39:15

is and that's what companies really want

39:17

. I would say

39:19

I don't know

39:21

, maybe I'm just nerdy . To me , I think that's

39:24

probably the only downside . It's

39:26

just a lot of reading and there's a lot more

39:28

stuff

39:32

in the press around privacy

39:34

. I remember when I

39:36

first

39:38

, over a decade ago , maybe like

39:41

15 years ago , I put out a Google

39:43

alert for privacy and there was nothing

39:45

like not one thing

39:47

for years , like I want to say like

39:49

almost like six or seven years , it was

39:51

like no articles . And then now

39:53

, like you know , my

39:56

Google alert may have 10 , 10 or

39:58

12 every day . Yeah , right

40:00

, so it's changed a lot , a lot , lot , and so

40:02

I think for me being

40:04

able to look you know people call

40:06

me a futurist because I'm good at predicting

40:08

what's going to happen next . But you know I'm

40:10

always looking at the technology because

40:12

the technology um

40:15

, you know law

40:17

follows technology . So

40:19

law , you can't lead with law . Law , law is like

40:21

backward looking , yeah

40:23

. So if you're thinking about the new thing

40:25

, like you know , like when the Vision Pro headset

40:28

came out , oh wow , well , what could be

40:30

the privacy issues with that ? Right , and

40:32

so it may not be on your desk

40:34

today , but if you're thinking about those things

40:36

ahead , when it comes up , then

40:39

you're already in a good position to

40:41

be an advisor or being a trusted person

40:43

in that area .

40:44

Yeah , this is a little

40:46

off script here , but you

40:49

mentioned that you do about five hours of research today

40:51

. Could you tell us a little bit , like , what

40:53

is your ? What is your , your sort of

40:55

your regimen

40:57

? What's what do you ? Where do you start each

40:59

day when you're trying to do research ? It

41:02

sounds like you're . You're also the the Google

41:04

alert diva here as well , but like what are some

41:06

of the other ? Like go to sort of news sources

41:08

that you you check every day , or

41:10

like what is your ? You know I jump from here to here

41:12

, to here to here each day . Do you have like a routine

41:15

at all ?

41:15

Yeah , I have an app that I use

41:17

called Flipboard , and

41:19

Flipboard allows you to collect articles

41:23

and stuff and it makes it , you can

41:25

make it a magazine . So I have a research magazine

41:28

and every time I see something that I

41:30

think is of interest , I have like a research

41:32

file that I save it to and then every

41:35

night for a couple hours I go through

41:37

my research file and I just read

41:39

, you know , just read through stuff , and

41:42

so and of course it was like bigger things

41:44

. Another thing I do like these

41:46

bigger laws . Sometimes I use

41:48

an app called Speechify where

41:51

I have it read it to me so I can be

41:53

like washing dishes or doing

41:55

something . So , I'm not reading , I'm just

41:57

listening . You know doing different

41:59

things , just taking it in and stuff like that

42:01

. So those are two things that helped me a lot

42:03

, and so I do videos every week . I've

42:06

actually been doing those for over five years , so I do

42:08

one video a week that I release . And

42:10

so , uh , because

42:12

I what I found that it was too

42:14

hard to start and stop research

42:17

. That's why I always do it , yeah

42:19

no yeah continue to do it .

42:21

And then when people call me , they're like oh , you need

42:23

to look at your notes , like no , no , really

42:25

yeah

42:27

, for for those of us with uh , you know I have adhd

42:29

and I know other people as well

42:32

but like , sometimes the prospect of like , okay

42:34

, learn all the privacy now feels like

42:36

you know that old like game show thing where

42:38

you're in like a wind tunnel and there's dollars flying everywhere

42:40

and you're just constantly trying to grab . So I I think

42:43

that's a that's a really good advice , especially

42:45

the uh , uh , the flipboard thing and sort

42:47

of making the magazines Cause . Again , I think , if

42:49

you're like , well , I'm grabbing

42:51

this , I'm grabbing this , but what am I going to get to it . But if

42:53

you sort of like slap it all together and say , okay

42:55

, two hours a night , I'm just going to go through

42:57

this that

43:00

you know you're going to read , I think that's

43:02

a really good way to kind of like get your

43:04

head around what

43:06

all this is , because there's , you know , there's a million

43:09

options and there's a billion ways

43:11

to do it , right and wrong and so forth . So , yeah

43:14

, that's great advice . Now I want

43:16

to ask one more thing

43:18

regarding , like , careers and stuff

43:21

Are there particular skills gaps among

43:23

people trying to get hired in data privacy positions

43:25

you see on a regularly , regular

43:27

basis that you

43:29

know you wish were

43:32

more common , like are there things

43:34

that you know people are like I'm

43:36

a data privacy person ? You're like well , why aren't you doing

43:38

this ? Or I wish you did more of this . I wish you

43:40

had more of this skill . Is there anything like that that

43:43

people should be aware of

43:45

?

43:47

That's a great question , I would

43:49

say , and you probably wouldn't

43:51

think this was

43:53

typical . But you know

43:55

, the gap that I see the most are

43:58

technology people who don't

44:00

know how to talk in

44:02

ways that anybody can understand

44:04

, and legal people who also have the same problem

44:07

. Yeah , so you know

44:09

, we have , like legal people who want to do alphabet

44:11

soup in acronyms

44:13

and shorthand and stuff , and then

44:15

the tech people have their own acronyms

44:17

and shorthand and so the problem

44:19

is in a privacy

44:22

role , you have to be able to

44:24

communicate across all

44:26

levels of the organization and with anybody

44:28

. So if you're saying some acronym

44:31

soup thing , you know people are going to

44:33

pay attention to you , they are going

44:35

to listen to what you have to say . So

44:37

to me , that gap really is understanding how to

44:39

be a great communicator . Understanding how to be a great communicator

44:42

, right ? So the person that

44:44

you're talking to like

44:47

, let's say , you're being asked to brief the CEO of a company about a particular issue

44:49

and this happened to me before where

44:52

I talk with maybe the legal people like , hey

44:54

, you all need to do this , and then I talk to the

44:56

technical people , hey , and they're like well , I

44:58

need you to explain it to the CEO . So I

45:00

know that the CEO doesn't understand the legal

45:03

, he doesn't understand tech stuff

45:05

in the same way , so I have to be able to communicate

45:07

that to him differently . Or even people

45:10

when I'm doing training , like for a whole organization

45:12

, like I've done trainings for , like

45:14

you know , coca-cola , johnson

45:16

Johnson , like all types of companies , right

45:18

, and so you have to make it easy

45:21

enough for anyone , regardless

45:24

of where they are in the organization , to be able to understand

45:26

what you're trying to say , and so that's a

45:28

skill , just in general , that

45:30

I think is going to be highly relevant

45:32

in the future , not just for privacy

45:35

, but all jobs . You know , ai

45:37

is very complex , right ? So

45:39

if you can break down

45:42

what AI systems are doing in an

45:44

easy way , you can elevate

45:46

yourself in your organization , because

45:48

very few people have

45:51

honed those skills . It's

45:53

so funny because even when

45:57

I was asked to talk on PBS about

46:00

privacy , they don't tell you what they're going to ask you . They just

46:02

put you on TV and they start asking questions . But

46:05

I had to think in my head . I kind of stopped

46:07

for a second . I thought , wait a minute , I have to be able to explain

46:09

this to someone's grandmother , you

46:12

know , or someone who's 10

46:14

, you know so I can't explain

46:16

it in a way that a legal person or a technical

46:19

person , so I had to break it down as easily

46:21

, as simply as possible , and so that's

46:23

a skill that I think will help anybody

46:25

in any type of career . So if you're a good

46:27

communicator you can communicate

46:30

not in legalese or not

46:32

in technical jargon you'll

46:34

go far in any career that you

46:36

want to go into .

46:37

I completely agree . Now

46:40

you mentioned , obviously , the sort

46:42

of alphabet soup and the sort of talking past

46:44

each other between you know , legal and tech and so

46:46

forth Is is there . Is it ever

46:48

a case where , like , the privacy person

46:50

is asking the company to make difficult

46:53

changes and I imagine there's gotta be some element

46:56

of like persuasion involved right as well

46:58

where you're saying , like look , I know you

47:00

really don't want to put in this extra money to like

47:02

or lose this data that we were otherwise

47:05

going to harvest this way , that way and the other way or

47:07

whatever . So I imagine you're also

47:09

having to sort of like patiently

47:11

explain , like no , we don't get to do that . Is

47:13

that ? Is that the case as well , or is that someone else's

47:15

job ?

47:16

Yeah , absolutely Right . So I guess it's

47:19

the art of saying no , in a way , you're

47:29

like , oh , you can't do this or you shouldn't do this , right , but you know , when you're an advisor

47:31

, you know , I say consultant , but you know , advisor , yeah , uh , interchangeably , uh , you know , and it may

47:33

be frustrating or you say , hey , here's the law here , this is what you're

47:35

doing , this is what we recommend that you do . But

47:37

you know , companies even though

47:39

privacy is important , it's not the only

47:41

consideration , and so companies have

47:43

to make their own choices . But

47:45

you want to make sure that they're making an educated

47:48

decision , right ? So you

47:50

don't want them to make a decision because they don't

47:53

know something . You want to be able to say , hey

47:55

, here's the lay of the land , this

47:57

is what I think . You know that here

47:59

will be my advice for what you do . But

48:01

then you have to decide as an organization

48:04

. You know what is your culture , what is

48:06

your standard , what are you going to do ? You know , maybe

48:09

you're somebody like Facebook , you're

48:11

like , well , we don't care , because we're going to do

48:13

what we want . We're going to pay a billion dollars

48:15

and that's fine .

48:16

You know that's their choice Right

48:18

.

48:18

You may not like that , but you

48:20

know , and I feel like sometimes I

48:22

see on LinkedIn people like slamming

48:25

people who work for certain companies . I

48:32

can't believe your company does this . It's like you know you just have one job Right , so you're

48:34

not the CEO . You don't get to pick and choose what companies do . All

48:36

you can do is tell them like this is what

48:39

is going on , this is what our obligations

48:41

are , this is what I think you should do

48:43

. This is how you know and this is where

48:45

, to me , the cyber data people come in

48:47

. How do you do it ? Yes

48:50

, so it's one thing to say okay

48:52

, you need to comply with this law . Okay , Well , how

49:00

do you do that ? Yeah , I don't know . Like , how do I change the way that we operate to

49:02

to be able to get in line with ?

49:03

this . So that's that's the gap way that we operate to be able to get in line with this .

49:05

So that's the gap you have to sort of show the entire pathway there , then , yeah , exactly

49:07

, like you know , it's easier to say

49:09

, okay , this law came out and you have to comply

49:11

with it , but

49:17

then how do companies change ? And so that's the problem that they're

49:19

having . That's why they need data people , because they need

49:21

to know operationally , on a you know

49:23

, hands-on basis , what

49:25

do you need to do to change your behavior

49:27

in that organization .

49:29

Yeah , awesome , yeah , and I I

49:31

think that's probably another one of those sort of underside

49:33

things worth noting is like you can make recommendations

49:35

to your company and and I also

49:38

have to understand that they might they might

49:40

not take all of your advice , right .

49:43

Yeah , absolutely . It's part of the advisory

49:47

that you do .

49:48

Yeah , I can only tell you what you need to

49:50

do . I can't put it into your hand and make you

49:52

do it , that's right

49:54

. So this has been an amazing conversation

49:57

. We're bumping up against an hour here . I would love to

49:59

have you back on , if you're available , to talk Internet

50:01

of Things and especially AI and sort

50:03

of drill into those topics better . But I really enjoyed

50:05

getting your insights on sort of

50:08

career related questions

50:10

around data privacy . But before I let you go , debbie , can I

50:12

ask what's

50:14

the best piece of career advice you ever received

50:16

, whether it was from a mentor or a teacher or a colleague

50:19

or just something you learned along the way ?

50:22

Oh , wow , I think probably the best career

50:25

advice I received

50:27

, maybe from my parents . So my

50:30

parents were very into education

50:32

, they were very much in the learning and they never

50:34

put limits on what we

50:36

could do or what we can learn Right

50:38

. And so I would say don't put

50:40

limits on yourself , don't ? You know ? I

50:43

learned not

50:45

to put myself in a box because

50:48

I don't fit in a box , right . You know

50:50

, I have a lot of different interests and so I'm

50:52

lucky that I have a company

50:54

where I can exercise all the things

50:56

that I'm interested in , even

50:58

though they may not even seem related . Right

51:01

, like I one of my early jobs

51:03

when , when I said I was doing desktop publishing

51:05

, like I do a lot of graphics . You know I have

51:08

a media company as well , so I do a lot of graphic

51:10

design . For that , I

51:12

mean , that's just because that's something that I've done

51:14

forever and that's kind of a fun artsy

51:16

thing . You know , gets me out of the , gets

51:19

me out of the . You know the privacy

51:21

, you know the privacy , you know wonky world and

51:23

I can kind of do more creative stuff . But

51:25

I would say for people , don't put yourself in a

51:27

box , and you'd be surprised how much maybe

51:30

skills that you have in

51:32

different areas may come together at

51:34

some point .

51:35

Yeah , fabulous advice , thank you , so

51:37

I'm gonna let you go here . But one last question

51:39

. If our listeners want to learn more about you , debbie Reynolds

51:41

, the Data Diva , the Data Diva podcast

51:44

or the other 150 things you got going

51:46

on , where should they look for you online ?

51:49

Yeah , well , people can always connect with me on

51:51

LinkedIn . You just type in Data

51:53

Diva Debbie Reynolds and connect

51:55

with me , happy to . Or

51:57

they can look at my website , debbiereynoldsconsultingcom

52:00

. I have all my videos and newsletters

52:03

and events and everything on that , the

52:05

website .

52:07

Yeah , and don't , and don't forget to check out the data diva

52:09

talks privacy podcast . I I

52:11

got mine on my regular podcatcher and , uh

52:13

, highly recommend it . So , uh , well , this

52:15

has been great , debbie . Thank you so much for joining me today . I

52:17

really enjoyed learning from you .

52:19

Thank you so much . I love the show , I love

52:21

your flow , very good flow

52:23

of the show .

52:24

I really appreciate that . Thank you , and

52:27

to everyone out there , I'd like to thank you

52:29

everyone who's watching and listening and writing into

52:31

the podcast with feedback , as usual

52:33

. If you have any topics you'd like us to cover or guests you'd

52:35

like to see on the show , drop them in the comments . We've

52:38

been adjusting our

52:40

content accordingly so you are getting heard , adjusting

52:42

our content accordingly so you are getting heard . Before

52:45

I go , I don't want to forget to have you check infosecinstitutecom

52:47

slash free , where you can get a whole bunch of free and

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exclusive stuff for CyberWorks listeners . This

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includes our security awareness training series , work

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clicking on the treasure map someone just emailed you making sure your non-nocturnal vampiric

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professional and more . One more

53:43

time , that is infosecinstitutecom . Slash

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free and yes , the link is always in the description

53:48

below . One last time . Thank you so

53:50

much to Debbie Reynolds and thank you all for watching

53:52

and listening Until next week . This is Chris Sanko

53:54

signing off , saying happy learning .