0:01

The Art of Leadership Network. We've

0:03

already seen the impact that COVID and

0:05

the smartphone has had on young people's

0:07

ability to form lasting social bonds

0:09

with one another, to have

0:12

deep conversations and deep relationships. And

0:15

who knows already what knock on impact that's going

0:17

to have 10 years down the road to the

0:19

population, let alone anything else. If young men can't

0:21

find young women to build the

0:23

population with without some other artificial intervention,

0:25

we're going to have problems, guys. That's

0:27

the way it's going.

0:29

And to the ability for you to have

0:32

a virtual girlfriend or a virtual boyfriend and

0:34

fall in love with the chatbot and be

0:36

totally happy with that, I think

0:38

is a relational category that we don't want

0:40

to see emerge. And that's actually probably the

0:42

more likely worst case scenario that

0:44

we are already seeing companies

0:47

building tools, building experiences where you

0:49

can essentially take a step back

0:51

from society and have pretty much

0:54

everything done for you, both

0:56

your work product, your relational product, your

0:59

call it whatever aspect of your life

1:01

you want managed. And we

1:04

end up in a kind of, you remember that

1:06

Disney movie, Wally, right? We kind of end up

1:08

in that kind of all sat slightly in a

1:10

half vegetative state looking like a potato leaning back,

1:12

watching a recycling truck clean up the world. That's

1:16

not a great outcome, generally

1:18

speaking. Welcome

1:23

to the Kerry Newhoff Leadership Podcast. It's

1:26

Kerry here and I hope our time

1:28

together today helps you thrive in life

1:30

and leadership. Man, I am excited to

1:32

talk about all things AI with James

1:35

JP Polter. He has started

1:37

and sold an AI company. We talk

1:39

about, well, everything for the church and

1:42

he's involved in that space. And

1:44

believe it or not, if you've been like a late

1:47

adopter, hey, we got some really practical tools to get

1:49

you started. If you like me are interested in the

1:51

meta issues as well, like what is this going to

1:53

do to us? We can talk about

1:55

that and a whole lot more. Today's episode is brought

1:57

to you by my live event, The Art of Life.

2:00

of Leadership Live. I'd love for you to

2:02

join me in Dallas, Texas September 16th to

2:04

18th. So if you're

2:06

ready to break through what's

2:08

been holding you back,

2:10

you can secure your

2:12

spot by visiting theartofleadershiplive.com.

2:14

That's theartofleadershiplive.com. And today's

2:16

episode is brought to you by my friends

2:19

at 10 by 10. You know they are

2:21

committed to making faith matter more to the

2:23

next generation. You can visit 10X10. That's t-e-n-x-1-0.org

2:28

slash R-D-I to complete a

2:30

free assessment that will measure your

2:32

youth ministry's efforts. So that's 10

2:35

by 10.org/R-D-I to complete

2:37

your free assessment today. Well,

2:40

what is the best case scenario for

2:42

AI in the next decade? What's the

2:44

worst case scenario? What are some practical

2:46

tools you could start using now? And

2:49

what are the pastoral implications of AI?

2:51

I sit down with James Polter. JP

2:54

is the head of AI and innovation

2:56

at House 337, former

2:59

CEO of Vixen Labs, which sold to House 337

3:01

in December of 2023. Vixen Labs is one of

3:06

the leading consultancies focused on

3:08

conversational AI. JP is

3:10

also the founder of Eclizia, a think

3:12

tank focused on the future of AI

3:14

for the church. He was previously the

3:17

head of emerging platforms and partnerships at

3:19

the Lego Group, cool job, where he

3:21

set up the likes of

3:23

Lego Life, the company's social network

3:25

for children, and oversaw a

3:27

number of the group's partnerships with Meta,

3:30

Spotify, and many more. He's

3:32

a sought after international speaker,

3:34

podcaster, and writer on the

3:36

future of AI and voice

3:38

assistance and innovation culture. So

3:40

really delighted to have him on the podcast

3:42

today. Hey, leaders, if you're looking to level

3:45

up your leadership and level up your church,

3:47

I'm hosting my very first conference, The Art

3:49

of Leadership Live in Dallas,

3:51

Texas from September 16th

3:53

to 18th. So conference is going to be

3:56

a little bit unconventional instead of listening to

3:58

eight hours of keynotes each day. day

4:00

and leaving with pages of notes that never

4:02

turn into real results. You've been there, right?

4:04

You get done those conferences. The

4:06

Art of Leadership Live has a really

4:08

cool balance of teaching, connection, and free

4:10

time so you can find the right

4:12

insights with the right people and act

4:14

on them. So yeah, I'm going to

4:16

be giving some talks, but we're

4:19

going to have open and honest discussion with me and

4:21

with other people who are there. Practical

4:23

takeaways. It's an intimate event. We cap

4:25

registration at a very low number. So

4:28

to ensure the right people are there

4:30

with you, the event is by application only.

4:32

There are only a limited number of spots.

4:35

It is close to being full. So

4:38

act now. You can go

4:40

to theartofleadershiplive.com to learn more

4:42

and register before it's sold

4:44

out. Go to theartofleadershiplive.com. Register

4:47

now before it's too late. And then

4:49

in my conversations with a lot of

4:51

you, you've shared about the challenges you're

4:53

facing with engaging young people in your

4:55

church. I get it, man. It's hard.

4:57

I know you're trying everything from outreach

4:59

activities to small group, but do

5:01

you know whether you're actually making a difference

5:04

or not? Well, our friends at 10 by

5:06

10 are committed to making faith matter more

5:08

to the next generation. They're

5:10

offering you a free five-minute

5:12

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5:15

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5:17

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5:20

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5:22

against the seven discipleship emphases that

5:25

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5:27

in relational discipleship, radically focused on

5:29

Jesus and his love for the

5:32

next generation. So you can

5:34

visit 10by10.org/RDI. That's

5:38

t-e-n-x-1-0.org/RDI. To

5:41

complete your free assessment today,

5:43

that's 10by10.org/RDI, and you can

5:45

get your free assessment. And

5:47

now my conversation with JP

5:50

Polter. JP, welcome to the

5:52

podcast. Okay, thanks so much for having me. It's a

5:54

pleasure to be here. Yeah, so I wanna start in

5:56

the deep end. What

5:58

are the threats? of AI.

6:00

There's like two different views, right? There's

6:02

the benevolent view of AI, and then

6:05

there's the malevolent view of AI. So

6:07

from where you sit, what are the

6:09

threats, the existential threats that AI poses

6:11

right now? Well, I

6:13

think the biggest distinction is that I'm not

6:15

sure that AI is the existential threat, but

6:17

it's AI in the hands of humans that

6:19

might be the existential threat, which

6:22

is probably an important distinction. In

6:24

the church, we have a habit, sometimes a nasty

6:26

one when it comes to technology of looking for

6:29

666 in the code of everything that

6:31

we use, assuming that there's

6:33

something evil lying behind it. I

6:36

don't think that that's what's happening here, but we

6:38

obviously know from all the work that's being done

6:41

across the industry that AI does have the potential

6:43

to radically transform society and particularly when

6:45

put in the hands of those that may not

6:47

want to use it for good, can

6:49

really have some pretty devastating

6:51

impacts on things like the economy, on

6:54

politics, and on the geopolitical

6:56

space. There's a real opportunity that

6:58

things could go awry with AI

7:01

being used by bad actors. But AI itself

7:03

doesn't seem to, at the moment, want to

7:05

come and kill us all, even

7:07

though it might have the potential to do so. So

7:10

I don't think that we are starting the

7:12

conversation from a position that we should be

7:15

fearful of AI. But we are

7:17

in a position where we need to be

7:19

faithful with it and particularly take a considered

7:21

approach to how we use it as Christians and how we

7:23

bring it into the church and everything else that we do.

7:26

One of the things that I

7:28

think about a lot is unintended

7:30

consequences. So if you look at

7:33

social media a decade ago, most people,

7:35

well, maybe not a decade ago, but

7:38

15 years ago as it was developing,

7:40

most people would say, oh, this is

7:42

good. We had no idea it would

7:44

produce the unintended consequences, particularly among teenage

7:46

girls. Gen

7:48

Z with the anxiety, Jonathan Haidt

7:50

has done some incredible work in

7:52

that area this year. Just highlighting.

7:55

I've just got finished reading The Anxious

7:57

Generation. I think we see that those...

8:00

like second and third order consequences just

8:02

couldn't have been anticipated when that technology

8:04

emerged. Well, exactly. And I mean, you

8:06

know, I didn't see it either

8:09

and I was an avid adapter and you

8:11

know, now I realize, oh yeah, this is

8:13

messing with my brain too. So,

8:15

you know, when you think about AI in the

8:18

future, one of these sub

8:20

arguments under how social media is used but

8:22

also AI is it's all

8:24

monetized. Like there's government policy can hardly

8:26

keep up. The EU has done probably

8:28

the best job globally or worst job

8:30

depending on how you look at it

8:33

of regulating technology. But like the

8:36

government doesn't even understand it. And

8:38

I was reading some backstory on Sam

8:40

Altman being kicked out of the

8:43

board for OpenAI earlier this

8:45

year and then being

8:47

brought back in after he was offered

8:49

by Microsoft and it seemed to be

8:52

the backstory there from what I

8:54

can determine. And again, I don't know Sam Altman

8:56

and I don't live in Silicon Valley is

8:59

that it was his seeming lack

9:01

of regard for the

9:04

human consequences of AI and really

9:06

the race to be first to

9:08

market, dominant market, profit, profit, profit.

9:11

Any thoughts on that when really you

9:13

can make an argument with the magnificent

9:15

seven that it's just

9:17

a race to shareholders, greatest profitability to

9:20

be first, et cetera. Is that what

9:22

you mean by the existential threat being

9:24

in the hands of humans? Or

9:26

what's your take on monetization and all

9:29

of this? Well, so

9:31

the existential threat problem mostly comes from

9:34

these models getting out of hand and

9:36

into the hands of those that might

9:38

use them for nefarious purposes. We think

9:40

about things like fake news, mass generation

9:43

of content that may affect

9:45

elections. Obviously we're in the year, as

9:47

we record of the elections. And

9:49

depending on when this comes out, we'll see how many of

9:52

those it's been affected by AI. But I would guess a

9:54

lot. Whether or not there's a

9:56

real effect or at least a correlatory

9:58

effect that we point out. and

10:00

say, hey, there was fake news in the

10:02

ecosystem. It'll be hard to make an argument

10:04

with anybody that that's not really been the

10:06

case. Whether or not it's had any real causal

10:08

effects on the outcome of

10:10

elections, that's yet to be seen. But certainly, that it'll

10:13

be out there and it'll be something that people point

10:15

at. And that in itself is disruptive, right? When

10:18

something like this new technology comes into the space,

10:20

long before, think back to Cambridge Analytica, think

10:22

back to what happened with Facebook. Long before anyone found

10:25

out there was something going

10:27

on under the hood there, people were still

10:29

pointing at Facebook and pointing at many other

10:31

social platforms and saying, this is going to

10:33

have a negative effect on our elections or

10:35

on the outcome of other social issues. And

10:38

I think we can already do that with AI

10:40

in an unchecked, unregulated way. Now, the

10:42

good thing is I do think global regulators

10:44

are learning from what's happened in the social

10:46

media space. And as you

10:48

say, in the EU and in the US and around

10:50

the world, people will move fast to

10:52

try and bring some kind of regulation in. But

10:55

the big difference here is that this isn't a

10:58

channel that we're talking about. AI isn't something

11:00

that has just become one person's job in

11:02

the company or one person's job in the

11:04

church. This affects everything. It's affecting all the

11:07

tools that we use. Now, even the things

11:09

we're using to record this podcast or the

11:11

computer that you're using today, certainly

11:13

the phone that you're going to use in the next 24 months is

11:16

going to have some kind of AI living inside of it. And

11:18

until we all have a better understanding of what that

11:21

means for us, we're not going to be turning it

11:23

off by default. We're most of the time going to

11:25

be opted into it. And so we

11:27

could accidentally, if we're not careful, sleepwalk into

11:29

another type of experience that we've had with

11:31

social media where we are falling foul to

11:33

giving our data over to platforms that may

11:35

want to use it for different purposes, even

11:38

if that's just to monetize it with us

11:40

not knowing about it, even if that's just

11:42

the worst thing that happens, that's still something

11:44

that could be happening to us that we

11:46

might not want to be participating in. And

11:48

I think that's why we've got to be

11:50

cautious. Strange

11:53

analogy here, but I

11:55

just interviewed William Urie, who will

11:57

be on the podcast. So he wrote the infamous Getting Out

11:59

of the World. and TS Fisher and Yuri, and

12:02

has been involved in really

12:05

the biggest negotiations in the last 50 years. And

12:07

although we didn't spend a lot of time on

12:09

it in the conversation, remember talking

12:11

to him off mic about the arms race, like

12:13

the start talks, the salt talks. You're probably too

12:15

young to remember those in real time. I was

12:18

in college, I remember them. Right about them. And

12:20

there was the arms race, right? Like in the

12:22

80s, that was a very real thing. And

12:25

it looked like, you know, there was

12:27

the mad pack, the mutually assured destruction that

12:30

if the United States or the Soviet Union,

12:32

now Russia, press a nuclear button,

12:35

the planet was blown to smithereens

12:37

in minutes. And we came close

12:39

a few times and then that

12:41

decelerated. So do you see

12:43

right now, we can have another race

12:46

in technology to the top. It's profit

12:48

driven. It's not driven by states and

12:51

governments, it's driven by private

12:53

industry. Do you see

12:55

any kind of, and I know you work in

12:57

this area, hence the question, any kind of, not

13:02

external ethical counsel, but internal

13:04

where OpenAI sits down with

13:07

Anthropics, sits down with the

13:10

thousands of startups, with Meta and

13:12

says, hey, what are we doing

13:14

here that will benefit humanity?

13:16

Do you see any of that happening? Or

13:18

is that really left to outside actors? Well,

13:22

I think that it's definitely coming because the pressure

13:24

is there for them to all be on the

13:26

same page. The challenge obviously with the commercial side

13:29

of it is that none of them want to

13:31

share their toys, right? They all wanna keep their

13:33

own little special source. And that's understandable too. I

13:36

mean, the AI wars, they're basically becoming a

13:38

proxy for the cloud wars that we've seen

13:40

over the past decade of, the Amazons, the

13:42

Googles, the competing, but the difference is that

13:44

they've all been leapfrog by some of these

13:47

startups that they couldn't have anticipated at the

13:49

time. And hence the investments that are coming

13:51

in left, right and center. What's really

13:53

interesting, if you look at the board makeup of

13:55

many of these companies, they've got people sitting across

13:57

them from all these different companies on

13:59

each other's. boards, they're building up different teams.

14:01

You've got people like from Google that are

14:03

now on the Anthropic board, you've got Amazon

14:05

investing in them as well as Google investing

14:08

in them. And so

14:10

it does make the landscape quite muddled, but

14:12

they all are essentially moving towards the same

14:14

thing of for profit as the means of

14:16

growing these things. And there's nothing necessarily intrinsically

14:19

wrong with that. But

14:21

the accountability is the thing that we want to

14:23

see. And obviously, that's the work that's being done

14:25

by the EU with the AI act that's just

14:28

been passed, is what's going through

14:30

Congress at the moment. I'm sure what will be coming

14:32

out in both the Canadian and the UK governments

14:34

as they try and bring something that's of parity

14:37

to those registrations

14:39

and legislations. But

14:41

the challenge is how will we as a

14:43

society respond to this? I think that's the

14:46

bigger problem because governments, they're

14:48

great at regulating big companies. It's much easier for them

14:50

to do because there's less people they have to talk

14:52

to. But I kind of look at

14:54

it as the analogy of when we wanted to

14:56

make cars safer, we had to do two things

14:58

at the same time. You had to go to

15:00

Ford and GM and Volvo and everyone and say,

15:02

hey, put seatbelts in the car. And

15:04

that was one part of the problem. And then the other part

15:07

of the problem was telling all of us to put the seatbelts

15:09

on when we got in the car. And

15:11

that's the bit that seems to me is

15:13

missing. We're not seeing an awful lot of

15:15

work by governments, regulators, but other public bodies

15:18

to make sure that Kerry knows what he's doing

15:20

with his data and JP knows what he's doing

15:22

with his data and just put that on a

15:24

higher pedestal than we do right now. And

15:27

we see this all across the place. And

15:29

you mentioned Johnson Heights work around

15:31

the anxious generation. We're just handing over

15:33

so much of our data in the

15:35

form of our smartphones. And particularly we're

15:37

handing over those smartphones to our kids

15:40

without training them on, hey, this is what's

15:42

going on with the data that you're giving

15:44

away when you sign that little tick box

15:46

without reading the terms and conditions. That's

15:49

where we need to be paying more

15:51

attention. So does anybody read the terms

15:53

and conditions? Like seriously, I know, I

15:55

know. And then it's accept

15:58

all cookies, decline all cookies. or

16:00

worse, manage your preferences. And I've hit the

16:02

manage your preferences. And I'm

16:05

led into this confusing landscape that

16:07

I'm just like, all right, I'll

16:09

just accept them. What's at stake

16:11

in moments like that where we're

16:13

accepting terms and conditions and

16:16

cookies. And I know that Google's gonna

16:18

change that massively this year

16:20

as well with the death of third party cookies. Well,

16:23

I mean, the history of the

16:25

internet is us giving up privacy

16:27

for utility, right? If we find

16:29

enough utility in anything, we'll give up some privacy

16:31

for it. Every time that you want an Uber

16:34

to arrive and find you on the street, you're

16:36

giving up a little bit of privacy for that

16:38

utility. The same if you want your Shopify account

16:40

to remember your login details, or if you want

16:42

to use meta products to browse what your college

16:44

roommates are up to. Every time

16:46

we do that, we're giving up some level

16:49

of privacy for that social utility back. And

16:51

the history of, as I say, the internet

16:53

says that we will continue to do that

16:55

because as humans, just by our very nature,

16:58

we're quite lazy animals. We like to find straight

17:00

paths between point A and point B. And

17:03

as long as we're those lazy animals,

17:05

we'll continue to find ways, even self-inflicted,

17:08

of exploiting that laziness to

17:10

get what we want. And that's where

17:12

the biggest problem is, is that most often

17:14

these products are not particularly clear about what

17:16

they're doing with the data. And

17:18

even if they are clear with what they're doing with

17:20

the data, they're moving at such a speed that we

17:22

can't really know five, 10 years from now what

17:26

this is gonna look like. The AI that we

17:28

have today, as our mutual friend,

17:30

Kelly Zhang says, is the dumbest it will

17:32

ever be. Yes. Right? Yeah.

17:35

And that's the thing that we can't anticipate. If you even think

17:37

about the advancements we've seen in the past 48 months from

17:41

these quite simple language models, things like

17:43

Alexa, things like Google Assistant, then we

17:45

get the first version to chat GPT

17:47

that can just about write something interesting.

17:50

But then these leaps and bounds to the video

17:52

and the imagery that they're able to create. If

17:55

that curve continues to grow exponentially, five

17:57

years from now, 10 years from now.

18:00

now, we can't even imagine what these

18:02

things are going to be able to do. And

18:04

they're all learning from the data that we're giving

18:07

them right now. And they'll

18:09

learn from the data that we create using

18:11

these tools in the years to come. And

18:14

so that's why we need to take more

18:16

accountability for what we're using them for. Well,

18:18

this is relevant on an individual user basis,

18:20

but also for all the leaders who run

18:23

organizations whose organizations are collecting this kind of

18:25

information too, right? So two

18:28

questions for you. Number one, what do you do?

18:30

Do you accept all cookies? Do you decline some?

18:32

Do you manage your preferences? What do

18:35

you do personally with that? Knowing what you know,

18:37

which is probably more than

18:39

most of us listening to this podcast and

18:41

certainly more than the person conducting this interview.

18:45

I think you're more educated than you let on.

18:47

Oh, I do. I would say. A little knowledge

18:49

is dangerous, J.G. It's very dangerous. I

18:52

try. I think I try, but I'm not going

18:54

to say that I'm not guilty of this myself

18:57

because I too want all of those things. But

18:59

I would be particularly when it comes to these AI

19:01

tools that are now being built on top of the

19:03

language models, let's move like the social networks and other

19:06

things like the iTunes privacy agreement

19:08

to one side and think

19:10

about particularly these AI tools. One

19:12

of the things I'm always doing is looking at what

19:14

models are they built on top

19:16

of. You've obviously got things like chat

19:18

GPT, which we all know many people

19:20

might have tried out something like Claude

19:23

or perplexity. And then there's the new

19:25

AIs that tend to feel more friendly

19:27

like the Pi from inflection. Some

19:29

of these tools you guys may find or you'll find in the

19:31

show notes, I'm sure. But these new

19:34

types of tools, they're not

19:36

always the experience that you're having

19:38

with them at least is not always built

19:40

by that same company. We're seeing lots of

19:42

startups, lots of people building new experiences that

19:45

you can use on your phone or on

19:47

the desktop that are wrappers on top of

19:49

other language. It's like a skin, right? Exactly.

19:52

It's a skin with some prompt engineering

19:54

and... Specialized utility.

19:57

If you don't know what model is underneath that...

20:00

you don't know where your data is ultimately going to

20:02

and what it's being used for in the future. Now,

20:04

personally, I don't think there's anything particularly

20:07

nefarious going on at any of these

20:09

companies right now. There's no

20:11

evidence to suggest that from what I'm seeing.

20:13

They all ultimately, as you've alluded to before,

20:15

are commercial enterprises and they want to make

20:18

money. The minute that they lose

20:20

our trust is the minute they stop making

20:22

money. There

20:24

is that kind of interesting tension that the

20:26

commercial aspect of all this holds. It

20:29

doesn't mean that the companies building on top of these things don't

20:32

want to do things that either are not, like

20:35

I say, bad in themselves. But they may

20:37

not be things that we necessarily want to

20:39

support as a society and particularly within

20:41

leadership or within church contexts. These

20:44

are the issues that I think we want to pay more

20:46

attention to because just because something can be done

20:49

doesn't necessarily mean that it should be done or

20:51

certainly that we would want it to be done.

20:54

So when you think about the future, I like

20:57

to think in terms of trajectory

20:59

or trendlines, JP. So

21:01

if you look at the decline of the church

21:03

over time, there's a trendline. And

21:05

even after COVID, I was reading a few graphs

21:07

recently. Basically there's an interruption pattern

21:09

interruption, and then it continues on the

21:12

historic trendline down, which is really too

21:14

bad. Other companies like the

21:16

rise of tech, market capitalization or user

21:18

share. The trendline is here's 2010, here's 2015,

21:20

here's 2020, here's 2024. So

21:26

with no current, no future intervention

21:28

beyond what we see now, I'd

21:32

like to go into the worst case for

21:34

AI and the best case for AI. And

21:37

I know, ask 10 people, get 10 opinions. I get

21:39

it. But I would love your take as

21:41

somebody who's literally built and sold companies in

21:43

AI and who sits

21:45

on a board and has your

21:47

resume. What is the worst case

21:50

that we could imagine a world

21:52

five, 10 years down the road in terms of

21:54

AI and where it's going? Well,

21:57

if anyone has watched the recent Mission Impossible.

22:00

movies, they'll have seen what looks

22:02

like potentially the worst-case scenario, which

22:04

is some kind

22:06

of large-scale AI emerges as

22:08

being... I would

22:11

not say sentient because I'm not sure

22:13

that that's actually possible within our theology,

22:16

but something that emerges with a super

22:18

intelligence that is beyond our control and

22:21

starts deciding that either it's going to

22:23

align itself with those that

22:26

would seek to see the downfall

22:28

of society or the end of the Western world or however

22:30

you want to put it, or that

22:32

it just makes that decision in and of itself

22:34

and says, you know what, humans, you're not doing

22:36

a great job looking after this planet. Maybe we

22:38

would be better off without you. And

22:40

that argument has been made by many. The

22:44

likelihood of that happening, I think, is far

22:46

off because I think there are many steps

22:48

between here and there before we get anywhere

22:50

near that being a challenge. But it's not

22:53

entirely impossible. And

22:55

because it's not entirely impossible, we should at least give it

22:57

some level of attention, if

23:00

nothing else, to make sure it shapes the way that

23:02

we follow policy and that we keep away from those

23:04

things in the same way that we did with nuclear

23:06

weapons, which is often the comparison.

23:10

And probably more importantly, the way that we didn't

23:12

really do it with social media, which is probably

23:14

a more accurate comparison in terms of the actual

23:16

net impact that it's had on people around the

23:18

world. So I think in terms of worst case

23:20

scenarios, that's kind of out there in the existential

23:22

threat category. But what I think is more the

23:25

likely worst case scenario is

23:27

that these models continue to grow

23:29

unchecked and that we just begin

23:31

to adopt them into society in a way that we

23:33

just wouldn't want to see happen. I think the one

23:36

area that I'm particularly passionate about is in

23:38

relationships. We've already seen the

23:40

impact that COVID and the smartphone has

23:42

had on young people's ability to form

23:45

lasting social bonds with one another, to have

23:48

deep conversations and deep relationships. And

23:51

who knows already what knock on impact that's going to

23:53

have 10 years down the road to the population, let

23:56

alone anything else. If young men can't find

23:58

young women to build population

24:00

with without some other artificial intervention, we're going

24:02

to have problems, guys. That's the way it's

24:04

going. Add to

24:06

the ability for you to have a virtual

24:09

girlfriend or a virtual boyfriend and fall in

24:11

love with the chatbot and be totally happy

24:13

with that. I think it's a

24:15

relational category that we don't want to see

24:17

emerge. And that's actually probably the more likely

24:19

worst case scenario that we are

24:21

already seeing companies building

24:24

tools, building experiences where you can

24:27

essentially take a step back from society

24:29

and have pretty much everything done for

24:31

you, both your work product,

24:33

your relational product, your call it whatever

24:37

aspect of your life you want

24:39

managed. And we end up

24:41

in a kind of, you remember that Disney movie,

24:43

Wally, right? We kind of end up in that

24:45

kind of all sat slightly in a half vegetative

24:47

state looking like a potato leaning back, watching a

24:50

recycling truck clean up the world. That's not a

24:53

great outcome, generally speaking.

24:56

And that's before they all had like AI friends,

24:58

they at least were talking to one another. So

25:00

I think that's where we could

25:03

end up in some form. And that

25:05

is to me a more likely worst

25:07

case scenario that necessarily something

25:10

releases all the nukes or turns off all of

25:12

the energy grid. Yeah. And so sort

25:14

of a general social

25:16

degradation over what we have now.

25:19

And for regular listeners, Scott Galloway

25:21

is on this here again. I

25:24

don't know exactly when compared when all the

25:26

episodes will be released, but he sees that

25:28

as a massive threat

25:30

to our culture is disengaged

25:33

young men. He says that's

25:35

where things go bad.

25:37

All right, now be the optimist. I'm

25:39

sure you've got an optimistic framework. Again,

25:41

all things being equal, nothing in the

25:44

future radically changing from the current trajectory.

25:46

What is the possible best case scenario?

25:49

Well, I think this is interesting. You recently

25:51

have Morgan on your show, I think talking

25:53

about kind of the things that don't change.

25:55

Yes. Yes, I'm going to have him. Yeah.

25:58

Or you're going to have him on and yeah. And

26:00

you know, he is

26:02

his recent book, I think is really fascinating because

26:05

he told about the things that that don't change

26:07

over time. And I think that's

26:09

actually more likely. There's a bunch of human characteristics

26:11

that don't change as much as we're worried about

26:13

things like a girlfriend's and stuff. I actually think

26:15

that the overwhelming majority of us still find

26:18

the pull to be with one another in

26:20

the physical space. The real

26:22

optimistic view of AI is that it can

26:24

just take away so many of the drudgery

26:27

tasks that we all have to deal with.

26:29

Yeah, particularly in the ministry

26:31

context or work context. You

26:34

know, we spend so much time administering

26:36

the work we do rather than doing

26:38

ministry. Or we spend so much time

26:40

on the busy work that is often

26:42

called rather than actually being busy working

26:45

on the thing that we want to focus on. And

26:47

AI does hold the promise to be able

26:50

to eliminate vast amounts of that work, days,

26:52

if not weeks, a year of that, you

26:54

know, filling in a spreadsheet or entering

26:56

a form for the 17th time that was built

26:59

on Windows 97 or whatever it might be. Like

27:01

these things are out there still.

27:04

And as much as the technical world has

27:06

been revolutionized, you walk into any public municipal

27:08

building or hospital or school and you'll find

27:10

technologies that have been leapfrogged time and time

27:13

again still running in, you know, many of

27:15

these systems. And AI

27:18

potentially could come along and if not replace those

27:20

technologies, just fill those things in for us, which

27:22

would make things a lot easier for most of

27:25

our lives. So administration, I

27:27

think, is going to be one of the big things that

27:29

maybe we do end up in the world of being able

27:31

to do the four day work week and, you know, living

27:33

that kind of dream that Tim Ferriss has been selling to

27:35

us for a number of years. That we

27:37

actually might have some lifestyle, you know,

27:40

benefit over time. I think that's one of the big things. But

27:43

it's also imperative, right? Like if we want to

27:45

solve some of the biggest issues in the

27:47

world, climate change, cancer, other

27:49

kind of diseases, and

27:52

also make sure that our politics is actually something

27:54

that can sustain itself over time. We

27:56

haven't done a great job of that as of late as the

27:58

human race since the industrial era. revolution. And

28:01

those problems are now so big that the

28:03

speeds required to fix them doesn't seem to

28:06

be possible in and of ourselves. And

28:08

so my optimistic view would be that we

28:10

will see massive breakthroughs whether it's the work

28:12

that's being done on things like protein folding,

28:15

or the discovery of new drugs, the

28:17

identification of new cancers, the solving of

28:19

the climate race, or emergence of

28:21

things like small nuclear

28:24

fusion and nuclear fission reactors, which will give

28:26

us boundless energy sources. We're not going to

28:28

get to those things about artificial intelligence.

28:30

We don't have the collective brainpower on

28:32

our own. And so I

28:34

think that we could begin to see the

28:36

new renaissance begin to emerge over the next

28:39

decade as these technologies get

28:41

smarter, so long as the negative

28:44

opportunities don't outweigh the positive ones,

28:47

and that people continue to seek

28:49

for human flourishing rather than the

28:52

rather commercial, sad

28:55

story that is being told at the

28:57

moment, just flooding the internet with garbage

28:59

content. That's what seems more likely right

29:01

now. But I'm hopeful that

29:03

we might see a new generation

29:06

of technologists arrive that say, wow, we can

29:08

use this stuff to do immense good. We'll

29:11

probably toggle between the macro and the micro,

29:13

but to dip down into the micro for

29:15

a moment, what are some of

29:17

the most interesting uses

29:20

of AI that you're seeing right now?

29:22

And I'd love you to take that

29:24

in two phases. Number one, just what's

29:26

on your phone, what's on your laptop

29:29

that you're finding absolutely fascinating on

29:31

a micro level, and then other

29:34

technologies that perhaps you haven't discovered

29:36

personally yet, but you know are out there.

29:38

What's got your attention? Well, I mean, the

29:41

app that probably gets more attention on my

29:43

phone, if I think about it here than

29:45

any other, is perplexity

29:48

at the moment. As a search engine, it

29:50

has almost entirely replaced my use of Google.

29:52

This is not an endorsement for them. I

29:55

don't have a particular affiliation. Nothing

29:58

of that nature, but I would just say. from

30:00

straight out usage, it's amazing

30:02

how quickly that has replaced things.

30:06

A story from this week, a client

30:08

rang us out of the blue at Vixen Labs, the

30:10

agency that I run, saying,

30:12

hey, I got in touch with you because I found

30:14

an article about the very specific thing I was looking

30:16

to do with AI this week. And you were the

30:18

top answer ranked on complexity because it

30:20

was found very specifically the article he

30:23

was looking for in a way that

30:25

Google had no ranking for us whatsoever.

30:28

And even if you take that in

30:30

microcosm, it's a really good example of

30:32

how these new tools are helping find

30:34

much more contextual information. So it's amazing.

30:38

If nothing else, because I can ask it

30:40

questions and ask it follow-up questions and it

30:42

seems to do a better job of looking

30:44

at stuff than I can do on my

30:46

own. Just Google search has so degraded over

30:48

the last couple of years. I know they

30:50

keep making changes, but it's not functionally useless,

30:52

but it's approaching that. And

30:55

once these Gemini models begin to roll out

30:57

into mainstream Google search, which we can only

30:59

anticipate they will, then I think there's a

31:01

real chance Google catches up. But for now,

31:03

for me, I spend an awful lot

31:05

of time in perplexity for anyone that

31:07

makes that slide where or content for the

31:10

internet, which is sure is all of us

31:12

that get stuck in PowerPoint from time to

31:14

time. I've been using tools like beautiful.ai, which

31:16

has an amazing ability for, you know, if

31:19

you're a pastor or an executive leader of

31:21

some description right now having to put together

31:23

this year's annual report or quarterly earnings, being

31:26

able to design a slide deck which

31:28

has the Claude model from Anthropic running

31:30

inside of it. You can

31:32

create an entire 20 slide presentation with one

31:35

line text prompt. It does

31:37

the layouts for you. It goes to Dali and

31:39

creates images for you. It chooses the most appropriate

31:41

slide layout like it's an amazing tool. Again, not

31:43

aligned with them, but just that's the one that

31:46

I spend literally hours in

31:48

every single day. But perplexity and beautiful.ai.

31:51

Yeah, for sure. Those are two. I'll be checking those out. Those

31:53

are new to me. I've heard of them, but I haven't done

31:55

anything with them. Yeah, they're definitely great

31:57

places to start. And if you are already using.

32:00

something like chat GPT, you can access the

32:02

GPT-4 models, you can access the Claude models

32:04

inside of complexity as well. So you can

32:06

switch around and pay one subscription price. Is

32:09

it just me or is Claude significantly

32:11

more intelligent than chat GPT-4 right now?

32:15

It's certainly more eloquent, not necessarily more

32:17

intelligent, which is really interesting. What

32:20

we're beginning to see with some of

32:22

these models, they're bringing personality in some

32:25

ways. Claude model is particularly good at

32:27

long form written content. That's probably why

32:29

I like it. Yeah, well

32:31

for you exactly and for myself as well. It's

32:34

much better at emulating my voice when I

32:36

give it examples than chat GPT is. And

32:39

it sticks to the task for longer

32:41

than kind of wandering off and doing

32:43

something strange, which GPT can kind of

32:45

be prone to do. So yeah, I

32:47

would definitely say Claude is also

32:49

a really good place to play around with, particularly

32:51

if you're a content creator, if you're a writer,

32:53

if you're someone that writes press releases or social

32:55

media content or biographies or whatever

32:58

it might be, anything that's longer form,

33:00

Claude is probably your go-to model right

33:02

now for doing that well. And what's

33:04

really promising is those models are getting

33:06

small enough to be able to run

33:08

on a phone offline, which opens up

33:11

some really interesting opportunities in places where

33:13

connectivity is bad or

33:15

parts of the world where AI tools

33:17

would be pretty hard to justify

33:19

just because of the amount of data that they use. So

33:22

I'm particularly excited about where they might go.

33:25

Yeah, that's interesting. So again, a one-on-one

33:27

question, and by the way, for Canadian

33:29

listeners, most are American. You

33:31

can't get Claude, at least at the time of recording

33:33

this, but a VPN will work you around that pretty

33:35

easily. Yeah, well, yeah. And you can

33:37

also access it via some of these other tools as well,

33:39

which is again, the thing we were

33:41

saying before about some of these tools, they have

33:44

other models inside of them. So yeah, your mileage

33:46

might vary, but play around. And a VPN is

33:48

a great idea anyway on public internet, but beyond

33:50

that, that's a virtual private network. Claude, by the

33:53

way, is C-L-A-U-D-E.AI. And

33:57

what it, okay, so help me

33:59

understand as. somebody who does not code

34:01

and someone who is not into AI deeply. ChatGPT

34:04

is an LLM, Clode is an LLM

34:06

as well, large language model. Is that

34:08

right? But they're trained on

34:10

different things. Like I don't understand, because

34:12

they are very different. Like

34:14

user interface, Clode is like, oh, that

34:16

was really helpful. ChatGPT is one more

34:19

time please with feeling. You know? Yeah.

34:21

So it's helpful to understand the difference

34:23

between a large language model and the

34:25

app that you might use that thing

34:27

in. Yeah. Clode

34:29

has, there are a number of different Clode

34:31

models. It doesn't help that they're called Clode

34:33

as well, but there are a number of

34:35

different Clode models. If you go to clode.ai,

34:37

you can interact with the Clode model or

34:40

at the time of recording, it may be

34:42

a different one from when you're listening to

34:44

this, but the Clode 3 model or Clode

34:46

4, Clode 5, whatever comes down the line.

34:48

So the language model

34:50

itself is trained on a massive

34:52

amount of human created data, some

34:54

synthetic created data living on the

34:56

internet. And depending on who you're

34:59

getting that model from, they've sourced it from

35:01

different places. Some have more commercial agreements in

35:03

place, others are just scraping stuff that's in

35:05

the public domain. But the big

35:08

difference is the way that they're trained and tuned

35:10

to behave in different ways. And then when you

35:12

come and use them inside of a tool, for

35:14

example, inside of ChatGPT, you're using

35:16

what is probably the GPT 3.5 or GPT 4 model. Those

35:21

different models have different amounts of data in

35:23

them, different knowledge, and they behave in slightly

35:25

different ways, but you can access both of

35:27

them inside of the ChatGPT app. And

35:30

it's the same models that if you

35:32

use BingChat, for example, or you're using

35:34

Microsoft Copilot, you're using the GPT 4

35:37

model inside of those tools.

35:40

And they have different abilities too. So Bing Search is-

35:42

That's sort of the stream idea, right? Yeah,

35:44

but so Bing Search uses the same model that

35:46

ChatGPT has, but it has the ability to go

35:48

to the internet and pull in real time results

35:51

and blend it with the content that the

35:53

model can produce. The same thing that Perplexity

35:56

is able to do when they're using their

35:58

own Perplexity search model and clause. isn't

36:00

able to do in and of itself because

36:02

it doesn't have live internet access. So they

36:05

all have slightly different abilities. It's

36:07

kind of like having a range of different assistants that

36:10

you might employ to different jobs. Some

36:12

of them are going to be better at different things. And

36:14

so chat GPT is particularly good at tasks

36:16

and handling data. It's particularly good at writing

36:18

code. Claude is much better

36:21

at linguistic tasks, long form textual

36:23

tasks. And neither of

36:25

those produce images, but that's why you have

36:27

things like DALI from OpenAI or Mistral.

36:30

And there are many others that can produce

36:32

visuals as well. Okay. So just

36:36

from a basic thing, Anthropic, which

36:38

is the company behind Claude, are

36:42

they working totally independently from

36:45

chat GPT? There's no master data source.

36:47

These are two separate companies that have

36:49

developed themes from scratch. As far as

36:51

we're aware. As far as

36:53

we're aware. Let's not get into conspiracy theories.

36:55

Well, no, but it is an important thing

36:58

to highlight that none of these companies publish

37:00

exactly what data has been trained to make

37:02

them work. Not in full

37:04

anyway, even the open source ones. Now you

37:06

can begin to get an understanding of what

37:09

might be in there because we've seen examples.

37:11

And this is the basis of the court

37:13

case being held by the

37:15

New York Times against OpenAI at the

37:17

moment is that clearly chat GPT is

37:19

able to produce, well, at least was

37:22

able to produce long form examples of

37:24

what seemed to be exactly copies of

37:26

New York Times articles. Therefore, you can

37:28

assume it was in the training data.

37:31

It may no longer be. And

37:33

so each of these different models, they have slightly

37:36

different training data that goes inside of them. And

37:38

that's what makes them better or worse at certain

37:40

tasks. There are some models that are trained, for

37:42

example, just on scientific papers. And so scientific papers,

37:44

if you're going to write them, they have a

37:46

very specific linguistic style, a way of referencing, et

37:48

cetera. And so you would want

37:50

a model that was trained on that. And this is where we see

37:52

a lot of companies going right now is

37:55

building on top of these language models with

37:57

their own data sets. So you've seen examples

37:59

from Blue. Bloomberg doing it with financial data,

38:01

or McKinsey, the consulting firm, doing it with

38:03

all of their consulting content. And we're now

38:06

seeing in the Christian world, Bibles being built

38:08

on top of just seeing the release this

38:10

past couple of weeks of Bible.ai, which is

38:12

a project that's trying to build a large

38:14

corpus of Christian content to

38:16

train a foundational language model so it's

38:19

better at producing biblical related content. So

38:21

we're going to see examples of that

38:23

type of thing emerge as well. It'd

38:25

be fun to see him merge so

38:27

many different theologies into one that'll be

38:29

absolutely fascinating to watch. And that's

38:31

the problem, right? Because first of all, you want to

38:33

put something in them, you've got to agree with what

38:35

we agree on. Which is

38:38

not always the easiest of things. Okay, I'm going

38:40

to have to track that one. Now that's a

38:42

good survey of the landscape, it really is, JP.

38:45

You specialize in conversational AI.

38:47

What is that? So

38:50

yeah, so we started Vixen Labs, which is the agency

38:52

I've run for the past five or six years, really

38:55

with intent around making experiences

38:58

of talking with the companies and organizations that

39:00

you have to do business with every day

39:02

a little bit better through

39:04

talking to them rather than having

39:06

to click and scroll and swipe

39:08

down. Is this like instead of

39:10

press five? Precisely. And

39:12

so we've been really focused on things

39:15

like voice technologies, we spend a lot

39:17

of time building applications for Alexa, for

39:19

Google Assistant over the past couple of years. And

39:21

now that's emerged into these large language models

39:24

that can help us build things like chatbots

39:26

and voice assistants that are just much more

39:28

pleasurable to use and actually helpful than

39:31

they have been historically, more than just

39:33

doing timers and reminders, which

39:35

is what they've been good for for a little while. So

39:37

yeah, we focus on that because I think

39:39

we want the future of using the internet

39:41

to be one that's just a little bit

39:43

more personal and more human,

39:46

ironically. Which

39:48

we are conversational animals, right? That's how

39:50

we get things done. You don't

39:52

roll up a McDonald's drive-thru in order

39:56

to have a chat with someone. But

39:58

the means that you do so... the

40:00

means you get that burger delivered into the car,

40:02

or whatever your order is, is through

40:05

the art of conversation. And that's the way

40:07

we've always done things as humans. We believe,

40:10

certainly from a Christian perspective, we

40:12

began with the word, right? And say, we

40:14

know that conversation and the art

40:16

of talking to one another is an important thing. So

40:19

I would love to see more of our technology

40:21

head in that direction, rather than it being this

40:23

kind of screens in front of us at all

40:25

times head down in a phone. We

40:28

think that by bringing the ability to talk to

40:30

and type to if necessary, tech,

40:33

it lifts us out of that trap and

40:36

lifts us out of that doom scrolling mentality. Oh,

40:39

that's a great thing. So for those who've

40:41

called Apple in the last six, seven years,

40:44

you'd be familiar with that kind of conversational

40:46

AI where it's like, I'm a fully trained

40:48

voice specialist that can help you. What's wrong?

40:50

And then you tell it, my computer won't

40:52

boot up. And it's like, oh, it sounds

40:54

like you need technical support. Hang on. I'll

40:56

put you right through that kind of thing.

40:59

Well, so that's the, I think what we would see as

41:01

conversational tech, like 1.0 is from natural

41:05

language processing and being able to

41:07

understand natural language understanding. So

41:10

that is the press one for this. And it

41:12

knows at least what you said. But the difference

41:14

now we see is with these language models is

41:16

that you could say the entire thing of what's

41:18

wrong with your Mac book. And

41:21

if Apple chose or other manufacturers chose to

41:23

put these systems in place, it

41:25

could do what chat GPT could do, which is

41:27

take all of that information from you directly and

41:29

actually give you the answer. It would probably work

41:32

out pretty well because it's the same

41:34

technology. It's the same technology. It's just being spoken to

41:36

you rather than showing you as a line of text

41:38

on screen. And we're seeing this now if you use

41:40

the chat GPT app on your phone, you can talk

41:42

to it and it talks back to you in a

41:44

variety of different voices. And you can always flick away

41:47

and look at the screen. But actually

41:49

that experience of talking to these things with

41:51

your voice is actually quite delightful and

41:54

certainly feels far more human even though

41:56

it's not than typing

41:58

into a screen or into a text box. Yeah.

42:01

All right. I want to talk about because

42:03

you work with Ecclesia,

42:07

Ecclesii. How do you pronounce it? Ecclesii.

42:10

Ecclesii. I think the pronunciation we got

42:12

in was about, you know, sing it written down is different. It's

42:15

a think tank that is starting to

42:17

process or that is processing the theological

42:19

issues associated with AI. What

42:22

is, if you were to look at

42:24

an agenda of what consumes your time

42:26

and Ecclesii's time,

42:28

what are the top two or

42:31

three things on your agenda right now? What

42:33

are you working on? So

42:35

I think, Ecclesii, we founded the think tank at the end

42:37

of 2023 as we began to see the

42:41

emergence of the church really responding

42:43

to the AI revolution and particularly

42:45

for church leaders in all contexts,

42:48

whether that's in ministry, in

42:51

parachurch organizations, in non-profits, but Christian

42:53

leaders looking for guidance on how

42:55

do I wrestle with some of

42:57

these big topics that are arising.

42:59

And broadly speaking, we've rallied around three big

43:02

areas. One is to have a better theology

43:04

of AI because it does raise some existential

43:06

questions. Maybe we can get into those. I know you've done a

43:09

lot on that in the past. But

43:11

then the practical and the pastoral implications of

43:13

the other two real areas. So

43:16

practically, what does it mean to have an AI

43:18

policy for your church or for your charity? What

43:20

does it mean to have a code of ethics? How

43:23

will you physically go around choosing which tools to

43:25

use and which ones that sit outside of things?

43:28

And then pastorally, using that as a kind

43:30

of broad catchall, is how you

43:32

deal with the issues that arise from AI

43:35

in ministry or in society. And I always use

43:37

this example, which I know is maybe a bit

43:39

trite, but when a young person comes to a

43:41

youth worker and says, hey, I've fallen

43:44

in love with this chatbot. What do

43:46

I do? How does a

43:48

youth worker or a minister in that context

43:50

respond to that question? What do

43:52

they actually say? Do they acknowledge the feelings which

43:54

may be very real for that young person who

43:56

feels like they truly have a relationship with these

43:59

things? In recent

44:01

months of people sadly committing suicide when

44:03

these bots break up with them or

44:05

that they have tried to marry them,

44:07

that we've seen both the good

44:09

and the bad of these things and that's already now, let

44:12

alone 24 months from now when this stuff gets really smart.

44:15

So how do we contend with these issues? This

44:17

is the stuff we're trying to wrestle with because

44:20

even if you choose not to, quote

44:22

unquote, use AI in your ministry, your

44:25

congregations, those that you're trying to seek to

44:27

reach and be impacted and certainly on the

44:29

mission field, they will be using it. There's

44:31

no way that we're putting this back in

44:33

the box. And so what we really want

44:36

to see at Ecclesiast is the church be

44:38

prepared and equipped to respond to that situation

44:40

and to be able to roll with these things

44:43

as they emerge, not be caught on the back

44:45

foot as we've so often seen it be the

44:47

way in the past when it comes to technology

44:49

and the church where we're often bad at it

44:51

or often late or often both. And

44:54

I think we could do a better job of it this time around.

44:57

I really appreciate it. And that example of

44:59

somebody falling in love with an AI or

45:01

a chatbot has been used before on this

45:03

podcast and it sounds

45:05

like science fiction, but it's not

45:07

science fiction. Yeah. So I

45:10

mean, one of the things that we see

45:12

and I saw this at a hackathon that

45:14

I was at recently where there was an

45:16

example of a church organization that was trying

45:18

to create a technology using CCTV and

45:20

AI and it could do face tracking to monitor

45:22

attendance. Now there's probably a bunch of good reasons

45:24

why you might want to do that, but

45:27

there's also a lot of challenges with it as well,

45:29

right? Totally doable with

45:31

existing technology like plug together a few

45:33

different tools. Totally doable right now. Should

45:36

it be done? I think real

45:38

problematic use case because

45:41

the minute you start tracking who's there, who's

45:43

not, who's to stop someone calling them up

45:45

and saying, Hey, your giving looks like it's

45:47

dropped this past month and you've not been

45:49

at church three times or worse. Hey,

45:52

I saw you sit next to the same woman three

45:54

times in the past month in church and she's not

45:56

your wife and your wife wasn't there. Is there something

45:58

going on there? Like these are... Again,

46:01

it's not about the AI being

46:03

nefarious. It's AI in the hands

46:06

of someone that might use it in the wrong way that is

46:08

the problem. These are real-time

46:10

things and we need the church to be not

46:12

just going, oh, isn't this exciting? I

46:14

can do things that, well, I don't have to have someone

46:17

at the back with a clicker registering how many people showed

46:19

up this Sunday. I can just have an AI do it.

46:21

Well, where is that data going? What are you

46:23

going to do with that data? What are the

46:26

ways you're going to keep that person safe, let

46:28

alone the safeguarding implications and many other issues besides?

46:31

These types of things are already happening.

46:33

The technology is already there to use

46:36

it. I want us to use

46:38

this technology. I don't want to sound like I'm saying put the

46:40

brakes on, but you wouldn't get in

46:42

a car with a great accelerator with no brake pedal.

46:45

We need to have both. That's what we're advocating

46:47

for is we need to go

46:49

forward and try and find use cases for this stuff,

46:51

but also know when we need to apply the brakes

46:54

and make sure that we're driving on the right road. Well,

46:57

and I think that's a good point. I

46:59

mean, that product probably isn't at market right

47:01

now and hopefully not being developed, but

47:04

it probably will be and it probably will be

47:06

released by somebody down the road, whether it's out

47:08

of that source or a different source. And

47:10

then you need the wisdom to figure it out.

47:12

I was thinking when you were saying the unintended

47:15

and the intended consequences of AI are in your

47:17

church. Imagine a church in 2008, just

47:22

as Twitter was emerging, Facebook was starting to

47:24

escape out of campuses saying, we're not doing

47:26

social media. We're not doing, as we called

47:28

it then, Web 2.0. It's banned

47:30

in our church. We won't have an account if

47:33

that happened. And let's say you're still reaching people

47:35

in 2024, which is a whole other question. Everybody

47:39

in your church, you're dealing with

47:41

increased teen anxiety, depression, polarization,

47:44

extremism, all of those things have

47:46

happened to your church, even

47:49

though you're off social media. And

47:51

your argument is you can, and a surprising number,

47:53

I mean, Glue has done the studies on that

47:56

Glue and Varna, surprising number of people in

47:58

the church are opposed to AI. AI and

48:00

saying, we're not going to use it. Well, first of all,

48:02

you're probably already using it and don't realize it. Secondly, even

48:05

if you did that, that doesn't mean your church isn't

48:07

going to have a whole bunch of people, like meaningful

48:09

percentages in love with chatbots,

48:12

using technology for malevolent purposes, not knowing

48:14

ethically what to do as a Christian

48:16

about how to integrate it in their

48:18

businesses and in their home, what to

48:21

do with their teenagers, their marriage broke

48:23

up, um, over AI. Like

48:26

all that stuff is coming in here. It's all

48:28

coming. And it's all coming out. It's also coming,

48:30

you know, for the church leader that might be

48:32

listening, it's also coming into the actual delivery of

48:34

ministry as well. Right. Yeah. We, we get this

48:36

question all the time about, can I use chat

48:38

GBT to help me write a sermon? And

48:41

I know that we can because you, you and

48:43

many other works on building helpful tools to help

48:45

you do exactly that because it can't be done.

48:48

Um, but you know, should we be

48:51

asking it to write all of our prayers for a Sunday

48:54

and just reading them the base and you know,

48:56

should we be asking it to compose

48:58

worship music and using that without the

49:00

spirit being part of that process? Like

49:02

these are really thorny theological issues that

49:04

we have to try and unpick. And

49:07

I don't think most churches let

49:09

alone have time to think about this stuff

49:12

or the, or the knowledge or education to

49:14

do so. And nor should they, they're not

49:16

AI theologians sitting around thinking about this stuff,

49:18

we need to equip them with the, with

49:20

this knowledge. Um, but yeah,

49:22

it's very much starting at the baseline of do

49:24

people know what the tools are? Do

49:26

they know how they're being used? And

49:28

crucially, are we thinking critically about them

49:30

before we actually pick up and log

49:32

in before you click yes to the

49:34

terms and conditions again, without reading them.

49:37

Um, just because the thing looks like it's

49:39

going to save you two hours of an

49:41

afternoon, like these are the steps we need

49:43

people to take and to be aware that,

49:46

um, when we add technology to

49:48

anything, we give it the opportunity

49:50

for it to take over some of our decision-making,

49:52

which we might want, but we also give it the

49:54

opportunity to take over some of our mistakes, which we

49:56

don't want. And that's the thing that

49:59

we want to be conscious. of is that if you

50:01

wouldn't be willing to give this task to an assistant

50:04

without checking what they were doing, don't give it to

50:06

an AI to do it either. We

50:08

need to stay in the loop and help use

50:11

these tools responsibly, particularly in the ministry context

50:13

if we want trust in the church to

50:15

increase, to use your analogy

50:17

to that trendline rather than decrease as

50:19

it so often has done. So

50:21

what should the average church leader

50:25

and the average business leader, because we have a lot

50:27

of business leaders listening to... Yeah. So

50:30

what questions should they be asking? What should they

50:32

be paying attention to? What should

50:34

they be doing right now? Well,

50:37

the first thing goes for either if you're in an enterprise

50:39

context or you're in a small business or

50:41

if you're a church leader or in a

50:44

charity is do you even know what AI

50:46

is being used in your organization? If you

50:48

can't answer that question confidently,

50:51

then that's the first place to start. And that might

50:53

mean, yes, you need to do a survey and find

50:55

out how many people have signed up to a chat

50:57

TBT Plus with their private credit card and they're charging

51:00

it back. Or how many

51:02

of you have turned on an AI

51:04

module inside of your conferencing software without

51:06

looking at how that data is being

51:08

collected or stored? Do you

51:10

know how the tools that you're using

51:13

are using AI and what models are they using? Because

51:16

we've seen, as we've said, AI has shown up

51:18

now not just in a, hey, I bought an

51:20

AI product. It's showing up in all of the

51:22

technology we use from the mailbox provider that you

51:24

choose to things like Canva and Notion and Asana

51:27

and all of the things that we use to

51:29

keep our day-to-day projects going

51:31

in the digital ecosystem and many of those being

51:33

used, obviously, in the church as well. These

51:36

all are beginning to have AI tools added to

51:38

them. It may not be the headline. It may

51:40

be just a part of the stack. And

51:42

so the first thing to do is pay attention to that.

51:45

What's going on? Do you know what's being

51:47

used? The second is actually to use some of it and

51:49

crucially to pay for some of it, which I know

51:51

might seem counterintuitive. But what I mean

51:53

by that is use some of these tools to get

51:55

familiar with them. As I say, I don't think open

51:57

AI, what they're trying to do is evil. endorse

52:00

you, go play around with complexity and chat GPT,

52:02

but do it in a responsible way where you're

52:04

keeping things private that should stay private. Don't put

52:06

anything on the internet that you don't want on

52:08

the internet. It applies to AI tools as

52:10

well. And comply with all of

52:12

the usual things like GDPR and copper

52:15

compliance if you're in the US or whatever else

52:18

regulations apply at the time of listening

52:20

to this. Take

52:22

those regular precautions, but go and play around. And why

52:24

I say pay for it is because when you begin

52:26

to pay for these tools, they

52:28

are not using your time and attention as

52:31

the currency. They're using your money as

52:33

the currency in the interaction

52:35

with these models. And that means that more

52:38

often than not, you're not having any of

52:40

your data go to train future versions of

52:42

the model. You've got the

52:44

ability usually to delete what you've put in

52:46

and that you can remove it if you want to.

52:49

And that you will be getting enterprise level

52:51

safety and security at both ends when

52:53

you're sending data up and receiving it.

52:56

I did not know that. When you pay

52:58

for these things, you get those benefits. So

53:00

when you pay, you're under a stricter

53:03

level of privacy, security, etc. than when you're using

53:05

the free stuff. Did not know that. Just think

53:07

the difference between YouTube and YouTube Premium. What do

53:09

you get when you pay for YouTube Premium? You

53:12

don't get any ads. Because you're

53:14

no longer the product. I

53:16

happily pay for YouTube Premium in the past few years.

53:18

I do. That's all my nine I pay every month.

53:21

12.99 a month. Sign me up. But

53:24

it goes the same way. So when you pay

53:26

for Perplexity Plus or Pro, whatever they call it,

53:28

they're all called Pro Plus Max or Ultra, I

53:31

think is usually the way. But

53:33

whatever one you're paying for, the likelihood is

53:35

that the terms of service have changed and

53:37

you're no longer paying to train the model.

53:40

Your data is yours. So

53:42

again, you might not want to pay money to these people and

53:44

that's absolutely fine. But if you're going to use them, you're actually

53:46

better off paying for it most of the time. So

53:49

I would say first thing is know what's

53:51

going on. Second is try. Test it out.

53:54

And then the third thing is be transparent. Which

53:56

is if you're going to use these tools, whether

53:58

it's in the creation of... ministry resources, whether

54:00

it's in the administration of your business,

54:03

whether it's managing the data of your

54:05

people in whatever context, just

54:07

be upfront and transparent with the people that are

54:09

going to be affected by that. The best thing

54:11

you can do is publish ethics policy or a

54:13

transparency policy around AI, put it up on your

54:16

website in the same way you would do with

54:18

your privacy policy or other things, and

54:20

just state how you're using tools, what you're

54:22

using them for, crucially what you're not using

54:24

them for, and be upfront with

54:26

your congregation or your business about it because the

54:28

last thing that anyone wants is for there to be

54:31

some kind of sneaking suspicion that, hey, I think

54:33

the vicar or the pastor or the minister is

54:35

writing all of his statements with chat GPT and

54:38

it turns out to be true. You know,

54:40

at least if he's upfront about it then maybe

54:42

that's okay, but you don't

54:44

want to be found out and that's what

54:46

we want to make sure that people are

54:49

taken seriously. I think there's a lot of

54:51

fear around transparency

54:54

and I wonder if it's tied. I mean

54:56

you're working with the Church of England on

54:58

ethics on this. I just

55:01

read a case to, it might have been in the New

55:03

York Times, they have

55:05

an ethicist column and this pastor

55:07

served for 50 years, retired,

55:10

and someone in the church

55:12

just happenstance discovered another

55:14

sermon that sounded an awful lot like one

55:16

of his and then went back through his

55:18

work and discovered that they

55:21

were all ripped off, right down to the

55:23

stories that never happened to him. Like

55:25

told someone else's story as though he

55:27

had had that vacation or been to

55:29

that coffee shop, which to

55:32

me is unconscionable. The

55:34

ethicist was actually quite gentle saying, oh, let

55:37

this guy go into retirement. I'm like, no,

55:39

he lied. And yet

55:41

we've all used Google search for years,

55:43

right? I mean we use Google and

55:45

I mean... Anthosauruses

55:48

and concordances and assistant guides and

55:50

all these other things as well.

55:52

Biblical commentaries, it's all digitized now.

55:55

I still use chat DPT

55:57

for first drafts research. I've never found... a

55:59

good sermon to come out of AI yet.

56:02

That's just me. But sometimes if

56:04

I need something summarized or I want

56:06

ideas rebuilt or tested, I will

56:09

use it. So when it comes to

56:11

disclosure, like it's one thing to get up

56:13

there and say every Sunday, I used Google,

56:15

I read five commentaries, I went back to

56:17

the interlinear Greek, nobody does that. But I

56:19

have preached messages where I said, hey, a

56:21

lot of these ideas in the message, and

56:23

I'll give credit where they're due, came from

56:25

a sermon I heard from Tim Keller, or

56:28

Andy Stanley preached the series. I'm reteaching it right

56:30

now and it's got my own spin on it,

56:32

but you need to know these ideas came first

56:35

from Andy. I think that's a great example.

56:37

I think that's a great example. What

56:39

level of transparency would you give if

56:42

you weren't on the internet? That

56:45

should be the same level of transparency you

56:47

give with the internet, whether it's AI or

56:49

just Google. That's fine. That's what we're asking

56:52

for because it's

56:54

a good principle in general. I think it's a

56:56

Christian principle in general to be transparent about

56:59

these things, not necessarily to the

57:01

nth degree. Like you say, here's

57:03

my entire web search history that

57:05

went into this. That's not necessary. But

57:07

at least in the spirit of it is saying, hey,

57:09

I used... Or maybe it's once

57:12

a year or is part of your statement that's

57:14

just up on the website somewhere or on social

57:16

media that says, just so you know, these are

57:18

the tools that I regularly use to help with

57:20

my research and planning of this thing. It

57:23

hasn't happened to me yet where anything has

57:25

come out of Clodr, chat GPT or other

57:27

models where I'm like, oh, this

57:29

is like final draft 101. It's like, okay,

57:31

I have a few ideas. Let's get moving.

57:35

But I suppose the day is coming where

57:37

chat GPT will create a better sermon than

57:39

I could write or Clodr would.

57:42

I wonder... You're a good preacher. There's

57:44

a lot of like sermons that chat

57:46

GPT right now that's better than a

57:48

lot of sermons being written by humans.

57:50

Let's be honest. Perhaps.

57:52

And I guess you're at the point where

57:54

if I borrowed a John Orpburg sermon, I'm

57:56

just going to be like, hey, this started

57:59

with John Orpburg. or Berg, or,

58:02

and, you know, I put my spin on it,

58:04

or maybe you stand up one day and go,

58:06

you know what, chat GPT spit out this amazing

58:08

treatise on grace. And today

58:10

I'm going to share and a lot of

58:12

it was done via chat GPT. If it's

58:15

like 90% that and 10% you, I'm trying

58:17

to like, for example, AI helped write me

58:19

these questions for you. And I almost always

58:21

for the last year and a half, run

58:25

questions and guests through chat

58:27

GPT or Claude. And

58:29

then I sit down and I go, Oh, I never would

58:31

have thought to ask that. So it's

58:34

always a mix. It's somewhere between, sometimes

58:36

half. And sometimes it's like,

58:39

I kept one question or whatever.

58:42

So it's just the idea of transparency. And I

58:44

think you're right. Having a policy is really good.

58:46

Do you have a downloadable one? I know Kenny

58:49

Jang and church.tech and people like that are working

58:51

on that right now. I have not replicated one

58:53

because I would endorse the one that Kenny has.

58:55

So yeah, definitely go to church.tech and download his.

58:58

I was with him last week because we

59:00

were discussing exactly this and it's this is

59:02

the thing that I would recommend. So definitely

59:04

going if you don't follow Kenny, his AI

59:07

for church leaders, Facebook group is amazing. Church.tech

59:09

is great. So definitely go and

59:11

use that in the podcast. I recommend all his stuff.

59:14

But I would say that, you know, that's where we

59:17

do need to kind of, you know, we're getting more

59:19

of these practical guidelines, right? We're getting practical guidelines that

59:21

is beginning to emerge. I think the

59:23

theology of this stuff is still something we're going

59:25

to wrestle with for some time because,

59:28

you know, as these models emerge, what

59:30

happens when a great Christian theology based,

59:33

you know, model arrives that can write

59:35

sermons that was based on hopefully people

59:37

that opted into giving all of their

59:41

sermon content over. It

59:43

can create stuff. And then the question

59:45

is, well, where is, what is that? Is

59:50

that spoken into by God? Can

59:53

he use that stuff? And my answer

59:55

would be yes. I think God can use all things. That's

59:58

what we believe. But

1:00:01

particularly when it comes to teaching and

1:00:03

preaching, we have this very

1:00:06

specific call of ministry

1:00:08

onto that thing. And

1:00:10

we lump that in with the job of a church

1:00:12

leader. And I think

1:00:14

that's where we probably have gone a little bit

1:00:17

wrong along the way as we say the

1:00:19

church... For most church leaders, listening to this, if

1:00:22

that's your job, you probably are a staff member of

1:00:24

one. We often

1:00:26

think of the mega churches and the big places and that's

1:00:28

what a lot of the technology that's out there is catered

1:00:30

to. But for most people, certainly

1:00:32

here in the UK, the 17,000 churches across the Church

1:00:34

of England that I get to work with from time

1:00:37

to time, they're being led by

1:00:39

one person who doesn't have time to do this

1:00:41

stuff. And probably is trying to do all

1:00:43

aspects of leading a church and Kerry, I know you know

1:00:45

this firsthand, and not all of them are great

1:00:47

preachers. In fact, some of

1:00:49

them are really not great preachers at all. And

1:00:51

they would be the first to admit it because

1:00:53

they didn't get into leading ministry to be a

1:00:56

great preacher. They got into it, to

1:00:58

teach the poor or to be evangelists or to be

1:01:00

missioned. There's lots of different reasons. And

1:01:02

I think when

1:01:04

we think about these tools, there maybe is a

1:01:06

possibility that they could come along and really help

1:01:09

many people encounter the gospel in a way that they

1:01:11

weren't able to before through the voice of the person

1:01:14

in the local church who was speaking to them. But

1:01:16

we need to work through some of these things in terms

1:01:19

of like, what is our theology of that? And will we

1:01:21

accept that that can be part of the future of what

1:01:23

ministry looks like without necessarily going to

1:01:25

the nth degree of saying, we'll just stick chat

1:01:27

GPT with a voice assistant at the front of

1:01:29

church every Sunday and leave them to it. Well,

1:01:31

you bring your heart to it. You know, there's

1:01:33

a Canadian doctrine, I was just doing a quick

1:01:36

legal search from back in law school. It's a,

1:01:38

I don't think it's common law. So it could

1:01:40

be in England too. It's called passing off. And

1:01:42

it doesn't mean this, but in my head, I

1:01:44

always take that term and

1:01:46

apply it to church world. If I take,

1:01:49

you know, someone else's sermon or someone else's

1:01:51

book, like I've got William Uries here on

1:01:53

my desk, and I'm like reading

1:01:55

you chapter one and I pretend it's my

1:01:57

work. I'm passing it off as

1:02:00

though I did all the work, I did

1:02:02

all this stuff. And I think that's out

1:02:04

of bounds. I don't care whether it's analog

1:02:06

or digital. If you're pretending to do something

1:02:09

that you didn't do, on the other hand,

1:02:12

great books have great footnotes. And Tim

1:02:14

Keller joked that's been told on this

1:02:16

podcast once or twice, he was famous

1:02:18

for saying, well, first of all, almost

1:02:21

any random sermon you listen to by Tim Keller

1:02:23

probably has 25 to 50 references in

1:02:26

it. As C.S. Lewis says, as

1:02:28

Miroslav Volf says, as this person says, as

1:02:30

this person says, and you

1:02:32

don't think anything of it, you just think, wow,

1:02:34

that guy reads widely, which he does. And he

1:02:36

says, when I have time to write an original

1:02:38

sermon, that's how it goes. When I'm out of

1:02:40

time, I just quote C.S. Lewis. But he always

1:02:42

quoted C.S. Lewis. He never passed off. He would

1:02:45

say, as C.S. Lewis said, as C.S. Lewis said,

1:02:47

it was sort of a joke. But

1:02:49

one of the most profound thinkers of

1:02:51

this generation, Tim Keller, and he was

1:02:54

quoting people left, right, and center. So

1:02:56

if you're using chat GPT, throw your

1:02:58

heart into it, but just say,

1:03:00

hey, I had some help from this, or I had some

1:03:02

help here. But I think as a

1:03:04

pastor, you have to, and as a leader, I was

1:03:06

reading an article a friend sent me from

1:03:09

the Wall Street Journal, and it was

1:03:11

saying, what's happening to tech, Axios is

1:03:13

a media organization. And they're saying we're

1:03:16

humanizing the news at a very deep

1:03:18

level. They were founded in 2017

1:03:21

from people, I think, who started Politico, and

1:03:23

they're going to humanizing this at a very

1:03:25

deep level. I think when you bring your

1:03:27

humanity to the task, when I bring my

1:03:29

humanity to the show, when it's actually me

1:03:31

asking you the questions, and as you note,

1:03:33

like most guests do, how many

1:03:36

actual questions I sent you, did I actually use?

1:03:38

Very few. Because we're

1:03:40

having a great conversation.

1:03:42

But any agree, disagree? I'd

1:03:44

love your thoughts on that. Well,

1:03:47

no, so I agree. I think that

1:03:49

we all have to weigh

1:03:51

ourselves as to how much of my own

1:03:53

humanity do I want to bring to any

1:03:55

of these things that we do with AI,

1:03:57

whether that's preaching a sermon, whether that's writing

1:03:59

the annual. your address, whether it's writing a

1:04:02

birthday poem for a friend, whatever it

1:04:04

might be, or writing your... hopefully

1:04:06

you're not writing your wife's Christmas card,

1:04:08

kind of like a missive using AI.

1:04:11

But you might. You can

1:04:13

do all these things. We have to bring our humanity to and weigh

1:04:15

each of these things up individually. I mean, Kerry,

1:04:17

I'll turn it on you. How would you feel about

1:04:19

the idea of a Kerry bot in

1:04:21

the future? Long after you've kind of gone

1:04:23

to be with the Lord and

1:04:25

all of your sermon content falls over

1:04:27

into the public domain. Do you want

1:04:30

people interacting with Kerry 3.0 in the

1:04:32

future and downloading

1:04:35

future versions of sermons that you never wrote?

1:04:37

Write me a sermon on 1 Corinthians 13

1:04:39

with the theology of

1:04:42

C.S. Lewis and the style of Kerry Newhoff.

1:04:44

What would that look like? Yeah, I find

1:04:47

that very problematic. First of all, we were

1:04:49

talking about this as a team very recently.

1:04:51

I think most of the work I've done

1:04:53

in this life is going to disappear in a

1:04:55

generation. There's

1:04:57

very few people who get read beyond

1:05:00

their demise. But I think it...

1:05:02

Honestly, it's a great question, JP. Unless

1:05:06

things get upended very, very quickly,

1:05:08

I think the one thing

1:05:10

that has the potential to outlive you is a

1:05:12

book you write. Podcasts

1:05:15

come and go, blog posts come and

1:05:17

go, social media posts vaporize

1:05:20

with the dawn. I

1:05:22

think it's a book. And

1:05:25

what I like about a book when they're well

1:05:27

done is a book's taken you

1:05:30

anywhere from a lifetime to

1:05:32

multiple years to produce.

1:05:34

It's your best thinking on an issue. It's 30,

1:05:36

40, 50,

1:05:39

70,000 words on a dedicated subject.

1:05:42

And it makes a long-form argument that

1:05:45

you just can't make on

1:05:47

digital means. You can't do

1:05:49

it. And so, alternatively, if

1:05:53

you have a lecture series, you're a professor, it probably

1:05:56

has that level of thought to it in

1:05:58

lecture notes. But often, lecture in juror when

1:06:00

they get published. So I think if

1:06:02

you have a tome of work that

1:06:05

might be, by the time I'm gone, hopefully

1:06:07

I've written eight or nine books and that's

1:06:09

plenty for a lifetime. Maybe one of them

1:06:11

has a chance to be helpful beyond my

1:06:14

death, but the sermon chatbot

1:06:16

for Charles Spurgeon, I'm sure

1:06:19

is coming if it hasn't been invented yet.

1:06:21

But I think if you have legacy thinkers

1:06:23

or people who really helped shape the thought

1:06:26

of a generation that perhaps

1:06:28

a chatbot would be helpful. I

1:06:30

think for most of us, myself

1:06:32

included, it's like you made a contribution

1:06:34

in your lifetime, you did a good job and

1:06:37

most people tend, Gordon McDonald told me

1:06:39

years ago and he's written some amazing

1:06:41

books. I was asking him advice as

1:06:43

I stepped back from the teaching team

1:06:45

and like retired, retired at Connexus and

1:06:48

just became a congregant. He

1:06:50

said, Carrie, they forget you quickly. And

1:06:52

he was so accurate. And

1:06:54

that's humbling, but you just have to realize your

1:06:56

place in the culture. And so

1:06:59

yeah, I wouldn't have any doubt. I think

1:07:01

while I'm alive, we're working on a Carrie

1:07:03

bot so that people can ask

1:07:05

me questions and spit out, I have

1:07:07

thousands of articles and ideas

1:07:10

and published sources out there. We'll feed all

1:07:12

that into the GPT and

1:07:15

it'll pump out or LLM, it'll pump

1:07:17

out hopefully accurate answers. We haven't been

1:07:19

able to get it accurate enough yet,

1:07:21

but when we do get it,

1:07:23

I don't want to be responsible for saying things I

1:07:25

didn't mean and never intended to say. I

1:07:28

look forward to playing around with it. I might even write my

1:07:30

own seminar too using. That'd be

1:07:32

great. That'd be great. So I'm going to ask

1:07:34

you one or two more questions and then open

1:07:36

the floor to you. What do

1:07:39

you wish churches were doing with AI that they're not

1:07:41

doing right now? Wow.

1:07:43

I mean, there is a lot

1:07:45

just to kind of get off the starting blocks with,

1:07:47

which is again, we have

1:07:50

this wonderful opportunity, don't we, like in

1:07:52

church ministry to bring people

1:07:55

into relationship with Jesus and have them

1:07:57

grow and be nurtured and be discipled.

1:08:00

But the thing that often gets in the way

1:08:02

of that is just the day-to-day drudgery of managing

1:08:04

our money,

1:08:06

managing our teams, putting people on rotors,

1:08:08

all of this stuff. So one of

1:08:10

the big things I just wish churches

1:08:12

would be doing is seeing this massive

1:08:14

opportunity that's in front of them to

1:08:16

pick up a bunch of things that

1:08:18

might just make that task a little

1:08:21

bit easier this week, this month. Think

1:08:23

about, particularly in the post-digital age and

1:08:25

post-COVID, we're all wrestling with having to

1:08:27

basically compete for attention on social media,

1:08:29

to create content, to bring people through the

1:08:31

doors. It's the primary place

1:08:33

that people are spending time and money in terms

1:08:35

of evangelism and outreach. But most

1:08:38

churches don't have a church staff. As I

1:08:40

said before, most churches are one person with

1:08:43

an army of well-meaning volunteers. And

1:08:45

so they don't have teams that can help do

1:08:47

the social media posting or manage a schedule or

1:08:49

put together a rotor. And if

1:08:51

they are doing it, they're often having to do it in

1:08:54

their spare time. So I

1:08:56

think one of the big things is

1:08:58

that churches would adopt some of these

1:09:00

things just to get the basics done

1:09:02

and more of their well-earned time and

1:09:04

their congregation's resources on that, rather

1:09:06

than having to relearn how

1:09:08

to do another three social media posts in

1:09:10

Canva next Sunday. Robert Leonard So

1:09:12

you know what's fascinating? I've got a personal story on

1:09:14

that. We had some family over a couple of weeks

1:09:16

ago, and I have a niece who started her own

1:09:19

business. And she wasn't at the table,

1:09:21

but her mom was. And she was just saying

1:09:23

how overwhelming it was for my niece to

1:09:26

try to come up with social media. But she

1:09:28

wants to get the word out. And I'm like,

1:09:30

well, have you used AI? So we literally just

1:09:32

brought my laptop to the kitchen counter. And I

1:09:35

used a couple of AIs and just entered

1:09:37

a prompt that said, here's the name of

1:09:39

the salon. Here's the name of the person,

1:09:42

this location, this is specialization. Create

1:09:44

a social media plan for

1:09:46

the next 30 days on her Instagram

1:09:48

account. Literally, strategy,

1:09:51

exact text, everything,

1:09:53

image suggestions in

1:09:55

about 25 seconds. And my

1:09:57

sister-in-law started to cry. She's

1:10:00

like, this exists? I'm like,

1:10:02

absolutely. And that was the, well, I

1:10:04

think I was paid. I've done the same thing

1:10:06

with a teacher that I know, a friend of

1:10:08

mine, who's a teacher. She teaches fourth grade here

1:10:11

in the UK. And I showed

1:10:13

her how to transcribe a YouTube video, turn

1:10:15

it into a quick, short

1:10:17

story analogy for her class, and

1:10:19

then write a bunch of follow-up questions. And

1:10:23

that same reaction, just people's eyes light

1:10:25

up and like, this stuff is actually here. The

1:10:28

thing that I really want people to do is not just use it, but

1:10:30

know how to use it really well. Like, that's

1:10:32

where the real game changer is. So, yeah, I

1:10:34

don't know if you did this with your example,

1:10:37

with your friend, but, you know, telling it to

1:10:39

not just write social media policy, but tell it,

1:10:41

hey, you're going to behave like an absolute social

1:10:43

media expert. You know everything that you need to

1:10:45

know about how to post on this platform. You've

1:10:47

learned from all of the big influences. And

1:10:50

now this is all the information I want

1:10:52

you to go and produce for me. Those

1:10:54

little tweaks in the prompt do amazing things.

1:10:56

They still work. Okay, that's good to know.

1:10:58

They still work there. And these

1:11:00

models, they produce some fascinating results when you give

1:11:03

them a bit of personality to respond in before

1:11:05

you get started. So I think that's the other

1:11:07

thing I want people to do is use them

1:11:09

well. Well, there's

1:11:11

a lot of stuff we could get to, but we've

1:11:14

been an hour on this already. Anything

1:11:17

we haven't touched on that you'd like to touch

1:11:19

on? I think the main

1:11:21

thing I would say is that I

1:11:24

think that those are speaking to anyone that's

1:11:26

kind of working in technology or working in

1:11:28

leadership right now has a

1:11:30

responsibility when it comes to AI that they may not

1:11:32

think about, which is that

1:11:35

we are the last generation,

1:11:37

maybe the most anxious, we're

1:11:39

the last generation of

1:11:42

people, of leaders that will

1:11:44

remember what life was like before and

1:11:48

after this technology has

1:11:50

existed. Like my kids,

1:11:52

I've got at the time recording a

1:11:54

nine-year-old and a six-year-old, they

1:11:56

will not know what life is like to go

1:11:58

through school, to go into university. to

1:12:00

work in a workplace, to talk

1:12:03

to a social media thing and

1:12:06

not question whether or not is this a real person

1:12:08

or is this an AI? We're

1:12:11

the last generation to remember what that's like. And so

1:12:13

I think as leaders,

1:12:16

as technologists, as particularly

1:12:18

people working in ministry, we're

1:12:20

the last people to remember what that truly

1:12:22

disconnected experience was like. And we want to

1:12:25

try and look for what was the gold

1:12:27

in that that we want to bring into

1:12:29

the next generation and hold on to. And

1:12:32

what are the things that we want our AIs,

1:12:34

we want our technology to look like in the

1:12:36

future so that we end

1:12:38

up in that more positive view of

1:12:40

where that future curve might go rather

1:12:42

than the more negative. Because I think

1:12:45

we only get one shot at it.

1:12:48

We've seen so many times before that when this

1:12:50

technology or any technology gets out of the box,

1:12:52

there is no real putting it back in there. And

1:12:55

we're seeing obviously efforts at the moment to do that with

1:12:57

social media. We don't want to have to

1:12:59

go through the same thing with AI. And

1:13:01

I think that's our responsibility. It's all of

1:13:03

our responsibility. It comes back to the point

1:13:05

I made at the start, which is you

1:13:07

can wait for the government to regulate a

1:13:09

model or you can hope

1:13:12

that a benevolent AI council arises

1:13:14

out of the big seven companies

1:13:16

running the show or

1:13:19

you and your neighbors and your

1:13:21

children and the people that you work

1:13:23

with take collective responsibility to say, this

1:13:25

is what we want this to look

1:13:27

like in the future and

1:13:29

behave accordingly. And not just

1:13:31

give in to the easy thing,

1:13:34

not to give into the lazy thing

1:13:37

and not just give up more

1:13:39

utility for our privacy and end

1:13:41

up with unintended consequences. That's what

1:13:43

I really want people to try

1:13:45

and do. I think that is

1:13:47

a fantastic call to action for

1:13:49

older listeners. So I got

1:13:52

the internet when I was 31. I

1:13:54

got my first smartphone when I was 40 and

1:13:57

it was a blackberry. And I was so excited that I

1:13:59

could get emails on. It was primitive,

1:14:01

Philistine. I miss my black Yeah,

1:14:05

I know. Again, you're too young. But you

1:14:07

know what is interesting? And I've

1:14:09

often thought about pre-digital memory, but I was really

1:14:11

thinking about it. You know, I'm not young as

1:14:14

a leader anymore. And it's like, but

1:14:16

I do know what life was like before

1:14:19

we all got the internet, the prototype

1:14:21

of the internet, the dial up internet.

1:14:24

And I think, you

1:14:26

know, if you think about what it means to

1:14:28

be human, I have an interest in philosophy. It's

1:14:30

people like Voltaire. It's people like Sautre. It's people

1:14:33

like Kierkegaard and Nietzsche to some

1:14:35

extent, although he's pretty dystopian, who

1:14:40

really help us think... The most positive outlook.

1:14:42

Not the most positive outlook. And theologians who make

1:14:44

us think about what life is really about,

1:14:46

it would be wonderful in

1:14:49

these next few decades while those of us

1:14:51

who remember that are still alive, because we

1:14:53

won't be in 30, 40 years,

1:14:56

to know what it means to be

1:14:58

human and to really think about that.

1:15:01

Because I think you're right. Like civilization is about

1:15:03

to change fundamentally and

1:15:06

inalienably forever. And

1:15:09

maybe one of our contributions, because a lot of

1:15:11

older leaders feel useless. They feel like, oh, my

1:15:13

time is gone. I'm not a young leader anymore.

1:15:15

I think to be able to reflect

1:15:18

and prayerfully think through the theological, philosophical

1:15:20

dimensions of what was it like to be

1:15:23

the last generation to grow up with

1:15:25

a pre-digital memory and to interact

1:15:27

as human beings and

1:15:30

to have meaning in your

1:15:32

life. What does that look like? And

1:15:34

then the next generation will separate the wheat from the

1:15:36

chaff and figure out what it keeps and what

1:15:38

it discards. But that

1:15:40

is a tremendous help, I think, to people who

1:15:42

are older. And don't think you have to write

1:15:44

a book. Just get together with

1:15:47

some 25-year-olds and have conversations. That's

1:15:49

a beautiful call to action. I

1:15:52

think the thing that I hold onto is that

1:15:55

God could have chose to create anything.

1:16:00

have chosen to create us

1:16:02

as silicon-based intelligences, but he

1:16:04

chose to build us as carbon ones. And

1:16:07

I often have this phrase that I say a lot

1:16:09

which is that matter matters. We

1:16:11

are physical 3D living our

1:16:14

life out in the dimension of time for

1:16:16

a reason, because that's the way that God

1:16:18

intended it. And we don't

1:16:20

want to lose sight of that, that we get

1:16:22

a lot of these kind of digital fantasies that

1:16:24

live inside of the Silicon Valley bubble, thinking

1:16:26

that the future is us all being downloaded

1:16:29

onto a chip and having endless

1:16:31

life in that way. And that's just not

1:16:33

the model that we've been given. And I think we want

1:16:35

to hang on to that as best

1:16:37

as we can and be the story that

1:16:40

speaks into society that matter matters and that

1:16:42

we are built to be with one another

1:16:45

in an embodied way because that's... He

1:16:48

came to earth in bodily form for

1:16:50

a reason. He

1:16:53

didn't speak to us through a chatbot. Mm-hmm.

1:16:56

Fascinating. JP, people are going to want to

1:16:58

track with you. Where will they find you

1:17:00

online these days and any resources you want

1:17:02

to direct people to in particular? Yeah. Well,

1:17:05

I'm sure you'll find the links to the show notes, but

1:17:07

you'll find me at James Poulter at pretty much every social

1:17:09

media platform you need to. I write

1:17:12

mostly over on LinkedIn, if that's your place or if

1:17:14

you like to hang out. And

1:17:16

if you are interested, I

1:17:18

suppose, in getting more information

1:17:20

about how to follow along

1:17:22

with what we're doing at

1:17:24

Ecclesii, go to ecclesii.org. That's

1:17:26

A-E-C-L-E-S-I. That's the

1:17:29

Ecclesii.A-I-Bit.org. ecclesii.org.

1:17:31

And yeah, you'll get the resources, follow

1:17:33

the research, and engage in the conversation.

1:17:36

Fantastic. Thank you so much. Thank

1:17:38

you, Kerry. Man, I'm so glad

1:17:40

that we got to have this conversation.

1:17:42

Spent some time with JP recently in

1:17:45

London as well. He's a great leader

1:17:47

and I hope that was both practical

1:17:49

and kind of metaphysical for you.

1:17:51

I think that's what AI is

1:17:53

bringing to the table. Hey, next episode,

1:17:55

we've got Ken Blanchard and Randy Connelly.

1:17:57

Very excited to talk to the legend.

1:18:00

of the one-minute manager. We'll get the

1:18:02

backstory on that. Seagull management, the power

1:18:04

of simplicity and brevity, and a whole

1:18:06

lot more. And make sure you

1:18:09

check out today's partners. Did

1:18:11

you know I'm doing my first live

1:18:13

event? And if you haven't registered yet,

1:18:15

time is creeping up and

1:18:17

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1:18:19

So you can secure your spot

1:18:21

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1:18:23

the artofleadershiplive.com. Join me for three

1:18:25

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1:18:27

to do this. It's an intimate

1:18:29

event. I would love to have

1:18:32

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1:18:34

talking to you. Go to theartofleadershiplive.com.

1:18:36

And our friends at 10 by

1:18:38

10 want to help you

1:18:40

figure out the impact that your

1:18:42

ministry is making with the next

1:18:44

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1:18:47

fill out their free relational discipleship

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10.org/RDI today for your

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free assessment. That's t-e-n-x-1-0.org/RDI

1:18:59

to learn

1:19:02

more. As I said, Ken Blanchard's

1:19:05

coming up. We've also got Priscilla

1:19:07

Schreyer, Rich Vilodis, Steve Cuss, Nikki

1:19:09

Gumbel, Max Locato is

1:19:11

coming back, Andy Stanley, Ed Stetser, and a

1:19:13

whole lot more. And T Wright, did I

1:19:16

mention him as well? And then I've

1:19:18

got something for you because you listened to the end. First

1:19:21

of all, if you enjoyed this, please leave a

1:19:23

rating and review. And secondly, make sure you check

1:19:25

out the Preaching Cheat Sheet. You know, over 10,000

1:19:27

leaders use it pretty much

1:19:29

every week to help them determine ahead of

1:19:31

time whether their message is going to land

1:19:33

or whether it needs a little more work.

1:19:35

So you can go to preachingcheatsheet.com, download your

1:19:37

free copy of it. The link is also

1:19:39

available in the show notes. And thank you

1:19:41

so much for listening, everybody. I appreciate you

1:19:43

so much. I have spent a lot of

1:19:45

time on the road and I got to tell you, I

1:19:48

have loved meeting so many of you. A lot

1:19:50

of you go back to episode one, which is

1:19:52

incredible because we've been at this almost a decade.

1:19:54

And man, you're giving me like real time feedback

1:19:57

on all the things that made a difference in

1:19:59

your life. and I appreciate you and I

1:20:01

appreciate that so much. I can't believe we get

1:20:03

to do this. All right. Well, I

1:20:05

hope today's episode helped you identify and break

1:20:08

a growth barrier you're facing. We'll catch you

1:20:10

next time on the podcast.