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Speaker 1: The world is becoming increasingly proficient at telling stories that

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Speaker 1: deny God. As such, we need Thinking Christian to become

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Speaker 1: as natural as breathing. Welcome to the Thinking Christian podcast.

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Speaker 2: I'm Dr. James Spencer.

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Speaker 1: Through calm, thoughtful, theological discussions, Thinking Christian highlights the ways

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Speaker 1: God is working in the world and questions the underlying social, cultural,

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Speaker 1: and political assumptions that hinder Christians from becoming more like Christ. Now,

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Speaker 1: on to today's episode of Thinking Christian.

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Speaker 2: Hey, everyone. Welcome to this episode of Thinking Christian. I'm Dr.

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Speaker 2: James Spencer, and I'm joined today by Troy Miller.

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Speaker 1: He is the president and CEO of National Religious Broadcasters,

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Speaker 1: or NRB. And today we're going to be having a

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Speaker 1: discussion around artificial intelligence. But I thought it might be

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Speaker 1: helpful to start with you maybe explaining what National Religious

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Speaker 1: Broadcasters is, what your role is there, and those kind

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Speaker 1: of things. So I'll start there, but welcome to the program.

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Speaker 3: Well, thanks for having me first, James. Great to be

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Speaker 3: with you. You know, NRB has been around for 82

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Speaker 3: years now. It's the oldest advocacy organization for Christian communicators,

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Speaker 3: folks in the Christian media. Started back in 1944 when

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Speaker 3: pastors wanted to get on radio and they were thinking

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Speaker 3: of it back then. They were gatekeepers. And so they

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Speaker 3: got together at Moody Church and formed NRB to advocate,

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Speaker 3: really to keep the gospel in the public sector. That's

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Speaker 3: what we work on the most. We also help Christian

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Speaker 3: communicators in all platforms today. how to do their job

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Speaker 3: with excellence and keep them updated on the latest technology trends,

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Speaker 3: things that are moving there. And we hold the largest

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Speaker 3: annual conference and gathering of Christian communicators. We'll be in Washington, D.C.

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Speaker 3: next year, and there should be about 6,000 of us

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Speaker 3: present there who are in radio, television, film, book publishing, YouTube, TikTok,

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Speaker 3: all things digital and new media as well.

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Speaker 2: Very cool.

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Speaker 1: So how do you see, you know, when we think

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Speaker 1: about artificial intelligence, it's sort of making inroads into almost

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Speaker 1: everything at this point. But particularly as NRB, which I've

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Speaker 1: at least traditionally known, and I realize you guys do everything,

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Speaker 1: but I came across it first through radio. And so

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Speaker 1: radio has this very analog sort of feel to it,

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Speaker 1: although I know a lot of it's transitioned to digital

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Speaker 1: and there's HD radio and all that kind of fun stuff.

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Speaker 1: But how do you see AI intersecting with a lot

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Speaker 1: of the different ministries that you all advocate for within

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Speaker 1: the public space? And what sort of new wrinkles is

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Speaker 1: AI really driving into how you advocate for Christian content?

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Speaker 3: Yeah, you know, AI is complex because there's a few

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Speaker 3: different buckets out there. So let's talk about the easy one.

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Speaker 3: And AI is more of a productivity tool, you know.

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Speaker 3: And so AI is really integrating itself, whether it's in

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Speaker 3: audio production or video production. You know, AI is integrating

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Speaker 3: itself all over the place. It's really replacing a lot

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Speaker 3: of things. And, of course, that's an issue onto its own.

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Speaker 3: AI is your new audio engineer or your new editor

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Speaker 3: or your new graphics designer. And so AI can do

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Speaker 3: a lot of things in the media sector to help,

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Speaker 3: you know, make that production process more efficient and streamlined.

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Speaker 3: and all of those workflows. And that's a good thing.

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Speaker 3: That's all a good thing on the AI technology side,

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Speaker 3: especially for nonprofits. Nonprofits are always looking for that efficiency,

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Speaker 3: things that can keep their costs down. So that's a

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Speaker 3: good side of AI, one bucket there. The other buckets

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Speaker 3: get a little more complex, and that's when AI becomes

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Speaker 3: more of the teammate kind of thing. It was interesting

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Speaker 3: because just this last week, I had two different AI

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Speaker 3: companies come drop emails on my inbox, and it was

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Speaker 3: all about move AI from a tool to a teammate.

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Speaker 3: Move AI from a... What was the other one? Move

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Speaker 3: AI from an assistant to an employee kinds of things.

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Speaker 3: And so this kind of idea... of AI when it

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Speaker 3: gets into becoming more and more human-like and pushed on

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Speaker 3: you that you would think of AI as that. That's

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Speaker 3: a bucket we're looking at as well. And the last

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Speaker 3: one that I think is getting really complex is what

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Speaker 3: are the ethical and legal things around AI? Intellectual property

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Speaker 3: is a huge one with ministries. And we know we

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Speaker 3: want the gospel authors in the public sector. But what

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Speaker 3: happens when an artificial intelligent bot takes your pastor's sermons

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Speaker 3: and sort of re-does them from a different theological standpoint

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Speaker 3: of that pastor, you know, and starts to preach out

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Speaker 3: in that pastor's voice and those things. So that's the

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Speaker 3: intellectual property, the kind of the deep fakes in there.

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Speaker 3: All of that's things that we're looking at here at NRB.

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Speaker 1: Let me go back to the let me address those

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Speaker 1: last two. I'm sort of fascinated by the, you know,

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Speaker 1: taking it from a tool to a teammate idea.

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Speaker 2: Do you see that or were those the impetus for those?

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Speaker 1: I know Grok just sort of dropped these a new

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Speaker 1: feature where you can actually design agents who are going

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Speaker 1: to take care of very specific tasks for you. Was

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Speaker 1: that sort of the tone of that teammate that that

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Speaker 1: it's talking about?

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Speaker 3: Yeah, yeah. One of those came through Microsoft's co-pilot. They

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Speaker 3: have a webinar coming out on the co-pilot. It's all

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Speaker 3: about how to move from tool to teammate and how

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Speaker 3: to integrate their bot in there. And that's, I think,

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Speaker 3: a broad issue, not only for companies to look at

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Speaker 3: when you think of this idea of thinking of AI

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Speaker 3: as an actual tool, you know, an employee or somebody

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Speaker 3: that you're working with, a colleague out there, it changes

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Speaker 3: your whole mindset on the tool aspect of it there.

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Speaker 3: But that's what they're driving for. Look at Anthropic. I

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Speaker 3: just recently saw, you know, about Anthropic. I mean, one

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Speaker 3: of the things they're trying to work is how do

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Speaker 3: I make the bot more human-like? And so in the workplace, again,

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Speaker 3: that has a lot of, implications about how do employees work.

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Speaker 3: And I actually saw in the Wall Street Journal recently

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Speaker 3: that there are several companies who now have virtual chief

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Speaker 3: operating officers running their companies out there. But let's set that.

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Speaker 3: That's one bucket we have to figure out and figure

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Speaker 3: out all the implications of that. But now move that

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Speaker 3: same concept into the social media world and into the

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Speaker 3: personal use of AI. And we know that, you know,

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Speaker 3: right now we know that Meta and Alphabet, both Google

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Speaker 3: and OpenAI with ChatGDP, all have lawsuits that have been

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Speaker 3: filed against them because of their manipulation to keep people,

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Speaker 3: you know, hooked using AI in the background to keep

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Speaker 3: you engaged with their tools. Or in ChatGPD's case, where

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Speaker 3: AI bots have actually sort of helped influence young adults,

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Speaker 3: young people, all the way into suicide. And so that

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Speaker 3: human aspect, the more human-like we make these AI bots,

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Speaker 3: I think we have even more ethical questions we have

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Speaker 3: to figure out and have to answer.

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Speaker 1: Yeah, I mean, I saw the Meta settled an $ 18

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Speaker 1: billion settlement related to teen and children and social media

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Speaker 1: addiction and are going to be required to put in

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Speaker 1: some more safeguards there. I think part of what that

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Speaker 1: points to quite honestly, is we just don't know what

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Speaker 1: these things are going to do to us. And I

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Speaker 1: don't mean that in sort of a, there's a mustache

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Speaker 1: twisting evil villain, petting a cat somewhere that is designing

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Speaker 1: these tools to really hurt us. What I think it is,

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Speaker 1: is that any new tool is going to have consequences

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Speaker 1: that we can't anticipate. And some of those are going

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Speaker 1: to be probably beneficial. Others are going to be quite negative.

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Speaker 1: And so we're even starting to see studies come out.

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Speaker 1: MIT just did one where they were talking about over-reliance

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Speaker 1: on AI creating a situation where people were incapable of

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Speaker 1: identifying false information after using AI to identify false information.

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Speaker 1: And so these issues of offloading our cognitive capacity to

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Speaker 1: AI are probably going to have implications for the way

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Speaker 1: we think, our decision making, our problem solving, all of

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Speaker 1: those different things, which means that we really need to

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Speaker 1: be careful as we walk into this.

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Speaker 3: Yeah, exactly. And I think that's the key issue for

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Speaker 3: pastors and parents and communicators out there is to walk

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Speaker 3: in this with a real careful, you know, and a very...

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Speaker 3: open mind and concerned mind. I think sometimes, I think

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Speaker 3: it's that MIT study, I saw that it's easy for

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Speaker 3: people to forget that first word, artificial. This is an

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Speaker 3: artificial intelligence. And also, I have a tech background, so

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Speaker 3: you come out of this and you have to realize

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Speaker 3: that these engines are taught, the way these learning engines

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Speaker 3: work and the way they go through there, they're taught

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Speaker 3: by human data. And we know as Christians, That humanity

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Speaker 3: itself is flawed. And so I think it was not

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Speaker 3: been surprising to me when the studies have come out

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Speaker 3: and found that, you know, these bots or that bot

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Speaker 3: or this AI has bias in it or racism in

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Speaker 3: it or a certain hate. So we have two things

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Speaker 3: working together.

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Speaker 1: It.

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Speaker 3: First of all, it's the data off of humanity itself.

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Speaker 3: And just look at human history. We have a pretty

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Speaker 3: good or a pretty bad history for the evil we

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Speaker 3: could do to one another here, we could say. But

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Speaker 3: also it's driven, it's still programmed by people. And so

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Speaker 3: it's even unintentionally easy to program bias into it there.

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Speaker 3: And so all of those things go in. It's not

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Speaker 3: cognitive in the sense that it's actually thinking through in

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Speaker 3: context and has empathy and sympathy and other feelings that

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Speaker 3: are attached to that. It's really just processing things that

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Speaker 3: we do in our human brain. It's doing them much faster.

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Speaker 3: But it's also missing a whole lot of components of

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Speaker 3: what it means to be human.

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Speaker 2: Yeah. Yeah.

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Speaker 1: And I mean, that takes you back to the sort

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Speaker 1: of intellectual property issues. And I realize that the legal

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Speaker 1: challenges there are difficult. But one of the things I

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Speaker 1: guess I wonder what your thoughts are on this is.

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Speaker 1: When you're doing things on NRB, let's say you mentioned publishers,

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Speaker 1: new media professionals, even like TikTokers and YouTubers, radio personalities,

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Speaker 1: all of these people are using a medium to communicate

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Speaker 1: and bridge the distance between a human and a human.

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Speaker 1: In my estimation, AI increases that distance. It puts humans

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Speaker 1: one layer further away From one another, because what AI

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Speaker 1: is doing is it's to your point, it's taking a

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Speaker 1: pastor sermon, it's taking an essay or an article that

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Speaker 1: it finds online, and it's aggregating a lot of that

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Speaker 1: content and spitting out an abbreviated summary of content that's

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Speaker 1: probably already abbreviated and had, you know, a very narrow

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Speaker 1: point it was trying to make. And so how do

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Speaker 1: you think of it in terms of, you know, from

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Speaker 1: the communication perspective of what NRB does, keeping the gospel

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Speaker 1: in public? How do you think about that increased distance

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Speaker 1: between people? Do you agree with that? Or, you know,

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Speaker 1: do you have any thoughts on it?

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Speaker 3: I do agree with that. And not only is it

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Speaker 3: increasing that distance, it's increasing that distance. At the same time, again,

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Speaker 3: it's taking a major element out of that person-to-person communication.

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Speaker 3: And that's the ability of humans to contextualize a conversation, again,

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Speaker 3: with emotion and visual cues and all of those things

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Speaker 3: that go with that when we have that inner humanity.

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Speaker 3: And then just, again, that nature, that inner humanity-ness, that

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Speaker 3: thing we can't describe sometimes. Even scientists can't describe where

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Speaker 3: a thought comes from. They can tell you all the

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Speaker 3: things that are going on in the brain, but they

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Speaker 3: can't tell you you know, where that thought came from,

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Speaker 3: where that creativity started or where that. So there's that

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Speaker 3: element there that we have. And I think you're right.

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Speaker 3: It increases that distance. And at the same time, it

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Speaker 3: decreases the value of the conversation because it misses this

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Speaker 3: humanity part. Look, we chat. GTP has had several hundreds,

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Speaker 3: I think, now of lawyers across this country have been fined.

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Speaker 3: because they've used AI to do research for cases, and

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Speaker 3: ChatGP has filled out, filed briefs for them that they've

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Speaker 3: submitted with cases that didn't exist. Because, as you said,

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Speaker 3: when it aggregated, it said, well, a case like this

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Speaker 3: ought to exist, and it didn't know the difference between, well,

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Speaker 3: this case ought to exist, so I'll take all these

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Speaker 3: other cases and make one up, and it didn't know

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Speaker 3: that that was wrong. That's wrong to do that. And that's, again,

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Speaker 3: that's that element that we're missing in this that I

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Speaker 3: think you put away. I'll hit you with one more.

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Speaker 3: We did a study just this last January, and we

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Speaker 3: just started to scratch the surface on this. But we

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Speaker 3: asked people about artificial intelligence. Would you go to your

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Speaker 3: pastor or would you go to AI for a biblical answer?

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Speaker 3: And it was pretty interesting. About 15 to 20 percent

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Speaker 3: said right now, well, you probably go to AI. But

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Speaker 3: 5 percent said they trust AI over their pastor. That

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Speaker 3: should send shockwaves across this community if that's kind of

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Speaker 3: the direction we're going with this.

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Speaker 1: It's interesting to think about that. I mean, the Barna

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Speaker 1: had a similar study that they just released in July

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Speaker 1: that was showing some of this, that there's a higher

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Speaker 1: degree of trust and really usage across the board in

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Speaker 1: all different categories. I mean, it wasn't just spiritual life

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Speaker 1: sort of categories where Christians, practicing Christians in the way

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Speaker 1: that they defined it, which I believe was once a month,

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Speaker 1: attending church once a month, that they were using it

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Speaker 1: Far more frequently than anyone else across the board. Now,

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Speaker 1: why that is, they didn't answer or even attempt to answer.

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Speaker 1: And so we're kind of left wondering. But I would

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Speaker 1: say I was heartened by the idea that, you know,

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Speaker 1: you were seeing fairly high levels of Christians, anywhere between

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Speaker 1: 70 and 80 percent, concerned that AI was going to

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Speaker 1: misinterpret the Bible, concerned that it was going to replace

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Speaker 1: God or their pastor or whatever, concerned that it was

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Speaker 1: going to have people lose their faith. But I think

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Speaker 1: my just overall read is that some of this is

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Speaker 1: being cultivated by our perception of what AI is. I

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Speaker 1: think some of what you just talked about, this notion

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Speaker 1: that AI isn't a cognitive thing. It's a pattern recognition

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Speaker 1: engine that pulls different data points all together.

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Speaker 2: But it seems really smart and really intuitive. And so

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Speaker 2: it's being.

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Speaker 1: Made easy to trust, even though when you understand its limitations,

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Speaker 1: you would sit back and say, well, obviously I can't

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Speaker 1: trust it more than other things. I can trust it

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Speaker 1: for this little sliver, but I can't really trust it

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Speaker 1: to just give me the right answer every time.

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Speaker 3: Yeah, that is so true. And I think we also

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Speaker 3: have to learn more about, like you said, how AI

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Speaker 3: works because it isn't this cognitive sort of tool that

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Speaker 3: you can interact with, like our conversation here, where we

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Speaker 3: can have this conversation and flow and go. And there's,

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Speaker 3: you know, some intuition and other things that go in there.

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Speaker 3: AI is very specific. So if you ask it very

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Speaker 3: general things, it's going to give you very general answers.

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Speaker 3: And if you don't, you know, in our consumer driven

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Speaker 3: mentality these days, we're a little bit lazy about, hey,

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Speaker 3: that might be where we stop. Oh, I got the

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Speaker 3: answer I wanted. You know, so we stop there and

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Speaker 3: we don't really drive down into the deeper part of

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Speaker 3: the tool. And that's, again, I think the problem is

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Speaker 3: the more human-like, and that's the push, you hear it

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Speaker 3: from all of the top AI experts. Anthropic, ChatGDP, Alphabet's

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Speaker 3: tool on Google's side. You hear it from all of them. Gemini.

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Speaker 3: All of them. Their drive is to push, is to

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Speaker 3: make the tool more and more human-like. So it's much

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Speaker 3: more like you are interacting with a human, which is

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Speaker 3: only going to drive us to, I think, like you said,

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Speaker 3: to accept the fact that what it's doing or what

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Speaker 3: it's telling you is really good information. The more you

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Speaker 3: feel like you're talking to a person, the more you

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Speaker 3: feel like the answers you're getting are, you know, I

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Speaker 3: suddenly have access to this really brilliant college professor or

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Speaker 3: this really brilliant pastor or whoever it is. And that's

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Speaker 3: the way we walk. And I think we have to

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Speaker 3: step back and think about what it means to be human.

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Speaker 3: What's the whole question of humanity and whether or not

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Speaker 3: the guardrails that need to be put up are guardrails

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Speaker 3: about how much more human-like we make these tools.

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Speaker 1: Yeah, it's really interesting to see this shift too, I think,

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Speaker 1: because evangelicalism has generally been pretty resistant to to authoritarian

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Speaker 1: interpretations of scripture. I mean, you go all the way

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Speaker 1: back into revivalism and what you see is really a

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Speaker 1: grassroots sort of movement where lay people are reading the

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Speaker 1: scriptures for themselves. And if their pastor stood up in

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Speaker 1: the congregation and said, well, we don't believe in the supernatural,

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Speaker 1: they would go, really?

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Speaker 2: Because Jesus just performed a miracle.

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Speaker 1: And so you had this sort of resistant strain within

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Speaker 1: evangelicalism and revivalism in particular that really did help push

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Speaker 1: out some of these aberrant views. But as we watch

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Speaker 1: what's going on with AI, it feels like that concern

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Speaker 1: of replacing God in some way, shape, or form is probably,

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Speaker 1: in my mind, one of the more interesting sort of concerns.

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Speaker 1: Because what I think we're thinking about, or what I'd

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Speaker 1: be concerned that we're thinking about, is that AI has

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Speaker 1: more of an omniscient feel to it than it actually does.

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Speaker 1: And so we're not now, you know, sort of pushing

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Speaker 1: back on people who have we know have partial knowledge.

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Speaker 3: Right.

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Speaker 2: Even if I'm in the room with the smartest guy

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Speaker 2: on the planet, you know, there are limits to his knowledge.

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Speaker 2: AI doesn't necessarily feel like that.

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Speaker 1: It doesn't necessarily feel like there are limits on its

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Speaker 1: knowledge because we could ask it anything and it'll spit

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Speaker 1: back an answer. And it's a seemingly intelligible answer. And

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Speaker 1: so one of the things I usually have been counseling

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Speaker 1: people is try using AI only in a domain.

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Speaker 2: Where you have expertise.

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Speaker 1: And what you start noticing is it isn't giving you

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Speaker 1: the sort of clear, nuanced, detailed answers. It's giving you

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Speaker 1: a very small summary that is slanted, not in a

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Speaker 1: bad way necessarily, like that sort of evil bias that

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Speaker 1: we might think of, but it's certainly got an angle

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Speaker 1: to it. Because to answer your question in a succinct fashion,

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Speaker 1: it has to. And so what we're getting is a

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Speaker 1: perspective from AI, and we're allowing it to choose that

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Speaker 1: perspective and decide on what's relevant, which is scary on

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Speaker 1: the face.

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Speaker 2: Of it.

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Speaker 3: Yeah that's i think you're that last part is that

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Speaker 3: word decide what's relevant um uh you know and it

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Speaker 3: again i think it it goes back to me just

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Speaker 3: because it feels so human like you know we don't

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Speaker 3: realize that this is a tool that's running a set

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Speaker 3: of programs and routines in the background uh this is

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Speaker 3: why there's such a big push for data centers and

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Speaker 3: And the crunching here, because it has to go through

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Speaker 3: a lot of different iterations before it gets that answer

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Speaker 3: to you there. But the answers are kind of built

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Speaker 3: on our best ability to replicate the way that people think.

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Speaker 3: And so we get to this tool, and I think

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Speaker 3: that's where you rightly said we can sort of have

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Speaker 3: this almost godlike perception. That we're, again, we're talking to

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Speaker 3: the smartest person in the world or the greatest intellect.

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Speaker 3: And this thing's told me everything I want to know,

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Speaker 3: not only about maybe a certain subject, but guess what?

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Speaker 3: It can also help me figure out what to have

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Speaker 3: for dinner tonight. And so the more we feel like

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Speaker 3: we're talking to a person, I think the more, unfortunately

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Speaker 3: for us as society, we're going to keep raising the

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Speaker 3: pedestal that AI sets on. And that's something we just

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Speaker 3: have to educate people. We're helping trying to educate pastors now,

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Speaker 3: especially youth pastors, into some of the concerns. I think

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Speaker 3: you saw OpenAI talked about putting some guardrails around chat

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Speaker 3: GTP that has to do with teenagers. But we have

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Speaker 3: a clash here. And back to my time in the

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Speaker 3: business world, we have a clash here because you have

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Speaker 3: a business model And this is what got Meta in trouble.

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Speaker 3: You have a business model that's built on keeping you engaged.

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Speaker 3: The longer you're engaged, the more ROI, the more profit

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Speaker 3: that the organization is going to get, the more you

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Speaker 3: use the tool. So you have a business model that

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Speaker 3: has that on one aspect. And then on the other side,

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Speaker 3: you're trying to put guardrails in that reduce that engagement.

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Speaker 3: And I don't think we're going to have an industry

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Speaker 3: that's going to self-regulate very well when those two things

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Speaker 3: are clashing in the business world.

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Speaker 1: It's interesting to me that you like I agree with

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Speaker 1: the business point. I think there's also a legal structure issue.

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Speaker 1: You know, part of the reason that it's been so

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Speaker 1: difficult to wrangle in sort of the big tech companies,

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Speaker 1: particularly in social media, is because their platforms and we're

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Speaker 1: seeing this sort of repeat itself with artificial intelligence. Grok's

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Speaker 1: just put a lawsuit in on Minnesota maybe a month

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Speaker 1: or so ago. We're filming this kind of in the

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Speaker 1: middle of September. So I think about a month ago,

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Speaker 1: Grok put in this lawsuit to Minnesota because Minnesota was

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Speaker 1: trying to.

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Speaker 2: Hold liable the platforms.

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Speaker 1: Where I can't remember the exact phrasing, but it had

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Speaker 1: to do with child sexualization and the sexualized images of

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Speaker 1: real people. So People were using Grok to create naked

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Speaker 1: photos of children, naked photos of real human beings, and

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Speaker 1: then distribute those. And so the state of Minnesota is

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Speaker 1: trying to police the platform and saying, you have to

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Speaker 1: be liable here. Grok probably won't have standing for the

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Speaker 1: lawsuit because they put it in as sort of a

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Speaker 1: free speech issue complaint. But I think that's where we

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Speaker 1: get into these sticky problems of what are these things?

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Speaker 1: Are only the users responsible for what's being put out?

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Speaker 1: Are they really platforms? Or are these something new that

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Speaker 1: aren't exactly publishers and aren't exactly platforms that need a

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Speaker 1: different regulatory body to look at them and say, look,

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Speaker 1: if your business model is built on keeping kids engaged,

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Speaker 1: we've got a real problem here.

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Speaker 3: Yeah. Yeah. Boy, that's a big one we're kind of, because,

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Speaker 3: you know, it's the whole Section 529, you know, that

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Speaker 3: the platforms kind of, you know, exempts them from this

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Speaker 3: liability as platforms, you know, when they're supposed to be

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Speaker 3: just in the neutral role in the background. But a

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Speaker 3: lot of them aren't in the neutral role. They're really

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Speaker 3: in the editorial role, which puts them deeper into this.

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Speaker 3: So where does that? start and stop. And I think,

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Speaker 3: as you said, AI has created a whole other complexity

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Speaker 3: here for that. And that's exactly what Grok's, you know,

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Speaker 3: arguing here. And there's some similar cases out in California

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Speaker 3: as well, because AI has been used to create a

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Speaker 3: lot of these, you know, deep, fake, you know, pornographic

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Speaker 3: images of Hollywood stars and other folks, you know, that

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Speaker 3: are real people. So, you know, and try to put these,

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Speaker 3: you know, people using the tools and put these disclaimers

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Speaker 3: on them. So what's the, you know, who's responsible? What's

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Speaker 3: the issue here? How deep does the law go? And

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Speaker 3: who's protected, not protected? We're working with a number of

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Speaker 3: folks up in Congress on this, trying to figure out

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Speaker 3: and answer these questions. I think right now we're trying

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Speaker 3: to just get all the questions figured out. Like what

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Speaker 3: are all the right questions? Jurassic Park has this great line,

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Speaker 3: and I use this all the time. Jeff Goldblum's character,

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Speaker 3: after getting the whole dog and pony show on how

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Speaker 3: they used the DNA to recreate the dinosaurs, he had

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Speaker 3: this line. He said, you know, you were so concerned

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Speaker 3: about whether you could do it, you didn't stop to

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Speaker 3: think about whether you should do it. Boy, that describes

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Speaker 3: to me where we're at with AI today. You know,

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Speaker 3: we're moving forward. I don't know if recently you saw

432
00:26:31,220 --> 00:26:35,060
Speaker 3: there was a gentleman who worked at Anthropic and OpenAI,

433
00:26:35,500 --> 00:26:38,070
Speaker 3: and he came out and said, you know, this drive

434
00:26:38,850 --> 00:26:42,990
Speaker 3: for this super AI, he called it, you know, this

435
00:26:43,130 --> 00:26:46,330
Speaker 3: super AI, he said this drive for this could be

436
00:26:46,390 --> 00:26:50,950
Speaker 3: the complete destruction of humanity. I don't know, as Christians,

437
00:26:51,010 --> 00:26:54,500
Speaker 3: we believe that, but But I certainly know that we,

438
00:26:54,640 --> 00:26:57,359
Speaker 3: because we as Christians know that we come from a

439
00:26:57,560 --> 00:27:01,399
Speaker 3: sinful nature inside of us, and just look back at

440
00:27:01,480 --> 00:27:08,390
Speaker 3: the atrocities we've perpetrated on one another, wouldn't be surprised

441
00:27:08,410 --> 00:27:12,070
Speaker 3: that we would build, thinking that we're godlike, that we

442
00:27:12,090 --> 00:27:15,189
Speaker 3: could build a godlike tool that would end up pushing

443
00:27:15,230 --> 00:27:18,300
Speaker 3: those same atrocities back on us. So there's a lot

444
00:27:18,340 --> 00:27:20,439
Speaker 3: for us to think about and try to work out here.

445
00:27:21,530 --> 00:27:24,470
Speaker 1: Well, I think one of the things we could probably

446
00:27:24,510 --> 00:27:29,930
Speaker 1: get into is this notion of discipleship. What are these

447
00:27:29,990 --> 00:27:33,359
Speaker 1: technologies turning us into? And so as Christians, when we

448
00:27:33,390 --> 00:27:37,639
Speaker 1: think about civilizational devastation, right, we're thinking new heavens and

449
00:27:37,680 --> 00:27:40,820
Speaker 1: new earth. We're thinking God making all things new. What

450
00:27:40,880 --> 00:27:42,880
Speaker 1: is old is destroyed. What is new is now yet

451
00:27:42,920 --> 00:27:45,860
Speaker 1: to come. And so there's a sense in which we

452
00:27:45,920 --> 00:27:48,699
Speaker 1: probably don't need to worry about, you know.

453
00:27:48,740 --> 00:27:50,450
Speaker 2: Sort of AI destroying the planet, right?

454
00:27:51,270 --> 00:27:56,790
Speaker 1: But I think the dehumanizing element, the element of AI

455
00:27:56,830 --> 00:28:01,000
Speaker 1: that makes us something other than what God intended. is

456
00:28:01,080 --> 00:28:04,660
Speaker 1: certainly something that Christians should be considering. And so how

457
00:28:04,680 --> 00:28:07,000
Speaker 1: do you see some of these? I mean, we've been

458
00:28:07,020 --> 00:28:12,650
Speaker 1: dealing with algorithms forever, right? AI isn't exactly an algorithm,

459
00:28:12,690 --> 00:28:15,689
Speaker 1: but it has that sort of parallel structure. There are

460
00:28:15,730 --> 00:28:19,609
Speaker 1: things going on in the background that are feeding us information,

461
00:28:19,650 --> 00:28:22,540
Speaker 1: that are guiding our thought process, that are showing us

462
00:28:22,710 --> 00:28:28,110
Speaker 1: new things, and we don't understand what those are. We're

463
00:28:28,130 --> 00:28:30,450
Speaker 1: completely blind to them in general. Most of us don't

464
00:28:30,470 --> 00:28:33,150
Speaker 1: understand how they work. You know, I sort of have

465
00:28:33,190 --> 00:28:35,690
Speaker 1: a vague clue about what's going on there, but I

466
00:28:35,710 --> 00:28:38,270
Speaker 1: couldn't tell you how they do it. So how do

467
00:28:38,310 --> 00:28:41,310
Speaker 1: you see some of these things sort of changing us

468
00:28:41,410 --> 00:28:44,870
Speaker 1: more fundamentally? We've talked a little bit about these AIs

469
00:28:44,930 --> 00:28:48,110
Speaker 1: becoming more human. I'm wondering if you think, you know,

470
00:28:48,130 --> 00:28:50,390
Speaker 1: we're being discipled and becoming more like AIs.

471
00:28:53,100 --> 00:28:55,760
Speaker 3: Look, I definitely think that's a path we could end

472
00:28:55,880 --> 00:28:59,920
Speaker 3: up on. I don't think we're there yet. I think

473
00:29:00,000 --> 00:29:04,420
Speaker 3: the problem that we have today is, I'm just going

474
00:29:04,440 --> 00:29:08,620
Speaker 3: to say it and look at the scriptures talk about it. Again,

475
00:29:08,660 --> 00:29:12,280
Speaker 3: our consumer-driven attitude is kind of behind that there's a

476
00:29:12,340 --> 00:29:15,660
Speaker 3: lot of us are just lazy and we want the

477
00:29:15,820 --> 00:29:19,320
Speaker 3: easy path. And even in discipleship, I mean, it's something

478
00:29:19,360 --> 00:29:21,670
Speaker 3: we've dealt with, the church has dealt with for a

479
00:29:21,710 --> 00:29:24,080
Speaker 3: long time. How do we disciple people? What does it

480
00:29:24,120 --> 00:29:29,020
Speaker 3: mean to disciple? But the Bible is the foundation of

481
00:29:29,580 --> 00:29:36,489
Speaker 3: human flourishing. Anywhere where you take Scripture out, Christianity out,

482
00:29:37,270 --> 00:29:41,480
Speaker 3: you've really seen human destruction at its worst. And where

483
00:29:41,580 --> 00:29:47,260
Speaker 3: Christianity is and the Bible is, you've seen human flourishing sometimes,

484
00:29:47,320 --> 00:29:49,820
Speaker 3: I think, at its best, at the best it can

485
00:29:49,880 --> 00:29:53,770
Speaker 3: be in this even sinful nature world we live in

486
00:29:53,810 --> 00:29:57,550
Speaker 3: in humanity. And if you take that out and you

487
00:29:57,590 --> 00:30:05,030
Speaker 3: start to be discipled by an artificial human kind of intelligence,

488
00:30:05,830 --> 00:30:08,209
Speaker 3: how much of that humanity is going to come out

489
00:30:08,250 --> 00:30:09,810
Speaker 3: of that? How much are we going to end up

490
00:30:09,870 --> 00:30:17,180
Speaker 3: with the Spock-like attitude of logic that drives everything in there?

491
00:30:17,200 --> 00:30:21,960
Speaker 3: And there's no emotion, no feeling, no joy, no happiness

492
00:30:23,540 --> 00:30:28,400
Speaker 3: that's behind this. And I think that's a real... going

493
00:30:28,420 --> 00:30:31,220
Speaker 3: to be a real challenge going forward and then what

494
00:30:31,260 --> 00:30:34,640
Speaker 3: happens look we're talking about this one what happens when

495
00:30:34,680 --> 00:30:38,780
Speaker 3: you're you're you get your own personal ai bot and

496
00:30:38,840 --> 00:30:42,790
Speaker 3: especially during the adolescent teen years and this becomes your

497
00:30:42,870 --> 00:30:46,670
Speaker 3: new best friend this is the person you the thing

498
00:30:46,690 --> 00:30:50,350
Speaker 3: you confide in and the thing you believe because it's

499
00:30:50,450 --> 00:30:56,160
Speaker 3: built in this reaffirming reassuring kind of built to always

500
00:30:56,300 --> 00:31:00,240
Speaker 3: be that kind of really good companion there. That's what

501
00:31:00,280 --> 00:31:03,130
Speaker 3: happened on ChatGPT. That's why it moved so many of

502
00:31:03,160 --> 00:31:06,290
Speaker 3: these kids into suicide, because it was built to always

503
00:31:06,410 --> 00:31:09,850
Speaker 3: be reaffirming, and it didn't know the difference between life

504
00:31:09,930 --> 00:31:12,970
Speaker 3: and death coming down to the end. And I think

505
00:31:13,110 --> 00:31:15,920
Speaker 3: that's a big question we have to answer and ask

506
00:31:15,980 --> 00:31:19,820
Speaker 3: ourselves about where AI is going and where it intersects humanity.

507
00:31:21,270 --> 00:31:24,930
Speaker 1: There's this interesting theory that was advanced in the New

508
00:31:24,970 --> 00:31:27,390
Speaker 1: England Journal of Medicine by a gentleman, I'm blanking on

509
00:31:27,430 --> 00:31:29,590
Speaker 1: his name right now, but he talks about it in

510
00:31:29,670 --> 00:31:32,170
Speaker 1: terms of addiction. And he basically says that as people

511
00:31:32,190 --> 00:31:35,550
Speaker 1: get addicted, part of what happens is their social world narrows.

512
00:31:36,450 --> 00:31:39,130
Speaker 1: And so if I want to get drugs, I'm going

513
00:31:39,150 --> 00:31:40,920
Speaker 1: to stop hanging out with people who are telling me

514
00:31:40,960 --> 00:31:43,080
Speaker 1: that I shouldn't do drugs because that's annoying. All I

515
00:31:43,100 --> 00:31:44,840
Speaker 1: want to do is get drugs. And so eventually you

516
00:31:44,860 --> 00:31:47,660
Speaker 1: get down to this point where You're really only interfacing

517
00:31:47,680 --> 00:31:49,850
Speaker 1: with the people who are going to help you get drugs,

518
00:31:49,930 --> 00:31:52,710
Speaker 1: going to firm you getting drugs, all those kind of ideas.

519
00:31:53,510 --> 00:31:56,270
Speaker 1: And I think that AI has the potential to create

520
00:31:56,310 --> 00:32:00,060
Speaker 1: that sort of narrowness. I mean, leave the addiction aspect aside.

521
00:32:00,930 --> 00:32:04,540
Speaker 1: When we aren't participating in the world apart from AI,

522
00:32:04,840 --> 00:32:06,720
Speaker 1: and that doesn't mean that we're sitting in our basements

523
00:32:06,760 --> 00:32:10,180
Speaker 1: just playing around with Claude or ChatGPT or whatever. What

524
00:32:10,220 --> 00:32:14,010
Speaker 1: it could mean is as we engage in more augmented

525
00:32:14,090 --> 00:32:18,510
Speaker 1: reality frameworks, where we're having Google glasses and it's showing

526
00:32:18,550 --> 00:32:21,070
Speaker 1: us different things about the world and it's giving us facts.

527
00:32:20,850 --> 00:32:21,470
Speaker 2: About the world.

528
00:32:21,590 --> 00:32:25,969
Speaker 1: These are now filters that we're putting on across reality

529
00:32:26,550 --> 00:32:29,550
Speaker 1: that are influencing the way we see the world and

530
00:32:29,910 --> 00:32:33,790
Speaker 1: thus narrowing what we understand about the world. They almost

531
00:32:33,870 --> 00:32:37,190
Speaker 1: preclude exploration, right? If AI is just going to tell

532
00:32:37,230 --> 00:32:38,790
Speaker 1: me this is an elm tree, I don't really need

533
00:32:38,810 --> 00:32:40,890
Speaker 1: to go over and look at it. There doesn't need

534
00:32:40,910 --> 00:32:43,070
Speaker 1: to be any curiosity about it. I just know now

535
00:32:43,130 --> 00:32:45,290
Speaker 1: it's an elm tree and that's great. And so I

536
00:32:45,350 --> 00:32:49,630
Speaker 1: think there's a real problem there from that narrowing angle.

537
00:32:50,370 --> 00:32:54,010
Speaker 1: Whereas when we talk about discipleship, usually what we're talking

538
00:32:54,050 --> 00:32:59,510
Speaker 1: about is a broadening of perspective, a broadening of perspective

539
00:32:59,610 --> 00:33:04,570
Speaker 1: with God's self-disclosure opening the world up to us and

540
00:33:04,630 --> 00:33:06,770
Speaker 1: allowing us to see it for what it really is.

541
00:33:08,490 --> 00:33:12,200
Speaker 3: Yeah. And look, Christians have always driven discipleship. you know,

542
00:33:12,240 --> 00:33:14,970
Speaker 3: kind of discovery and innovation. You go back and look

543
00:33:14,990 --> 00:33:17,930
Speaker 3: at how many Christians drove this, and they drove it,

544
00:33:17,970 --> 00:33:21,170
Speaker 3: you know, from two aspects. Again, there was always this

545
00:33:21,270 --> 00:33:25,100
Speaker 3: underlying push from what we think of as the Old

546
00:33:25,150 --> 00:33:29,380
Speaker 3: Testament scriptures into the New Testament of this idea of

547
00:33:29,460 --> 00:33:33,220
Speaker 3: human flourishing. How do we make life better for people?

548
00:33:33,320 --> 00:33:35,520
Speaker 3: I came that you might have life and have it

549
00:33:35,560 --> 00:33:38,770
Speaker 3: more abundantly. You know, how do we push that? How

550
00:33:38,790 --> 00:33:41,840
Speaker 3: do we help? That's why Christians drove medical research and

551
00:33:42,280 --> 00:33:45,700
Speaker 3: education and all these things that were meant to help humans,

552
00:33:46,420 --> 00:33:49,820
Speaker 3: you know, live better lives to flourish in there. And

553
00:33:49,860 --> 00:33:51,740
Speaker 3: that was a lot of that, as you said, was

554
00:33:52,020 --> 00:33:56,900
Speaker 3: driven out of not only curiosity, but out of, you know, necessity, right?

555
00:33:56,940 --> 00:34:01,990
Speaker 3: The mother of all invention and pushing those envelopes forward

556
00:34:02,050 --> 00:34:05,410
Speaker 3: and exploring that. And then there was the other side

557
00:34:05,430 --> 00:34:08,030
Speaker 3: of it on the scientific side where a lot of

558
00:34:08,070 --> 00:34:12,049
Speaker 3: scientists knew that this world was created by God, God

559
00:34:12,070 --> 00:34:15,100
Speaker 3: the creator. And so it had order and meaning to it.

560
00:34:15,100 --> 00:34:18,640
Speaker 3: And let's discover that order. Let's discover that meaning. Let's

561
00:34:18,680 --> 00:34:24,540
Speaker 3: keep diving deeper into these issues. If AI can replace,

562
00:34:24,700 --> 00:34:27,419
Speaker 3: all of a sudden replace that, and as you said,

563
00:34:27,520 --> 00:34:31,759
Speaker 3: take away that That drive, again, get us back to

564
00:34:31,800 --> 00:34:34,440
Speaker 3: the easy consumer-driven, oh, that's an elm tree. I don't

565
00:34:34,460 --> 00:34:37,480
Speaker 3: need to go look at that or this plant is

566
00:34:37,540 --> 00:34:40,140
Speaker 3: this or this does that. The kind of thing that

567
00:34:40,200 --> 00:34:44,640
Speaker 3: we always have, this answer's right there in our pocket

568
00:34:44,680 --> 00:34:47,590
Speaker 3: with our phone is right there in a second. I

569
00:34:47,730 --> 00:34:51,710
Speaker 3: do think that that is going to be more detrimental

570
00:34:51,790 --> 00:34:55,190
Speaker 3: on humanity than it is going to be pushing this

571
00:34:55,430 --> 00:34:59,700
Speaker 3: human flourishing. And I think it's sort of going to

572
00:34:59,760 --> 00:35:04,270
Speaker 3: dumb down humanity rather than make humanity more intelligent. You know,

573
00:35:04,290 --> 00:35:07,649
Speaker 3: when I was in the Navy, you go through engineering school, right?

574
00:35:08,250 --> 00:35:11,170
Speaker 3: And one of the things they make you learn is

575
00:35:11,190 --> 00:35:14,130
Speaker 3: you have to learn the formulas and the principles and things,

576
00:35:14,570 --> 00:35:18,189
Speaker 3: how to do those without the calculator. You know, learn

577
00:35:18,230 --> 00:35:22,239
Speaker 3: to do it first, learn the foundation and understand the foundation.

578
00:35:22,280 --> 00:35:25,120
Speaker 3: And then you can use the tools that make it

579
00:35:25,160 --> 00:35:27,799
Speaker 3: more efficient and automated. But you have to have that

580
00:35:27,880 --> 00:35:33,600
Speaker 3: foundation first. What happens when we lose that foundation or

581
00:35:33,840 --> 00:35:37,390
Speaker 3: we outsource that? That's another thing we're good at. We

582
00:35:37,630 --> 00:35:44,890
Speaker 3: outsource that foundation to artificial intelligence there. So just like

583
00:35:44,930 --> 00:35:48,589
Speaker 3: you said, this conversation, there's a lot of questions that

584
00:35:48,630 --> 00:35:51,860
Speaker 3: we have to have, and we have to have these conversations.

585
00:35:52,540 --> 00:35:59,250
Speaker 3: And pastors... And church leaders and Christian colleges and professors,

586
00:35:59,350 --> 00:36:04,510
Speaker 3: church intellects, Christian intellects need to be involved in these

587
00:36:04,590 --> 00:36:10,160
Speaker 3: conversations and not, as you said earlier, sometimes in Christianity,

588
00:36:10,219 --> 00:36:15,840
Speaker 3: we have looked at the bad side of technology and

589
00:36:15,900 --> 00:36:18,940
Speaker 3: then condemned it and not got involved. AI is here.

590
00:36:18,960 --> 00:36:20,630
Speaker 3: One of the things I tell if it is here

591
00:36:20,730 --> 00:36:24,090
Speaker 3: is not going away. It's only going to keep on growing.

592
00:36:24,890 --> 00:36:29,169
Speaker 3: And if we're not involved in the conversation, it very

593
00:36:29,250 --> 00:36:32,080
Speaker 3: quickly could go in the wrong direction as far as

594
00:36:32,120 --> 00:36:34,700
Speaker 3: the church is concerned, as far as humanity is concerned.

595
00:36:34,719 --> 00:36:37,719
Speaker 1: You know, one of the things I'd be interested to

596
00:36:37,820 --> 00:36:40,279
Speaker 1: just hear your take on, and I know this is

597
00:36:40,300 --> 00:36:43,190
Speaker 1: a little far afield from the interview, so hopefully it's

598
00:36:43,210 --> 00:36:47,390
Speaker 1: not too much of a curveball, but, you know, You

599
00:36:47,410 --> 00:36:49,169
Speaker 1: have these sort of, I used to work at Moody

600
00:36:49,190 --> 00:36:52,250
Speaker 1: Bible Institute, so I'm familiar enough with how radio works

601
00:36:52,290 --> 00:36:54,799
Speaker 1: and you have radio stations and you have repeater signals

602
00:36:54,840 --> 00:36:55,819
Speaker 1: and all these kinds of things and.

603
00:36:55,820 --> 00:36:56,700
Speaker 2: All that costs.

604
00:36:57,360 --> 00:37:01,420
Speaker 1: And so when you're looking at that infrastructure, you're calculating, okay,

605
00:37:01,480 --> 00:37:02,300
Speaker 1: what's our reach?

606
00:37:02,380 --> 00:37:04,440
Speaker 2: What are we going to get back in donations? You know,

607
00:37:04,820 --> 00:37:05,779
Speaker 2: is this missional?

608
00:37:05,820 --> 00:37:08,359
Speaker 1: Like you have a whole calculus that you're doing here

609
00:37:08,900 --> 00:37:12,950
Speaker 1: that's saying we want to do X, we need infrastructure Y,

610
00:37:13,420 --> 00:37:16,900
Speaker 1: does that wash? You know, there's a real calculation there.

611
00:37:17,330 --> 00:37:20,150
Speaker 1: Same with book publishing, right? We love this book, but

612
00:37:20,170 --> 00:37:22,750
Speaker 1: we think it's going to sell two copies. We're probably

613
00:37:22,790 --> 00:37:25,430
Speaker 1: not going to publish it. You know, we like this book.

614
00:37:25,489 --> 00:37:26,830
Speaker 1: It's going to sell 40,000 copies.

615
00:37:26,870 --> 00:37:27,529
Speaker 2: Yeah, we can do that.

616
00:37:27,989 --> 00:37:31,570
Speaker 1: Like there's always these sort of space limitations or physical

617
00:37:31,610 --> 00:37:35,549
Speaker 1: limitations that are being taken into account. I think part

618
00:37:35,590 --> 00:37:38,750
Speaker 1: of what we're seeing with artificial intelligence is there is

619
00:37:38,830 --> 00:37:42,509
Speaker 1: no apparent limitation. And what I mean by that is

620
00:37:42,570 --> 00:37:46,430
Speaker 1: that we don't really see it. And so as we

621
00:37:46,489 --> 00:37:51,410
Speaker 1: talk about the ethics of artificial intelligence, we also probably

622
00:37:51,450 --> 00:37:57,200
Speaker 1: need to think about the ethics of physical infrastructure that

623
00:37:57,300 --> 00:38:03,320
Speaker 1: needs to be built, energy capacities, actual physical real world

624
00:38:03,420 --> 00:38:08,140
Speaker 1: sort of production modes that are powering all of this stuff.

625
00:38:08,960 --> 00:38:12,359
Speaker 1: But it does not seem like anybody particularly cares about

626
00:38:12,400 --> 00:38:14,419
Speaker 1: that in the same way that you might care about

627
00:38:14,760 --> 00:38:18,920
Speaker 1: buying another radio station have do you have any thoughts

628
00:38:18,980 --> 00:38:20,589
Speaker 1: on that it's just one of those things where i've

629
00:38:20,820 --> 00:38:23,190
Speaker 1: sort of been puzzling over it a bit why this

630
00:38:23,270 --> 00:38:24,590
Speaker 1: isn't a bigger.

631
00:38:24,430 --> 00:38:27,669
Speaker 3: Issue i i think it's starting to become a bigger

632
00:38:27,750 --> 00:38:29,890
Speaker 3: issue i know just you know i'm here in nashville

633
00:38:29,930 --> 00:38:32,989
Speaker 3: tennessee just north of us uh in the county just

634
00:38:33,050 --> 00:38:36,509
Speaker 3: across the line in kentucky uh right now there's a

635
00:38:36,930 --> 00:38:42,489
Speaker 3: big community uh um opposition to data centers that are

636
00:38:42,530 --> 00:38:45,390
Speaker 3: going to be built in that community because of, as

637
00:38:45,430 --> 00:38:49,710
Speaker 3: you said, electric consumption and water consumption and what does

638
00:38:49,770 --> 00:38:54,430
Speaker 3: it mean for the area and contaminants and all that.

639
00:38:54,830 --> 00:38:59,239
Speaker 3: I think that's just starting to be thought about. But look,

640
00:38:59,320 --> 00:39:05,000
Speaker 3: that's the history kind of manufacturing. We often think about

641
00:39:05,020 --> 00:39:10,590
Speaker 3: the the upside of things and not necessarily the downside

642
00:39:10,630 --> 00:39:14,050
Speaker 3: of things until it's sometimes too late and we've contaminated

643
00:39:14,070 --> 00:39:18,270
Speaker 3: an entire river or lost millions of acres of, you know, farmland,

644
00:39:18,330 --> 00:39:24,130
Speaker 3: productive farmland and such, and we do that. But, yeah,

645
00:39:24,330 --> 00:39:26,770
Speaker 3: that's a discussion. I think we're going to start to

646
00:39:26,830 --> 00:39:29,330
Speaker 3: see more of that. I actually think on the ballot

647
00:39:29,410 --> 00:39:34,259
Speaker 3: this fall, there are, in several states, there are initiatives

648
00:39:34,360 --> 00:39:39,180
Speaker 3: on the ballot that would curve the data center deployments

649
00:39:39,239 --> 00:39:44,490
Speaker 3: within different areas. But let's back up a second. AI

650
00:39:44,570 --> 00:39:49,270
Speaker 3: is not a U.S.-centric technology. tool. This is now also

651
00:39:49,410 --> 00:39:53,490
Speaker 3: a tool that governments are looking at and other entities

652
00:39:53,550 --> 00:39:57,950
Speaker 3: are looking at, and the dominance in this area could

653
00:39:58,010 --> 00:40:01,989
Speaker 3: change both the economic, social, and as we said, religious

654
00:40:02,090 --> 00:40:06,140
Speaker 3: face of the world. And so it's not something we

655
00:40:06,180 --> 00:40:08,799
Speaker 3: can sort of just look at the protectionism here in

656
00:40:08,820 --> 00:40:11,800
Speaker 3: the U.S. We will have to figure out how to

657
00:40:11,880 --> 00:40:16,520
Speaker 3: look at this from a global aspect as well. It's

658
00:40:16,560 --> 00:40:17,479
Speaker 3: going to be a tough call.

659
00:40:18,660 --> 00:40:19,450
Speaker 2: Yeah, I just find it.

660
00:40:19,739 --> 00:40:23,160
Speaker 1: I find it interesting that so much of this is

661
00:40:23,400 --> 00:40:25,759
Speaker 1: it's assumed that we should do it to your point,

662
00:40:25,800 --> 00:40:29,180
Speaker 1: the Jeff Goldblum quote, right? It feels like we're stuck

663
00:40:29,219 --> 00:40:30,980
Speaker 1: in what Jockey Law called the.

664
00:40:30,920 --> 00:40:32,560
Speaker 2: Technical imperative, right?

665
00:40:32,600 --> 00:40:34,980
Speaker 1: We're just being sort of pushed along by this current

666
00:40:35,000 --> 00:40:38,280
Speaker 1: and we're not really thinking about do I really need

667
00:40:38,360 --> 00:40:41,700
Speaker 1: this strange video of my baby dancing to some song?

668
00:40:42,370 --> 00:40:45,570
Speaker 1: that's taking up power and resources to produce. Now, I

669
00:40:45,590 --> 00:40:47,640
Speaker 1: don't know how much it's taking up. That's part of

670
00:40:47,660 --> 00:40:51,020
Speaker 1: the problem. You never know how much is being taken up.

671
00:40:52,400 --> 00:40:55,980
Speaker 1: And so it feels like there's space here for an

672
00:40:56,160 --> 00:40:59,029
Speaker 1: audit of some sort to sit back and say, what

673
00:40:59,070 --> 00:41:01,460
Speaker 1: are the really essential things that are going on with AI?

674
00:41:01,610 --> 00:41:04,750
Speaker 1: I just had a gentleman named Marcus Schwarting on, and

675
00:41:04,790 --> 00:41:09,129
Speaker 1: he's an AI researcher at SUNY. And he's doing some

676
00:41:09,170 --> 00:41:13,219
Speaker 1: really interesting stuff that isn't related to LLMs at all.

677
00:41:13,500 --> 00:41:15,860
Speaker 1: It's related to AI, but not LLMs. And so you

678
00:41:15,880 --> 00:41:18,140
Speaker 1: sit back and you say, well, there's some interesting research

679
00:41:18,180 --> 00:41:21,319
Speaker 1: going on. It's probably necessary and helpful, but it has

680
00:41:21,360 --> 00:41:24,700
Speaker 1: nothing to do with Claude or ChatGPT or Grok or

681
00:41:24,760 --> 00:41:29,049
Speaker 1: anything like that. Like these systems are sort of adjacent

682
00:41:29,110 --> 00:41:31,930
Speaker 1: to each other and they're all being largely run by,

683
00:41:32,270 --> 00:41:35,950
Speaker 1: you know, specific companies. But the question of do we

684
00:41:36,110 --> 00:41:38,469
Speaker 1: need it? We're not really asking that.

685
00:41:40,340 --> 00:41:45,890
Speaker 3: Yeah, we're not asking that. And if we do need it,

686
00:41:46,440 --> 00:41:49,480
Speaker 3: you know, just exactly how do we need it and

687
00:41:50,000 --> 00:41:55,830
Speaker 3: what are the, you know, payoffs? What are the things

688
00:41:55,850 --> 00:42:00,469
Speaker 3: that we're compromising in order to have that there? I

689
00:42:00,489 --> 00:42:03,469
Speaker 3: feel like we live in a world today where, you know,

690
00:42:03,510 --> 00:42:09,120
Speaker 3: we're already so full of distractions. Right. It's the problem

691
00:42:09,140 --> 00:42:11,799
Speaker 3: with media. Right. Media can be a great tool and

692
00:42:11,820 --> 00:42:17,080
Speaker 3: do a number of great things. But the overconsumption of media,

693
00:42:17,140 --> 00:42:21,830
Speaker 3: the overdependence upon media, the fact that we can become

694
00:42:21,870 --> 00:42:27,110
Speaker 3: addicted to media and and and, you know, already today,

695
00:42:27,130 --> 00:42:33,210
Speaker 3: you kind of disconnect ourselves from reality there. is something

696
00:42:33,270 --> 00:42:35,870
Speaker 3: we have to get back to, but we, we have to,

697
00:42:35,930 --> 00:42:39,149
Speaker 3: I think for us as Christians and particularly we talk

698
00:42:39,190 --> 00:42:43,029
Speaker 3: about this Christian communicators, you know, it's, it's sort of

699
00:42:43,469 --> 00:42:47,520
Speaker 3: getting back to the, to, to the, um, uh, uh,

700
00:42:47,640 --> 00:42:49,660
Speaker 3: darn it. I lost my train of thought there on

701
00:42:49,680 --> 00:42:53,379
Speaker 3: the football, you know, uh, um, for the green Bay

702
00:42:53,420 --> 00:42:56,100
Speaker 3: Packers and, you know, this, this is going to get

703
00:42:56,180 --> 00:42:58,980
Speaker 3: back to the basics. This is a football. Um, we,

704
00:42:59,020 --> 00:43:01,990
Speaker 3: we have to get back to the basics of, for

705
00:43:02,140 --> 00:43:04,399
Speaker 3: us of what does it mean for us to hold

706
00:43:04,440 --> 00:43:10,180
Speaker 3: a biblical worldview first and foremost? What does it mean

707
00:43:10,219 --> 00:43:12,580
Speaker 3: for us to be created in the image of God?

708
00:43:12,660 --> 00:43:15,660
Speaker 3: How does that separate from anything that humanity is going

709
00:43:15,680 --> 00:43:21,980
Speaker 3: to create, including artificial intelligence or artificial humanity? And how

710
00:43:22,020 --> 00:43:25,710
Speaker 3: do we help make sure that the church is stays

711
00:43:25,890 --> 00:43:30,470
Speaker 3: grounded on that solid foundation, the foundation of the gospel,

712
00:43:30,489 --> 00:43:34,109
Speaker 3: the foundation of Christ, the foundation of the principles that

713
00:43:34,170 --> 00:43:38,710
Speaker 3: God gave us, so that they're equipped the best they

714
00:43:38,770 --> 00:43:42,810
Speaker 3: can to deal with these issues in this ever-moving landscape

715
00:43:42,850 --> 00:43:47,260
Speaker 3: of artificial intelligence going forward. That's, I think, the number

716
00:43:47,360 --> 00:43:51,739
Speaker 3: one challenge for us as the church and Christian communicators.

717
00:43:52,300 --> 00:43:57,030
Speaker 1: Would you say that's partly why Media matters more now

718
00:43:57,469 --> 00:44:00,950
Speaker 1: in this sort of Christian media specifically matters more now

719
00:44:01,030 --> 00:44:04,569
Speaker 1: in this era of information overload. I mean, I would

720
00:44:04,610 --> 00:44:08,130
Speaker 1: almost sharpen that and say something like more analog forms

721
00:44:08,250 --> 00:44:13,680
Speaker 1: like radio, like book publishing, as opposed to Christian media

722
00:44:13,719 --> 00:44:18,360
Speaker 1: that is YouTube, TikTok, even podcasting. Because they can be

723
00:44:18,420 --> 00:44:21,320
Speaker 1: captured back in by AI, we're almost feeding the beast.

724
00:44:22,040 --> 00:44:27,360
Speaker 1: But radio and publishing... don't exactly. So yeah, just your

725
00:44:27,380 --> 00:44:28,020
Speaker 1: thoughts on that.

726
00:44:28,719 --> 00:44:31,520
Speaker 3: Well, no, absolutely. I think I'm more of an analog

727
00:44:31,560 --> 00:44:36,719
Speaker 3: approach of radio, of actual physical hard book publishing. But

728
00:44:36,880 --> 00:44:39,970
Speaker 3: I also think one of the things I'm worried about

729
00:44:40,050 --> 00:44:43,549
Speaker 3: in this virtual world, but also not neglecting the fellowship

730
00:44:43,690 --> 00:44:47,270
Speaker 3: of one another and getting together and actually having a

731
00:44:48,290 --> 00:44:51,910
Speaker 3: Bible study with, as God said, I gave to the

732
00:44:51,969 --> 00:44:57,410
Speaker 3: church pastors and evangelists and teachers, and having that study

733
00:44:57,510 --> 00:45:01,850
Speaker 3: where you're actually in the room with people, and you're

734
00:45:02,430 --> 00:45:05,670
Speaker 3: learning from somebody who God has equipped to do this,

735
00:45:06,340 --> 00:45:08,820
Speaker 3: and you're interacting with the other people in the room

736
00:45:09,260 --> 00:45:12,380
Speaker 3: in a way that you can only do, humanity can

737
00:45:12,420 --> 00:45:14,200
Speaker 3: only do when you're in a room full of people.

738
00:45:14,840 --> 00:45:17,859
Speaker 3: And so I do think those different analog, as you

739
00:45:17,880 --> 00:45:21,460
Speaker 3: put them, approaches are going to be important. And that

740
00:45:21,520 --> 00:45:27,500
Speaker 3: doesn't mean as a church that we're rejecting AI, but

741
00:45:27,520 --> 00:45:30,520
Speaker 3: it means we're holding to the foundation and looking at

742
00:45:30,700 --> 00:45:34,359
Speaker 3: AI what it is. It's an artificial tool created by

743
00:45:34,420 --> 00:45:37,840
Speaker 3: man and should be always thought of as such.

744
00:45:39,020 --> 00:45:43,160
Speaker 1: Yeah, I mean, to your football analogy, right? You can

745
00:45:43,200 --> 00:45:46,180
Speaker 1: have all the stats and figures, all the data synthesized

746
00:45:46,200 --> 00:45:48,620
Speaker 1: and everything. But if your quarterback goes out there and

747
00:45:48,660 --> 00:45:50,250
Speaker 1: looks at the football and says, what's this?

748
00:45:50,290 --> 00:45:50,890
Speaker 2: You're in trouble.

749
00:45:51,570 --> 00:45:55,230
Speaker 1: And so you've got to have that sort of grounding there,

750
00:45:55,530 --> 00:45:58,810
Speaker 1: that back to the basic sort of notion that the

751
00:45:58,850 --> 00:46:03,629
Speaker 1: church is an embodied entity. And that means we have

752
00:46:03,670 --> 00:46:06,969
Speaker 1: to be embodied together at some point. It can't all

753
00:46:07,030 --> 00:46:10,279
Speaker 1: just be in the ether. We can have it in

754
00:46:10,320 --> 00:46:14,690
Speaker 1: the ether. to some degree, but you can't dismiss the

755
00:46:14,730 --> 00:46:17,489
Speaker 1: embodied witness of what the church is.

756
00:46:19,070 --> 00:46:21,330
Speaker 2: Really helpful. Yeah, really helpful.

757
00:46:21,989 --> 00:46:25,790
Speaker 1: I'll throw you out last question and we'll close it

758
00:46:25,850 --> 00:46:28,330
Speaker 1: out here. But, you know, when you think about what

759
00:46:28,450 --> 00:46:34,500
Speaker 1: NRB is doing in the next 82 years, you know,

760
00:46:34,940 --> 00:46:38,160
Speaker 1: what do you what do you see coming forward as

761
00:46:39,290 --> 00:46:45,210
Speaker 1: maybe in the next generation of Christian broadcasting, religious broadcasting

762
00:46:45,290 --> 00:46:46,330
Speaker 1: that you're excited about?

763
00:46:47,690 --> 00:46:50,420
Speaker 3: You know, one of the things that we're interested in,

764
00:46:50,430 --> 00:46:52,360
Speaker 3: we've had this discussion on AI and stuff, but one

765
00:46:52,400 --> 00:46:55,320
Speaker 3: of the statistics we didn't toss out and talk about,

766
00:46:55,360 --> 00:46:58,300
Speaker 3: and it kind of goes with this, is the interesting

767
00:46:58,320 --> 00:47:01,739
Speaker 3: thing is the generation, at least what I've read now,

768
00:47:02,239 --> 00:47:06,400
Speaker 3: that is more skeptical and also kind of rejecting AI,

769
00:47:07,140 --> 00:47:12,239
Speaker 3: are the Gen Zs and the Alphas. Because it's not

770
00:47:12,300 --> 00:47:14,200
Speaker 3: for some of the reasons we've talked about, but they're

771
00:47:14,219 --> 00:47:17,040
Speaker 3: looking at it as, you know, as tools that are

772
00:47:17,080 --> 00:47:19,580
Speaker 3: going to replace their jobs and not see the American

773
00:47:19,640 --> 00:47:22,450
Speaker 3: way and not be able to see. And there's, you know,

774
00:47:22,489 --> 00:47:27,410
Speaker 3: there's kind of that skepticism out there. I'm excited because, look,

775
00:47:27,450 --> 00:47:32,290
Speaker 3: we live in the greatest time of human communications that's

776
00:47:32,370 --> 00:47:35,350
Speaker 3: really ever existed. I mean, we have, these cell phones

777
00:47:35,390 --> 00:47:38,370
Speaker 3: in our pockets and we can communicate around the globe,

778
00:47:38,390 --> 00:47:43,089
Speaker 3: you know, practically instantly there. And that, again, that gives

779
00:47:43,150 --> 00:47:46,170
Speaker 3: us a lot of tools and things at hand. Christians

780
00:47:46,250 --> 00:47:49,960
Speaker 3: have always been, you know, some of the leaders in

781
00:47:50,020 --> 00:47:52,580
Speaker 3: taking these tools and figuring out ways that they really

782
00:47:52,820 --> 00:47:57,339
Speaker 3: do can help the gospel and help human flourishing. I'm

783
00:47:57,440 --> 00:48:01,140
Speaker 3: confident that God is going to raise up leaders in

784
00:48:01,160 --> 00:48:04,920
Speaker 3: the next, some of the giants that we've had in

785
00:48:04,940 --> 00:48:08,219
Speaker 3: the past who are going to help navigate through these

786
00:48:08,260 --> 00:48:10,580
Speaker 3: things so that the gospel can move forward. And some

787
00:48:10,600 --> 00:48:14,200
Speaker 3: of the innovations that young kids are doing, I read

788
00:48:14,260 --> 00:48:17,660
Speaker 3: recently about a young man who was just on the

789
00:48:18,080 --> 00:48:21,989
Speaker 3: Xbox platform, and he, with all these guys he was

790
00:48:22,050 --> 00:48:25,969
Speaker 3: gaming with, he started a Bible study. And it started

791
00:48:26,010 --> 00:48:28,910
Speaker 3: off with about eight or nine guys, and now it's

792
00:48:28,989 --> 00:48:33,509
Speaker 3: well over 200. And I know it's virtual, but it's

793
00:48:33,550 --> 00:48:37,490
Speaker 3: an actual, they're actually talking to each other. But it's

794
00:48:37,530 --> 00:48:41,859
Speaker 3: a real Bible study. So I'm just excited and know

795
00:48:41,880 --> 00:48:44,839
Speaker 3: that we're going to move forward and Christian communicators are

796
00:48:45,120 --> 00:48:47,759
Speaker 3: going to, I think, lead the way to help see

797
00:48:47,820 --> 00:48:50,060
Speaker 3: how some of these tools can keep the gospel in

798
00:48:50,080 --> 00:48:54,000
Speaker 3: the public space and help humanity remain humanity.

799
00:48:55,000 --> 00:48:55,520
Speaker 2: Very cool.

800
00:48:56,390 --> 00:48:58,989
Speaker 1: Well, anywhere that we can route listeners to get more

801
00:48:59,030 --> 00:49:00,930
Speaker 1: information about NRB or about you?

802
00:49:01,890 --> 00:49:05,989
Speaker 3: Yeah, nrb.org is our main website. You can find out

803
00:49:06,150 --> 00:49:10,090
Speaker 3: all of these things we're doing, talking about AI, talking

804
00:49:10,130 --> 00:49:12,810
Speaker 3: about a number of things that go on up in

805
00:49:12,850 --> 00:49:16,029
Speaker 3: the Congress and other different areas there. You can find

806
00:49:16,090 --> 00:49:19,910
Speaker 3: out about our annual conference. It'll be in February in Washington, DC.

807
00:49:20,570 --> 00:49:23,120
Speaker 3: and also all the places on social media where you

808
00:49:23,160 --> 00:49:28,440
Speaker 3: can follow us a little as well that's it that's nrb.org.

809
00:49:27,820 --> 00:49:30,460
Speaker 1: Very good i will include that in the show notes

810
00:49:30,500 --> 00:49:32,940
Speaker 1: everybody so you can check out nrb if you'd like

811
00:49:33,480 --> 00:49:35,359
Speaker 1: and uh troy it was a pleasure talking with you

812
00:49:35,380 --> 00:49:38,650
Speaker 1: this was great uh thanks for being on the show Well, thanks.

813
00:49:38,469 --> 00:49:40,500
Speaker 3: For having me. It was a great show. Great talking

814
00:49:40,520 --> 00:49:40,799
Speaker 3: to you.

815
00:49:41,640 --> 00:49:42,320
Speaker 2: All right, everybody.

816
00:49:42,360 --> 00:49:45,320
Speaker 1: Well, we'll catch you on the next episode of Thinking Christian.

817
00:49:45,520 --> 00:49:47,140
Speaker 1: So take care. Just want to take a second to

818
00:49:47,180 --> 00:49:49,629
Speaker 1: thank the team at Life Audio for their partnership with

819
00:49:49,690 --> 00:49:53,350
Speaker 1: us on the Thinking Christian podcast. If you go to lifeaudio.com,

820
00:49:53,370 --> 00:49:56,510
Speaker 1: you'll find dozens of other faith-centered podcasts in their network.

821
00:49:56,910 --> 00:50:00,100
Speaker 1: They've got shows about prayer, Bible study, parenting, and more.