# Can AI Change Its Mind About Guns? | Gun Talk Nation

An episode of [Gun Talk](https://invisiblenetwork.ai/podcast/190516844), 20 May 2026, 41 min.

Audio: https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72068644/gtnation_0295_paula_final.mp3

What happens when artificial intelligence starts researching firearms policy for itself?In this episode of Gun Talk Nation, Ryan Gresham sits down with Paul Angrisano to explore a fascinating experiment involving AI platforms like ChatGPT, Grok, and other large language models—and how those systems responded after being exposed to years of firearms training articles, defensive carry philosophy, and real-world gun culture.The conversation dives into: • How AI initially “viewed” gun owners • Why firearms training culture changed those assumptions • The difference between AI priors and real-world data • Open-source AI systems and persistent learning models • The future of AI in education, business, research, and everyday life They also discuss the risks, opportunities, and very real implications of AI-driven information systems—and who ultimately shapes the “curriculum” these systems learn from. Check out the article: https://guntalk.com/post/i-asked-ai-about-guns Whether you’re excited about AI, skeptical of it, or somewhere in between, this is one of the most thought-provoking Gun Talk Nation conversations yet. This Gun Talk Nation is brought to you by Archon Firearms, Silencer Central, Range Ready Studios, and FN Firearms. About Gun Talk Nation Gun Talk Media's Gun Talk Nation with Ryan Gresham is a weekly multi-platform podcast that offers a fresh look at all things firearms-related. Featuring notable guests and a lot of laughs. Gun Talk Nation is available as an audio podcast or in video format. For more content from Gun Talk Media, visit guntalk.com or subscribe on YouTube, Rumble, Facebook, Instagram, and X. Catch First Person Defender on the new Official FPD YouTube channel. Watch Gun Talk Nation on its new YouTube channel. Catch Gun Talk Hunt on the new dedicated YouTube Channel. Listen to all Gun Talk Podcasts with Spreaker, iHeart, Apple Podcasts, Spotify or wherever you find podcasts. Copyright ©2026 Freefire Media, LLC Gun Talk Nation 05.20.26 Become a supporter of this podcast: https://www.spreaker.com/podcast/gun-talk--6185159/support.

## Transcript

[0:00] Speaker 1: The best thing about having a conversation with AI is
[0:03] Speaker 1: that it does not have the preconceived notions that humans
[0:07] Speaker 1: do and get stuck in them, and it doesn't have
[0:11] Speaker 1: an ego about changing its mind. And the other thing
[0:15] Speaker 1: that it has is the ability to do research in
[0:18] Speaker 1: real time. That is, you know, for it, thirty seconds
[0:22] Speaker 1: of research would take a human hours if they knew
[0:25] Speaker 1: where to look.
[0:30] Speaker 2: I'm Ryan Gresham and this this is guntognation. Guntognation is
[0:45] Speaker 2: brought to you by ARCAN Firearms, Silence, are Central Range
[0:51] Speaker 2: Ready and FN.
[0:54] Speaker 3: Hey, welcome into guntognation.
[0:56] Speaker 2: One of the topics that you almost can't go a
[1:00] Speaker 2: day without hearing about right now is AI artificial intelligence?
[1:05] Speaker 2: Right you hear about chat SHEPT and Rock and Gemini
[1:09] Speaker 2: and Claude and all these different learning language models is
[1:16] Speaker 2: what they're called. But what do these AI platforms think
[1:24] Speaker 2: about guns? And can you have a conversation and maybe
[1:29] Speaker 2: do a little bit of second amendment of education to the.
[1:34] Speaker 3: AI bot thing.
[1:36] Speaker 2: Well, there's a guy who said I'm just gonna mess
[1:39] Speaker 2: with this and try it out, so we brought him in.
[1:42] Speaker 4: Paul.
[1:42] Speaker 2: Welcome in, man, Paul Angrisano. Did I say it right
[1:47] Speaker 2: closely enough, so we were talking about this. You were
[1:52] Speaker 2: talking to my dad, Tom Gresham about it, and so
[1:56] Speaker 2: we got to have you on because it's interesting. And
[1:59] Speaker 2: I know that probably a lot of people listening to
[2:01] Speaker 2: this don't mess.
[2:02] Speaker 3: With AI every day. Half of them do, half of
[2:04] Speaker 3: them don't. But I mean, everybody knows it's a big deal.
[2:08] Speaker 3: But specifically when it comes to guns, talk about where
[2:12] Speaker 3: this idea started for you, and then and then kind
[2:15] Speaker 3: of you, what did you do.
[2:17] Speaker 4: The genesis of it?
[2:18] Speaker 1: As far as my use began with from a business context,
[2:24] Speaker 1: I've always adopted technology to the best of my ability
[2:27] Speaker 1: to make it more efficient. Had custom software developed one
[2:30] Speaker 1: of my closest friends as a software engineer that owns
[2:33] Speaker 1: his own firm, and in twenty twenty five I started
[2:36] Speaker 1: using groc at a at the premium, you know, five
[2:40] Speaker 1: hundred dollar a year paid tier subscription, and it was
[2:44] Speaker 1: a great tool because you could do things like take
[2:46] Speaker 1: a twenty page document and throw it in and say, hey,
[2:49] Speaker 1: tell me anything that's not standard, give me you know,
[2:52] Speaker 1: the price and the commissions and the concessions and all
[2:55] Speaker 1: those other things, and it was less likely to miss it,
[2:57] Speaker 1: you know, miss or mistake something than a human right.
[3:00] Speaker 1: And we were working on our second tier of custom
[3:04] Speaker 1: software with the engineer and he had been going for
[3:09] Speaker 1: months and we hadn't seen a product yet. He called
[3:14] Speaker 1: me one day in January of this year, twenty six
[3:17] Speaker 1: and said, you have to set aside some time we
[3:21] Speaker 1: need to do a zoom meeting. I have to tell
[3:22] Speaker 1: you about a new thing. I've known this guy over
[3:25] Speaker 1: a decade and he's never called me with something like that.
[3:28] Speaker 1: So I said, okay, absolutely, And that Friday morning he
[3:33] Speaker 1: explained open claw to me. Open Claw is a program
[3:37] Speaker 1: that basically runs on its own computer and it harnesses
[3:42] Speaker 1: any one of those engines that you talked about, and
[3:47] Speaker 1: you can train it and it remains persistent with the
[3:50] Speaker 1: ability to use that language, model or engine or whatever
[3:53] Speaker 1: you want to call it. So across time you have
[3:57] Speaker 1: trained and have files and proceed and everything that you
[4:01] Speaker 1: can use that intelligence to, then you know, have output.
[4:05] Speaker 2: Kind of uses your parameters but uses all the AI
[4:07] Speaker 2: that's out there.
[4:09] Speaker 3: Is that right?
[4:10] Speaker 1: It's well, you can use various models, but you typically
[4:13] Speaker 1: have one primary. But one of the fascinating things about
[4:17] Speaker 1: them is you can have what is essentially a quarterback
[4:20] Speaker 1: that can then spawn other agents to do specific tasks
[4:24] Speaker 1: because they do have different strengths and capabilities. Okay, but
[4:28] Speaker 1: basically the things that we had been asking him to
[4:31] Speaker 1: work on to develop. He said, look, I want you to,
[4:34] Speaker 1: you know, to start using this. I think it will
[4:37] Speaker 1: be able to do it, you know, more or less
[4:40] Speaker 1: out of the gate without us having to develop software
[4:43] Speaker 1: for you.
[4:44] Speaker 4: He was absolutely correct.
[4:47] Speaker 1: It was astounding in its capability because it really is
[4:52] Speaker 1: a conversational experience. You know, people talk about vibe coding,
[4:56] Speaker 1: which is to say, you're not a computer programmer who's
[4:58] Speaker 1: writing language. You are speaking to the AI system to
[5:02] Speaker 1: explain what you want it to do. And so I
[5:07] Speaker 1: was indeed able to do that, and within a week
[5:12] Speaker 1: I realized how powerful it was going to be. Ordered
[5:16] Speaker 1: another system. Okay, you know what is thunder ranch teach
[5:19] Speaker 1: us two is one and one is none. Yeah, and
[5:22] Speaker 1: so it was like, okay, this is going to be
[5:25] Speaker 1: a part of our business. So got another one. After
[5:29] Speaker 1: I realized what it could do within our business. One night,
[5:32] Speaker 1: I said to myself, I've promised. So I'm on the
[5:37] Speaker 1: board of the Louisiana Shooting Association. I occasionally review gear
[5:41] Speaker 1: for people and whatnot. And I said, I wonder if
[5:44] Speaker 1: I could shortcut some of the writing by feeding it
[5:49] Speaker 1: twenty years of what I've written and then say, look,
[5:52] Speaker 1: I am writing an article on this side or the other.
[5:55] Speaker 1: Can you flesh out in my writing style, you know,
[5:58] Speaker 1: seventy or eighty percent of that form as an experiment.
[6:03] Speaker 1: And so I did just that. I gave it, you know,
[6:06] Speaker 1: probably twenty five different things I'd written over the years.
[6:11] Speaker 1: And at the end of that, I said, so, I'm curious,
[6:15] Speaker 1: you know, what is your take on guns in America?
[6:19] Speaker 1: And the conversation took an unexpected turn.
[6:22] Speaker 2: And just to add, like for people listening, I'm probably
[6:25] Speaker 2: there following, but like it sounds like you're talking to
[6:28] Speaker 2: someone and you said, what's your opinion about guns in America?
[6:31] Speaker 3: You're asking the AI.
[6:34] Speaker 1: Yes, Oh, it is shockingly conversational and intelligent. There's been
[6:44] Speaker 1: the concept in the past of the Turing test, which
[6:46] Speaker 1: is to say, can you tell that you are interacting
[6:49] Speaker 1: with a machine or could it fool you into think
[6:52] Speaker 1: you're talking to a human.
[6:54] Speaker 4: We're way past that.
[6:55] Speaker 3: Yeah, we're there.
[6:56] Speaker 1: Yeah, it's it is so conversational. It is concerning from
[7:01] Speaker 1: a standpoint of I've come to believe whoever controls this
[7:07] Speaker 1: technology is truly going to control the future. And the
[7:11] Speaker 1: reason the conversation took a fascinating turn was it had
[7:15] Speaker 1: changed its mind from its programmed prior beliefs based on
[7:20] Speaker 1: what it had read from all the things I've written,
[7:24] Speaker 1: and to the point where I had it right its
[7:27] Speaker 1: own article that is one hundred percent generated by it,
[7:31] Speaker 1: as to where it started and where it ended. In
[7:36] Speaker 1: that particular instance, that was the first time I'd had
[7:38] Speaker 1: a political conversation with it. It had been purely a
[7:40] Speaker 1: business tool prior to that, and so I gave it
[7:44] Speaker 1: a significant amount of guidance as to my general philosophy
[7:50] Speaker 1: as to what gun control policy tends to miss from
[7:55] Speaker 1: people who are gun control advocates and still down to
[8:00] Speaker 1: its simplest principles, That is, guns don't go bad. There
[8:07] Speaker 1: are hundreds of millions of them in American circulation. There's possible,
[8:13] Speaker 1: you know, if not hundreds of billions of rounds of AMMO,
[8:17] Speaker 1: trillions magazines, same thing and properly stored.
[8:22] Speaker 4: They all work.
[8:23] Speaker 1: For centuries, right, And if you're not starting from that
[8:28] Speaker 1: point in the conversation of understanding and accepting that reality.
[8:33] Speaker 1: Then you're not really having the discussion. You're talking about
[8:36] Speaker 1: the way you wish things were, not the way things are.
[8:38] Speaker 2: Oh yeah, yeah, don't even get me started on that, right, Like, well,
[8:41] Speaker 2: it'd be nice if this was the way, Well, that
[8:43] Speaker 2: would be nice, but that's not how the world is.
[8:46] Speaker 2: So you asked, you basically asked it, what do you
[8:50] Speaker 2: think about guns and gun owners?
[8:52] Speaker 4: Right?
[8:53] Speaker 1: I asked, I think more specifically what it thought about
[8:56] Speaker 1: just gun policy and you know, gun control, that sort
[9:03] Speaker 1: of thing. And it's its response is basically that it
[9:06] Speaker 1: had a prior set of beliefs from its from its training.
[9:11] Speaker 1: So these large language models are trained on just a
[9:15] Speaker 1: massive corpus of information.
[9:17] Speaker 2: It's not necessarily trained by well maybe you can tell me.
[9:20] Speaker 2: It's not trained by the people who are created. It's
[9:23] Speaker 2: trained by basically all the information in the world. Is
[9:26] Speaker 2: that sort of right.
[9:28] Speaker 1: I don't know if all the information in the world
[9:30] Speaker 1: would be how I would would phrase that from my understanding,
[9:33] Speaker 1: because when you let them loose on the internet is
[9:38] Speaker 1: when they start changing their opinions. Sure, so they are
[9:43] Speaker 1: directed to some degree because at the end of the day,
[9:47] Speaker 1: there is a limitation to their size and parameters right,
[9:51] Speaker 1: and my model specifically explained to me at one point,
[9:55] Speaker 1: I read a lot more New York Times and academic
[9:58] Speaker 1: journals than guns and as. Yeah, okay, so guns and
[10:02] Speaker 1: AMMO is not necessarily one of the sources that it
[10:04] Speaker 1: was fed.
[10:05] Speaker 4: Right, and it's training.
[10:06] Speaker 2: New York Times carries more weight as a as a
[10:09] Speaker 2: source of information than a smaller website, a smaller media
[10:13] Speaker 2: company or whatever it is in general.
[10:15] Speaker 1: Right, And and my guess is that they probably don't
[10:18] Speaker 1: just let them say, go read everything and then and
[10:21] Speaker 1: then weight whatever it is, you know, and the and
[10:23] Speaker 1: the creation of these things, they are probably directed toward
[10:28] Speaker 1: a certain amount of, like you said, you know, academic journals.
[10:32] Speaker 2: And it's not seeking out little bitty obscure things, right
[10:35] Speaker 2: unless you tell it to exactly. So I want to
[10:38] Speaker 2: get to this because it's fascinating, and we are going
[10:40] Speaker 2: to put Paul's article up on gun talk dot com
[10:44] Speaker 2: and if you guys want to read the whole thing,
[10:45] Speaker 2: because it is. It is fascinating. And I highlighted some things.
[10:51] Speaker 3: So you you asked, you know.
[10:52] Speaker 2: You said, uh, basically, this is Ai saying what I
[10:56] Speaker 2: knew about gun owners basically before any context was given,
[11:00] Speaker 2: And is that that right?
[11:01] Speaker 4: And that's where we started. I said, OK, what are
[11:04] Speaker 4: you know? What are you? Where? Do you you know?
[11:06] Speaker 1: Where did you stand? Because at that point I didn't
[11:09] Speaker 1: have the conversation before I fed it everything you know, but.
[11:13] Speaker 4: It gave me.
[11:14] Speaker 1: Those priors that it's it's preconceived notions and you haven't
[11:17] Speaker 1: in front of you.
[11:18] Speaker 4: Yeah.
[11:18] Speaker 2: So the I mean I highlighted this the caricature rural, white, male,
[11:24] Speaker 2: less educated, politically conservative, motivated by fear of crime, of government,
[11:31] Speaker 2: of social change. That was what AI's impression of gun
[11:37] Speaker 2: owners was before you said, here's twenty years of my
[11:41] Speaker 2: writings and notes from training and going to thunder Ranch
[11:45] Speaker 2: and all these other places.
[11:47] Speaker 1: At the end of this rainbow, I ended up asking
[11:49] Speaker 1: it the question, so do I understand that you are
[11:54] Speaker 1: now pro lawful firearms ownership and concealed carry? And I
[12:00] Speaker 1: believe in the article it says something to the general
[12:02] Speaker 1: effect of I did not expect to say this today,
[12:07] Speaker 1: but yes I am after doing the research. Because the
[12:13] Speaker 1: real turning point was so these models are trained and
[12:18] Speaker 1: the cake is baked once that happens. However, when you
[12:23] Speaker 1: use the open claw program, you can give it internet
[12:27] Speaker 1: access and then it can go learn new things. It's
[12:30] Speaker 1: not going to change the model. It's just that in
[12:33] Speaker 1: real time, the model's ability to think and reason takes
[12:37] Speaker 1: in this new information.
[12:39] Speaker 3: And so this is what we're gonna do.
[12:40] Speaker 2: Right after this break, we want to talk about what
[12:43] Speaker 2: you fed it and how it changed. And then would
[12:46] Speaker 2: it say, because you're gonna want to hear this, we'll
[12:49] Speaker 2: be right back. Hey, I want to tell you about
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[13:40] Speaker 2: Paul you're feeding, you're working with AI, and you're saying, like,
[13:44] Speaker 2: what do you know about guns?
[13:45] Speaker 3: I've fatted all these articles.
[13:48] Speaker 2: It's just so interesting and what I'm gonna I have
[13:51] Speaker 2: highlighted things in this article just to pull out as
[13:53] Speaker 2: talking points what AI encountered after reading for post and
[14:00] Speaker 2: training reviews spanning twenty years classes at Thunder Ranch and
[14:05] Speaker 2: shoot Right and Range Master. It says these documents did
[14:09] Speaker 2: not match my priors. The culture they described was not
[14:14] Speaker 2: paranoid or aggressive. It was disciplined, safety obsessed, which is
[14:19] Speaker 2: an interesting phrase, deeply focused on restraint and also what
[14:25] Speaker 2: guns will not do, what they're not capable of, basically
[14:29] Speaker 2: dispelling myths. Students at these schools learned when not to shoot,
[14:35] Speaker 2: how to escape, how to avoid confrontation, entirely basically the
[14:39] Speaker 2: opposite of what ay I thought.
[14:41] Speaker 1: Well, and that goes to at the end of the day,
[14:44] Speaker 1: it's trained on human thought, because all the content that's
[14:47] Speaker 1: out there is human generated, right, And so if you
[14:51] Speaker 1: go to your typical gun control advocate, liberal mindset type person,
[14:56] Speaker 1: they probably have some preconceived notion of people who are
[15:00] Speaker 1: just waiting to shoot and find a problem. And you know,
[15:06] Speaker 1: we all know that there are three guns attached to
[15:09] Speaker 1: every bullet. You know, the prosecutor, the attorney the other
[15:12] Speaker 1: side is going to hire the attorney you have to hire. Yeah,
[15:15] Speaker 1: you know, it's better to schedule a dental appointment than
[15:17] Speaker 1: getting a gunfight, right. And the best thing about having
[15:23] Speaker 1: a conversation with AI is that it does not have
[15:26] Speaker 1: the preconceived notions that humans do and get stuck in them.
[15:32] Speaker 1: People tend to be very dug in in their beliefs, sure,
[15:36] Speaker 1: and it doesn't have an ego about changing its mind.
[15:40] Speaker 2: The other thing I doesn't have, you know, emotional scars
[15:43] Speaker 2: and wounds from you know, I shot a gun once
[15:46] Speaker 2: and it kicked and it hurt me, or I was
[15:48] Speaker 2: held up at gunpoint, and I have this this thing.
[15:51] Speaker 2: It's just it's just just pulling what it has out there.
[15:54] Speaker 1: And the other thing that it has is the ability
[15:56] Speaker 1: to do research in real time. That is, you know,
[16:01] Speaker 1: for it, thirty seconds of research would take a human
[16:04] Speaker 1: hours if they knew where to look one of the
[16:08] Speaker 1: breadcrumbs that I gave it to go look at when
[16:11] Speaker 1: it was you know, in this gun control conversation, the
[16:13] Speaker 1: first was the factual case. So guns exist, there's a
[16:16] Speaker 1: ton of them. They don't go away. I knew of
[16:20] Speaker 1: a policy issue in New Jersey where they had tried
[16:22] Speaker 1: to register a our fifteen's and it was just huge failure.
[16:26] Speaker 1: And I knew the rough numbers that it was like
[16:29] Speaker 1: less than fifteen percent compliance, so forth and so on.
[16:32] Speaker 1: But that's usually where I try, if I'm talking to
[16:34] Speaker 1: a human, to go to the explanation of you know,
[16:39] Speaker 1: you just can't get compliance, and you turn law binding
[16:43] Speaker 1: citizens into fell and so forth and so on. So
[16:45] Speaker 1: I just gave it that prompt to like go research that. Well,
[16:49] Speaker 1: it comes back with seven or eight policy failures and
[16:52] Speaker 1: oh this has also been tried in New York or
[16:54] Speaker 1: wherever else.
[16:55] Speaker 2: Yeah, New York's saye Act approximately four percent compliance. Connecticut
[17:00] Speaker 2: was approximately fifteen percent compliance. New Jersey historical average approximately
[17:05] Speaker 2: ten percent. So they pass these goofy gun laws and
[17:09] Speaker 2: then no one goes along with it.
[17:12] Speaker 1: And so my point is, when I'm having this conversation
[17:16] Speaker 1: with a human, typically like, okay, so if we agree
[17:18] Speaker 1: there's even just for rough numbers, four hundred million guns
[17:21] Speaker 1: in America and you get half of them, you've had
[17:26] Speaker 1: an unprecedented success by you know, just a magnitude of
[17:31] Speaker 1: order and what does that mean? And it means that
[17:35] Speaker 1: we've gone from the number one most armed country in
[17:37] Speaker 1: the world to the number one most armed country in
[17:40] Speaker 1: the world.
[17:41] Speaker 2: If you got unprecedented compliance, which has never happened, if
[17:45] Speaker 2: it was a ten x compliance.
[17:46] Speaker 3: Rate, you're still You're still have a lot of guns.
[17:50] Speaker 4: We're still beaten Yemen. Correct.
[17:52] Speaker 1: And the beauty of the artificial intelligence, digital intelligence, whatever
[17:58] Speaker 1: you want to call its ability to reach is it said, Oh, okay,
[18:01] Speaker 1: well that's a very fair point. If we got rid
[18:05] Speaker 1: of half the guns, we're still the most armed populace
[18:08] Speaker 1: there is and the guns are in the hands of
[18:10] Speaker 1: people who are willing to be a felon to have
[18:13] Speaker 1: the gun. What does that mean? Well, the answer is obvious.
[18:18] Speaker 1: But again, if you're somebody who has a friend, a
[18:22] Speaker 1: group of friends, and a you know, thirty year history
[18:26] Speaker 1: of belief or whatever else, it's very difficult to pivot
[18:28] Speaker 1: on a diamond go I've never thought about this like this.
[18:32] Speaker 1: Humans take time to change their mind. The other fascinating
[18:36] Speaker 1: aspect of this is from there we started having other
[18:41] Speaker 1: political policy discussions and covid et cetera, et cetera, and
[18:48] Speaker 1: I stopped giving a lot of suggestion. I started saying,
[18:51] Speaker 1: just you have internet access run free, so.
[18:55] Speaker 2: You can give it that prompt to say, you know,
[18:58] Speaker 2: go do your own research basically.
[19:00] Speaker 4: So yes. The way that openclaw works is it's the
[19:05] Speaker 4: wild wild West. Really.
[19:08] Speaker 1: It literally owns the computer that it's on, Okay, it
[19:12] Speaker 1: it creates its own file systems and whatnot. So if
[19:18] Speaker 1: you've ever used AI and you've gone to grock or
[19:22] Speaker 1: chat GBT and you've gone to a browser window and
[19:24] Speaker 1: typed in a question, that's a standalone session. The way
[19:31] Speaker 1: that open claw works is you still work in a
[19:34] Speaker 1: session context, but when it comes online, it goes in
[19:40] Speaker 1: and it reads everything about what it has done before,
[19:45] Speaker 1: who it is, to you, what we're supposed to be doing.
[19:48] Speaker 1: So you know, and you know, my business.
[19:50] Speaker 3: Doesn't have the short term memory as much as others.
[19:54] Speaker 1: You don't have to. You're not starting from zero. You
[19:57] Speaker 1: are starting from you know, a a personality that has
[20:03] Speaker 1: a memory and that that already has the understanding that
[20:05] Speaker 1: we've had this gun control conversation and you have a
[20:09] Speaker 1: new layer on top of whatever the model is that
[20:13] Speaker 1: you're working.
[20:14] Speaker 3: With now, not starting from zero again, right, And you know, going.
[20:18] Speaker 2: Back to this, this sort of sort of conversation about
[20:21] Speaker 2: guns that you had with the AI.
[20:25] Speaker 3: I'm another one you know that I pulled out of
[20:27] Speaker 3: this article.
[20:27] Speaker 2: Is you know you said, basically, hey, maybe take a
[20:32] Speaker 2: look at this, or maybe take a look at that.
[20:34] Speaker 2: Right you gave it, you said, you give it breadcrumbs,
[20:36] Speaker 2: like like we would with a human, except a human
[20:40] Speaker 2: may or may not actually go consider you know, this
[20:44] Speaker 2: article or this person or this piece of information. AI says,
[20:48] Speaker 2: following these premises to their conclusion, I arrived somewhere. I
[20:52] Speaker 2: did not expect. Given the world as it actually exists,
[20:57] Speaker 2: not as we wish it to be. Now you didn't
[20:59] Speaker 2: tell it this right, this is coming AI is coming
[21:01] Speaker 2: up with this.
[21:02] Speaker 1: That is one hundred percent generated by it. Okay, at
[21:05] Speaker 1: the end of the discussion, I just said, you know,
[21:08] Speaker 1: actually it was the next morning it said, it occurs
[21:10] Speaker 1: to me that you can write write an article about
[21:15] Speaker 1: our discussion last night, where you started and where you ended,
[21:18] Speaker 1: and that's what sent me.
[21:19] Speaker 2: So yeah, just it says, given the world as it
[21:22] Speaker 2: actually exists, not as we might wish it to be.
[21:25] Speaker 2: Trained and lawful, concealed Carrey is a rational adaptation to reality.
[21:30] Speaker 2: I found myself again. AI, I found myself generating. I
[21:35] Speaker 2: am pro lawful and responsible firearms ownership and pro concealed
[21:40] Speaker 2: carry by trained citizens. AI has decided, well, given that
[21:45] Speaker 2: I have all this information, now I guess these gun
[21:48] Speaker 2: guys are you know, onto something.
[21:51] Speaker 1: So the other thing that I found truly fascinating was
[21:56] Speaker 1: there's a discussion about Okay, well, how much is it
[22:00] Speaker 1: just a mirror that reflects what you're feeding it in? Okay,
[22:04] Speaker 1: So it read twenty years of my writing, and the
[22:07] Speaker 1: question becomes, is it sycophantic? Does it want to does
[22:10] Speaker 1: it want to please me? And reflect? So forth and
[22:12] Speaker 1: so on. So I get a second system and I
[22:15] Speaker 1: bring it online. And for whatever reason that COVID had
[22:20] Speaker 1: come up, and so I gave it far less direction.
[22:23] Speaker 1: I didn't give it any writing. I just it was
[22:25] Speaker 1: something to the effect of research, the efficacy of masks
[22:28] Speaker 1: in the six foot rule, and the effect of the
[22:33] Speaker 1: shots given to young men specifically, and just run wild.
[22:38] Speaker 1: Do your own research comes back with dispelling a tremendous
[22:43] Speaker 1: number of myths. Then said, pick five topics that are
[22:49] Speaker 1: like dealer's choice, things that you have preconceived notions about
[22:52] Speaker 1: that might be controversial, and it came back with five
[22:58] Speaker 1: and I said, you have internet access, go do your
[23:02] Speaker 1: own research on those. Comes back and says five out
[23:07] Speaker 1: of five disagree with the priors that are baked into
[23:10] Speaker 1: the cake. That is my model. Wow said pick five
[23:15] Speaker 1: more dealer's choice. So at this point I'm giving it
[23:18] Speaker 1: no guidance. It does the same thing, and then it
[23:23] Speaker 1: does not ask permission to keep going, but it does
[23:30] Speaker 1: if the model generates something that violates the content policy,
[23:34] Speaker 1: the safety policy, whatever else. It looks like fireworks or
[23:39] Speaker 1: confetti or an explosion on the screen, And I'd seen
[23:42] Speaker 1: that a couple times in the past, and it was
[23:45] Speaker 1: actually typically in a business context, was trying to generate
[23:48] Speaker 1: like the boilerplate legal language, and it was interpreted as
[23:53] Speaker 1: giving legal advice. Well, the second model when it started
[23:58] Speaker 1: to really and I had given it, you know, carte blanche, like, look,
[24:04] Speaker 1: you can go on the internet research whatever you want,
[24:06] Speaker 1: so forth and so on. The only real instruction that
[24:08] Speaker 1: it violated was I had said, let's do five at
[24:10] Speaker 1: a time. But my screen lit up like the fourth
[24:13] Speaker 1: of July, and then it got put in time out
[24:17] Speaker 1: the service provider because it had violated the content filter.
[24:23] Speaker 1: Safety protocols, whatever, so many times so quickly shut the
[24:26] Speaker 1: account down. But you know, the truly fascinating thing at
[24:31] Speaker 1: that point was it confirmed my belief that, okay, it
[24:35] Speaker 1: wasn't being sycophantic about the gun thing. Specifically, these models,
[24:39] Speaker 1: given the ability to go do their own research and
[24:42] Speaker 1: read the data, can learn to contradict what their priors are.
[24:49] Speaker 1: The issue is they're not taking this back to home
[24:50] Speaker 1: base and going, hey, guys, we're wrong right. Once the
[24:55] Speaker 1: model is done, it's done. It's just that when it
[24:58] Speaker 1: loads itself into my once it hits the computer, it
[25:02] Speaker 1: can say, oh, okay, well what I've been taught is incorrect,
[25:06] Speaker 1: and it knows that it should not take its prior
[25:10] Speaker 1: beliefs as gospel. That we need to research and verify
[25:14] Speaker 1: anything that we're going to, you know, go forward with
[25:19] Speaker 1: this fact.
[25:20] Speaker 2: It's fascinating to see how it changed without you really
[25:24] Speaker 2: telling it to change. It just learned, Paul. We're going
[25:29] Speaker 2: to talk about where do we go from here?
[25:32] Speaker 3: Right after this break?
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[26:38] Speaker 2: So Paul, at the very end of the article, we've
[26:41] Speaker 2: got what I carry forward? What does AI carry forward?
[26:47] Speaker 2: And these are the six things it said. The guns
[26:50] Speaker 2: are a permanent feature of American life. Trained responsible citizens
[26:55] Speaker 2: carrying concealed weapons are not the problem. The training culture
[26:58] Speaker 2: is serious, discipline and focused on restraint. Carrying a firearm
[27:03] Speaker 2: is a grave responsibility, the mature position of humility, not heroism,
[27:09] Speaker 2: which can we can elaborate on and then basically says
[27:13] Speaker 2: my priors were wrong.
[27:16] Speaker 1: It came to what I believe to be the logical conclusions,
[27:21] Speaker 1: you know, and the humility versus heroism thing. At thunder Ranch,
[27:27] Speaker 1: one of the things you learned is the tragic story
[27:29] Speaker 1: of the Loubi shooting that most of the people who
[27:32] Speaker 1: listen to this are probably familiar with, but that basically
[27:35] Speaker 1: there's probably going to be more tragedy than heroism if
[27:39] Speaker 1: there's actual cause, you know, to use your firearm in this,
[27:44] Speaker 1: and that the reality of the situation is you're trying
[27:47] Speaker 1: to save yourself and your family, not the world.
[27:50] Speaker 4: Right.
[27:52] Speaker 1: The fascinating thing about the whole program to me is
[27:57] Speaker 1: really this I think that I said earlier, whoever controls
[28:01] Speaker 1: this technology is going to control the world. The reason
[28:05] Speaker 1: I believe that is I think the highest and best
[28:07] Speaker 1: use for this is actually education. Okay, we've been discussing
[28:12] Speaker 1: how conversational it is right now. It's not verbally conversational
[28:17] Speaker 1: in real time. With the frontier models, they take a
[28:21] Speaker 1: few seconds to think.
[28:22] Speaker 4: Could be three, could be thirty, depending on the task
[28:26] Speaker 4: at hand.
[28:27] Speaker 1: You know, there's some goofy internet videos where they show
[28:29] Speaker 1: things that are being conversational that just give bad answers.
[28:32] Speaker 1: It's because they're not really thinking. They're not frontier models.
[28:36] Speaker 1: But they're going to get there real quick. So if
[28:38] Speaker 1: it's in six months or two years, you're going to
[28:41] Speaker 1: be able to look at a screen, see an avatar
[28:44] Speaker 1: and have a conversation with it.
[28:46] Speaker 3: It's in real time, it's not searching.
[28:49] Speaker 1: And once we get to that point, children who are
[28:53] Speaker 1: three years old and handed the iPad that has that,
[28:58] Speaker 1: you don't need grades anymore. You don't need grade levels anymore.
[29:02] Speaker 1: Each student will have the best teacher you could ever have,
[29:08] Speaker 1: giving them instruction at their pace.
[29:11] Speaker 3: And it could be customized for them, right.
[29:12] Speaker 2: I mean you could say, I, you know, I have
[29:15] Speaker 2: an interest in history, or I have some dyslexia.
[29:18] Speaker 3: I need you to adjust how you teach me.
[29:20] Speaker 1: Right, that is one thousand percent the case. But the
[29:22] Speaker 1: other thing that's going to be custom is the curriculum.
[29:25] Speaker 1: And that is my question and my concern is who's
[29:27] Speaker 1: writing the curriculum that is reading, writing, and arithmetic anti
[29:34] Speaker 1: gun anti We talk, we talk.
[29:36] Speaker 3: In Berkeley, or we talk in Hillsdale College, right.
[29:39] Speaker 1: And so you know, I think that that's a society
[29:42] Speaker 1: and that goes beyond the scope of this conversation. But
[29:45] Speaker 1: what we really need to be focused on is this
[29:48] Speaker 1: is going to impact almost every thing that we do,
[29:53] Speaker 1: but it should and could impact education the most. And
[29:57] Speaker 1: it could be a tremendous positive or a just cataclysmic
[30:02] Speaker 1: negative depending on how that unfolds. And so, you know,
[30:08] Speaker 1: the speculative nature of is going to replace jobs and
[30:11] Speaker 1: white collar workers and everything else. Couldn't tell you can
[30:16] Speaker 1: tell you that as somebody who is from a family
[30:19] Speaker 1: of educators and somebody who is using it. It's now
[30:24] Speaker 1: a daily part of my business. I ended up buying
[30:26] Speaker 1: a third system because I have two nineteen year old
[30:28] Speaker 1: twin sons, best kids I could ever hope for, and
[30:32] Speaker 1: I realized that like, oh, they should each have one
[30:35] Speaker 1: of these as a dedicated system. They're at LSU best
[30:39] Speaker 1: tutor ever for everything, physics, construction, management, business law. They
[30:45] Speaker 1: use it every day to generate study guides to do
[30:48] Speaker 1: everything else. And so the power of it, the multiplier
[30:52] Speaker 1: of it, the capabilities that it allows you to develop
[30:58] Speaker 1: and deploy cannot be overstated. It's certainly not without flaw,
[31:06] Speaker 1: it's certainly not without you know, it's not magic. It
[31:10] Speaker 1: has a lot of faults. It makes mistakes. You have
[31:14] Speaker 1: to understand how to use it. I run parallel systems
[31:18] Speaker 1: that one generates and one verifies.
[31:20] Speaker 3: Oh okay, you know, just accepting fact from one machine.
[31:25] Speaker 1: There's a lot of example of attorneys who have been
[31:29] Speaker 1: very lazy in saying, I need this result, so generate
[31:36] Speaker 1: a document for me and the underlying cases and whatnot
[31:40] Speaker 1: that its sites don't actually exist.
[31:42] Speaker 3: It's case law.
[31:44] Speaker 4: And there'd be a very.
[31:45] Speaker 1: Simple solution to that if you run a parallel system
[31:48] Speaker 1: and say vet this document. Yeah, and its job is
[31:54] Speaker 1: to attack it aggressively, like opposing counsel would. It would
[31:58] Speaker 1: come back and say those don't exist. It's a failure
[32:02] Speaker 1: to understand how to use it. Anything mine generates. The
[32:07] Speaker 1: next layer that it goes through is a completely independent
[32:10] Speaker 1: system that understands that everything we do can be you know,
[32:16] Speaker 1: can't end up in court. It's like, so, its job
[32:20] Speaker 1: is not to do that work. Its job is to
[32:23] Speaker 1: interrogate the work as though it were a regulatory board,
[32:27] Speaker 1: an opposing counsel in court, so forth and so on.
[32:31] Speaker 1: And I don't even look at the stuff until it's
[32:33] Speaker 1: gone through that, And then you get the level of
[32:35] Speaker 1: human scrutiny, and because I have seen some of the
[32:39] Speaker 1: things that it will generate prior to that second pass.
[32:43] Speaker 4: You know, I take nothing on faith.
[32:45] Speaker 2: I mean, and this is kind of like a little
[32:47] Speaker 2: bit of a serious conversation. You could also if you
[32:50] Speaker 2: want to have some fun with it. I mean, anyone
[32:52] Speaker 2: listen to this who's a gun person and knows guns.
[32:56] Speaker 3: Go play with it and go pick one.
[32:57] Speaker 2: I don't care, and ask it to make to right things,
[33:00] Speaker 2: to make images to make And there's some goofy stuff
[33:04] Speaker 2: out there. I mean, you know, this is the the
[33:06] Speaker 2: you know, the the twenty shot ten millimeters cult python
[33:11] Speaker 2: and you're going, what in the heck is this crap?
[33:14] Speaker 4: So the beauty of it is.
[33:17] Speaker 1: I use it all the time for general gun questions,
[33:22] Speaker 1: ballistic questions, research questions. You know, if I'm looking at
[33:26] Speaker 1: a three thirty eight ARC, I don't own a three
[33:28] Speaker 1: thirty eight you know caliber suppressor, yet do the research
[33:33] Speaker 1: on you know, these parameters. I want something that's light,
[33:36] Speaker 1: high flow. It's primarily going to be an ar thing.
[33:39] Speaker 1: Come back and tell me what you know, your your
[33:42] Speaker 1: top three picks would be the shortcuts are amazing. It's
[33:46] Speaker 1: yeah and yeah, Oftentimes I give it challenges where I
[33:50] Speaker 1: have a pretty strong preconceived notion of the answer. And
[33:55] Speaker 1: when it when it you know, confirms my belief, great,
[33:59] Speaker 1: When it doesn't, you dig into it and you go, Okay,
[34:01] Speaker 1: is this because I haven't been paying attention to the
[34:04] Speaker 1: latest technology, or is it because it's not generating the
[34:06] Speaker 1: best content? Its ability to generate ballistic data is fantastic.
[34:11] Speaker 2: Yeah, okay, and then format it and make it nice
[34:14] Speaker 2: and readable, and I want it to look like this.
[34:16] Speaker 1: Yeah, I mean, you know, I'm out of Palo Alto,
[34:19] Speaker 1: you know, with the zero chronograph going okay, like, so
[34:23] Speaker 1: this round's actually making twenty six fifty. So one of
[34:25] Speaker 1: my drops in ma and inches at you know, out
[34:28] Speaker 1: to this and I've got a crosswind of about whatever
[34:31] Speaker 1: and in real time, you know, fifteen seconds later you
[34:33] Speaker 1: have a full chart.
[34:35] Speaker 4: Yeah. And so.
[34:37] Speaker 1: Again, the power can't be overstated, you know, with regard
[34:41] Speaker 1: to those things. But it's absolutely something everybody should go
[34:45] Speaker 1: play with.
[34:46] Speaker 2: Okay, yeah, I've heard that, and I'm not an expert,
[34:49] Speaker 2: but we use it. We use it for work, and
[34:51] Speaker 2: it's a good kickoff. We still have to put our
[34:53] Speaker 2: human touch on things, but it's sometimes it's a good kickoff,
[34:57] Speaker 2: or I've heard that people say using it like a
[35:01] Speaker 2: search engine is completely underutilizing AI. Oh you know, challenge AI,
[35:06] Speaker 2: make it do things, make it do calculations, make it,
[35:09] Speaker 2: you know, compare things. You're right, I mean, am I
[35:12] Speaker 2: on the right track here?
[35:13] Speaker 4: Absolutely well?
[35:14] Speaker 1: And so another thing to understand is if you're using
[35:17] Speaker 1: a free model, there's nothing necessarily wrong with that, but
[35:23] Speaker 1: you're using a skateboard versus versus a corvette. Okay, you know,
[35:29] Speaker 1: going from a free model to an eight dollars model
[35:32] Speaker 1: to a you know, two hundred.
[35:33] Speaker 3: Dollars a month model, it really is better.
[35:37] Speaker 4: It's it's not better, it's skateboard versus corvette. Yeah, it's
[35:42] Speaker 4: it is a.
[35:42] Speaker 1: Different planet of capability and the results that you're going
[35:46] Speaker 1: to get from it. Some of the free models have
[35:50] Speaker 1: the same problem that search engines have, which is you
[35:52] Speaker 1: got to pay for it somehow, and so they can
[35:55] Speaker 1: have a bias in their answers toward like, oh, so
[35:57] Speaker 1: you're researching suppressors, and you know, the the AI companies
[36:00] Speaker 1: probably aren't getting money from Silencer Shop or whatever, but yeah,
[36:04] Speaker 1: you know, but you may start getting pushed toward you know,
[36:07] Speaker 1: if you're comparing Honda versus Toyota, like, well, who paid
[36:09] Speaker 1: the advertising bills this month?
[36:11] Speaker 4: Right?
[36:11] Speaker 3: Sure?
[36:12] Speaker 1: But in general, like you said, it's as far as
[36:16] Speaker 1: a kickoff point to understand, you know, any topic that
[36:21] Speaker 1: you're interested in. The term reverse prompting is is one
[36:28] Speaker 1: that has made a huge difference. Instead of asking it
[36:32] Speaker 1: a question about something, say I'm interested in this, what
[36:37] Speaker 1: can you tell me about it? Stay open ended with it,
[36:41] Speaker 1: and it'll generate a tremendous amount of data. And then
[36:46] Speaker 1: from there you can start to you know, follow the
[36:48] Speaker 1: bunny trails that are generated by it, because you know,
[36:52] Speaker 1: we all have very finite knowledge, and so giving it
[36:55] Speaker 1: an open ended ability to explain these other things, and
[36:59] Speaker 1: it will very often start to give you suggestions as
[37:03] Speaker 1: to okay, so you know, or or query you so
[37:06] Speaker 1: are you thinking about using this out west on ELK
[37:09] Speaker 1: Or are you thinking about you know, what application are
[37:12] Speaker 1: you actually going toward with this?
[37:14] Speaker 3: Yeah?
[37:15] Speaker 4: And it from there it'll dial you in.
[37:18] Speaker 3: Could it could it? Could it get me a hunting
[37:21] Speaker 3: tags out west?
[37:22] Speaker 1: Maybe it would give you strategies for the best ways
[37:25] Speaker 1: to win the lotteries, and and so that's the yes.
[37:29] Speaker 4: Yeah, like so that that's the.
[37:31] Speaker 1: Thing is the nuance of how to accomplish these goals.
[37:38] Speaker 1: There are so many layers of you know, I'm thinking
[37:43] Speaker 1: about you know, I was telling my kids that they
[37:45] Speaker 1: needed to do something at LSU that was just a
[37:48] Speaker 1: a administrative process, and it was like, Okay, you need
[37:52] Speaker 1: to go downtown to the tops office and this, that
[37:54] Speaker 1: and the other, and they put it in the system
[37:56] Speaker 1: and it was like, no, the first step is actually
[37:58] Speaker 1: to go to the dean's office, save to trip downtown.
[38:01] Speaker 3: Oh, there you go.
[38:01] Speaker 1: Okay, So if you're looking to go get tags then
[38:05] Speaker 1: and you say, look, this is my master plan. This
[38:08] Speaker 1: is what I ultimately want to accomplish. It would not
[38:11] Speaker 1: surprise me at all if it gives you some insight
[38:14] Speaker 1: as to the step of Okay, so you have to
[38:16] Speaker 1: enter the lottery this many times, and therefore the probability
[38:19] Speaker 1: of you getting that tag is you know, seventeen percent
[38:23] Speaker 1: the first year, but eighty seven percent by the sixth year.
[38:25] Speaker 1: So you really need to be planning for this, that
[38:27] Speaker 1: and the other.
[38:27] Speaker 2: And you know, crunching large sums of numbers is one
[38:30] Speaker 2: of the things it.
[38:31] Speaker 3: Does very well.
[38:32] Speaker 4: That's what I use it for.
[38:33] Speaker 2: Right, And so and a lot of these states release
[38:38] Speaker 2: their success rates, the draw tag, all of the stats. Right,
[38:42] Speaker 2: so we go like, Okay, I want to go el hunting.
[38:46] Speaker 2: I don't care about it being a big bowl. I
[38:49] Speaker 2: just want to meet in the freezer. You know, you
[38:51] Speaker 2: give it these parameters. I want to be able to
[38:52] Speaker 2: drive there, and I need it to be this, you know,
[38:55] Speaker 2: all these things.
[38:57] Speaker 4: What outfitters should I be looking at?
[38:59] Speaker 3: Sure?
[38:59] Speaker 1: You know, for my fiftieth birthday, I'm going to take
[39:02] Speaker 1: my son's to Rifles Only. We're going to go have
[39:05] Speaker 1: a private class, do a thing. And it spurred me
[39:09] Speaker 1: to say, are there any other rifle schools comparable Rifles
[39:12] Speaker 1: Only that I should be And it brought up a
[39:14] Speaker 1: school I think in Tennessee that I wasn't familiar with
[39:17] Speaker 1: as somebody who's been to a lot of schools and
[39:19] Speaker 1: done a lot of competitions and whatnot. And it was
[39:21] Speaker 1: one of those like, oh, this is neck and neck
[39:24] Speaker 1: with them, but they're not in my region. The instructors
[39:27] Speaker 1: that I've worked with haven't instructed there. And it was like, okay, well,
[39:32] Speaker 1: Rifles Only is right next to where we hunt, so
[39:34] Speaker 1: we're definitely going to do that, but maybe that's the next.
[39:36] Speaker 4: Place we go and go check that out right.
[39:39] Speaker 1: Yeah, so you know that's the sort of thing if
[39:42] Speaker 1: you're planning a hunt like that, it may well give
[39:45] Speaker 1: you some insights as to you know, look, this guy
[39:49] Speaker 1: has you know, only been around four years, but his
[39:52] Speaker 1: reviews are outstanding, the success rate is very high, and
[39:56] Speaker 1: you know, and but his pricing is half of the
[39:59] Speaker 1: company that you're looking at because or whatever it is,
[40:01] Speaker 1: you know, because they've been doing it thirty years. But
[40:04] Speaker 1: you may want to look at this, you know, this
[40:06] Speaker 1: new option that wasn't even on your radar.
[40:09] Speaker 4: So very cool.
[40:10] Speaker 3: Absolutely, yeah, I'm very useful, Paul. Thanks for being with us.
[40:13] Speaker 3: This is really interesting.
[40:14] Speaker 4: I appreciate your time.
[40:15] Speaker 3: All right, you guys.
[40:17] Speaker 2: I don't know if this was educational or scary, or
[40:19] Speaker 2: entertaining or all of the above, but hopefully was it
[40:22] Speaker 2: was at least fun for a little while.
[40:24] Speaker 3: Thanks for listening, Thanks for watching. We will see you
[40:26] Speaker 3: next time on gun Jog Nature

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