The founder of Raising Cane's Chicken Fingers buys a lottery ticket for all 50,000 of his employees. Observers are baffled by a series of mysterious holes in the ocean floor. Perhaps most disturbingly, a new algorithm created over at the University of Chicago seems to accurately predict crimes a week before they occur -- and exposes deep biases in law enforcement. All this and more in this week's Strange News.
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Episode Transcript
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Speaker 1 (00:00):
From UFOs to psychic powers and government conspiracies. History is
riddled with unexplained events. You can turn back now or
learn the stuff they don't want you to know. A
production of My Heart Radio. Hello, welcome back to the show.
(00:25):
My name is Matt, my name is Noel. They called
me Ben. We're joined as always with our super producer
Alexis code named Doc Holiday Jackson. Most importantly, you are you.
You are here, and that makes this the stuff they
don't want you to know. Uh. If you are, if
you're like us and you scan the news pretty frequently,
(00:46):
then we're sure you are already well aware that there
is a nationwide epidemic apparently of people pretending to play
the violin is a true story. But I got I've
got to say, though, when the one thing that bugs
me about like some films, even if the production value
is super high, Uh, pantomiming of playing instruments is almost
(01:10):
always very bad. Guys. Yes, when I grew up playing
the violin, so it vexes me when I see someone
shredding on the violin in a movie and just clearly
not moving their fingers in the right way at all.
And I imagine this would be the same thing with
these uh, these fraudulent buskers. It's it's the same thing
with any almost any specific physical skill. When you see
(01:34):
it in a film. Often if it's not an action scene,
then experts will be driven crazy watching watching someone acted
out right. That's why the good move for a lot
of films is to teach the actors how how to
at least play parts of a song or instrument and
then just do the cutaway to the hands and boom,
(01:54):
boom boom. But we're not talking to wait, what the
Jamie Foxx performance? What was what was the movie? Um,
Charles Ray Charles documentar or uh biopic? He learned all
that stuff. That's how you do it, filmmakers listening. So
did the dude that played Eddie Munson and Stranger Things
(02:14):
when he did the Master of Puppets scene. He actually
there's video of him learning to play that, so it
really makes a huge difference, even if it wasn't actually
his audio. And then there was the other one. There's
that other uh oh, They're numerous examples, cent your favorite.
For now, we just want to give a special shout
out to all the people actually busting by playing a violin.
(02:36):
We also want to give a shout out to the
sea floor and everything holy about it. You'll see what
you mean. Uh, we want to give we want to
give a shout out to uh the terrifying, the terrifying
uh rise of pree crime, which is probably gonna happen. Now.
We predicted it, and as we said earlier, it's sad.
(02:59):
But usually when we predict a bad thing happening, we
tend to be correct. Just once we want to predict
a good thing. But you know, hope springs eternal, especially
if you are someone playing the lottery in the United
States today segue, Oh, the luck is in your favor,
(03:19):
except it's not ever because that's not a thing, well
maybe a thing. I heard the lottery once described as
a tax on people who are bad at math kind of.
But as we're gonna learn in this uh this segment,
let's call it, we're gonna learn that the lottery can
(03:39):
be a fun and good thing. Uh. And here's why.
If you like chicken fingers, you're gonna love this story.
Shout out to the guys over it. This is important.
They're the reason I even know about the chain we're
going to discuss today. Today's story comes out of CNN,
and it is about a certain franchise owner, a company
(04:01):
owner that purchased lottery tickets for the Mega Millions lottery
for all fifty thousand of his employees. Wow, a good, happy,
nice story. So what really? Yes, let's die the twist
in the darkness. I'm waiting for the other shooting drop
the twist in the dark coming. Ben already kind of
(04:23):
hinted at. But we'll we'll get into it really fast.
So as of yesterday, Tuesday, July, the lottery, the Mega
Millions lottery jackpot hit eight hundred and ten million dollars.
That's a lot of money. So a gentleman named Todd
Graves who is the founder of a little place called
Raising Canes. Uh, this is a chicken finger restaurant. If
(04:47):
you like chicken fingies, this is a place to go.
If you don't like chicken finghies, stay far away because
that's all you gott are They tends as well, I
think tendees fingies, strips. No nuggies, Yeah, no nugs, No nuggs.
You can just you can cut a fingy into fourth
(05:08):
and when you get your nuggies, gotta be change d
I y Seriously, I went on their website. It's literally
chicken fingers, some fries. I think there might be coastal
involved if you get one specific thing. There's Texas toasts
that looked like little hot dog bunts and cane sauces,
(05:29):
the big But you know what, I respect it, Matt.
I respect it because at some point they said we're
going to focus on one thing and we're going to
nail it and do a good I mean, I appreciate that.
I respect it. I'm not necessarily given to it. But uh,
this was just this past Monday, right now, as you
were saying, till over eight hundred million dollars, and I
(05:50):
guess eight hundred million was the threshold for the head
guy of this company to say, all right, I'm gonna
drop what fifty grand, get everybody a one dollar ticket.
Oh no, no, no, no, no no, this is a
hundred grand. So these are mega millions cost two dollars
to buy. That's along with the old powerball, right, five
(06:12):
regular old numbers and then one power ball and you
can you can play whatever numbers you want, or you
can just get them to randomly generate numbers for you
as well. Correct yes, yes, yes, yes, yes, yes you can, yeah,
and you have to use cash. By the way, you
can use a credit card to buy these tickets. And
(06:32):
this person, Todd Graves, founder of this place, did indeed
spend a hundred thousand dollars to buy fifty thousand tickets.
And the concept here was if anyone in the company
won this lottery through one of these tickets, then all
of the fifty thousand employees would share this money, which
is really really nice a cool idea. Again, I think
(06:53):
this is like one of the best ideas that I
that I've heard. Back in the day, we used to
we used to pool our money at ye old how
stuff works, and we would buy lottery tickets and if
any one ticket one within the pool, everybody who played
gets to share the winnings. Um. But we did that internally,
we spent our own money. In this case, it's a
(07:15):
company owner, you know, showing up their own cash as
a possible benefit for the entirety of the company, which
is just really cool. And you know, I think is
interesting about that is that in our situation, which is
common to many workplaces, at least in the States, in
our situation, there was some psychology at play because you
(07:35):
would have you know you've got some change, you got
a couple of bucks or whatever. You don't want to be,
even if you never ordinarily gamble, you don't want to
be the one person who wasn't on the list. And
now everybody work with except for you is a a millionaire.
You know what I mean. It's like the risk aversion
gets switched. So now the founder Graves has done something
(07:58):
really interesting. He's basically giving everybody two bucks and the
chance to have much more, so you don't have that
same fear motivator. I think that's cool. I think it's
a neat gesture. Unless there's like more to this story,
it's a bold move on his part two because if
you know, if everyone, if there is a win, he's
gonna be out an entire workforce. I mean, that's no,
(08:21):
there's okay, there's caveats, Okay, Okay, this is why. Okay.
So when you win a large lottery like this, you
have two options, especially here in Georgia, and I'm pretty
sure it's for every place that plays this mega millions lottery.
You can either take payments that will be sent to
you like kind of like a paycheck basically, and they
(08:43):
increase in amount over time to adjust for inflation, but
it would just be you'd be getting smaller, much much
smaller payments over time. Or you can cash out and
you just take a huge cash some and at that
point the full thing, the full amount is taxed. So
the estimated cash value of that eight hundred and ten
million dollar jackpot from yesterday was in fact around four
(09:06):
hundred and seventy point one million dollars at least according
to CNN. And that means if you divide that up
by the fifty thousand employees that would be getting a share,
you get around nine thousand, four hundred dollars for each
individual person, Okay, which was that's no, that's no small sum, right,
(09:27):
my goodness, nine nine point four grand just as an
extra thing coming to you, that would be amazing, right. Uh,
But it's not the same as everybody's like, I'm out
of here, um, no more raising this cane. I'm gonna
go to Chick fil a. I guess no, I don't know.
I don't know how you presumably, how dare you go
(09:50):
to Chick fil a? Judas I say, well, they have
more than one sauce, I mean they do. I like
that Polynesian sauce. You can actually buy that bottle that
the crow around here which you homophobia is what it
sounds like. Yeah, live for it now, very very streamlined operation.
(10:11):
They do say, they say my pleasure too much. That
weird to me out, But no question is the idea
the idea here? I guess is that you know, with
fifty thousand uh tickets in the game, you know you
you you raise your odds. I guess if were they
all randomly generated? Is that how he played it there?
What was the idea? And what are the logistics of
(10:32):
buying fifty thousand lottery tickets with cash as a single
human being? How do you even get them? Yeah? I
I don't have all of that information. All we know
from that CNN article is that it was difficult to
buy fifty thousand lottery tickets. I tweeted that it's harder
than you think. Yeah, yeah, exactly. Um, I'm assuming it
(10:55):
was through some kind of cashier's check. I'm imagining, because
that's that whole thing is got to be weird. You
certainly do kind of raise the odds. Except for as
we discussed before, and Ben, I'm gonna lean on you
for this just a bit every time you play, especially
if you're randomly generating numbers, you have the same odds
(11:15):
every time you play the lottery, essentially, is what I'm saying.
And it's one in three something million, some ridiculous number. Um,
a crazy flow chance that you would actually win this
lottery no matter how many times you play. It's weird, Okay,
So maybe a way to explain it is, uh, you
(11:35):
know how gravity is just a little bit different if
you're in very very very very elevated places. But it's
a very very very small change. You can use that
analogy to think about the way the lottery works. So
if your chance is, for instance, one in just twenty
(11:56):
nine point two million, that's a that's a number I
saw in a statistics article on this, then you can
up your odds by buying ten tickets. You spent way
more money than you meant to, and in exchange for that,
your odds go from one in twenty nine point two
million to ten in twenty nine point two million. It's
(12:18):
like it does have an effect, but it is so
small you can only call it technically improving your chances.
It's kind of like how, um, if you if you're
running late and you try to speed on the interstate.
You can shave a couple of minutes off, but you're
probably still going to be late. If you're already like
more than fifteen minutes late, it's probably not gonna happen,
(12:41):
you know what I mean. Yeah, so, statistically, you're not
really raising your odds, even even though you technically are.
You are a little bit. Yeah, you are a little bit,
but it's um not significantly. To do it significantly, you
would have to, you know, by millions of lottery tickets.
(13:01):
But to this point, I think we're going well. You also,
you'd also have to make sure that none of those
none of those sets of numbers are repeating increase your odds.
But with that, but if they were randomly generated, right,
that's what I was going to say. If they're randomly generated,
they're not the odd like the odds of those same
numbers being randomly generated in that string that is winning
(13:26):
just another crappier lottery basically in terms of the odds. Right, So,
uh so I think it's I mean, I still like
it's a good question. Fifty fifty thousand tickets, to what
degree does that increase your odds? Right? If it's one
iteration or one instance each. Still, I don't think, you know,
(13:47):
if you're comparing millions to tens of thousands, it's not
a huge bump. But it is still a really nice gesture, right,
and not not to be cynical about it, but it's
a damn fine PR move for a small company that's
you know, a single owner who presumably treats his employees
(14:08):
better than you know, larger fast food chains. They're not
infinite numbers of these. There isn't one in Georgia or
in Atlanta currently, um there, you know, there's there's a
limited number of them, and so I think it's more
of that, like, see, we take care of our people.
We were all in this together. You know. It's definitely
I mean obviously got picked up you know, far and
wide this story. Yeah, it really did. You're correct, it's
(14:29):
a great PR move. Sadly, guys, it is Wednesday as
we record this, and uh, nobody won, not a single
person one the major jackpot all six numbers. Uh. Oh
and and by the way, according to AP, the chances
of winning all six or getting all six numbers correct
(14:50):
is one in three d and two point five million,
which seems like, uh okay, thinking it's thinking it's a
love but that means you, guys, in between the time
that we are recording this right now and the time
that this comes out on Monday next Monday, which is
(15:12):
today when you're hearing this, somebody may have won that lottery.
And the founder of Raising Kanes has said he's going
to play again, and he's going to keep playing until
he wins, or until someone wins, until someone wins, because
imagine like dropping a hundred thousand dollars twice a week.
(15:33):
Chicken fingers. It's so many chicken fingers. Al Right, guys,
we don't have to talk about this too much more,
but there are a couple of places you can go
to to learn more about the lottery. Not long ago
we talked about I think it was a woman who
dreamed about numbers and then play the lottery in one
was a while ago, um, but we we brought up
(15:55):
some of the same things I wanted to bring up today,
but I don't think it's necessary. You can go to
every state's lottery website and check out. Usually they have
a section called where the money goes. So if you
go to g a lottery dot com, you can navigate
to their where the money goes section and you can
actually see how much money is spent on uh. You know,
(16:18):
employees who work for Georgia Lottery on their overhead, basically
how much they they spend on their staff with the
money that's brought in by these lottery tickets. It shows
you how much money is paid out to players, and
how much money is paid to retailers so people actually
sell the lottery tickets, and how much money actually goes
to education. And in the state we live in in Georgia,
(16:41):
in fiscal year one, Georgia Lottery gave one point five
four billion dollars in funds to education, which includes things
like the Hope Scholarship that allows children to go to
college here in Georgia and in every state has things
like the Hope scholar Ship, not necessarily the exact same thing,
(17:01):
but things like that when it comes to funding education
in their state. Uh. Texas is the only place that
was really weird. I couldn't find exact numbers on the
Texas Lottery stuff they want, you know, Matt, Matt, what
is it that causes the pot to get so much
bigger when we have these historically large lottery pots, more
people play. Yeah, right, that's it. I mean, because as
(17:23):
that number gets bigger, more people are like, all right,
I've reached my threshold of going mine as well. Waste
five dollars, ten dollars, whatever it is, two dollars, feedback
loop and the and the cost that makes senst risk
analysis or the cost benefit analysis changes because the the
infinitesimal chance of winning is more attractive as there's more
(17:47):
and more stuff. And if you're listening, and if you
won by the time this comes out, uh, congratulations. Just
give you a couple of quick tips. Don't tell anyone,
don't tell us, don't tell your family. Honestly, I'm gonna
say it, this might be a hot take. I would
think very carefully about telling your romantic partner. Also, don't
tell your children. Literally omerta for for the rest of
(18:09):
your life. That's the only way to do it. Make
a trust fund for each kid, put most of it
in there, and then enjoy what you got lord like
like gust spring or something. You know, you just gotta
really Uh yeah, it's such a weird curse to all
of a sudden that much. Don't take your job, you
(18:32):
know what I mean? Keep showing up to work for
at least like a year. Seriously, you know, it seems
like a long time because you're a billionaire now or
you will be. And then also obviously don't take the
lumps some at all. Don't do it unless you have to. Yeah,
speaking a billionaire. The Friday drawing that's occurring, you know
again that just occurred when you're hearing this. It is
(18:54):
over one billion dollars, were right about one one point
zero two billion, which is nuts. And and this has
been our giving advice for things that will never happen segments, Well, statistically,
it will happen to someone because someone will win. I
guess what was the most recent payout. It wasn't It
wasn't insane, It was just a couple of mill Like, wait,
(19:15):
what's the largest historical lottery payout that's ever happened? I
think it was one point five billion that was but
individual it can be that can be split sometimes too. Yeah,
but that's the that's the amount, right, that's the prize
amount and then the cash out amount, like like for
this one that's happening, it's it's valued at one point
(19:38):
oh two billion dollars, but the actual cash out number
is six hundred and two point five million. Got it? Yeah,
so made fortune favor the bold, right, Uh, and you know,
insert different Hunger Games quotes here. But don't let the
money change you. Listen, folks, a great amount of fame
(19:59):
or success, financial, social, whatever you wanna call it it. Uh.
It doesn't necessarily make people bad. It just allows them
to be more concentrated, transparent versions of who they were
in the beginning. So don't let it touch you, you know.
And at the towns people start approaching you with rocks
and their clenched fists. Runaway. There you go, guys, next time,
(20:23):
maybe even a full episode. There's a great story out
of the Grillo and it's discussing how much the state
lottery board makes for every one dollar they spend on ads.
So like the lottery board takes in around a hundred
and twenty eight dollars for every one dollar they spend
on ads, which think about that the amount of gains
(20:46):
you get for putting out just um promotion for your lottery. Hey,
come on, play the lottery, you might win. You ever
roll the dice, you might win, and there bucks back
for everyone. They it's just a lottery episode. Let's do it.
The time has come. I'll gamble on that. I bet
it'll be interesting. That's what I'm betting to. All Right,
(21:08):
we're gonna leave for now, hear words from our sponsor,
maybe the lottery, and we'll be right back with more
strange news. And we've returned with some strange news from
the bottom of the sea. To take a quick diversion,
have you guys seen the movie Sing We Sing Too,
(21:31):
perhaps with c g I animals that sing like popular songs. Um.
I only bring this up because I recently watched Sing
Too and was very pleasantly surprised to hear a song
pretty prominently featured by a little remembered band called Mercury
rev Um, who, in my opinion, sort of had that
(21:52):
flaming lips sound that like post you know um clouds
taste metallic flaming lips sound like the soft bullets and era.
They had that sound on the lock before the flaming
Lips ever even you know touched it and they have
the same exact producer, a guy named Dave Fridman. So
I I like the flaming lips, I like that era,
but I really feel like they kind of eight mercury revs. Lunch.
(22:13):
And there's a song in scent too. It's quite beautiful
called holes. Um. And I always really just tickled when
it when it came on. UM. So yeah, this this
is about holes at the bottom of the seed. There's
an article on Vice that cited a report from the
National Oceanic Atmospheric Administration, a federal agency that studies weather
(22:35):
at the sea and things like that. This is specifically
a wing of Noah that does oceanic exploration. Uh. And
they had this to say via a tweet on Saturday's dive.
We saw several sublinear sets of holes in the sea floor.
The origin of the holes as scientists stumped. The holes
look human made, but the little piles of sediment around
(22:58):
them suggest they were ex ai aided by something. What's
your hypothesis? And it's true there are these neat and tidy,
little evenly spaced out rows of holes. Um. And I
learned a new word by the way from this, uh,
this Noah reporting. Uh. It's called leben spurring or laban spur,
(23:19):
which sounds vaguely German to me, which is a term
for biological formed structures things like holes or burrows or
mounds and then the like. Um. But here's the thing.
They could have been made perhaps by some sort of
crab or or or lobster or something with sort of
like a probing kind of like pointy you know, appendage. Um.
(23:44):
But upon further exploration and close up photography again, this
is a mile over a mile under the ocean. Sorry
not again, I haven't told you. It is in the
mid Atlantic Ridge area of the ocean, which is deep, deep,
deep dark shan, which is essentially might as well be space.
I mean, the reason they're exploring the stuff is because
(24:05):
it holds all kinds of as of yet undiscovered things, um,
certain species of sea creature. Ben, you had mentioned that
you went down a sea creature rabbit hole recently because
of some of the new ones that have been discovered
from this very type of exploration, right, yeah, right now.
The weird thing, and I think I mentioned this before,
the human species actually knows more about the surface of
(24:28):
the Moon than it does about the oceotic depths, you know,
once you get to the very bottom. And so if
you are a fan of cryptids, if you hold out
hope that uh, there are more creatures yet to be
discovered than the deep sea is one of the places
to start. There's actually, uh, the one that I was
(24:50):
talking to you about that messed up my research, some
of the research I was doing this after dude, I
totally stopped and learned too much about a rare tentacle
looking creature that scientists just discovered at the bottom of
the Pacific Ocean. I'll throw it in the chat so
you guys can get a little grossed out as we're
(25:13):
talking about this. But but yeah, right, vaguely extraterrestrial appearance. Right,
It's like someone grabbed the top of an octopus or
squid and then just sort of taffy pulled it out
into this long trail and then said, Okay, yeah, that's fine.
It's a spen. These are real things. Spens are already
(25:35):
a known thing, but this is like a new possibly
a new species. But all of this justice saying they
are continually, uh, strange discoveries being made at the ocean depths.
And that's why, at least with this story. No, I
would totally not be surprised if there's a mundane explanation,
but I would also totally not be surprised if it
(25:57):
was something brand new, because these do look. Uh, they're
curring at a regular interval like they look purposefly perforated.
There we go. Uh, I everything you're saying about this creature,
it's given me flashbacks. I just watched Nope, no spoilers,
no spoilers, but I just watched the movie Nope, And uh,
(26:22):
have you guys seen it yet? I'm very excited to
see it now. I talked to another friend today who
saw it and and said they absolutely loved it. So
I'm looking forward to it. I haven't seen it, but
you know me, I I read everything about it, so
I haven't. I like, I'd like Peel enough to not
spoil his stuff for myself because he's sort of like
he's like Shamlan but like, you know, good and then
(26:43):
we has an outstayed as welcome, and Shimlan was good
when he was good. But I just think he's kind
of like he's uh, his twists have gotten a little
bit repetitive and and predictable, whereas I think Peel has
always managed to surprise me. I really liked get Out obviously,
and and us, um here's the thing, there was actually
another Oh sorry, I was I sort of backtracked a
little bit too to describe where this was. Uh, this
(27:07):
discovery was found, um, and I didn't mention what was
said about They could have been made by you know,
certain types of sea creatures. But there's blind lobsters that
lived down There's something called squat lobsters, different types of
you know, subterranean deep deep sea dwelling crustaceans that have
little pokey diggy things. Um. But upon close ups and
(27:28):
further inspection, Uh, there weren't any signs of of living organisms, um,
inhabiting the holes, the researchers said. Um. They go on
whether the holes were connected beneath the sediment surface was
not visible. We hope that future studies of the laban
sporing Uh forgive me if I'm mispronouncing that we report
(27:48):
here will resolve the mystery of what created them. Um.
And this has actually happened before. In two thousand three,
scientists and investigating the same area published a study in
the journal Frontiers and Marine Scientists, and they found similar
types of you know, anomalous kind of holes. They were
described as raised sediment around these holes that indicated they
(28:11):
could have been dug out by deep sea crustaceans. Like
I said, um or perhaps excavated by animals living inside
the sea floor, but the authors were left with without
a definitive answer um And and we're basically just as
stumped as the scientists with noah have been about this
current run um. So I don't know. I like the
(28:32):
idea that it could be some mysterious creature that's doing it.
I like the idea that they had. The idea that
it's man made is interesting to me. And that was
actually in the in the headline for the Vice article
by Becky uh Ferrara, which I think is a little
bit of a bait and switch. But they did say
it look human made. They didn't really go back to
to justify that or quantify that at all. Sort Of
(28:54):
an odd thing to say without any context, but definitely
got my imagination running wild. We're not talking about somebody
diving down there, and yeah, why unless you're James Cameron
or you know, like the government, you can't get down
here because no, there's no casual exploring the c floor
(29:17):
um of the mid Atlantic Ridge. I will warn folks,
mainly because it gives me an excuse to use this term,
this word I never get to use. If you experience
uh tripophobia or a fear or discuss the patterns of holes.
This may not be the article for you. God, I
love the English language. There's so many words that will
(29:39):
just will never use, like, yeah, these holes are all
totally thankfully, these holes as all in a line and
they're not like clusters. Those are the ones that really
set off people with that with that condition, there's actually
an episode or a season of American Horror Story, which
is not always great, but there's a season where it
(30:00):
revolves around characters deepest fears and triple phobia is one,
and they you know, in typical Brad Felt, Chuck and
whatever that other guy's name is fashion, they go way
over the top and depicting what the people are seeing
who are freaked out by holes pretty gross. What if
you got a little philosophobia, which let's go through more phobias,
(30:22):
let's do some phobia born I think lorophobias. But if
you don't have that condition, if you're a deep sea
investigator and you see this trail of holes and all
of a sudden you see a clown, you get chlorophobia
pretty quick just standing there, you know, arms akimbo, and
it waves to you. I think, right, deep seed clowns.
(30:46):
Why is that not yet? God deep sea clowns with wings?
That would freak me out. I have or phobia. I
don't know why. That feels like a lounge in number
to me. And maybe in a David Lynch. And also
that super producer Alexis code enamed Doc Holiday. Jackson pointed
(31:07):
out that Holes on the Ocean Floor would be a
really good name for like an emo or post rock
type band. So yeah, don't steal it. Yeah, I think
post rock is great. Don't don't steal it. Conspiracy realist.
Let let Alexis have this named doc is gonna invite
us to the show next week, she said, So yeah,
I'm I'm hoping for some very plodding, slow instrumental jams. Okay,
(31:31):
you just have to wait and see. Yes, Doc, I'm
gonna buy some shoes specifically for gazing at your show.
Let's not get it twisted. That would be more of
a post rock shoegaze kind of situation, and they're not
mutually exclusive. But they also don't always have to belong
to you. It's a big diagram that's getting the specific
shoes you know they need the top of the shoe
(31:52):
needs to be essing like clown shoes. What about clown shoes?
My feet are now you're to U. Yeah, my feet
are basically hands, So I don't want to add more.
It's more shoe to look at, you know. That's what
I That's what I say, more shoe to look at.
But then also you have to stand really far away
from your massive pedal board, you know, and i'd be
(32:13):
really hard to hit those buttons with the with the
tip of that giant shoe, whichould get pretty broad at
the top. You'd be like slamming all three pedals, which
actually might be desirable. Uh, you know, if you're one
of those uh, you know, pedal heads. Anyway, this is
an interesting one. UM. Thank you all for chatting it
through and uh and indulging um the speculative kind of
bent in this story. UM. But I look forward to
(32:34):
hearing more, um, you know, because these scientists still seem
to be kind of baffled, and hopefully they'll come to
some conclusion and share with the class. But in the meantime,
let's take a quick break here, a word from our sponsor,
and be back with one more piece of strange news.
And we've returned, So best of luck to the good
(32:59):
people at Canes, and best of luck to the scientists
doing tremendous, mysterious work there at the ocean floor. Our
last story is a prediction that has come to pass.
For many years when we talk about big data, big data,
whatever your preference may be, we've often pointed out the
(33:23):
imperfections of applying technology to predicting the actions of human beats.
We've also, not for nothing, sort of internalized the cautionary
tale of minority reports, the idea that predicting crime, even
when it seems to be accurate, can be dangerous and
(33:44):
can have unintended consequences. Well, as we record today and
as you hear this on Monday, it happened, we're at
the dawn of pre crime right now. There's a great
study came about University of Chicago, which is frankly terrified.
These very clever researchers have created an algorithm that, according
(34:06):
to them, can predict crime a week in advance with accuracy.
That's the headline before we go on, Do you guys
believe it? What data are they using? What are they
feeding into the thing? Is it? If it's social media? Well, like, really,
(34:27):
if it's social media posts that are private somehow, or
really I don't know, maybe their public posts, but they're
just monitoring specific things. I think you could probably predict
some mass shooting events if you had the like, the
most granular data on everybody. But you know, I mean
(34:47):
on social media, everyone is just portraying the rosiest version
of their psychopathy, you know. I mean they want everyone
to think they're the best, sweetest, happiest psycho in the world.
I mean, nothing on social media has actually should be
taken a phase value, right, I'm kidding. Obviously people use
it for all kinds of reasons, but it makes me
think of there's an Atlanta rapper now I'm forgetting his name,
(35:08):
but he got wrapped up in some gun charges. I
don't remember. I'll figure it out a second, But the
point is, uh, and this might ring a bell for y'all.
They used his lyrics uh to as evidence against him,
which obviously isn't it the same as pre crime? But
I wonder if you could use that, you know, for
as a form of pre crime. You know, someone is
(35:30):
rapping about something that maybe as a fantasy, you know,
or it indicates where their minds, their headspaces. Maybe that's
something you could use someone's art against them. Well, this
happened to other performers, to other musicians. There. There's also
a fantastic key and Peel sketch about this. I will
(35:52):
send it to you all if you haven't seen remember this.
I like it's like the five and just yes exactly,
but it shows that beautifully right. But there's a good
question where they're getting Where are they getting the information
that they are feeding the algorithm. They are using publicly
(36:16):
available data, So this would be reports of crimes. Uh,
this would be any imaginable demographic metric of a community
and what they what, what kind of stuff we're talking about.
Just to give you a brief laundry list. This is
pulled from the history of the city of Chicago, and
(36:38):
they had too broad categories that they were testing the
tool against. Once they fed all this junk into it,
they wanted to see what they could predict. Their two
buckets are one violent crimes, homicides, assaults, batteries, you know,
all of those. And then property crimes burglary, theft, grand theft, auto,
all the hits and these these particular ones were used
(37:03):
because they were most likely to be reported to police
in those areas because as anyone who's lived, you know,
on the edges of different things, knows, many crimes never
have the police involved, right, and it's just sort of
understood between the victim and the perpetrator, even when they
(37:24):
switch sides and revenge schemes, you know. But they also said, Okay,
these are going to be reported in urban areas where
there is historical distrust and lack of cooperation with Johnny law.
They still they thought, Okay, even if you don't like
the cops, you're still gonna say, hey, someone stole my car.
So we know that because of that, there's a high
(37:46):
likelihood that the number of crimes that have occurred in
that regard are is very close to the number of
crimes that are reported, meaning the data is more solid, right,
especially more solid than something like drug times or some
misdemeanor in fractions, because those are prone to what's known
as enforcement bias, which is exactly what it sounds like.
(38:08):
We don't have to overthink it. So this the PhD
senior author of the study, uh Ishano Chado Padhai uh
in part of my mispronunciation of getting this wrong, has
said that this tool is different because it takes in
the complex social environment of cities, and it also considers
(38:28):
the relationship between crime and the effects of police enforcement.
It's pretty smart. It divides, so picture yourself playing like
uh SimCity or Civilization or something. It divides the city
of Chicago into tiles. They're pretty small, about a thousand
feet across, and it predicts crime within those areas instead
(38:53):
of relying on traditional boundaries of like neighborhoods or political districts,
because those are all of subject to bias. It did
this in Atlanta, in Austin, Detroit, Los Angeles, Philadelphia, Portland,
and San Francisco in addition to Chicago. So they tested
this in a couple of different places and what they found,
(39:16):
and what seems to be true is that they yes,
they can predict crime about a week in advance, so
that like about a week in advance with accuracy, they
can take what happened in the past, and then through
this algorithm they can they can run it through this
thing with all these other intervening variables and then it
(39:38):
will tell them like, hey, the specifics are a little
tough for me. But then we'll say something along the
lines of, hey, they're gonna be x number of cars
stolen next week or something like that. I don't know
how predictive they can be or how sophisticated. I don't
know if they could say in two thousand four green
Honda Odyssey right with a with a crappy transmission or
(39:59):
anything like that. Do they have to have info on
the people, like specific to the people, like psychological profiles
or any information that that that's specific to individuals or
is it more big picture and like you know, like
that's a really good point bend civilization or like some
city like a top down kind of view where the
individuals are less important than just the way the complex
(40:22):
system of it all. Kind of yeah, I don't I
don't think it has a right it's if you're we're
just talking about the overlay of the city, right, look
at it like a grid and like here's when things
happen and exactly where within these little specific parts of
the city. And I don't know that it's so weird
to ben. I don't see how you can make it actionable,
(40:43):
like who can Like who cares if we know that
five cars are gonna get stolen in the next few days?
Are we talk about this on The Boys? The Boys
in that show that like The Seven, they have these
you know, this department that looking into crime and someone
makes a comment, they can usually predict a crime like
(41:04):
a week or so before it happens, So it's you know,
similar kind of data that they're crunching. It also reminds
me of this anime called psycho pass Um that is
more about the individuals where they can actually they're taking
measurements of the citizens of Japan's you know, biometrics of
their brains and generating these they call them sematic scans
(41:24):
that allow them to with a pretty high degree of certainty,
predict who will be potential criminals, you know, criminal criminality.
Potential is the term they use, and they get color
coded on a map. But the dangerous is that this
is science fic. Well, there's there's something very dangerous with
all these things and their historical precedents. Right, law enforcement
(41:46):
throughout all civilizations, various versions of law enforcement were attempting
to predict crime, and their rubric for this although it
varied widely, it was hardly scientific and most times it
was really rooted in xenophobia, in racism, in some other
form of discrimination. Right. Uh So, the question is how
(42:09):
much of that has descended to this program. And if
you look at the research just got published in Nature
Human Behavior, and what they found was a twist to
the plot, but Shamalan twists, you could say, and I
don't think it's that bad. But they found that this
thing could accurately predict crime, especially in Chicago. But it
(42:32):
also laid bare some heavy biases in police responses. They
found stuff like if you stress the system, that's what
the senior author calls it. It requires more resources to
arrest more people in response to crime in a wealthy area,
and that almost always draws police resources away from areas
(42:56):
with lower socioeconomic status. So police are paying more attention
to the quote unquote good parts of town. They're also
working kind of in response to earlier experiments from Chicago
p D or associated with Chicago Police Department. UH. A
while back, the Chicago p D tried another algorithm that
(43:19):
created a list of people deemed most at risk being
involved in a shooting, and it turned out that over
half of the black men in Chicago between twenty and
appeared on it. So this is why the people who
made this new algorithm, this new AI algorithm, are really
(43:41):
concerned that the data that they're using in their model
may be biased, which therefore means to your point, Matt,
that the conclusions it creates will be biased. And they
also said, just to answer another couple quick questions about
how far into the dystopio we are, they also said
that the algorithm, the AI does not identify specific subjects. Right,
(44:07):
So it's not it's not saying Paul mission controlled decand
is out on another loose diamond heist over at Zails
or whatever is in your neck of the woods. Folks
there used to be Shane Company here. The commercials were hilarious. Instead,
instead of identifying specific subjects, identifies potential sites of crime.
(44:30):
And they've released the data and the algorithm. They didn't
keep it proprietary. They released in the public sphere because
they want other researchers to check out its reasoning, its conclusions.
They want to test it. And then one thing that
really caught me is I was comparing this to previous
previous kind of DARPA work or DARPEST sponsored excuse me
(44:53):
work with creating virtual models things like Afghanistan or other
communities or other areas of the world, you could say,
and their idea there which was pretty like frighteningly successful.
Their idea was that if you can create a simulated
version of a place with enough sophistication, with enough fidelity,
(45:17):
if you have enough information about it, then you can
plug in changes right in your make it up seas universe,
and then what happens as a result of that in
this virtual environment will be very close to what happens
in the real world with the same set of actions.
(45:37):
So that's what they have done. They said, We've made
this thing that is close enough to the actual city
of Chicago or those seven other cities for our purposes
that when we feed it data from the past, it
tells us what will happen in the future, because like
a love Craft in Elder God, it sees beyond time.
(45:59):
They and say that last part I added that in
for a little bit of editorial, you know style. But
he also said it's not magical, it has limitations quote,
but we validated it and it works very very well.
So if that's what's happening, if we have a kind
(46:21):
of a thing that's kind of like a a precog
precognitive bloodhounds for geography of crime, how far along a
slippery slope are we Do you guys think this would
get deployed in uh in other cities or get used
past the experimental proof of concept phase. I mean, I
(46:41):
think people in the real estate industry would be very
interested to have this information. Yeah, oh yeah, I can
imagine that when it comes to how like how much
they could charge or how little they should charge for homes.
Everything part of it for the buyers and the sellers,
you know, if you know, like because there are crime ratings, right,
(47:03):
safety ratings, who might be called by zip code? Um,
maybe that's maybe that's not the best example. I don't know.
It's just like, if you have that statistic, why what's
the stop please from just saying, okay, we're going to
pretty much garrison people in these things for a week. Yeah,
I don't know if that's smart. Yeah, now I get it,
(47:24):
or or like set up points of entry, you know,
like roadblocks kind of like you know, I mean, that's
it sort of takes the sport out of it, doesn't
I don't mean to sound flipping like that, just you
know what I mean. Anyway, I'm just gonna go back
to what I my thought in the beginning of this then,
and that is, if you take this the models they're
creating in the statistical analysis that they're doing, and you
(47:47):
combine that with something like sesame credit or something that
is very closely monitoring social media and purchases and interaction
like in interpersonal interaction on that way and generating that
data set. If you combine those two things, that's when
you get actual pre cog pre crime insanity. Right, You
(48:08):
just have to you know, I was thinking about the
same thing, man, because if you look at your phone,
a lot of people are listening to this on their phone, right,
So you look at your phone right now, and imagine
it's not just as a single invention, but imagine it
as a multitude of separative inventions that have been combined
(48:28):
to create something amazing. That's how these sorts of innovations occur.
That's what pre cog and pre crime stuff will be.
It will be like your phone, It'll look like one
thing in the end, but it's really going to be
uh mass and aggregation of innovations like this, is this
good will this maybe save lives? Of course that's the hope, um,
(48:53):
But that part is up to society at large. And
I want to shout out the science tis involved who
did excellent work on this study and on this algorithm,
because they're incredibly conscientious about this is very much a
case of them having done everything they can do, you
know what I mean. They can't start a vigilante squad
(49:15):
and go try to save a Honda Odyssey for some reason. Also,
why would you? But yeah, but but but I do
think it's worth everybody's time if you're interested in this.
I know we have a lot of thoughts on this,
folks um, fellow conspiracy realists. I would recommend checking out
(49:36):
the study firsthand and then reading what people have written
about it. The title is event level prediction of urban
crime reveals signature of enforcement bias in US cities, So
they put it in the title. It came out at
the very end of June Nature Human Behavior. That's the journal. Uh,
do check it out. Would love to hear your thoughts.
(49:56):
I would love to hear your take on Kanes. Would
love to hear what you think about the lottery. And again,
you know, we want your opinions on what lurks at
the ocean's depths. We want you, specifically, you conspiracy realist, no,
not that person next to you. You to write in
be part of a show. Join us for our listener
(50:18):
mail segment. As a matter of fact, the only person
we don't want to hear from if you recently won
a lottery, don't tell us, keep it secret, keep it
safe otherwise for everybody else. We try to be easy
to find online. Correct. You can find us all over
the internet. We are conspiracy stuff on Facebook, Twitter, and YouTube,
Conspiracy Stuff show on Instagram. Hey, and if you did
(50:41):
win the lottery, why not chip in by about I
don't know, four hundred thousand copies of our new books
stuff they don't want you to know. We can distribute
them across the planet together, diary of hearing about it.
It's like it's a it's pledge drive rules you know
were and are. Just get the book and then we
(51:01):
could stop talking about That's it. I'm sorry. You can
also reach us my phone. Our number is one h
three three st d w y t K. Tell them
about it, Ben, that's right. You will hear a hopefully
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(51:23):
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Tell us what's on your mind, let us know if
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(51:45):
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All you have to do is send us a good
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(52:19):
know is a production of I heart Radio. For more
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From UFOs to psychic powers and government conspiracies. History is
riddled with unexplained events. You can turn back now or
learn the stuff they don't want you to know. A
production of My Heart Radio. Hello, welcome back to the show.
(00:25):
My name is Matt, my name is Noel. They called
me Ben. We're joined as always with our super producer
Alexis code named Doc Holiday Jackson. Most importantly, you are you.
You are here, and that makes this the stuff they
don't want you to know. Uh. If you are, if
you're like us and you scan the news pretty frequently,
(00:46):
then we're sure you are already well aware that there
is a nationwide epidemic apparently of people pretending to play
the violin is a true story. But I got I've
got to say, though, when the one thing that bugs
me about like some films, even if the production value
is super high, Uh, pantomiming of playing instruments is almost
(01:10):
always very bad. Guys. Yes, when I grew up playing
the violin, so it vexes me when I see someone
shredding on the violin in a movie and just clearly
not moving their fingers in the right way at all.
And I imagine this would be the same thing with
these uh, these fraudulent buskers. It's it's the same thing
with any almost any specific physical skill. When you see
(01:34):
it in a film. Often if it's not an action scene,
then experts will be driven crazy watching watching someone acted
out right. That's why the good move for a lot
of films is to teach the actors how how to
at least play parts of a song or instrument and
then just do the cutaway to the hands and boom,
(01:54):
boom boom. But we're not talking to wait, what the
Jamie Foxx performance? What was what was the movie? Um,
Charles Ray Charles documentar or uh biopic? He learned all
that stuff. That's how you do it, filmmakers listening. So
did the dude that played Eddie Munson and Stranger Things
(02:14):
when he did the Master of Puppets scene. He actually
there's video of him learning to play that, so it
really makes a huge difference, even if it wasn't actually
his audio. And then there was the other one. There's
that other uh oh, They're numerous examples, cent your favorite.
For now, we just want to give a special shout
out to all the people actually busting by playing a violin.
(02:36):
We also want to give a shout out to the
sea floor and everything holy about it. You'll see what
you mean. Uh, we want to give we want to
give a shout out to uh the terrifying, the terrifying
uh rise of pree crime, which is probably gonna happen. Now.
We predicted it, and as we said earlier, it's sad.
(02:59):
But usually when we predict a bad thing happening, we
tend to be correct. Just once we want to predict
a good thing. But you know, hope springs eternal, especially
if you are someone playing the lottery in the United
States today segue, Oh, the luck is in your favor,
(03:19):
except it's not ever because that's not a thing, well
maybe a thing. I heard the lottery once described as
a tax on people who are bad at math kind of.
But as we're gonna learn in this uh this segment,
let's call it, we're gonna learn that the lottery can
(03:39):
be a fun and good thing. Uh. And here's why.
If you like chicken fingers, you're gonna love this story.
Shout out to the guys over it. This is important.
They're the reason I even know about the chain we're
going to discuss today. Today's story comes out of CNN,
and it is about a certain franchise owner, a company
(04:01):
owner that purchased lottery tickets for the Mega Millions lottery
for all fifty thousand of his employees. Wow, a good, happy,
nice story. So what really? Yes, let's die the twist
in the darkness. I'm waiting for the other shooting drop
the twist in the dark coming. Ben already kind of
(04:23):
hinted at. But we'll we'll get into it really fast.
So as of yesterday, Tuesday, July, the lottery, the Mega
Millions lottery jackpot hit eight hundred and ten million dollars.
That's a lot of money. So a gentleman named Todd
Graves who is the founder of a little place called
Raising Canes. Uh, this is a chicken finger restaurant. If
(04:47):
you like chicken fingies, this is a place to go.
If you don't like chicken finghies, stay far away because
that's all you gott are They tends as well, I
think tendees fingies, strips. No nuggies, Yeah, no nugs, No nuggs.
You can just you can cut a fingy into fourth
(05:08):
and when you get your nuggies, gotta be change d
I y Seriously, I went on their website. It's literally
chicken fingers, some fries. I think there might be coastal
involved if you get one specific thing. There's Texas toasts
that looked like little hot dog bunts and cane sauces,
(05:29):
the big But you know what, I respect it, Matt.
I respect it because at some point they said we're
going to focus on one thing and we're going to
nail it and do a good I mean, I appreciate that.
I respect it. I'm not necessarily given to it. But uh,
this was just this past Monday, right now, as you
were saying, till over eight hundred million dollars, and I
(05:50):
guess eight hundred million was the threshold for the head
guy of this company to say, all right, I'm gonna
drop what fifty grand, get everybody a one dollar ticket.
Oh no, no, no, no, no no, this is a
hundred grand. So these are mega millions cost two dollars
to buy. That's along with the old powerball, right, five
(06:12):
regular old numbers and then one power ball and you
can you can play whatever numbers you want, or you
can just get them to randomly generate numbers for you
as well. Correct yes, yes, yes, yes, yes, yes you can, yeah,
and you have to use cash. By the way, you
can use a credit card to buy these tickets. And
(06:32):
this person, Todd Graves, founder of this place, did indeed
spend a hundred thousand dollars to buy fifty thousand tickets.
And the concept here was if anyone in the company
won this lottery through one of these tickets, then all
of the fifty thousand employees would share this money, which
is really really nice a cool idea. Again, I think
(06:53):
this is like one of the best ideas that I
that I've heard. Back in the day, we used to
we used to pool our money at ye old how
stuff works, and we would buy lottery tickets and if
any one ticket one within the pool, everybody who played
gets to share the winnings. Um. But we did that internally,
we spent our own money. In this case, it's a
(07:15):
company owner, you know, showing up their own cash as
a possible benefit for the entirety of the company, which
is just really cool. And you know, I think is
interesting about that is that in our situation, which is
common to many workplaces, at least in the States, in
our situation, there was some psychology at play because you
(07:35):
would have you know you've got some change, you got
a couple of bucks or whatever. You don't want to be,
even if you never ordinarily gamble, you don't want to
be the one person who wasn't on the list. And
now everybody work with except for you is a a millionaire.
You know what I mean. It's like the risk aversion
gets switched. So now the founder Graves has done something
(07:58):
really interesting. He's basically giving everybody two bucks and the
chance to have much more, so you don't have that
same fear motivator. I think that's cool. I think it's
a neat gesture. Unless there's like more to this story,
it's a bold move on his part two because if
you know, if everyone, if there is a win, he's
gonna be out an entire workforce. I mean, that's no,
(08:21):
there's okay, there's caveats, Okay, Okay, this is why. Okay.
So when you win a large lottery like this, you
have two options, especially here in Georgia, and I'm pretty
sure it's for every place that plays this mega millions lottery.
You can either take payments that will be sent to
you like kind of like a paycheck basically, and they
(08:43):
increase in amount over time to adjust for inflation, but
it would just be you'd be getting smaller, much much
smaller payments over time. Or you can cash out and
you just take a huge cash some and at that
point the full thing, the full amount is taxed. So
the estimated cash value of that eight hundred and ten
million dollar jackpot from yesterday was in fact around four
(09:06):
hundred and seventy point one million dollars at least according
to CNN. And that means if you divide that up
by the fifty thousand employees that would be getting a share,
you get around nine thousand, four hundred dollars for each
individual person, Okay, which was that's no, that's no small sum, right,
(09:27):
my goodness, nine nine point four grand just as an
extra thing coming to you, that would be amazing, right. Uh,
But it's not the same as everybody's like, I'm out
of here, um, no more raising this cane. I'm gonna
go to Chick fil a. I guess no, I don't know.
I don't know how you presumably, how dare you go
(09:50):
to Chick fil a? Judas I say, well, they have
more than one sauce, I mean they do. I like
that Polynesian sauce. You can actually buy that bottle that
the crow around here which you homophobia is what it
sounds like. Yeah, live for it now, very very streamlined operation.
(10:11):
They do say, they say my pleasure too much. That
weird to me out, But no question is the idea
the idea here? I guess is that you know, with
fifty thousand uh tickets in the game, you know you
you you raise your odds. I guess if were they
all randomly generated? Is that how he played it there?
What was the idea? And what are the logistics of
(10:32):
buying fifty thousand lottery tickets with cash as a single
human being? How do you even get them? Yeah? I
I don't have all of that information. All we know
from that CNN article is that it was difficult to
buy fifty thousand lottery tickets. I tweeted that it's harder
than you think. Yeah, yeah, exactly. Um, I'm assuming it
(10:55):
was through some kind of cashier's check. I'm imagining, because
that's that whole thing is got to be weird. You
certainly do kind of raise the odds. Except for as
we discussed before, and Ben, I'm gonna lean on you
for this just a bit every time you play, especially
if you're randomly generating numbers, you have the same odds
(11:15):
every time you play the lottery, essentially, is what I'm saying.
And it's one in three something million, some ridiculous number. Um,
a crazy flow chance that you would actually win this
lottery no matter how many times you play. It's weird, Okay,
So maybe a way to explain it is, uh, you
(11:35):
know how gravity is just a little bit different if
you're in very very very very elevated places. But it's
a very very very small change. You can use that
analogy to think about the way the lottery works. So
if your chance is, for instance, one in just twenty
(11:56):
nine point two million, that's a that's a number I
saw in a statistics article on this, then you can
up your odds by buying ten tickets. You spent way
more money than you meant to, and in exchange for that,
your odds go from one in twenty nine point two
million to ten in twenty nine point two million. It's
(12:18):
like it does have an effect, but it is so
small you can only call it technically improving your chances.
It's kind of like how, um, if you if you're
running late and you try to speed on the interstate.
You can shave a couple of minutes off, but you're
probably still going to be late. If you're already like
more than fifteen minutes late, it's probably not gonna happen,
(12:41):
you know what I mean. Yeah, so, statistically, you're not
really raising your odds, even even though you technically are.
You are a little bit. Yeah, you are a little bit,
but it's um not significantly. To do it significantly, you
would have to, you know, by millions of lottery tickets.
(13:01):
But to this point, I think we're going well. You also,
you'd also have to make sure that none of those
none of those sets of numbers are repeating increase your odds.
But with that, but if they were randomly generated, right,
that's what I was going to say. If they're randomly generated,
they're not the odd like the odds of those same
numbers being randomly generated in that string that is winning
(13:26):
just another crappier lottery basically in terms of the odds. Right, So,
uh so I think it's I mean, I still like
it's a good question. Fifty fifty thousand tickets, to what
degree does that increase your odds? Right? If it's one
iteration or one instance each. Still, I don't think, you know,
(13:47):
if you're comparing millions to tens of thousands, it's not
a huge bump. But it is still a really nice gesture, right,
and not not to be cynical about it, but it's
a damn fine PR move for a small company that's
you know, a single owner who presumably treats his employees
(14:08):
better than you know, larger fast food chains. They're not
infinite numbers of these. There isn't one in Georgia or
in Atlanta currently, um there, you know, there's there's a
limited number of them, and so I think it's more
of that, like, see, we take care of our people.
We were all in this together. You know. It's definitely
I mean obviously got picked up you know, far and
wide this story. Yeah, it really did. You're correct, it's
(14:29):
a great PR move. Sadly, guys, it is Wednesday as
we record this, and uh, nobody won, not a single
person one the major jackpot all six numbers. Uh. Oh
and and by the way, according to AP, the chances
of winning all six or getting all six numbers correct
(14:50):
is one in three d and two point five million,
which seems like, uh okay, thinking it's thinking it's a
love but that means you, guys, in between the time
that we are recording this right now and the time
that this comes out on Monday next Monday, which is
(15:12):
today when you're hearing this, somebody may have won that lottery.
And the founder of Raising Kanes has said he's going
to play again, and he's going to keep playing until
he wins, or until someone wins, until someone wins, because
imagine like dropping a hundred thousand dollars twice a week.
(15:33):
Chicken fingers. It's so many chicken fingers. Al Right, guys,
we don't have to talk about this too much more,
but there are a couple of places you can go
to to learn more about the lottery. Not long ago
we talked about I think it was a woman who
dreamed about numbers and then play the lottery in one
was a while ago, um, but we we brought up
(15:55):
some of the same things I wanted to bring up today,
but I don't think it's necessary. You can go to
every state's lottery website and check out. Usually they have
a section called where the money goes. So if you
go to g a lottery dot com, you can navigate
to their where the money goes section and you can
actually see how much money is spent on uh. You know,
(16:18):
employees who work for Georgia Lottery on their overhead, basically
how much they they spend on their staff with the
money that's brought in by these lottery tickets. It shows
you how much money is paid out to players, and
how much money is paid to retailers so people actually
sell the lottery tickets, and how much money actually goes
to education. And in the state we live in in Georgia,
(16:41):
in fiscal year one, Georgia Lottery gave one point five
four billion dollars in funds to education, which includes things
like the Hope Scholarship that allows children to go to
college here in Georgia and in every state has things
like the Hope scholar Ship, not necessarily the exact same thing,
(17:01):
but things like that when it comes to funding education
in their state. Uh. Texas is the only place that
was really weird. I couldn't find exact numbers on the
Texas Lottery stuff they want, you know, Matt, Matt, what
is it that causes the pot to get so much
bigger when we have these historically large lottery pots, more
people play. Yeah, right, that's it. I mean, because as
(17:23):
that number gets bigger, more people are like, all right,
I've reached my threshold of going mine as well. Waste
five dollars, ten dollars, whatever it is, two dollars, feedback
loop and the and the cost that makes senst risk
analysis or the cost benefit analysis changes because the the
infinitesimal chance of winning is more attractive as there's more
(17:47):
and more stuff. And if you're listening, and if you
won by the time this comes out, uh, congratulations. Just
give you a couple of quick tips. Don't tell anyone,
don't tell us, don't tell your family. Honestly, I'm gonna
say it, this might be a hot take. I would
think very carefully about telling your romantic partner. Also, don't
tell your children. Literally omerta for for the rest of
(18:09):
your life. That's the only way to do it. Make
a trust fund for each kid, put most of it
in there, and then enjoy what you got lord like
like gust spring or something. You know, you just gotta
really Uh yeah, it's such a weird curse to all
of a sudden that much. Don't take your job, you
(18:32):
know what I mean? Keep showing up to work for
at least like a year. Seriously, you know, it seems
like a long time because you're a billionaire now or
you will be. And then also obviously don't take the
lumps some at all. Don't do it unless you have to. Yeah,
speaking a billionaire. The Friday drawing that's occurring, you know
again that just occurred when you're hearing this. It is
(18:54):
over one billion dollars, were right about one one point
zero two billion, which is nuts. And and this has
been our giving advice for things that will never happen segments, Well, statistically,
it will happen to someone because someone will win. I
guess what was the most recent payout. It wasn't It
wasn't insane, It was just a couple of mill Like, wait,
(19:15):
what's the largest historical lottery payout that's ever happened? I
think it was one point five billion that was but
individual it can be that can be split sometimes too. Yeah,
but that's the that's the amount, right, that's the prize
amount and then the cash out amount, like like for
this one that's happening, it's it's valued at one point
(19:38):
oh two billion dollars, but the actual cash out number
is six hundred and two point five million. Got it? Yeah,
so made fortune favor the bold, right, Uh, and you know,
insert different Hunger Games quotes here. But don't let the
money change you. Listen, folks, a great amount of fame
(19:59):
or success, financial, social, whatever you wanna call it it. Uh.
It doesn't necessarily make people bad. It just allows them
to be more concentrated, transparent versions of who they were
in the beginning. So don't let it touch you, you know.
And at the towns people start approaching you with rocks
and their clenched fists. Runaway. There you go, guys, next time,
(20:23):
maybe even a full episode. There's a great story out
of the Grillo and it's discussing how much the state
lottery board makes for every one dollar they spend on ads.
So like the lottery board takes in around a hundred
and twenty eight dollars for every one dollar they spend
on ads, which think about that the amount of gains
(20:46):
you get for putting out just um promotion for your lottery. Hey,
come on, play the lottery, you might win. You ever
roll the dice, you might win, and there bucks back
for everyone. They it's just a lottery episode. Let's do it.
The time has come. I'll gamble on that. I bet
it'll be interesting. That's what I'm betting to. All Right,
(21:08):
we're gonna leave for now, hear words from our sponsor,
maybe the lottery, and we'll be right back with more
strange news. And we've returned with some strange news from
the bottom of the sea. To take a quick diversion,
have you guys seen the movie Sing We Sing Too,
(21:31):
perhaps with c g I animals that sing like popular songs. Um.
I only bring this up because I recently watched Sing
Too and was very pleasantly surprised to hear a song
pretty prominently featured by a little remembered band called Mercury
rev Um, who, in my opinion, sort of had that
(21:52):
flaming lips sound that like post you know um clouds
taste metallic flaming lips sound like the soft bullets and era.
They had that sound on the lock before the flaming
Lips ever even you know touched it and they have
the same exact producer, a guy named Dave Fridman. So
I I like the flaming lips, I like that era,
but I really feel like they kind of eight mercury revs. Lunch.
(22:13):
And there's a song in scent too. It's quite beautiful
called holes. Um. And I always really just tickled when
it when it came on. UM. So yeah, this this
is about holes at the bottom of the seed. There's
an article on Vice that cited a report from the
National Oceanic Atmospheric Administration, a federal agency that studies weather
(22:35):
at the sea and things like that. This is specifically
a wing of Noah that does oceanic exploration. Uh. And
they had this to say via a tweet on Saturday's dive.
We saw several sublinear sets of holes in the sea floor.
The origin of the holes as scientists stumped. The holes
look human made, but the little piles of sediment around
(22:58):
them suggest they were ex ai aided by something. What's
your hypothesis? And it's true there are these neat and tidy,
little evenly spaced out rows of holes. Um. And I
learned a new word by the way from this, uh,
this Noah reporting. Uh. It's called leben spurring or laban spur,
(23:19):
which sounds vaguely German to me, which is a term
for biological formed structures things like holes or burrows or
mounds and then the like. Um. But here's the thing.
They could have been made perhaps by some sort of
crab or or or lobster or something with sort of
like a probing kind of like pointy you know, appendage. Um.
(23:44):
But upon further exploration and close up photography again, this
is a mile over a mile under the ocean. Sorry
not again, I haven't told you. It is in the
mid Atlantic Ridge area of the ocean, which is deep, deep,
deep dark shan, which is essentially might as well be space.
I mean, the reason they're exploring the stuff is because
(24:05):
it holds all kinds of as of yet undiscovered things, um,
certain species of sea creature. Ben, you had mentioned that
you went down a sea creature rabbit hole recently because
of some of the new ones that have been discovered
from this very type of exploration, right, yeah, right now.
The weird thing, and I think I mentioned this before,
the human species actually knows more about the surface of
(24:28):
the Moon than it does about the oceotic depths, you know,
once you get to the very bottom. And so if
you are a fan of cryptids, if you hold out
hope that uh, there are more creatures yet to be
discovered than the deep sea is one of the places
to start. There's actually, uh, the one that I was
(24:50):
talking to you about that messed up my research, some
of the research I was doing this after dude, I
totally stopped and learned too much about a rare tentacle
looking creature that scientists just discovered at the bottom of
the Pacific Ocean. I'll throw it in the chat so
you guys can get a little grossed out as we're
(25:13):
talking about this. But but yeah, right, vaguely extraterrestrial appearance. Right,
It's like someone grabbed the top of an octopus or
squid and then just sort of taffy pulled it out
into this long trail and then said, Okay, yeah, that's fine.
It's a spen. These are real things. Spens are already
(25:35):
a known thing, but this is like a new possibly
a new species. But all of this justice saying they
are continually, uh, strange discoveries being made at the ocean depths.
And that's why, at least with this story. No, I
would totally not be surprised if there's a mundane explanation,
but I would also totally not be surprised if it
(25:57):
was something brand new, because these do look. Uh, they're
curring at a regular interval like they look purposefly perforated.
There we go. Uh, I everything you're saying about this creature,
it's given me flashbacks. I just watched Nope, no spoilers,
no spoilers, but I just watched the movie Nope, And uh,
(26:22):
have you guys seen it yet? I'm very excited to
see it now. I talked to another friend today who
saw it and and said they absolutely loved it. So
I'm looking forward to it. I haven't seen it, but
you know me, I I read everything about it, so
I haven't. I like, I'd like Peel enough to not
spoil his stuff for myself because he's sort of like
he's like Shamlan but like, you know, good and then
(26:43):
we has an outstayed as welcome, and Shimlan was good
when he was good. But I just think he's kind
of like he's uh, his twists have gotten a little
bit repetitive and and predictable, whereas I think Peel has
always managed to surprise me. I really liked get Out obviously,
and and us, um here's the thing, there was actually
another Oh sorry, I was I sort of backtracked a
little bit too to describe where this was. Uh, this
(27:07):
discovery was found, um, and I didn't mention what was
said about They could have been made by you know,
certain types of sea creatures. But there's blind lobsters that
lived down There's something called squat lobsters, different types of
you know, subterranean deep deep sea dwelling crustaceans that have
little pokey diggy things. Um. But upon close ups and
(27:28):
further inspection, Uh, there weren't any signs of of living organisms, um,
inhabiting the holes, the researchers said. Um. They go on
whether the holes were connected beneath the sediment surface was
not visible. We hope that future studies of the laban
sporing Uh forgive me if I'm mispronouncing that we report
(27:48):
here will resolve the mystery of what created them. Um.
And this has actually happened before. In two thousand three,
scientists and investigating the same area published a study in
the journal Frontiers and Marine Scientists, and they found similar
types of you know, anomalous kind of holes. They were
described as raised sediment around these holes that indicated they
(28:11):
could have been dug out by deep sea crustaceans. Like
I said, um or perhaps excavated by animals living inside
the sea floor, but the authors were left with without
a definitive answer um And and we're basically just as
stumped as the scientists with noah have been about this
current run um. So I don't know. I like the
(28:32):
idea that it could be some mysterious creature that's doing it.
I like the idea that they had. The idea that
it's man made is interesting to me. And that was
actually in the in the headline for the Vice article
by Becky uh Ferrara, which I think is a little
bit of a bait and switch. But they did say
it look human made. They didn't really go back to
to justify that or quantify that at all. Sort Of
(28:54):
an odd thing to say without any context, but definitely
got my imagination running wild. We're not talking about somebody
diving down there, and yeah, why unless you're James Cameron
or you know, like the government, you can't get down
here because no, there's no casual exploring the c floor
(29:17):
um of the mid Atlantic Ridge. I will warn folks,
mainly because it gives me an excuse to use this term,
this word I never get to use. If you experience
uh tripophobia or a fear or discuss the patterns of holes.
This may not be the article for you. God, I
love the English language. There's so many words that will
(29:39):
just will never use, like, yeah, these holes are all
totally thankfully, these holes as all in a line and
they're not like clusters. Those are the ones that really
set off people with that with that condition, there's actually
an episode or a season of American Horror Story, which
is not always great, but there's a season where it
(30:00):
revolves around characters deepest fears and triple phobia is one,
and they you know, in typical Brad Felt, Chuck and
whatever that other guy's name is fashion, they go way
over the top and depicting what the people are seeing
who are freaked out by holes pretty gross. What if
you got a little philosophobia, which let's go through more phobias,
(30:22):
let's do some phobia born I think lorophobias. But if
you don't have that condition, if you're a deep sea
investigator and you see this trail of holes and all
of a sudden you see a clown, you get chlorophobia
pretty quick just standing there, you know, arms akimbo, and
it waves to you. I think, right, deep seed clowns.
(30:46):
Why is that not yet? God deep sea clowns with wings?
That would freak me out. I have or phobia. I
don't know why. That feels like a lounge in number
to me. And maybe in a David Lynch. And also
that super producer Alexis code enamed Doc Holiday. Jackson pointed
(31:07):
out that Holes on the Ocean Floor would be a
really good name for like an emo or post rock
type band. So yeah, don't steal it. Yeah, I think
post rock is great. Don't don't steal it. Conspiracy realist.
Let let Alexis have this named doc is gonna invite
us to the show next week, she said, So yeah,
I'm I'm hoping for some very plodding, slow instrumental jams. Okay,
(31:31):
you just have to wait and see. Yes, Doc, I'm
gonna buy some shoes specifically for gazing at your show.
Let's not get it twisted. That would be more of
a post rock shoegaze kind of situation, and they're not
mutually exclusive. But they also don't always have to belong
to you. It's a big diagram that's getting the specific
shoes you know they need the top of the shoe
(31:52):
needs to be essing like clown shoes. What about clown shoes?
My feet are now you're to U. Yeah, my feet
are basically hands, So I don't want to add more.
It's more shoe to look at, you know. That's what
I That's what I say, more shoe to look at.
But then also you have to stand really far away
from your massive pedal board, you know, and i'd be
(32:13):
really hard to hit those buttons with the with the
tip of that giant shoe, whichould get pretty broad at
the top. You'd be like slamming all three pedals, which
actually might be desirable. Uh, you know, if you're one
of those uh, you know, pedal heads. Anyway, this is
an interesting one. UM. Thank you all for chatting it
through and uh and indulging um the speculative kind of
bent in this story. UM. But I look forward to
(32:34):
hearing more, um, you know, because these scientists still seem
to be kind of baffled, and hopefully they'll come to
some conclusion and share with the class. But in the meantime,
let's take a quick break here, a word from our sponsor,
and be back with one more piece of strange news.
And we've returned, So best of luck to the good
(32:59):
people at Canes, and best of luck to the scientists
doing tremendous, mysterious work there at the ocean floor. Our
last story is a prediction that has come to pass.
For many years when we talk about big data, big data,
whatever your preference may be, we've often pointed out the
(33:23):
imperfections of applying technology to predicting the actions of human beats.
We've also, not for nothing, sort of internalized the cautionary
tale of minority reports, the idea that predicting crime, even
when it seems to be accurate, can be dangerous and
(33:44):
can have unintended consequences. Well, as we record today and
as you hear this on Monday, it happened, we're at
the dawn of pre crime right now. There's a great
study came about University of Chicago, which is frankly terrified.
These very clever researchers have created an algorithm that, according
(34:06):
to them, can predict crime a week in advance with accuracy.
That's the headline before we go on, Do you guys
believe it? What data are they using? What are they
feeding into the thing? Is it? If it's social media? Well, like, really,
(34:27):
if it's social media posts that are private somehow, or
really I don't know, maybe their public posts, but they're
just monitoring specific things. I think you could probably predict
some mass shooting events if you had the like, the
most granular data on everybody. But you know, I mean
(34:47):
on social media, everyone is just portraying the rosiest version
of their psychopathy, you know. I mean they want everyone
to think they're the best, sweetest, happiest psycho in the world.
I mean, nothing on social media has actually should be
taken a phase value, right, I'm kidding. Obviously people use
it for all kinds of reasons, but it makes me
think of there's an Atlanta rapper now I'm forgetting his name,
(35:08):
but he got wrapped up in some gun charges. I
don't remember. I'll figure it out a second, But the
point is, uh, and this might ring a bell for y'all.
They used his lyrics uh to as evidence against him,
which obviously isn't it the same as pre crime? But
I wonder if you could use that, you know, for
as a form of pre crime. You know, someone is
(35:30):
rapping about something that maybe as a fantasy, you know,
or it indicates where their minds, their headspaces. Maybe that's
something you could use someone's art against them. Well, this
happened to other performers, to other musicians. There. There's also
a fantastic key and Peel sketch about this. I will
(35:52):
send it to you all if you haven't seen remember this.
I like it's like the five and just yes exactly,
but it shows that beautifully right. But there's a good
question where they're getting Where are they getting the information
that they are feeding the algorithm. They are using publicly
(36:16):
available data, So this would be reports of crimes. Uh,
this would be any imaginable demographic metric of a community
and what they what, what kind of stuff we're talking about.
Just to give you a brief laundry list. This is
pulled from the history of the city of Chicago, and
(36:38):
they had too broad categories that they were testing the
tool against. Once they fed all this junk into it,
they wanted to see what they could predict. Their two
buckets are one violent crimes, homicides, assaults, batteries, you know,
all of those. And then property crimes burglary, theft, grand theft, auto,
all the hits and these these particular ones were used
(37:03):
because they were most likely to be reported to police
in those areas because as anyone who's lived, you know,
on the edges of different things, knows, many crimes never
have the police involved, right, and it's just sort of
understood between the victim and the perpetrator, even when they
(37:24):
switch sides and revenge schemes, you know. But they also said, Okay,
these are going to be reported in urban areas where
there is historical distrust and lack of cooperation with Johnny law.
They still they thought, Okay, even if you don't like
the cops, you're still gonna say, hey, someone stole my car.
So we know that because of that, there's a high
(37:46):
likelihood that the number of crimes that have occurred in
that regard are is very close to the number of
crimes that are reported, meaning the data is more solid, right,
especially more solid than something like drug times or some
misdemeanor in fractions, because those are prone to what's known
as enforcement bias, which is exactly what it sounds like.
(38:08):
We don't have to overthink it. So this the PhD
senior author of the study, uh Ishano Chado Padhai uh
in part of my mispronunciation of getting this wrong, has
said that this tool is different because it takes in
the complex social environment of cities, and it also considers
(38:28):
the relationship between crime and the effects of police enforcement.
It's pretty smart. It divides, so picture yourself playing like
uh SimCity or Civilization or something. It divides the city
of Chicago into tiles. They're pretty small, about a thousand
feet across, and it predicts crime within those areas instead
(38:53):
of relying on traditional boundaries of like neighborhoods or political districts,
because those are all of subject to bias. It did
this in Atlanta, in Austin, Detroit, Los Angeles, Philadelphia, Portland,
and San Francisco in addition to Chicago. So they tested
this in a couple of different places and what they found,
(39:16):
and what seems to be true is that they yes,
they can predict crime about a week in advance, so
that like about a week in advance with accuracy, they
can take what happened in the past, and then through
this algorithm they can they can run it through this
thing with all these other intervening variables and then it
(39:38):
will tell them like, hey, the specifics are a little
tough for me. But then we'll say something along the
lines of, hey, they're gonna be x number of cars
stolen next week or something like that. I don't know
how predictive they can be or how sophisticated. I don't
know if they could say in two thousand four green
Honda Odyssey right with a with a crappy transmission or
(39:59):
anything like that. Do they have to have info on
the people, like specific to the people, like psychological profiles
or any information that that that's specific to individuals or
is it more big picture and like you know, like
that's a really good point bend civilization or like some
city like a top down kind of view where the
individuals are less important than just the way the complex
(40:22):
system of it all. Kind of yeah, I don't I
don't think it has a right it's if you're we're
just talking about the overlay of the city, right, look
at it like a grid and like here's when things
happen and exactly where within these little specific parts of
the city. And I don't know that it's so weird
to ben. I don't see how you can make it actionable,
(40:43):
like who can Like who cares if we know that
five cars are gonna get stolen in the next few days?
Are we talk about this on The Boys? The Boys
in that show that like The Seven, they have these
you know, this department that looking into crime and someone
makes a comment, they can usually predict a crime like
(41:04):
a week or so before it happens, So it's you know,
similar kind of data that they're crunching. It also reminds
me of this anime called psycho pass Um that is
more about the individuals where they can actually they're taking
measurements of the citizens of Japan's you know, biometrics of
their brains and generating these they call them sematic scans
(41:24):
that allow them to with a pretty high degree of certainty,
predict who will be potential criminals, you know, criminal criminality.
Potential is the term they use, and they get color
coded on a map. But the dangerous is that this
is science fic. Well, there's there's something very dangerous with
all these things and their historical precedents. Right, law enforcement
(41:46):
throughout all civilizations, various versions of law enforcement were attempting
to predict crime, and their rubric for this although it
varied widely, it was hardly scientific and most times it
was really rooted in xenophobia, in racism, in some other
form of discrimination. Right. Uh So, the question is how
(42:09):
much of that has descended to this program. And if
you look at the research just got published in Nature
Human Behavior, and what they found was a twist to
the plot, but Shamalan twists, you could say, and I
don't think it's that bad. But they found that this
thing could accurately predict crime, especially in Chicago. But it
(42:32):
also laid bare some heavy biases in police responses. They
found stuff like if you stress the system, that's what
the senior author calls it. It requires more resources to
arrest more people in response to crime in a wealthy area,
and that almost always draws police resources away from areas
(42:56):
with lower socioeconomic status. So police are paying more attention
to the quote unquote good parts of town. They're also
working kind of in response to earlier experiments from Chicago
p D or associated with Chicago Police Department. UH. A
while back, the Chicago p D tried another algorithm that
(43:19):
created a list of people deemed most at risk being
involved in a shooting, and it turned out that over
half of the black men in Chicago between twenty and
appeared on it. So this is why the people who
made this new algorithm, this new AI algorithm, are really
(43:41):
concerned that the data that they're using in their model
may be biased, which therefore means to your point, Matt,
that the conclusions it creates will be biased. And they
also said, just to answer another couple quick questions about
how far into the dystopio we are, they also said
that the algorithm, the AI does not identify specific subjects. Right,
(44:07):
So it's not it's not saying Paul mission controlled decand
is out on another loose diamond heist over at Zails
or whatever is in your neck of the woods. Folks
there used to be Shane Company here. The commercials were hilarious. Instead,
instead of identifying specific subjects, identifies potential sites of crime.
(44:30):
And they've released the data and the algorithm. They didn't
keep it proprietary. They released in the public sphere because
they want other researchers to check out its reasoning, its conclusions.
They want to test it. And then one thing that
really caught me is I was comparing this to previous
previous kind of DARPA work or DARPEST sponsored excuse me
(44:53):
work with creating virtual models things like Afghanistan or other
communities or other areas of the world, you could say,
and their idea there which was pretty like frighteningly successful.
Their idea was that if you can create a simulated
version of a place with enough sophistication, with enough fidelity,
(45:17):
if you have enough information about it, then you can
plug in changes right in your make it up seas universe,
and then what happens as a result of that in
this virtual environment will be very close to what happens
in the real world with the same set of actions.
(45:37):
So that's what they have done. They said, We've made
this thing that is close enough to the actual city
of Chicago or those seven other cities for our purposes
that when we feed it data from the past, it
tells us what will happen in the future, because like
a love Craft in Elder God, it sees beyond time.
(45:59):
They and say that last part I added that in
for a little bit of editorial, you know style. But
he also said it's not magical, it has limitations quote,
but we validated it and it works very very well.
So if that's what's happening, if we have a kind
(46:21):
of a thing that's kind of like a a precog
precognitive bloodhounds for geography of crime, how far along a
slippery slope are we Do you guys think this would
get deployed in uh in other cities or get used
past the experimental proof of concept phase. I mean, I
(46:41):
think people in the real estate industry would be very
interested to have this information. Yeah, oh yeah, I can
imagine that when it comes to how like how much
they could charge or how little they should charge for homes.
Everything part of it for the buyers and the sellers,
you know, if you know, like because there are crime ratings, right,
(47:03):
safety ratings, who might be called by zip code? Um,
maybe that's maybe that's not the best example. I don't know.
It's just like, if you have that statistic, why what's
the stop please from just saying, okay, we're going to
pretty much garrison people in these things for a week. Yeah,
I don't know if that's smart. Yeah, now I get it,
(47:24):
or or like set up points of entry, you know,
like roadblocks kind of like you know, I mean, that's
it sort of takes the sport out of it, doesn't
I don't mean to sound flipping like that, just you
know what I mean. Anyway, I'm just gonna go back
to what I my thought in the beginning of this then,
and that is, if you take this the models they're
creating in the statistical analysis that they're doing, and you
(47:47):
combine that with something like sesame credit or something that
is very closely monitoring social media and purchases and interaction
like in interpersonal interaction on that way and generating that
data set. If you combine those two things, that's when
you get actual pre cog pre crime insanity. Right, You
(48:08):
just have to you know, I was thinking about the
same thing, man, because if you look at your phone,
a lot of people are listening to this on their phone, right,
So you look at your phone right now, and imagine
it's not just as a single invention, but imagine it
as a multitude of separative inventions that have been combined
(48:28):
to create something amazing. That's how these sorts of innovations occur.
That's what pre cog and pre crime stuff will be.
It will be like your phone, It'll look like one
thing in the end, but it's really going to be
uh mass and aggregation of innovations like this, is this
good will this maybe save lives? Of course that's the hope, um,
(48:53):
But that part is up to society at large. And
I want to shout out the science tis involved who
did excellent work on this study and on this algorithm,
because they're incredibly conscientious about this is very much a
case of them having done everything they can do, you
know what I mean. They can't start a vigilante squad
(49:15):
and go try to save a Honda Odyssey for some reason. Also,
why would you? But yeah, but but but I do
think it's worth everybody's time if you're interested in this.
I know we have a lot of thoughts on this,
folks um, fellow conspiracy realists. I would recommend checking out
(49:36):
the study firsthand and then reading what people have written
about it. The title is event level prediction of urban
crime reveals signature of enforcement bias in US cities, So
they put it in the title. It came out at
the very end of June Nature Human Behavior. That's the journal. Uh,
do check it out. Would love to hear your thoughts.
(49:56):
I would love to hear your take on Kanes. Would
love to hear what you think about the lottery. And again,
you know, we want your opinions on what lurks at
the ocean's depths. We want you, specifically, you conspiracy realist, no,
not that person next to you. You to write in
be part of a show. Join us for our listener
(50:18):
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(50:41):
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