Artificial Intelligence: Crime, Entertainment & Health

In this episode, Robin explores the multifaceted role of artificial intelligence in shaping the worlds of entertainment, art, and crime prevention.

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Episode Transcript

Speaker 1 (00:01):
Sunny spaces, smiling faces, happy places. But every sunny space
holds a shadow. Behind every smile, our sharp teeth, and
every happy place has something sinister lurking just below the surface.
Welcome to We Saw the Devil, the podcast diving deep

(00:22):
into the chilling realms of true crime. Join your host
Robin as she unravels mysteries that have left investigators baffled
and armchair sleuth's obsessed. Be forewarned, Dear listener, We Saw
the Devil is not for the faint of heart. Our
unflinching exploration will take you to the darkest corners of
the psyche and through the unimaginable depths of human darkness

(00:45):
to unearth stark secrets. To the harsh light of day.
Nothing will be left untouched.

Speaker 2 (00:51):
Are you ready?

Speaker 1 (00:52):
Are you sure?

Speaker 2 (00:54):
We Saw the Devil?

Speaker 3 (01:00):
Everyone you are listening to We Saw the Devil. This
is Robyn and yes, you guys, I am back. I
know it's been like two months since the last episode.
I'm gonna be honest, I have been incredibly busy. I've
done a bit of traveling, I have been sick. I
actually currently have COVID as I record this. It's been

(01:22):
a lot, and I'm so sorry for the delay yet again.
I just I've traveled a lot lately, and unfortunately, between
you know, work and travel and the zoo that I possess,
been a little bit late on getting new episodes out.
But I am settled again, and new episodes they are
a common on the docket. We have the final Chris

(01:43):
chan episode, which is going to come out early next week. Today,
I wanted to do with something a little bit different
because in the news a lot lately, actually over the
last couple months, I would say, I'm starting to see
a lot of talk about AI, how it can impact
criminal investigations, healthcare, a lot of different aspects, music, art, entertainment,

(02:07):
things like that, So I kind of wanted to talk
about it just an overview of AI. If you listen
to the show, you know, I do random topics here
and there beyond true crime, like the dark Web and
things like that. And I'm really fascinated by AI. Name
a day that any of us go on the Internet
and see a post, a video, a real something that

(02:31):
was not generated solely by AI, and there are so
many moral questions and conundrums surrounding it. So that's what
I want to talk about today. I really don't have
any housekeeping today other than I'm back. We're approaching the
best season of the year. I'm really excited about that.

(02:52):
I don't know how many of you guys are already,
you know, ready for Hoodie and Gene and pumpkin spice,
every thing. Pumpkin beer is my favorite. So I'm just like,
it's a great time of year, you guys, and I'm
really glad to be back. I may currently feel like
sh doodle, but I am excited to get the show
back up and running and put out consistent episodes. I'm

(03:15):
going to finish the revamp of the website, y'all. That
is coming, I promise for now, though. If you want
to keep track of news or updates or random posts
anything like that, make sure to follow We saw the
Devil podcast on Instagram and you can follow me personally
see my adventures, my dogs, my food, random music musings

(03:37):
at Robin Underscore WSTD. But let's go ahead and get
into it, you know. Like I said earlier, artificial intelligence
has rapidly become one of the most contentious topics in
contemporary technology discussions. I mean, it has the potential to
transform entire industries, coupled with its associated ethical, privacy and

(03:59):
secure challenges, there's a lot of really intense debate across
basically everything. Like I mentioned earlier, entertainment, healthcare, crime, criminal investigation,
and things like that. Artificial intelligence is making waves in
pretty much every single industry that you can think of.
So in crime prevention, it's like having a super sleuth

(04:20):
or super detective that just sifts through data to help
catch the bad guys before they strike or before they
commit crimes. For artists or for art lovers, AI is
creating everything from music to visual art, voiceovers, voice acting,
and it adds a futuristic kind of twist to the
creative process. And healthcare, AI is helping doctors diagnose diseases

(04:46):
faster than ever, and it helps develop personalized treatments, So
it makes a real difference in patient care. And we
can't forget the military because AI is streamlining operations and
improving strategies because it has a knack for handling huge
amounts of data. And for me as a tech nerd engineer,

(05:07):
it's fascinating to see how AI is reshaping just so
many different fields in changing the way that we all
live and work on a daily basis. So again for
this episode, I'm going to discuss AI across all of
these different industries, but particularly how it can be used
to combat crime as well. And when you finish listening,

(05:27):
make sure to head over again to the Instagram that
we saw the double podcast and let me know on
the current episode post what you think should we be
embracing AI and its integration into law enforcement? Is it
too early? I want to know what you think, because
police departments all over the country like this is a
very real, pressing thing that is happening. Would you feel

(05:51):
comfortable with AI sifting through data and making predictions and
risk assessments or do you want a real live persons
in that chair controlling it. But we're going to start
off with healthcare because this is something that's really really
interesting to me, in particular because AI's promise to me,
in my opinion, is exemplified in the field of health care.

(06:15):
Advanced algorithms enable rapid and precise analysis of medical data,
which can lead to earlier detection of diseases, again, the
development of personalized treatment plans and innovative drug discoveries. You know,
for example, AI systems can process such vast amounts of
patient data and then identify patterns that might elude human doctors.

(06:38):
So that could totally revolutionize diagnostics and treatment. And more
than two million people are diagnosed with breast cancer each year.
It is the most common form of cancer globally. It
impacts men and women, and early detection through breast cancer
screening can lead to better chances of survival. Now, while

(06:59):
the while those screenings are critical to improving the outcomes,
there is a shortage of specialists around the world, so
that means that these screening systems are generally pretty overburdened.
It leads to long wait times for people awaiting their
results and can you imagine how anxiety inducing that is.

(07:20):
In the UK, there was an AI breast screening solution
called MIA and it helped doctors find an additional twelve
percent more cancers than in routine practice. If deployed across
the entirety of the NHS, a twelve percent uplift in
the detection of breast cancer could lead to better outcomes
for thousands of women across the UK. The augmented AI

(07:43):
workflow also showed a decrease in women recalled unnecessarily for
further assessment and modeled a workload reduction of employees of
up to thirty percent. So again, twelve percent more cancers
detected than in routine practice, and it also showed a
decrease in women brought back in for further testing. Have

(08:04):
you have any of you ever gotten a call or
had a lump or anything like that and then you
were brought back in for further testing. AI systems were
able to prevent a lot of those, not to mention,
to reduce the workload of up to thirty percent. In manufacturing,
AI driven automation is transforming production processes. Intelligent systems and

(08:25):
robots handle repetitive tasks with greater accuracy and efficiency than
human workers. I mean that is a fact. It minimizes errors,
optimizes the workflows, and that not only boost productivity, but
also allows human employees to engage in more complex value
added tasks and jobs. AI also hits retail. It can

(08:47):
sip through the consumer data and perform behavior analysis. Then
there's public safety, which I'm going to talk about in
greater detail here in a moment. Predictive policing, that's what
it's called. Typically, now, when the AI is utilized with
public safety, it leverages AI to forecast crime hot spots

(09:09):
by analyzing historical crime data and socioeconomic factors. Now we're
going to touch on this in a moment in greater detail,
but more or less. My point here is these applications
demonstrate AI's potential to enhance various aspects of our lives,
and that drives progress. When you are enhancing efficiency, saving lives,

(09:33):
saving money, increasing productivity, things like that, I mean, that
is progress and it can improve our quality of life.
But there are some really niche areas that I want
to touch on in more depth as well now, and
the number one is actually dating. I have a girlfriend,
but I don't know how many of you guys have
seen on Instagram or Facebook or whatever. There are now

(09:55):
AI dating robots, and they've been in Japan for a
couple of years now, but we're just starting to see them,
i would say, more publicized and marketed here in the
United States in the last like year or so. And
what they are is they're basically it's code that facilitates
romantic interactions and relationships through the AI. So these robots

(10:19):
combine AI technology with either a physical or virtual interface
to assist the users. The end users in dating in companionship,
and you're seeing it again more so in Japan and whatnot,
and people are actually falling in love with these virtual companions.

(10:40):
So the purpose and functionality of them is again companionship
and matching. So AI dating robots, they can provide the
companionship imagine an advanced theory that you can actually talk to,
and then it actually provides affection, words of affirmation, encouragement reminders,
things like that. It can also assist the users and

(11:00):
finding combatible partners based on shared interests, preferences, personality traits.
They can use algorithms to suggest potential matches and dating services.
The physical robots, and this is something that I've talked
about as well, but imagine the real dolls. Have you
guys seen the documentary and Advice News did a big
thing on it. But there's a thing called a real doll,

(11:22):
which is more or less, yes, a sex doll, but
they've also made them with AI capabilities so they can talk.
And these physical robots, these are machines more or less
that can interact with users in person, so they can
have humanoid features, make have different facial expressions, gestures, and
vocal communication abilities. And then now we're also starting to

(11:45):
see the dating apps. I saw one on Instagram, like
an ad or something, and it was like, you know,
check in with your virtual boyfriend. One I saw in
a documentary on dating in Japan because you know, population
and whatnot, more men, fewer women in terms of dating
and marrying age, so a lot of single men in Japan,
and they actually sell the documentary that I saw maybe

(12:05):
two years ago.

Speaker 2 (12:06):
It's like a little.

Speaker 3 (12:07):
Box and in the middle of the box is like
it's like a glass cube think of it that way,
with a speaker, and it just talks to them. It
just talks to them, asks them, how's your day, sweetie.
It can talk about sex, it can have not really
phone sex, but just I guess role playing out loud.
Imagine if Siri became naughty. It's basically the same concept.

(12:29):
And that's what's so interesting to me is natural language
processing or NLP. AI dating robots use NLP to understand
and generate human like responses, so that makes conversations more
natural and engaging. Have you ever been using I personally
am an Amazon like an echo person. There's an option

(12:49):
sometimes it'll ask you, you know, do you want to
talk to me, ask me questions. Because it's talking to
AI just constantly increases its capabilities. It can learn very
nuanced things such as tone, accents words. Not only that,
but through AI, robots have been shown that they can

(13:11):
actually recognize and respond to certain emotional cues, like if
I were to start talking and then sound sad or
start to cry, a robot through AI and data analysis
can pick up okay, that human is having sad emotion.
Things like that, maybe ask me how I am, what happened,

(13:33):
what it can do to make me feel better? I mean,
that is the future of where some of this is going,
and it's actually already here. Maybe not on a wide scale,
but it is. The company Realbotics has a robot called Harmony,
and it's a physical robot that combines AI with physical
features to engage users in romantic interactions. It can have

(13:54):
conversations and adapt its behavior based on those interactions. And
again it is a physical robot, and there are some
that are attached with genitals, whether you choose a male
or a female, and it can actually move and respond
and say certain things and learn different behaviors. The impact
of AI dating robots on emotional well being and the

(14:17):
nature of human relationships. This is a debate that I love.
I actually was reading technology magazine not terribly long ago,
and it was this entire kind of pros and cons
list of AI and robot you know, dating, these types
of whether it's a physical or virtual, and you know,
concerns include the potential for dependency on artificial companionship. There

(14:40):
is a very real impact on real life social skills,
do you guys remember you know, the COVID babies And
no offense to any of you who gave birth during
the rona or had a two, three, four five year
old during the pandemic and whatnot, but it has been
proven that their social skills from being kept at home
were stunted a little bit, you know what I mean.

(15:00):
Unless parents went way out of their way, they did
not develop the same social skills as their peers and
other periods where you know, people weren't in longdown more
or less.

Speaker 1 (15:12):
You know.

Speaker 3 (15:13):
Not only that, but you have to wonder about the
handling of personal data. You know, a say, AI dating
robots right, it raises privacy concerns because sensitive information may
be collected and use for either matchmaking purposes behavioral responses.
Things like that, so I guess in summary here, more
or less, you know AI dating robots. They leverage artificial

(15:34):
intelligence to enhance romantic and social interactions. So yes, it
does provide people, I guess, particularly lonely people, ways to
connect and engage to something, and that is a positive
for mental health. But while they offer solutions for companionship, matchmaking,
love attention, they also raised important questions about the nature

(15:56):
of human relationships as a whole and private. Now moving
on to art, and this is probably what's engaged my
interest and piqued my interests the most when it comes
to AI is because one day I was on Instagram
and I saw probably one of the coolest prints I've
ever seen in my entire life. It was just like

(16:18):
this weird artwork i'd style I'd never seen before. It
was super dark but just beautiful, and it was selling prints.
This channel was selling prints, and I was like, holy shit,
I would love a print of this. So I went
onto the website that it linked to. One print was
like seven hundred and fifty dollars, a little out of
my budget, but you know, but I dug into it
a little bit more and it was AI. It was

(16:41):
all AI generated and the artist you know, probably had
a thirty dollars account on some AI generation platform and
they would type in very very very detailed prompts. Now
what a prompt is is you can I don't know
how many of you guys use chat GPT. I use
it constantly for work, especially in my day job. If
I'm stuck on sending a professional email or something like that,

(17:06):
you know, I'll type in generate an email asking a
client blah blah blah, right, and it will pop out something.
The art aspect of AI works quite similarly. You'll go
onto a website. There are a lot of ones just
for art, an art, and video. Ang'll type in a
prompt create a thirty second video of God, I don't know,

(17:27):
P Diddy in a CBS buying baby oil, right, and
then it will pop it out for you after a
couple of minutes. Or create a painting of an old
Gothic Americana mansion in a swamp and in the style
of X Y or Z or muted colors, things like that,
and it just pops it out. So there are whole

(17:48):
hosts of people right now that create art in that way.

Speaker 2 (17:52):
One of the.

Speaker 3 (17:53):
Biggest I guess instances of art that I've run into
is if you know me, you know that I am
obsessed with a band, Circus Survive, best band in my opinion,
too ever exists. Anthony Green is my favorite artist. I
listened to all of his side projects. The newest one
currently since Circus Survive broke up. You can't see me,

(18:14):
but I'm doing a religious assigning and you know, rest
in Peace is ls Dunes.

Speaker 2 (18:20):
Now.

Speaker 3 (18:20):
Last year, LS Dunes made huge news because they were busted.
I mean, they were open about it. They didn't try
to pass the work off them as their own, but
they made a music video and in that music video,
they utilized AI tools to generate the entire video. Without
kind of fully disclosing the extent of the AI involvement,

(18:43):
they kind of said, yeah, we utilized and played around
with AI to you know, create some cool visuals here,
and it pissed a lot of people off. It pissed
a lot of people off because when it comes to
art again, we've already established that AI to learn has
to scan through insane amounts of data. That's how it

(19:04):
learns the same thing with art, music, literature, with painting,
just all art, right, it scans the Internet entirely data
warehouses things like that, and it scans and learns and
then spits stuff out, So it's not actually one hundred

(19:24):
percent authentic in what it's doing. It's kind of scanning
and using other established work to create something new. Now,
in the case of ls Dunes, you know, they came out,
they admitted to it, they were open about it. I mean,
the world lost its shit. I mean people were sending
death threats. Anthony Green in particular used to be I mean,

(19:46):
he has a very very sordid long history with drug
abuse and depression, suicide attempts, the whole bit. I mean
people were coming onto ls Dunees's channels and telling him
to kill himself, go overdose, things like that. I mean
it was wild to witness in real time, really, but
I think the lack of disclosure, you know, and for
me when I went on Instagram and I saw the

(20:08):
artists and loved the art and then saw that it
was AI, it highlights concerns about transparency and LS Dunes's case,
fans and critics were pissed that to the extent at
which AI was used in that creative process, that it
wasn't clearly communicated, and so that raises concerns and questions
about authenticity and originality of the content. Again, I've already

(20:33):
talked about the copyright issues and intellectual property. You know,
there were legal and ethical questions regarding the ownership of
AI generating content. The project faced so much scrutiny over
who owned the rights to content.

Speaker 2 (20:46):
Produced by AI.

Speaker 3 (20:48):
You know, does it belong to the creators who use
the AI tools and created the prompts and things like that,
Does it belong to the developers of AI or are
we ushering in in you know, twenty twenty four a
brand new category of intellectual property law. In my opinion,
I'm not going to get into it here right now,

(21:08):
but in my opinion, yes, I think we need a
new category of intellectual property to stay with the times
and these new technologies that are coming out all the time.
Critics have often argued too, that relying on AI for
the creative process might undermine human creativity and artistic expression
if you have more people using it. You know, the
concern is that AI generating content might dilute the value

(21:32):
of human created art and potentially replaced jobs in creative industries.
And I don't know if you've seen there was a
really great video of it on Facebook that discussed this
and covered this. It was a voiceover actor and they're
standing like in a theater or a booth or something,
and then they're talking. They introduce themselves and ad runs

(21:52):
like a commercial spot and you think, oh, they're just
doing a voiceover example, and they said, that's not me,
that's AI taking my voice and doing this. I didn't
you know, I wouldn't get paid for this. This was
not me, And that's terrifying. And all of this has
sparked a broader discussion in the music and creative industries
about the ethical use of it. There's a need for

(22:15):
clear guidelines and standards regarding AI's role in the creative process.
And I can understand it too. I am someone that
is so wholly moved by art.

Speaker 2 (22:27):
I am.

Speaker 3 (22:28):
If you know me, you know that I'm not an
incredibly emotional person. Like nobody sees me cry, no one
sees me react. I am very very, very very mild
mannered ninety nine percent of the time. But when I
see art that is beautiful or thought provoking, transgressive, whatever,
just regardless of the media, physical, music, film, whatever it

(22:53):
moves me and it makes me feel right. So imagine
a film like Martyrs or Dancer. Let's say Dancer in
the Dark. Dancer in the Dark is one of the
most absolutely depressing. I've seen it probably fifty times, and
I saw like a child every time I see it,
just because it hits me in a place that allows

(23:15):
me its catharsis really right. Imagine finding out that someone
didn't actually create or write that, that it was computer generated?

Speaker 2 (23:24):
Would that ruin your experience?

Speaker 3 (23:26):
Would you value it less if you knew that someone
didn't take the time to write the story, storyboard it,
you know, write the screenplay and cast and actors and
so forth like.

Speaker 2 (23:37):
Would that mean less to you?

Speaker 3 (23:41):
Also, one of the most pressing ethical concerns related to
AI is the potential for bias. AI systems. Again, like
I've said fifty times so far, learn from historical data
vast amounts, and that data may contain inherent biases, and
if those bias are not addressed, AI can perpetuate or

(24:03):
even exacerbate discriminatory practices in areas such as HR hiring,
law enforcement, and lending. I mean, for example, predicted policing
algorithms might disproportionately target certain communities if trained on bias data,
and we're going to talk about that more in depth

(24:23):
here in a moment as well. But I would say
a really good example of the bias is facial recognition technology.
Facial recognition systems have been proven to exhibit racial and
gender biases. Studies have been done, such as the largest
one by MIT's Media Lab and the AI Now Institute,
have shown that they tend to have higher error rates

(24:46):
for people with darker skin tones compared to lighter skin tones.
Probably the most prominent example is the research conducted on
commercial facial recognition systems, which demonstrated that these systems were
significantly less accurate in identifying the gender of black and
Asian faces compared to white faces. Another study done highlighted

(25:08):
that facial recognition algorithms had higher error rates for women,
particularly women of color, and they often misclassified black women
at higher rates than white men due to insufficient diversity
in training data and inherent biases in the algorithms. And
then again, hiring and recruitment a gender bias. One example

(25:31):
is the Amazon hiring tool, which was found to be
biased against women. The tool developed by Amazon was it
was developed to screen resumes, and it was trained on
historical hiring data that reflected past gender imbalances in the
tech industry, and consequently it penalized resumes with references to

(25:52):
female oriented activities and preferred resumes with male associated language.
And that happened nat really just based on the data
that the AI system that the tool analyzed. There's also
a study by pro Publica on a widely used risk
assessment tool in the criminal justice system HUMPAS, which stands

(26:13):
for a correctional Offender Management profiling for Alternative Sanctions. Now,
that study revealed that that particular tool disproportionately flagged black
defendants as high risk compared to white defendants, even when
controlling for the actual recidivism risk. It can also exacerbate

(26:34):
geographic bias. And now let's talk about predictive policing for
a little bit now, because I mean, this is a
true crime podcast after all. These algorithms used for predicted
policing often rely again on historical crime data, which can
reflect systemic biases and policing practices. So, for example, say

(26:54):
you have a neighborhood and it was heavily policed in
the past, it may appears a higher crime area in
the data, leading to increased policing and potentially reinforcing the
cycle of over policing in that particular area, because again
everything analyzed is historical. There was a report by the
AI Now Institute and it highlighted that predictive policing tools,

(27:18):
which again predictive policing, what that is is forecasting. It
forecasts crime hot spots based on past data. That these
tools can lead to biased enforcement practices. They disproportionately target
certain communities based on those historical arrest data rather than
actual crime risk.

Speaker 2 (27:39):
Then we have other.

Speaker 3 (27:40):
Instances as well, like you know, healthcare and medical algorithms,
and the theme is the same guys, racial bias and
gender bias AI systems. When it comes to healthcare, the
algorithm's favored patients who had previously received more medical services.
Black patients historically receive far less medical care or quality

(28:02):
of care compared to white patients, so less accurate predictions
for black patients as health care needs. And then in
medical diagnostics, some systems have been found less accurate in
detecting certain conditions in women in comparison to men. Then
you have finance and credit. There's a socioeconomic bias. You know,
when the algorithms assess credit worthiness based on past barring behavior,

(28:26):
it even came down and this proven that it has
less chance of you know, credit worthiness and acceptance from
marginalized communities who have had historically less access to financial institutions.
And then also racial and gender bias again in lending,
and this is a common theme basically through all of this.

(28:47):
There is a racial and gender bias. And if we know,
based on data that we have that the world is
changing for the better, yes, but women, people of color,
minorities as a whole aren't heavily represented in ways that
they necessarily should be. Again, bias comes. And something that

(29:08):
I found really interesting, especially as I started kind of
getting into AI and the ethical debate surrounding it is
I was watching The Boys, and I don't know how
many of you watched The Boys, but there was an
episode in this last season where Vought is having a
conference and they're announcing all of this stuff, and The
Deep was, you know, they're talking about product placement and

(29:29):
you may recall this scene at vot com and The
Deep in a train introduced this new marketing placement system
and it would basically show African American aligned products to
black households and white aligned or associated projects to white households.
That's literally what this is talking about. And this is real.
This is a real thing. And the boys was making

(29:50):
fun of it, you know, and some dark humor and whatnot,
that it's already happening, you guys. And studies again have
shown that AI driven ad platforms can result and guess
what I mean, you guys can go ahead and finish
my sentence, racial and gender biases. Job ads for high
paying positions have been shown more frequently to men than women,

(30:11):
and ads for housing or finance products may be targeted
differently based on that particular user's demographic profile. And I
love and I'm obsessed with social media and AI, especially
the ad platforms, because social media platforms may create filter
bubbles that reinforce a user's existing beliefs or preferences. And

(30:35):
we see it all the time on Facebook and things
like that, right, I mean, it really is this simple.
You know, Aunt Judy who believes in www dot fucky
Americanamericaneagle dot com right in their news and crazy reports
and stuff like that, when she clicks on these different sites,
and you know, the cookies. AI can predict and say, okay,
this woman is you know, white, Christian, far right dah

(30:59):
da da da, and then list or provide ads to
products and services and other sites based on her profile
and social media profile that her footprint more or less,
and then that data is going to one day be
historical data that another aisystem learns from. I mean it

(31:19):
literally is basically a big circle jerk. Every time we
do anything in this world, we are leaving our data
and our footprint, whether it's our phones tracking us, listening
to us. How many of you guys have been sitting
having a conversation with a friend or spouse or whoever
and you talk about something so fucking random, right. I
was making some cardamom strucful muffins one night and which

(31:44):
they're my favorite, and all of a sudden, all of
a sudden, out of nowhere, I started getting laundry ads
for it, for cardom scented laundry pods. So we are
constantly being tracked and listened to, and we have data.
There's I can't remember at the time of recording this,
but there is an incredible documentary on Netflix about just

(32:06):
how wide our data footprint goes and it's crazy. It
goes way above and beyond anything that you would ever
even imagine. And that's what's currently happening. And all of
this data is that's where the money is, y'all. It's
in the selling of data. How do you think Twitter

(32:27):
made its money? I was a Twitter employee and that's
how Twitter makes its money. Data is the most valuable
asset that most companies can have, and that brings up
questions like who owns this data? What happens if this
data gets leaked? You know, there is a very low
degree of transparency currently in terms of data handling practices,

(32:49):
and that's essential ensuring someone's control over their own personal
information in how it's used. Facebook makes a half assed
attempt at pretending like we do here download your file,
or you can you remove your Facebook account and blah
blah blah. But it's still there. All of our data
is still there. And Facebook is one of the worst.
It's selling our information to companies and other entities. Then

(33:15):
we have the you know, economic impact of AI too,
AI and automation technologies, because as technology grows and progress
is made on the technological front, you know, we're always
looking to make our lives more simple to increase efficiency,
especially god bless capitalism. Basically, fuck the people, increase efficiency.

(33:37):
And so we have things like self checkouts or automated systems,
and increasingly robots and things like that. And as machines
take over all of these different tasks, there's a growing
concern about widespread job displacement and its impact on the workforce.
And then as everyone knows impact on the workforce directly
impacts the economy and automation and manufacturing and customer service

(34:02):
and things like that. You know, how many of you
guys are pissed off at the virtual chatbot? Like if
I have a question about my AT and T phone
bill or my internet bill, or you know anything, and
you can't get through to a person anymore. You have
a virtual assistant or a virtual chat box things like that.
How many people do you think AT and T or

(34:23):
Comcast or whoever laid off or didn't hire because they
now have a virtual assistant that can scan thousands of
pages of data and process and SOPs and answer questions.
They don't have to pay someone to sit on the
phone at a cubicle somewhere. But I would like to

(34:44):
get back to crime detection and policing. AI has evolved
from a speculative concept into an actual tangible asset in
various sectors, especially in law enforcement, and its integration into
policing has trans formed how authorities approach crime detection and prevention.

(35:04):
And there are so many different applications of AI in policing,
its growth and specialization, and also the implications for future
law enforcement practices because a lot of you're going to
see a lot of change in modern policing because of
AI and AI's integration into law enforcement has it has
proven to significantly enhance the efficiency and effective effectiveness of

(35:29):
crime detection. Historically, AI technology found its primary applications in
things like finance, healthcare, transportation, especially manufacturing, but its adoption
by police forces worldwide is a more recent phenomenon, and
the transformative potential of AI and policing is becoming increasingly

(35:51):
evident as law enforcement agencies leverage these tools to bolster
their capabilities and currently as it stands right now today,
modern law enforcement agencies utilize AI for several different functions
like surveillance, video analysis, facial recognition. AI systems can monitor crowds,

(36:13):
analyze video footage for criminal activity, and utilize facial recognition
technology to identify suspects. And this technological advancement allows law
enforcement agencies to focus their resources more strategically and efficiently.
Say you have a drone equipped with sensors that can

(36:33):
provide valuable data about locations, you know, facilitating informed decision
making before conducting operations. We see that all the time
in the military, drones equipped with different technologies and provides
I in the sky, things like that it can scan
faces from literally thousands of feet above and things like that.

(36:55):
Its role in crime prevention and resolution is expected to
become even more pronounced. And there's a lot of contention
and debate and controversy surrounding that. And as I've stated,
facial recognition technology is the most prominent AI application in policing.
I mean, by far, no contests, no question. By using

(37:16):
closed circuit cameras in public spaces, authorities can identify and
apprehend individuals involved in criminal activities. And this technology is
particularly useful in high security areas like airports, railway stations,
where constant surveillance is crucial. Imagine AI. You know, closed

(37:37):
circuit camera right in a busy airport, and it's just
constantly scanning, scanning, and it can connect to different systems
and identify people things like that. I mean, that's a
kind of terrifying, right, But b it could stop an
attack of some sort, or you know, locate a criminal

(37:57):
who's trying to flee to a different state, something like that. Like,
it has different applications, and in addition to the facial recognition,
AI's application extends to video technology, which aids in monitoring
large crowds like festivals, sporting events, things like that. AI
powered cameras and video systems enhance the ability of law

(38:18):
enforcement agencies to detect suspicious activities in real time. And
that's vital for ensuring public safety in large gatherings where
manual surveillance would be impractical. You know, you think about
older films and stuff like that where it has some
greasy dude in an office watching five thousand cameras. I mean,

(38:39):
that's just not logical. When we have a technology like
this available. And then when it comes to policing, the
use of robots is on a huge increase. These robots
can perform dangerous tasks like bomb disposal, reconnaissance, imagine hostage
taking in environments things like that. By utilizing AI, the

(39:00):
robots can navigate complex situations and do tasks that would
be too hazardous for human officers. So that obviously not
only enhances the operational safety, but also expands the scope
of tasks that can be efficiently managed by law enforcement agencies.
If a department doesn't have to worry about sending fifty

(39:22):
officers into, you know, surrounding or going into say a
bank robbery, you know that has hostages, and they can
send in a robot to see, you know, a robot
equipped with thermal and video speaker of the whole bit.
I mean, that's a huge upgrade. Ani's ability to analyze
vast amounts of data provides law enforcement with tools for

(39:44):
predicting the criminal activities. As we've talked about, artificial neural
networks are what they're called, and they're employed to identify
patterns and predict potential criminal behavior by analyzing data sets,
and that includes social media posts, internet activity. So that
predictive capability extends to detecting crimes such as money laundering

(40:06):
and fraud. Because AI can identify suspicious financial transactions and
other anomalies in literally a millisecond, point police in the
right direction and in terms of financial transactions, I mean
that can also be said for retail too. AI can
help identify or flag suspicious purchases of chemicals or tools

(40:29):
or things like that. Shipping companies can use AI to
prevent human trafficking by identifying suspicious cargo. I mean, there
are so many different applications from it that would be
just transformative to the world of criminal to modern policing.
And of course we need to be thinking about human
rights and privacy throughout all of this. And I think

(40:53):
that's the most interesting debate when it comes to policing
is privacy. I mean, how would you like it if
you're entire the entirety of your all of your social
media platforms, right the data from Facebook, Instagram, Snapchat, like
all of these places, Twitter, all of your posts that
you've ever made have been you know, basically put into
a database or if it's public or whatever. You know,

(41:15):
the system can just in less than a millisecond scan
through all of it. In the wrong hands, that's terrifying.
But what's been rolled out so far, it's called real
time Crime centers or rtccs. They are quite literally revolutionizing
how law enforcement agencies process, analyze, and respond. And the

(41:36):
primary advantage of AI in these rtccs is its capability
to handle and interpret and analyze vast quantities of data
from a variety of sources in real time. So again,
it enhances threat assessment, strategic planning, and overall crime prevention efforts.
If AI can identify crime trends, hot spots, and prevalent

(41:59):
prevalent criminal tactics, that allows law enforcement to allocate resources
more effectively, schedule their patrols based on new patterns, implement
targeted crime prevention strategies. I mean, it really can change
and do a lot proactively, and that's a forward looking approach.
It really doesn't enhance public safety by allowing early intervention.

(42:24):
Once trained, they can recognize specific features and images. Imagine
for a second, the Moscow murders, right, Brian Coberger and
all of that. You know how they kind of sort
of identified the car pretty quickly within you know, like
the first week or so, they knew which make and
model of the car they were looking at. AI can

(42:44):
actually assist with that. It can analyze every picture of
every model of car basically in the history of the world,
and then analyze and cross reference that against the CCTV
footage and then pop out with huge accurate see the
make and model of a vehicle that was involved in
the crime, just by analyzing pixel patterns, which wouldn't be

(43:08):
impossible for a human or officer to do, but it
sure makes it a hell of a lot easier in
a few split seconds versus someone sitting down and zooming
in pixel to pixel and having to learn everything. I mean,
it is pretty damn near impossible for a human.

Speaker 1 (43:21):
To do that.

Speaker 3 (43:23):
Same thing after math of say a hit and run accident.
It can cross reference surveillance footage with descriptions all on
social media. Imagine a terror attack or a mass shooting
or something of that nature. It can simultaneously search social
media for any sort of threat or information description. You know,

(43:43):
things like that because it minimizes the biases that can
affect human judgment, and it ensures, typically in these instances
at least, that decisions are based on objective data rather
than subjective beliefs, stereotypes and opinions. And as AI technologies
advanced their impact on policing and our TCCs is expected

(44:06):
to grow. You know, they may have responsible AI dashboards,
multimodal collaboration, tools, real time officer wellness monitoring, and advanced
anomaly detection systems.

Speaker 2 (44:17):
I mean, it.

Speaker 3 (44:18):
Could really facilitate deeper integration with digital currencies, cryptocurrency, cybercrime analytics,
and there could also be a global network of the
real time crime tracking. In Malaysia, AI software for CCTV
cameras is being developed to autonomously detect and report crimes

(44:39):
in real time by analyzing the footage, so the software
can identify if a person is wheeling a weapon, it
can assess aggressive behavior based on body movements, and then
it alerts law enforcement. So if someone runs down the
street with a gun out, or you know, shooting at someone,
or even just waving or wielding a machete, the AI

(45:00):
system can automatically detect that and then alert the local
the closest law enforcement department in Malaysia, they actually have
it down so that it can identify you know, it
has facial recognition and gate recognition. If you have a
wonky leg, you're not gonna get past it. And then
it's not only even active current policing, it's also being

(45:23):
utilized in forensic science. AI has greatly enhanced DNA processing,
leading to breakthroughs and solving cold cases. You know, we
all have done at least I mean, guilty is charged.
Here the DTC genetic databases that have been instrumental in
solving over one hundred and fifty cold cases and identifying

(45:44):
notorious criminals like the Golden State Killer. How many stories
have you seen where ancestry dot Com or twenty three
AE meters helped find helped police officers or genetic genealogists,
forensic genealogists solved a.

Speaker 2 (46:00):
A cold case.

Speaker 3 (46:01):
You know, from twenty nineteen there were six five hundred
and forty four cold cases. And this technology continues to
offer people hope that one day maybe they had a
cold case, or a friend loved one was murdered five
or six years ago. You know, there's still hope that
maybe one day that that can be solved. And the
hope hinges typically on DNA and these types of systems.

(46:26):
And then we have the RAIS, which is risk assessment instruments,
and that's used to evaluate the likelihood of a suspect reoffending.
It can assist in the prosecution process, so even in trials,
AI can be utilized because studies have shown that RIIS
can provide consistent and accurate risk assessments, particularly when doing

(46:48):
checklist style algorithms to evaluate factors like age, number of
court appearance appearances, seriousness of the offense, so it could predict,
potentially with great action if this person. You know, let's
say a guy stalks his girlfriend and an assaults her,
what is the percent chance of him reoffending and doing

(47:10):
this to someone else? But most importantly, when it comes
to policing, all anyone really cares about is if it
can solve crimes, like has AI solved crimes thus far?

Speaker 2 (47:22):
An example of this would be the Warner.

Speaker 3 (47:23):
Robbins Police Department out of Georgia, and that department is
one of the first law enforcement departments to provide a
pretty compelling pace study in the integration of AI technology
into traditional investigative practices. This particular department did not have
a dedicated cyber crime division, so the WRPD, again Warner

(47:45):
Robbins Police Department, turned to cybercheck, which is a software
designed to enhance investigative capabilities through data analysis.

Speaker 1 (47:55):
Now.

Speaker 3 (47:56):
Cybercheck was developed by Adam Moscher in twenty sixteen, and
it's an AI program that basically aggregates and analyzes extensive
amounts of online data, and the software has gained prominence
for its ability to generate comprehensive quote unquote cyber profiles
or cyber DNA of individuals involved in criminal investigations because

(48:20):
what it does as a tool is it scours multiple
layers of the Internet and then it provides law enforcement
with insights that are almost always missed by conventional methods.
It can collate a wide array of data, including social
media interactions, employment records, IP address even cryptocurrency transactions, cell

(48:45):
phone numbers, address in the rest of everything, and it
can do it in almost no time at all. And
that information allows investigators to form a detailed profile of
both suspects and victims and can you know, reveal connections
and leads, can forecast, can do all the things in cyberchech.

(49:06):
In particular, its impact on solving criminal cases has been
pretty notable. According to Cyberchech's website, it has played a
role in resolving two hundred and nine homicide cases, one
hundred and seven cold homicide or missing person cases, eighty
eight child pornography cases, in thirty seven instances of human

(49:27):
trafficking across several states, including Florida, North Carolina and California.
That's a lot of success for an AI tool, and
for the Warner Robbins Police Department, cybercheck has become an
invaluable asset in tackling cold cases. A gentleman by the
name of Lieutenant Justin Clark, who oversees the department's use

(49:50):
of cybercheck, has highlighted its importance in providing new leads
and insights that otherwise would have been hidden. And the
thing about it is that the integration of cybercheck, and
this is one of the very first studies that have
been done in terms of a full scale police department
adopting an AI tool, there were some challenges. A pro

(50:12):
would be that it can obviously analyze vast quantities of
data like witness statements, digital forensic evidence, you know, everything
that I've mentioned already. But the thing about it is
that the program is straightforward and it pulls from all
of these different layers of the Internet and life. But
for really complex cold cases from the past, it can

(50:34):
take months to actually receive the results of that, and
the software can only handle just like a limited number
of cases at one time, so the need for prioritization.
But I mean, those are really small scale challenges at
the end of the day, right, cybercheck has proven effective,
particularly in providing new leads and identifying connections between people.

(50:57):
I mean, imagine, you know, analyzing someone like a robber
or homicide person, and then you're able to just base
solely on pulling all of these different types of records
or social media accounts or whatever, able to pinpoint a
new person or make a connection or a link between people,
maybe providing a motive things like that. I mean, it's

(51:18):
actually pretty incredible. But again we have the question of
human rights and privacy. The use of AI and law
enforcement does raise really important ethical considerations.

Speaker 2 (51:32):
So with cybercheck.

Speaker 3 (51:33):
Cybercheck operates by analyzing publicly available information, which means that
investigators can access that data without a warrant. It would
just take them an ungodly amount of time, whereas cybercheck,
depending on the age of the case itself, can do
it in a day or months, whereas it would take
detectives years potentially depending on how complex and.

Speaker 2 (51:55):
Old it is.

Speaker 3 (51:56):
But that absolutely, I mean, the approach is legal for cybercheck,
but it underscores the need for balancing investigative benefits with
respect for someone's privacy. And in conclusion here because we've
reached the end of this episode, the Warner Robbins Police
departments experience with Cyberchech exemplifies how AI can transform law

(52:17):
enforcement practices. There are challenges, but I think that if
you're interested in this topic whatsoever, just read about the
successful application of cybercheck in solving cold cases, because that
really does highlight the potential of AI with policing AI
as a whole, and how it can make significant contributions
to criminal investigations. And if we know anything you guys,

(52:41):
technology is going to continue to advance and the collaboration
between AI tools and traditional investigative methods, I mean it
is going to shape the future of law enforcement and
the justice system. I mean it really, really, really is.
And I know that a lot of you who listen
are really interested in the criminal justice justice reform, you know,

(53:01):
things like that sentencing, and it is going to throw
all of that on its head. It's definitely going to
compliment it. But again, because of the ethical issues and questions,
there's a lot to discuss, and I'm really fascinated by
all of the different debates surrounding this topic. Now because
it's just so much especially, I mean, AI is just

(53:23):
becoming and drenched in everything now. It's really interesting to
the difference in age, right how people are responding. I
feel like the younger generations are just ripshit livid over
the adoption of AI, and then the older generations are
just like, Eh, who cares, that's cool.

Speaker 2 (53:44):
I don't I don't really care. You know, in the
case of L. S.

Speaker 3 (53:47):
Dunes and Anthony Green, you know, they came out, there
was so much hatred, in vitriol just against them when
that music video came out and the band was like, yeah,
we understand, we're listening to you. Sorry, you know, we're
but we're listening to you. And then Anthony Green came
out and was like, I don't understand why it's such
a big fucking deal, and then you know, reigniting the controversy.
So it's it's fascinating, But I want to know, above anything,

(54:10):
what you guys think. Are you a fan of AI
and its integration into modern society?

Speaker 2 (54:17):
Do you think it should be regulated?

Speaker 3 (54:21):
Do you think we need to quickly look at legal
avenues for you know, safety, privacy, intellectual copyright, you know,
things like that, like should we be currently trying to
further safety.

Speaker 2 (54:36):
And precaution and that you know, the precautions for.

Speaker 3 (54:38):
AI or is this something that's like nope, let's just
get into the future and figure it out as we go,
because it is here that is certain. But that's it
for today.

Speaker 1 (54:48):
Guys.

Speaker 2 (54:49):
Again, you've been listening to We Saw the Devil. This
is Robin.

Speaker 3 (54:52):
The website is still a work in progress. I promise
you it'll be up and running, you know, pretty soon.
Beyond that, you can follow the s show on Instagram
or Twitter I refuse to call it X or Twitter
at We Saw the Devil podcast and We Saw the Devil,
or you can follow me personally at Robin Underscore WSTD.
The next episode, early next week is going to be

(55:14):
the final again, the final Chris Chan episode. I am
super super, super super super excited about that. God, it
seems like it's taken forever. I'm not gonna start crapping
on myself here, guys, but I swear to God, I
found Chris Chan so fascinating in the beginning, and there
was just so much information to cover with him, and

(55:34):
I am so tired of it. So I'm gonna join
with you guys, and celebrating the final episode of Chris
Chan But beyond that, y'all, we are approaching Halloween again
and that means.

Speaker 2 (55:47):
It's horror movie time.

Speaker 3 (55:49):
So I may be bringing people on to discuss some
horror films and things like that occasionally because it is
the season and it's what makes me happy. And you
guys are going to meet my girlfriend and she's going
to come on and talk about movies. And also she's
from a county here in Tennessee, Born that has very
storied crimes, crime family constantly in the news, and so

(56:11):
maybe some little stories and things like that.

Speaker 2 (56:14):
And as always, if you.

Speaker 3 (56:15):
Have any questions, compliments, complaints, you can send those over
to info at wesawthedevil dot com. But that's it for today, y'all.
Until next Crime