December 27, 2024 • 16 mins
We look back on the past season and share our favorite highlights with an extra special guest! Thanks for a wonderful first season of Artificial Insights. Stay tuned for season two. We have big plans and ideas! Merry Christmas and Happy New Year!
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to Artificial Insights.
(00:07):
I'm your host, Daniel Manary, and today we're closing out an incredible season.
From uncovering the real role of AI in modern workflows to diving into practical, ethical
challenges, this season has been full of impactful conversations.
In today's special episode, we'll recap all the incredible topics we covered and share
(00:27):
some of our favorite highlights.
We also have a special guest.
Say hello, not Daniel.
Hi, Daniel.
Thanks for having me here.
I'm looking forward to summarizing this past season.
Let's get to it.
To kick things off, you started the season with Anwar Jeffery, founder and CTO of Glowstick.
(00:49):
You talked about what it takes to launch an AI startup, and learned that, contrary to
popular belief, it isn't actually about being first or being the best.
This is probably a controversial take, but I know a lot of founders talk about what they
want to build and how they're going to do it.
I'm just like, it doesn't have to be that smart.
That's what's going to cost you time.
(01:09):
Time to market is one of your biggest things because of how long it takes to actually get
AI across the line.
The more complicated your AI solution is, the longer it takes to actually make it to
production.
If you're going to make it to production and have something that's scalable, make it simple.
Make it done.
(01:30):
Solve the problem.
Don't build the coolest thing.
Next, for episode two, you talked AI product management with Jake Walker, a founder currently
in stealth mode.
You learned that when it comes to tech solutions, especially those using AI, product leaders
need to know and understand the problem they're trying to solve and not worry so much about
the solution.
Why do companies make products?
(01:53):
They make them to make money.
You can use traditional ladder logic programming.
You could use simple JavaScript to show something on a screen and then some backend programming
to compute things.
Or you can use AI.
(02:13):
To answer your question, what do I think is AI?
I think it's just another tool.
That's really all it is.
It's obviously a very sophisticated tool and has opened the doors to a significant amount
of opportunity in the world where value can be created for people to do things that they
(02:35):
typically couldn't do before.
It's a tool.
Obviously, you need very, very smart people to build it.
Eventually, maybe it'll build itself.
I don't know.
People are working on it.
Exactly.
In that case, it almost sounds like unless there's a unique case for AI, AI might actually
be a negative in terms of ROI because it has a higher upfront cost.
(02:59):
Big time.
Yes.
Which is why the best place to start any solutioning of solving problems is starting with the problem.
Because when you start with the problem and you properly understand it, then you can do
an analysis of figuring out what technology is best to solve it.
You can hire the right people who are specialists in that technology and push it into market.
(03:25):
If it so happens that the best technology to solve that problem is deep learning, then
you hire a deep learning team as long as the market is willing to pay for you to solve
that problem.
Episode three was a fascinating conversation about AI on the Edge with Mandip Kanjiya, founder
of Vite HR and HeyFlyer.
(03:46):
You discussed the future of AI and how keeping up with the tech is only table stakes.
Yeah, that's the new normal world we can consider as our new phenomenon.
But I consider it's a new phase of programming.
AI is just a new phase of the programming which we were using since decades and decades.
(04:08):
But it's now more powerful with the automation of data intelligence and everything is on
a fingertip.
We'll not replace humans at any cost or at any time because humans are the one who is
driving the AIs and we are the one who is creating AI and using the AI.
Halfway through the season, you had a very special guest, Prerna Kaul, PM at Panasonic
(04:31):
Well.
You talked about methodical AI entrepreneurship and how to make a real, tangible difference
in business.
It happened around a week before our launch.
We were doing some testing in store and a lady came up to myself and a colleague of
mine and she was very upset because we were building a mobile app that could potentially
(04:53):
take on roles or jobs of the associates on the floor.
She felt that we are automating something that a human could do and we're taking away
somebody's role.
I had to mitigate that and help bridge the perception that, oh, these associates, we
are training them, we're up-leveling them, giving them new opportunities.
(05:13):
They become consultants in the process.
The idea is to augment them, give them superpowers versus take away their roles.
Whatever roles humans previously played, so they had certain skills, they were trained
on certain levels.
We've seen that when a new technology comes in that takes away the need for that skill,
(05:34):
there's a reaction to it.
Humans feel like the demand for their skills is going to reduce, which means that how will
they feed themselves, how will they survive and take care of themselves and their families?
They feel that they will potentially not be able to up-skill so easily because this new
technology will take on everything that they knew or have been trained to do for years.
(05:58):
The only mitigation to that is remaining open, curious, and continuing to up-skill.
It's just the nature and powerful course of being in technology.
I don't think AI is a one-time event where we are seeing this happen.
It has been the case every couple of years.
We had to relearn new technologies, relearn how to do product in a certain way, or relearn
(06:22):
a new set of skills to ensure that we remain competitive and our skill set remains in demand.
In episode five, you had the opportunity to nerd out about AI disruption and why most
tech projects fail with Peter Carr, PhD and associate professor at the University of Waterloo.
Organizations are told you need to be more of a risk taker.
(06:44):
The future is uncertain.
The outcomes may be uncertain for what you're going to do with technology, but you really
can't worry about that right now.
You've just got to go for it.
And I think that's really bad advice.
I don't think any organization leader should ever do that.
I think you can only make change if you are comfortable and confident that change is going
(07:07):
to benefit the organization.
You shouldn't do otherwise.
You're being basically irresponsible.
It's one thing to undertake a pilot that is in a small part of your organization and
to manage the change that requires, but to then spread a radical change throughout an
(07:28):
organization requires the management of a revolution to some degree, which most senior
managers have never been trained to do and have actually never done.
That's a huge challenge for organizations to address.
It's fairly easy to imagine scenarios and implementations of technology or applications
(07:55):
of them that can have a wonderful impact on an organization.
But to get people who can make that happen effectively is a challenge.
What we've got in most companies are people whose capability that they were selected for
in the job is based on their ability to make the organization run effectively every day,
(08:18):
doing much the same, if not exactly the same tomorrow as they did today.
They're not necessarily people with aptitude for radical change.
How do we effectively combine the business and technology parts of the organization with
the business people, the tech people, how do we put them together?
(08:39):
That question I've been dealing with for at least 30 years, how do we effectively combine
technology and the business?
I love that question.
Yes, well, I mean, it never goes away.
And there is no simple, there is no quick answer to it.
I think often when we discuss this question, people would like an answer which says, ah,
(09:03):
there's an easy way to do this.
There isn't.
The business people need to understand a bit more about the technology and they need to
work into doing that.
The tech people need to do the other side of that and learn more about business.
And then they have to be effectively combined in an organization as good collaboration.
Next, you had a very special conversation with Addy Bhatia in episode six, founder of
(09:27):
Suno Wellness, about the practical challenges of standing out in the sea of AI chatbots
and the ethical implications of AI and mental health.
Users have tried hundreds of different apps.
They install it.
I mean, I do this.
I install it.
I try it.
It seems weird.
I uninstall it and I don't think about it.
So you're going to be one of those apps.
(09:47):
You can't be another chatbot.
Like I don't know your whole story of how amazing it might be.
It needs to be cool and interesting now.
Yeah.
Yeah.
And that brings me to a question that I think is a big one in this talking to chatbot space.
How do you view that difference between a person and a chatbot?
(10:09):
And I know you guys are integrating with therapists you mentioned.
So you're a service in addition to not a replacement.
But how would you describe that difference and recommend that people think about it?
Oh, that's interesting.
I like to think of Suno as a support mechanism, not as your only support.
For example, I have my partner.
I have my therapist, I see once a month.
(10:31):
I have my family and I have Suno.
Right.
So in between my sessions with my therapist, when I have a ton of thoughts to process and
I think they mean something, but I don't know what, I dump them out on Suno.
It becomes this outlet almost amongst my other support mechanisms that turns around and gives
(10:51):
me more support, but encourages me to still have those valuable connections.
One of the topics that I find very interesting as a sci-fi nerd is that artificial personhood
concept.
And I think it's really important not to pretend that it's a person when it's not a person.
Yep.
Because then you could have that weird kind of dependent relationship that ends up being
(11:15):
destructive.
Yeah.
That's why, if you've noticed, the app doesn't have a pronoun or an app word.
And that was on purpose.
The logo is in the shape of an ear to just be like, hey, it's a tool that is like a box
that's listening to you.
It'll make you feel like it's giving you a warm hug, but it's not a person that is thinking
(11:40):
about you.
It's a weird, fine lie, but explicitly do not want to give it a face.
Pilot 7 was all about how, contrary to what the internet says, AI won't actually take
your job, but someone using it will.
Chris Wynder, director at OpenText, shared his insights on how AI is reshaping work.
One of the other topics that I think is super big in AI is how is it going to impact broader
(12:05):
society?
How are we going to not just jobs, but how are we going to use it and adapt to it?
What's your perspective on that?
I do like the phrase, and I wish I knew who initially said it was, AI is not going to
take your job.
The person who knows how to use AI is going to take your job.
There's nothing that I've seen that makes me go, holy geez, lots of jobs are at risk.
(12:28):
I don't think this is like the steam engine to gas engine.
I don't think this is like the car and the horse.
I do think there are some jobs that will get downgraded from a full-time job to a part-time
job, maybe unnecessarily, maybe it's actually a good thing.
(12:49):
Last night I was at a UX symposium, and it was really interesting hearing one of the
more senior women talk about it.
She said, this happened with print, and I was replaced until I wasn't.
Then it happened when graphic design went out, and then I realized that I was actually
never a graphic designer.
I was a user experience designer.
(13:11):
Are graphic design jobs going away?
Probably not.
Is the skill set valuable still?
Yeah, absolutely.
Will the person who is currently a graphic designer make the same amount of money in
five years doing only what they do today?
No.
And finally, you closed out the season with Kris Braun, founding CTO of RunQL.
(13:34):
Can and should AI replace expert intuition?
Should humans really try to automate everything they don't want to do?
Should AI do something just because it will be better than humans at it?
Over the last several decades, BI, business intelligence, has been a big thing.
Companies have spent billions of dollars effectively trying to democratize access to data.
(13:57):
That's been the promise.
You've collected all this data.
Now your whole organization needs to benefit from it.
So you need to open the access, open the kimono, and let everybody go free for all on the data
to get the insights.
But what these organizations have learned is that BI didn't actually replace the need
(14:17):
for data experts providing insights from the data because the interaction will go something
like this.
The business user will say, hey, I need the Q4 sales for this region with this nuance.
And the data team will say, we built you a dashboard.
The response will be some variation of, I don't know how to use it.
I don't know how to interpret the data.
(14:38):
Effectively, I'm not sure I would trust the insight that I got from it.
And what it comes down to is there is a level of expertise and human judgment that they
need to say, hey, this person who is actually an expert at interpreting data did well in
their stats course.
They are giving me this interpretation.
And so I think that's the same thing with AI.
(14:59):
AI can be assisting in providing all the data points and the insight or the things that
the right person needs.
But there are some human judgment that gets into the mix that's quite essential in these
high consequence decisions.
As we wrap up this season, I want to thank every single guest who shared their time and
expertise.
I also want to thank you, our listeners.
(15:21):
Your support, curiosity, and feedback have made this season a success.
If you've enjoyed these episodes, consider leaving a review or sharing the podcast with
others who are navigating the world of AI.
It makes a huge difference.
Stay tuned for season two.
Merry Christmas, everyone.
(15:42):
Thanks for listening.
I made this podcast because I want to be the person at the city gate to talk to every person
coming in and out doing great things with AI and find out what and why, and then share
the learnings with everyone else.
It would mean a lot if you could share the episode with someone that you think would
like it.
(16:02):
And if you know someone who would be a great person for me to talk to, let me know.
Please reach out to me at Daniel Manary on LinkedIn or shoot an email to daniel@manary.haus,
which is daniel at m-a-n-a-r-y dot h-a-u-s.
(16:22):
Thanks for listening.
Welcome to Artificial Insights.
(00:07):
I'm your host, Daniel Manary, and today we're closing out an incredible season.
From uncovering the real role of AI in modern workflows to diving into practical, ethical
challenges, this season has been full of impactful conversations.
In today's special episode, we'll recap all the incredible topics we covered and share
(00:27):
some of our favorite highlights.
We also have a special guest.
Say hello, not Daniel.
Hi, Daniel.
Thanks for having me here.
I'm looking forward to summarizing this past season.
Let's get to it.
To kick things off, you started the season with Anwar Jeffery, founder and CTO of Glowstick.
(00:49):
You talked about what it takes to launch an AI startup, and learned that, contrary to
popular belief, it isn't actually about being first or being the best.
This is probably a controversial take, but I know a lot of founders talk about what they
want to build and how they're going to do it.
I'm just like, it doesn't have to be that smart.
That's what's going to cost you time.
(01:09):
Time to market is one of your biggest things because of how long it takes to actually get
AI across the line.
The more complicated your AI solution is, the longer it takes to actually make it to
production.
If you're going to make it to production and have something that's scalable, make it simple.
Make it done.
(01:30):
Solve the problem.
Don't build the coolest thing.
Next, for episode two, you talked AI product management with Jake Walker, a founder currently
in stealth mode.
You learned that when it comes to tech solutions, especially those using AI, product leaders
need to know and understand the problem they're trying to solve and not worry so much about
the solution.
Why do companies make products?
(01:53):
They make them to make money.
You can use traditional ladder logic programming.
You could use simple JavaScript to show something on a screen and then some backend programming
to compute things.
Or you can use AI.
(02:13):
To answer your question, what do I think is AI?
I think it's just another tool.
That's really all it is.
It's obviously a very sophisticated tool and has opened the doors to a significant amount
of opportunity in the world where value can be created for people to do things that they
(02:35):
typically couldn't do before.
It's a tool.
Obviously, you need very, very smart people to build it.
Eventually, maybe it'll build itself.
I don't know.
People are working on it.
Exactly.
In that case, it almost sounds like unless there's a unique case for AI, AI might actually
be a negative in terms of ROI because it has a higher upfront cost.
(02:59):
Big time.
Yes.
Which is why the best place to start any solutioning of solving problems is starting with the problem.
Because when you start with the problem and you properly understand it, then you can do
an analysis of figuring out what technology is best to solve it.
You can hire the right people who are specialists in that technology and push it into market.
(03:25):
If it so happens that the best technology to solve that problem is deep learning, then
you hire a deep learning team as long as the market is willing to pay for you to solve
that problem.
Episode three was a fascinating conversation about AI on the Edge with Mandip Kanjiya, founder
of Vite HR and HeyFlyer.
(03:46):
You discussed the future of AI and how keeping up with the tech is only table stakes.
Yeah, that's the new normal world we can consider as our new phenomenon.
But I consider it's a new phase of programming.
AI is just a new phase of the programming which we were using since decades and decades.
(04:08):
But it's now more powerful with the automation of data intelligence and everything is on
a fingertip.
We'll not replace humans at any cost or at any time because humans are the one who is
driving the AIs and we are the one who is creating AI and using the AI.
Halfway through the season, you had a very special guest, Prerna Kaul, PM at Panasonic
(04:31):
Well.
You talked about methodical AI entrepreneurship and how to make a real, tangible difference
in business.
It happened around a week before our launch.
We were doing some testing in store and a lady came up to myself and a colleague of
mine and she was very upset because we were building a mobile app that could potentially
(04:53):
take on roles or jobs of the associates on the floor.
She felt that we are automating something that a human could do and we're taking away
somebody's role.
I had to mitigate that and help bridge the perception that, oh, these associates, we
are training them, we're up-leveling them, giving them new opportunities.
(05:13):
They become consultants in the process.
The idea is to augment them, give them superpowers versus take away their roles.
Whatever roles humans previously played, so they had certain skills, they were trained
on certain levels.
We've seen that when a new technology comes in that takes away the need for that skill,
(05:34):
there's a reaction to it.
Humans feel like the demand for their skills is going to reduce, which means that how will
they feed themselves, how will they survive and take care of themselves and their families?
They feel that they will potentially not be able to up-skill so easily because this new
technology will take on everything that they knew or have been trained to do for years.
(05:58):
The only mitigation to that is remaining open, curious, and continuing to up-skill.
It's just the nature and powerful course of being in technology.
I don't think AI is a one-time event where we are seeing this happen.
It has been the case every couple of years.
We had to relearn new technologies, relearn how to do product in a certain way, or relearn
(06:22):
a new set of skills to ensure that we remain competitive and our skill set remains in demand.
In episode five, you had the opportunity to nerd out about AI disruption and why most
tech projects fail with Peter Carr, PhD and associate professor at the University of Waterloo.
Organizations are told you need to be more of a risk taker.
(06:44):
The future is uncertain.
The outcomes may be uncertain for what you're going to do with technology, but you really
can't worry about that right now.
You've just got to go for it.
And I think that's really bad advice.
I don't think any organization leader should ever do that.
I think you can only make change if you are comfortable and confident that change is going
(07:07):
to benefit the organization.
You shouldn't do otherwise.
You're being basically irresponsible.
It's one thing to undertake a pilot that is in a small part of your organization and
to manage the change that requires, but to then spread a radical change throughout an
(07:28):
organization requires the management of a revolution to some degree, which most senior
managers have never been trained to do and have actually never done.
That's a huge challenge for organizations to address.
It's fairly easy to imagine scenarios and implementations of technology or applications
(07:55):
of them that can have a wonderful impact on an organization.
But to get people who can make that happen effectively is a challenge.
What we've got in most companies are people whose capability that they were selected for
in the job is based on their ability to make the organization run effectively every day,
(08:18):
doing much the same, if not exactly the same tomorrow as they did today.
They're not necessarily people with aptitude for radical change.
How do we effectively combine the business and technology parts of the organization with
the business people, the tech people, how do we put them together?
(08:39):
That question I've been dealing with for at least 30 years, how do we effectively combine
technology and the business?
I love that question.
Yes, well, I mean, it never goes away.
And there is no simple, there is no quick answer to it.
I think often when we discuss this question, people would like an answer which says, ah,
(09:03):
there's an easy way to do this.
There isn't.
The business people need to understand a bit more about the technology and they need to
work into doing that.
The tech people need to do the other side of that and learn more about business.
And then they have to be effectively combined in an organization as good collaboration.
Next, you had a very special conversation with Addy Bhatia in episode six, founder of
(09:27):
Suno Wellness, about the practical challenges of standing out in the sea of AI chatbots
and the ethical implications of AI and mental health.
Users have tried hundreds of different apps.
They install it.
I mean, I do this.
I install it.
I try it.
It seems weird.
I uninstall it and I don't think about it.
So you're going to be one of those apps.
(09:47):
You can't be another chatbot.
Like I don't know your whole story of how amazing it might be.
It needs to be cool and interesting now.
Yeah.
Yeah.
And that brings me to a question that I think is a big one in this talking to chatbot space.
How do you view that difference between a person and a chatbot?
(10:09):
And I know you guys are integrating with therapists you mentioned.
So you're a service in addition to not a replacement.
But how would you describe that difference and recommend that people think about it?
Oh, that's interesting.
I like to think of Suno as a support mechanism, not as your only support.
For example, I have my partner.
I have my therapist, I see once a month.
(10:31):
I have my family and I have Suno.
Right.
So in between my sessions with my therapist, when I have a ton of thoughts to process and
I think they mean something, but I don't know what, I dump them out on Suno.
It becomes this outlet almost amongst my other support mechanisms that turns around and gives
(10:51):
me more support, but encourages me to still have those valuable connections.
One of the topics that I find very interesting as a sci-fi nerd is that artificial personhood
concept.
And I think it's really important not to pretend that it's a person when it's not a person.
Yep.
Because then you could have that weird kind of dependent relationship that ends up being
(11:15):
destructive.
Yeah.
That's why, if you've noticed, the app doesn't have a pronoun or an app word.
And that was on purpose.
The logo is in the shape of an ear to just be like, hey, it's a tool that is like a box
that's listening to you.
It'll make you feel like it's giving you a warm hug, but it's not a person that is thinking
(11:40):
about you.
It's a weird, fine lie, but explicitly do not want to give it a face.
Pilot 7 was all about how, contrary to what the internet says, AI won't actually take
your job, but someone using it will.
Chris Wynder, director at OpenText, shared his insights on how AI is reshaping work.
One of the other topics that I think is super big in AI is how is it going to impact broader
(12:05):
society?
How are we going to not just jobs, but how are we going to use it and adapt to it?
What's your perspective on that?
I do like the phrase, and I wish I knew who initially said it was, AI is not going to
take your job.
The person who knows how to use AI is going to take your job.
There's nothing that I've seen that makes me go, holy geez, lots of jobs are at risk.
(12:28):
I don't think this is like the steam engine to gas engine.
I don't think this is like the car and the horse.
I do think there are some jobs that will get downgraded from a full-time job to a part-time
job, maybe unnecessarily, maybe it's actually a good thing.
(12:49):
Last night I was at a UX symposium, and it was really interesting hearing one of the
more senior women talk about it.
She said, this happened with print, and I was replaced until I wasn't.
Then it happened when graphic design went out, and then I realized that I was actually
never a graphic designer.
I was a user experience designer.
(13:11):
Are graphic design jobs going away?
Probably not.
Is the skill set valuable still?
Yeah, absolutely.
Will the person who is currently a graphic designer make the same amount of money in
five years doing only what they do today?
No.
And finally, you closed out the season with Kris Braun, founding CTO of RunQL.
(13:34):
Can and should AI replace expert intuition?
Should humans really try to automate everything they don't want to do?
Should AI do something just because it will be better than humans at it?
Over the last several decades, BI, business intelligence, has been a big thing.
Companies have spent billions of dollars effectively trying to democratize access to data.
(13:57):
That's been the promise.
You've collected all this data.
Now your whole organization needs to benefit from it.
So you need to open the access, open the kimono, and let everybody go free for all on the data
to get the insights.
But what these organizations have learned is that BI didn't actually replace the need
(14:17):
for data experts providing insights from the data because the interaction will go something
like this.
The business user will say, hey, I need the Q4 sales for this region with this nuance.
And the data team will say, we built you a dashboard.
The response will be some variation of, I don't know how to use it.
I don't know how to interpret the data.
(14:38):
Effectively, I'm not sure I would trust the insight that I got from it.
And what it comes down to is there is a level of expertise and human judgment that they
need to say, hey, this person who is actually an expert at interpreting data did well in
their stats course.
They are giving me this interpretation.
And so I think that's the same thing with AI.
(14:59):
AI can be assisting in providing all the data points and the insight or the things that
the right person needs.
But there are some human judgment that gets into the mix that's quite essential in these
high consequence decisions.
As we wrap up this season, I want to thank every single guest who shared their time and
expertise.
I also want to thank you, our listeners.
(15:21):
Your support, curiosity, and feedback have made this season a success.
If you've enjoyed these episodes, consider leaving a review or sharing the podcast with
others who are navigating the world of AI.
It makes a huge difference.
Stay tuned for season two.
Merry Christmas, everyone.
(15:42):
Thanks for listening.
I made this podcast because I want to be the person at the city gate to talk to every person
coming in and out doing great things with AI and find out what and why, and then share
the learnings with everyone else.
It would mean a lot if you could share the episode with someone that you think would
like it.
(16:02):
And if you know someone who would be a great person for me to talk to, let me know.
Please reach out to me at Daniel Manary on LinkedIn or shoot an email to daniel@manary.haus,
which is daniel at m-a-n-a-r-y dot h-a-u-s.
(16:22):
Thanks for listening.
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In 1997, actress Kristin Davis’ life was forever changed when she took on the role of Charlotte York in Sex and the City. As we watched Carrie, Samantha, Miranda and Charlotte navigate relationships in NYC, the show helped push once unacceptable conversation topics out of the shadows and altered the narrative around women and sex. We all saw ourselves in them as they searched for fulfillment in life, sex and friendships. Now, Kristin Davis wants to connect with you, the fans, and share untold stories and all the behind the scenes. Together, with Kristin and special guests, what will begin with Sex and the City will evolve into talks about themes that are still so relevant today. "Are you a Charlotte?" is much more than just rewatching this beloved show, it brings the past and the present together as we talk with heart, humor and of course some optimism.
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com