Hello, this is Eva and you're listening to the In Between Tech
and Trust podcast. In this week's episode, we dive
into one of the most relevant topics that you can look into in
the AI era, and that is the intersection of AI media and
journalism. And for that topic, I have one
of the leading voices with me in conversation, and that is Doctor
Paul Elvas. And Paul is head of AI at funk
comedian Cropper. He's also leading the AI lab
within the company, so he brings his practical view into
translating between stakeholders and implementing AI into the
journalistic aspects of how to publish content and contain
audience trust. So together we dive.
Into how AI intersects with trust, transparency, and the
journalistic. Practice, Paul also shares.
His view on how an AI newsroom of the future should look like.
We also look into the impacts of the so-called AI slop of what,
for example, deepfakes, audience mistrust, and AI generated
content does to the industry. But we also want to look into
tangible ways of how to maintain credibility, democratic
functions and navigating the rapidly changing technological
conditions. Hi, Paul.
Good morning. Good morning, Yifa, nice to be
here. I'm particularly intrigued to
dive into the intersection of tech, trust, and media with you
today. But before we start into the
topic particularly, I would love to hear your thought on the
intersection of tech and trust. What is the first thing that
comes to your mind when you hear that?
So I think like trust and tech isn't really about blind faith.
I think it's has a lot to do about understanding how the
systems work and and who's accountable basically.
So I think initially when especially tech is
transformative, people tend to mistrust the technology and a
lot of trust can be gained when you start working with it or
just do like, yeah, do something with it and then you build up
trust. You understand how the system
works and then you also find out or figure out which components
of the system you can trust and like which other parts of the
system maybe are a little bit more ambiguous and you have to
double check things in this domain.
So I think it has a lot to do with understanding the
technology to basically build up trust for things that are new.
And the things that I knew, something that is like on your
daily program, so to say, because as head of AI at one of
the largest like media houses in Germany, you're basically at the
linchpin of like newness and media and also the technology in
itself of what shapes the industry.
And you also sit at the core of digital transformation.
So what is, according to your opinion and expertise of what
you saw over the past couple of weeks and months, really the
biggest misconception when we talk about AI and journalism
today? I think we have to kind of
differentiate between those within the field of media and
and those who are basically more or less consumers of media.
I would say that as people who are reading the news or
consuming media primarily, there is this belief that that the
media is like not putting a lot of thought into how they use AI.
So I think some of them might have like the the conception at
least that that media companies start using AI just to create
content with it in a very naive manner.
And I think part of this is also true for those who are in the
field or working as, as journalists or in, in media
companies that they initially think now the shift towards AI
means that we have to naively adopt the technology and create
just more content without supervision, without shaping
this how the system work. And I would say the reality is
more like that that now is a, is a time where you basically can
reshape the whole process of creating media, creating
content. And those who basically put a
lot of effort into it and, and know how to integrate the
technology well, they will succeed in a way that they will
not just create a lot of AI slop, let's put it like that,
but actually use AI to amplify also the quality of the media.
I think you can like if you do it right, you can, you can
integrate AI at the right steps in the process of creating
various kinds of content that actually do amplify by the final
results instead of like lowering or damping what comes out.
And media companies shouldn't like just naively adopt the
technology. They should focus on on this
part of figuring out how you can create good content that people
are interested in with the technology.
And you said like a word that does actually all over the news.
It's like the AI slop. Well, does that mean to you
particularly? And also, could you explain a
little bit more of how it impacts your work or also
another work of like the media house that you're part of?
Yeah, I mean, AI slob, I kind of dislike the word a little bit,
but it it's just around there and people use it to describe, I
would say mediocre or bad content that is just created
with AI tools. Could be a short video for
social platforms could be news articles that are published on
pages that are not really trustworthy.
So this is typically the kind of content that we refer to with AI
slop, but also sometimes you can kind of like put this as a label
on a lot of different kinds of content, and sometimes you're
also not really appreciating certain kinds of AI content that
are actually good. I mean, I just recently talked
about the the cat that is playing various instruments on
on the front porch. And I actually believe this is
this is a unique kind of quality content.
Actually, while it is completely created by by AII think it's
VO3A video model that created these scenes where where a cat
is playing. I don't know, a lot of different
kinds of instruments, which obviously you could never film
because a cat would never do this.
But it's really entertaining to to see this kind of idea and
it's funny and, and it has a lot of things that that people would
usually put into content when they created.
So I think we have to be careful with the AI slot label.
But on the other hand, I think it really good, nicely describes
how consumers of media are now have a hard time navigating the
landscape of media and basically figuring out what is trustworthy
and what is not trustworthy. And it surfaces this challenge
that AI content gives us to basically also judge what is
true, what is not true, what can I believe and what is just like
fake news. And I think there are two sides
of like the fear that people have.
So on the one hand side, it's the fear of trusting the media
output and contents in terms of information that you consume.
And on the other side, it's also like losing the trust in
journalism overall and the craft of journalism and in itself,
because also there is a lot of talks that journalists won't
have a job. If you just would like put it
really like frankly, and that the quality is erode.
What do you see AI actually enabling, particularly when you
talk about quality or quantity? And where do you see legitimate
risks that could impact the way of how we the news that we
consume? I think AI, like in The
Newsroom, is really good at automating tedious tasks, tasks
that nobody really likes but you have to do as a journalist.
So transcribing things, summarizing things, doing the
research for your papers. AI can assist with a lot of
these processes and basically can give you more time to focus
on those parts of the process that should always be done by a,
by a human, by by somebody who is crafting the content and who
is in in the driver's seat for the final result.
So this is also something that we at for Comedian Corpora
inherently believe in that it is really important to keep the
human the center of the process at the beginning and the end.
So whenever content is created, a human should be the one who's
deciding how to create it. What, what message do you want
to convey? And also how should the final
piece look? And, but obviously AI can help
us to be a lot more efficient. And that's something that we
should appreciate and, and integrate.
But then I mean, on the other hand, we should always focus
that we will keep some things with the human in the loop.
And then you also asked about like trust, How can we keep the
trust basically with us? And I would say in the situation
right now where you have a lot of AI slot and users have
trouble like navigating to landscape brands and especially
also people become like very important to basically build up
trust. Because trust in media also for
me means to build up a relationship with either people
or it could also be a relationship to to a news brand
where you basically know that they work thoroughly.
And I think for media companies, this is kind of like something
that they should put on their top priority.
We have to like make sure that we always keep the trust with
our audience, that we keep this relationship to our audience,
and be really transparent about how we use AI to basically make
sure that we are the ones that people go to if they want to
know that they can trust us with how we talk about what's
happening in the world. If we talk transparency, it's
one of like the most crucial parts of of the whole discussion
of how we set up and interact with AI, particularly in the way
that content is shaped. Who do you think is responsible,
the consumer or the provider or like a third party organization
that provides, you know, frameworks for it?
I think it should be a shared responsibility that is with
everybody who's every party that is part of the process of
shaping or creating content. I think the those who trained
the big AI models, they, they could obviously do a lot more in
terms of transparency. We still don't really know which
data went to went into the models, into the big LLMS that
were trained. So we need a lot more
transparency about the training data.
But then also us as intermediaries who are using
this technology and either incorporate this into workflows,
we need to make sure that we be that we are transparent about
how we use it. And for instance, if we like, we
have a certain set of rules, for instance, that if something is,
is, it's created by AI. And then we, we label this piece
of content that is an AI created piece.
And we also make transparent about like what, what, what part
of this is created by an AI. So to give you an example, we
have a daily newsletter where people can now also listen to
the newsletter. And the newsletter is written by
one of the journalists in our newsroom.
And now they can hear the newsletter that is is an audio
spoken by the person who wrote the newsletter.
But we use AI to basically turn the text into audio.
So we use 11 apps here to basically create an audio
podcast for the newsletter. And this is really good because
we basically reach our readers or listeners in this case in
another type of media. And we can like transform the
original content piece into something else with very little
effort. We can use AI for this, but we
make sure that this is transparent and that that the
the the user knows like what is happening.
What's going on here? I think that is so like tangible
of how you incorporated it into your processes or the way that
you approach AI. From my experience, it's hard to
be that clear as the way that you also just reflected upon of
how you as an organization are. How did you get there?
Like how did you come up with this clarity of how you use AI
and who did you also loop into the preparation to get there?
Yeah, I think that's a, that's a, that's a big challenge
actually for for media companies, probably also for
companies in other domains because you AI is basically
everywhere and it it has they're like every part in your company
basically is more or less involved into this process of
agreeing on let's say a certain consensus how to use AI in the
company. And so, so in our case, we
basically had to make sure that we getting agreement between the
Workers Union, the, the, the high level executive board,
those who work in the unused room and, and, and basically
make sure that every party is involved in this process and can
like incorporate their perspective on this.
And then basically, you know, try to, to, to agree on
something certain set of rules that we all think are valid.
But also to be honest, I think because the technology is just
evolving so rapidly, this is not really for a long duration and
you basically always have to refine these things.
If you just think like how much has happened in this year alone
and also how much has the industry moved?
How much more are we like moving towards AI content?
If you look at video, for instance, like video AI at the
beginning of the year wasn't really a thing that you like,
think is is around there. But, but now it's like
everywhere on social media, you can find video AI.
So that just shows us like how fast things are moving and that
you constantly need to like re evaluate also the, the, the set
of consensus rules or points that you agree on and and make
sure that you're always in line with how the technology evolves.
But doesn't that make you like not only the head of AI, but
more of an in like integrator, orchestrator between the
different kinds of, you know, skill sets, stakeholders?
I mean, how you just walked us through of who's like needed to
be looped in. That's like quite the pool of
people that could form an opinion or so how do you
navigate that? Yeah, it's, it's really, it's
really crazy to basically have all these hats on and, and, and
shift between them. So basically in between a tech
lab that I'm also managing. And then basically this, this
role, which is more like an internal, I don't know, policy
team or whatever, who is trying to put every or get everybody on
the table. I think, I think this is just
part of the role. And also what I, what I see in
the industry is that this is an emerging role that many
companies now have. And there are people in other
companies who have similar challenges.
And, and I think it's, it's, it's just necessary.
Somebody needs to like, like connect the dots and make sure
that the Dai topic is just steered in the right way.
And, and this is you, you cannot like the, the, the topic is just
so big. You cannot, like, you cannot do
it this on your own. You cannot just like make
decisions on your own. You have to get everybody
involved. So it's it's just you have to do
it this way or I think it will fail, you know?
And when you now build or deploy the AI systems with the lab that
you have also the, you know, partnerships that you form, what
are key decisions of where like transparency, ethics and like
the technological infrastructure that's needed collide?
So, yeah, so I think there are like obviously like several
layers of or at several layers, you basically have to integrate
safety and also make sure that the system basically responds in
the way that is aligned with how you want it to respond and also
make sure that your ethical standards are met.
I think on a very low level, you basically have like the
decisions for the the models that you use in your system.
So basically we we make sure that we use models that we think
put a lot of effort into meeting ethics standards and were
transparent about, you know how they are at least a little bit
more transparent about how they train their models.
And also that they put efforts into making sure that these
models to at least to certain extent comply with some ethical
standards. So like we're not like
triggering hate speech or harmful content.
So that's on the on the model base where you basically select
certain types of model that you want to integrate into your
systems. And then basically on top of
that, you just build up the system.
So, and then it really depends on like what kind of system you
built. Do you build something for
internal use that is basically, I don't know, drafting something
or used in The Newsroom for like research purpose or for giving
you feedback on, on your article or anything like that.
Then we have different constraints and then we
basically can do like some internal testing.
We have feedback loops, these kind of things.
We also have the human in the loop principles.
So everything that where AI is used will always be reviewed by
human. And then we have other systems
where we basically built AI systems that are user facing.
So when users interact with AI systems, you cannot really make
sure that every answer is proof read by humans.
So basically then you have to double check that the system is
working. Accordingly, so we do intensive
red teaming. So basically we try to to get
like the worst out of the bot, so to speak.
So we're trying to trick the bot into giving us answers that the
bot shouldn't give us. We're trying to jailbreak the
bot in a way and only if like this red teaming and and several
other tests are positive, then we are rolling the system out to
the users. And then even if we rolled the
system out, we always make sure that we have feedback loop and
can check, check that the quality is good.
So yeah, several levels. Yeah.
I mean, that's amazing. And I think particularly when
you talk about the quality and coming back also to the craft
part of like output in itself or in the way that like news are
being brought to the market. Basically, we live in an era
where deep fake has never been that easy to produce.
And also like synthetic content that is actually not real but
artificial like logically, but is supposed to be hyper
personalized. It's also supposed to be in real
time. But still, there's this like
underlying feeling that I cannot trust of what I see in the news
that I consume anymore. And where is the tipping point
at which, like AI begins to distort reality more than it
supports it for you and also from your experience in the
field? I think we, we already reached a
point where this is like really a topic that we should take
seriously on several levels, also on our societal level.
And we need to like bring these discussions to the table.
There are studies that are showing that the majority of
content that is now being published online is AI created.
And from like anecdotal consumption of social media, you
can really see that there are a lot of instances where I'm not
able or where at at least I takes me several minutes to
basically think about if videos are real or not.
And, and I can't really tell. And these are obviously only the
examples that trigger this. There might be a lot of videos
that I see that are AI created and I'm I'm, I just don't
realize it anymore. So so I think this is really
really an important topic that we need to bring to the table
also to be discussed by our politicians, by those who shape
basically the guardrail. It's the, the, the, the laws
also for, for how basically the media landscape is, is created
because I think ultimately also like our democracy needs that we
have trustworthy media that basically is, is helping the
people in the country to shape their opinions in a way that
they're not just influenced by AI content.
And if we look at a very at the political, like the global
political landscape right now, there are many actors that can
definitely use AI for purposes that are very bad and that can
really harm our society. So, so this is not, not
something that maybe we need to talk about.
It's this is a serious topic that we need to talk about.
And I think like for us as a media company, we also have a
responsibility to, to, to participate into mitigating the
situation and basically helping people to build trust.
And I think for us this, this like, I mean, we have to
basically fight against this huge amount of synthetic
content. We have to be visible.
We have to convince our readers that we are trustworthy every
day again and again and build up our communities and our
audiences. I think we, we put a lot of
effort into, in into doing this and, and this like to, to be, to
be relevant in the future means to basically use AI but use it
in a good way and also show others that AI is it's, it's
not, it's not ultimately bad. It's, it's also, it's, it's in a
way also like tool. So if you're a bad actor and use
a tool for bad purposes, it can be very harmful.
But if you are somebody who tries to build up trust and be
trustworthy, you can also use AI.
But you have to make sure to use it in a transparent way.
Because then we can basically compete with this AI slot that
is out there and be visible and show users that we have
trustworthy information that they can consume.
And if you now think about like the way that you work, it's
mostly like summarized under the like newsroom that you like are
sometimes even literally in the room with.
And the way that you just reflected upon the impact of
trustworthy news versus like the fake news and the way that also
media like companies need to bring this to the consumer.
Does it have an impact on The Newsroom in an AI world, so to
say? And if so, if you yourself could
redesign a newsroom today for like the future, how would you
like? How would you set it up?
Why and how to get there? That's a really good question.
Yeah, I think that there could be a whole podcast episode in in
itself. So maybe I'll focus on on two
points. I think.
I think one truth that a lot of media companies still struggle
with is that news is inherently shifting from text to other
forms. It's more today, it's more about
audio, it's podcasts, it's video on social media platforms that
are consumed as a news source, especially by younger
generations. And we have to acknowledge this.
And I think in newsroom of the future would be a lot more video
first, podcast 1st and article second, I would say.
So that's one thing. And then also maybe the other
thing would be to also, yeah, design the The Newsroom AI
first. Because as you can imagine,
there are people who have been in journalism for 20 or 30 years
and they have a typical way how they, how they work, how they,
how they structure the work. And I think if you look at young
startups, for instance, at Morning Crunch, which is a
newsletter first news company, they build up a newsroom that is
basically AI first. So, and what that means
basically is to rethink every component of the process in
terms of where can we maximize the efficiency of AI for this
process without compromising any of the quality.
And I mean, obviously it's always easy to design this on
Greenfield and it's much more difficult to basically transform
legacy media into a new newsroom.
But but yeah, maybe maybe two things that I would that I would
emphasize is to, to go on on something like video 1st or the
1st and then basically create a create a more streamlined AI
first process of of how to work in The Newsroom.
And I like that you are so like specific about the forms of
content and like how it depends on the like, generations,
consumption, also the habits that we've formed.
But doesn't that also inherently mean that we need to think about
distribution of content? So currently, I would almost say
everyone's consuming media through social media and like on
a, let's say classical way that you go to a website or app of a
specific like news house. However, if we I now understand
you correctly, you also propose that the way that we like
consume it via the distribution channels will massively change
because the forms of contents change.
Or how would you also view that of like a prerequisite for media
houses to link it to the production?
And how would you then also regard it to be enabled through
AI or maybe also like challenged by AI because it's not possible
to for whatever reason? Yeah, I think, I think the
distribution also matters. In an ideal world, and I would
say like in a especially in a world before the introduction of
Cha Chi PT and Google AI overviews, Google AI mode, these
kind of things, we always as publishing houses after the
introduction of Internet, we were aiming for having direct
relationships to our consumers and basically making sure that
people will find us with relevant keywords that they
search for and then basically click on a link and then they
are on our website. What we see now today is that
this is becoming increasingly difficult and more and more
difficult basically because this this old contract of the
Internet, the search contract that you basically get referral
clicks for your content. This is not not really working
anymore. We see that ChatGPT and Google
AI overviews are having significantly lower click
through rates and referral traffic.
So, so it's becoming harder and harder to basically get people
on your, on your websites. And, and this is also true for,
for, for social media because it's, it's really difficult to,
to get out of there and, and, and the platforms make sure to
build up this water garden basically that's keeping people
inside the, the platform. However, I think it's, it's
still relevant to basically try getting people onto your
websites and to your products and to build up direct
relationships with them. I think there are a lot more
opportunities that media companies now explore.
This could be live events, this could be, I don't know,
mailings. This could be WhatsApp channels
that are like directly connected to your journalists and editors.
So basically like I think in the core is to build up this
relationship between you and and your readers and your audience
and make the best of how this how the the media landscape is
right now. And then I mean, on another
level, I think, and this is more on, on the political level, I
think we have to make sure to basically have a media landscape
that is, that is taking into account to basically have a, a
level playing field and have a, have a fair, fair market where
basically users are still able to, to get to, to the sources
and, and to get to the publishing companies.
Because as as a citizen of the country, I I strongly believe we
need independent media and we have to make sure that this that
this market still exists and will exist in the future.
And sorry, I I need to go. That was like a jump off point
for me into one of my passion topics, independent media.
And you linked it to because I'm a citizen of this country.
So you inherently linked like independent media to the
political landscape. And one key question that I
always have myself is how do we get there?
What would you propose? That's a.
That's a good question. If I would have the solution,
I'd probably have a. Different head on your head.
Yes, that would be really great if if somebody had the solution.
No, I think, I think, I think we have to at one point we have to
fight for like for, for a European standpoint and the
whole ecosystem because a lot of the media landscape today is
also shaped by big tech companies from the US and also
China. So basically we have to
basically build up our own standpoint.
This doesn't really mean to like cut off every connection to
them, but to basically find an agreement.
And I think, I think as I mentioned, the technology's
evolving so rapidly and I, I think like within this journey
also, I myself have like change my perspective on certain
things. And, and also on this question,
I would, I'm, I'm still a little bit optimistic that that I think
there is the potential that after a very rapid and
disruptive introduction of AI platforms like Chechi PT or also
the new AI summaries in Google, that we now can basically get
back to the table and negotiate with those companies also on
different levels, politics, the media companies and everybody
who was involved to basically find solutions that work for
everybody. Because I think in the end, this
experience shift that we observed with AI that was
introduced by chair GPT mainly and now is you can see in many
platforms, this is not going away.
I think because as a consumer, I love, I love this.
It's really, really nice way of getting information in a very
condensed way. And now we just have to
basically figure out how we can work with this new technology in
a way that independent media can still survive.
So right now I already have at least two another episodes that
I would want to do to the like first, The Newsroom of the
Future and 2nd Independent Media.
How do we get there? But for now, we're almost at the
end of this one. So I do want to cherish the
moment and have some so-called in between moments with you.
They are intuitive ones. And these are the ones where you
literally just share what comes to your mind 1st.
And I do want to start with like a key question for me to you,
what does trust and media feel like?
I would say it feels like a handshake that must be renewed
every single day. That is such a great visual.
Let's see how we can include that.
Anyways, what should I never do? I think it should never make
decisions that are for good reason, still in the hands of
people, like hiring people for instance.
And what will journalists always do?
I think journalists will always provide the context, they will
bring in the empathy and also their very own and unique
standpoint on how things are in the world.
What is the future of news? To make producing news very
efficient and high quality thanks to AI with the very
thorough overview of human experts.
And do you have an experience that you yourself are currently
in between? Yeah, I think in between.
I think I'm I'm always in between hype and reality when it
comes to AI because sometimes we're just thinking the whole
world change and then in the reality it's maybe not as big as
we think. And if we now close the session
and finish it with just a link to take and trust topic, and if
we if we assume that trust becomes a decisive competitive
advantage in media, what does it mean in your role to be a trust
builder when it comes to the future of media news?
I think to, to build up trust is it is really important to, to be
very transparent inside the company and also to your
audience about how you want to use AI, how you use it, what AI
is, what it can and what it can't.
And to basically for me like what is really at my heart to
everybody at Funker, to everybody who works at the
company, give them the opportunity to understand this
technology as good and as deep as they want, give them all the
resources. Because I think ultimately, and
this basically links back to what I said in the beginning, I
think trust is built on experience and understanding of
technology. Thank you so much for your time
and diving so deep into how you had fungus set up, AI overall,
but also how you view it for the industry.
It was super valuable conversation.
It was great having you. Thanks so much.
Thanks Yvonne, it was fun.