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Episode: AI Use Case Series: AI in Journalism and News [AI Today Podcast]

Author: AI & Data Today
Duration: 00:13:34

Episode Shownotes

AI in impacting every industry and Journalism & News is no exception. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer will discuss the use of AI in Journalism and News industry. Assisting with producing content for journalism and news For newsrooms that need to get content

generated, but might not have enough reporters, AI can quickly produce data-driven articles based on structured data, allowing journalists to focus on more complex stories. Continue reading AI Use Case Series: AI in Journalism and News [AI Today Podcast] at Cognilytica.

Full Transcript

00:00:00 Speaker_01
The AI Today podcast, powered by PMI, cuts through the hype and noise to identify what is really happening now in the world of artificial intelligence.

00:00:09 Speaker_01
Learn about emerging AI trends, best practices, and use cases on making AI work for you today with PMI hosts and expert guests.

00:00:21 Speaker_02
Hello and welcome to the AI Today podcast. I'm your host, Kathleen Malch.

00:00:25 Speaker_00
And I'm your host, Ron Schmelzer. And we're continuing along in our AI Use Case series. I've been talking about it at the beginning of the last bunch of podcasts, so I don't want to keep talking about it.

00:00:35 Speaker_00
But for those of you that are new to the AI Today podcast, what we do here is we talk about what's happening with AI Today.

00:00:40 Speaker_00
There's a lot of podcasts that talk about the future or that talk about some other issues, but we want to know, how is AI impacting our lives today?

00:00:47 Speaker_00
One of the best ways to do that is to look at how AI is impacting our real world and the industries we're working in, the products we're using, the services we're using, the organizations we're interacting with, government, public sector, private sector, whatever it is.

00:01:03 Speaker_00
And we're going to tackle on an industry by industry basis. We're going to look at how AI is impacting each of these industries. And yes, there's a lot of industries, so you can imagine there's a lot of episodes in this series, but it's very useful.

00:01:14 Speaker_00
Even if you're not focused in that particular industry, it's useful to hear how folks are applying AI to their problems today.

00:01:22 Speaker_00
to really make AI useful, to actually impact their organization, provide positive return, and really answer the question for what AI is truly good for and provide some benefits. So we're going to continue on that series here in this podcast today.

00:01:37 Speaker_02
Exactly, because sometimes we get these questions from people saying, you know, I want to bring AI into my organization, but I need use cases, or I need examples of how it's being applied in other industries so that I can get that buy-in.

00:01:50 Speaker_02
And that's why we decided to revisit our use case series, because it was incredibly popular a few years ago when we did it. And that was before generative AI came out and before people, you know, were really using AI on an everyday basis.

00:02:03 Speaker_02
So we want to revisit it in a number of different industries, like Ron said, And for today's podcast, we're gonna be talking about how AI is impacting journalism and news.

00:02:12 Speaker_02
So one of the very common ways that we're seeing AI being used with journalism and news is with automated news writing. So we know that AI systems, especially large language models now are really good at generating text, right? And generating content.

00:02:30 Speaker_02
So we're seeing AI powered tools being used to generate news articles on a variety of different topics such as sports, financial reports, or even breaking news, because what AI is really good at is being able to look at large amounts of data very quickly, especially some data driven

00:02:46 Speaker_02
you know, news and things. And so it's able to take that data, aggregate it, and then put together different reports.

00:02:52 Speaker_02
We've also seen this with political campaigns where it's able to quickly look at that data and then analyze and produce an article based on that.

00:03:02 Speaker_02
So it's now allowing newsrooms who maybe didn't have the staff to cover all of these different topics, the ability to write articles on it.

00:03:12 Speaker_00
Yeah, and I think some people may say, well, that doesn't sound so great. Don't we need journalism? Don't we need sort of objective viewpoints? Do we need opinions and things like that?

00:03:21 Speaker_00
And machines are just going to summarize and they're just going to maybe even hallucinate. It's possible. Right? You know, accuracy is sometimes called into question. Is that a good thing?

00:03:31 Speaker_00
And the answer is that, well, you know, it depends on the application, right? Obviously, if you're covering topics that require a human perspective, you don't want the human out of the loop. You really don't.

00:03:42 Speaker_00
And maybe for all these things, we're not saying the human is necessarily out of the loop. The human may still be involved in the process of editing and overviewing and foreseeing.

00:03:50 Speaker_00
But when we're talking about coverage of things, there's only so many reporters and journalists to go around.

00:03:57 Speaker_00
And if you have a high school team that never gets any attention, but they're like on a tear and they're doing really well or or some other thing, like you have some some local city government activities, maybe there's some conversation or some some decisions are being made and no one's there to cover it.

00:04:12 Speaker_00
That's that's the thing about news is that if it's not being covered, it's as if it doesn't exist. What ends up happening is that social media ends up filling the gaps.

00:04:19 Speaker_00
You have conversations happening on Facebook or next door or LinkedIn or whatever about something that happened in some meeting or some sports team. And talk about bias issues, right?

00:04:30 Speaker_00
When people are posting it that way, you're probably not getting the whole story. You're probably not getting the whole truth. So there is a balance here.

00:04:37 Speaker_00
There is a role for AI generation in news and journalism, as well as the role of the human in the process. So it's not all good, not all bad. I think this also connects to another way that we see AI being used in journalism.

00:04:51 Speaker_00
That's, of course, fact-checking and verification. Not everything that's published is always accurate. Sometimes things are published quickly and then they have to be retracted or some new facts are learned and something changes.

00:05:01 Speaker_00
Or maybe there's a conflict. Something was posted and it's clearly wrong. You know, you've said something. And if you had just done some research, you would have found out that answer is incorrect.

00:05:09 Speaker_00
Of course, during political campaigns, that happens all the time because politics is not a game of truth telling. It's a game of convincing. Right. So that's when fact checking is really helpful. But it's fact checking for all sorts of things.

00:05:21 Speaker_00
Economic reports. Or what happened, you know, as I mentioned, in a sports game, you know, you don't want to get that wrong, right? So AI systems are really, really good at that.

00:05:31 Speaker_00
And they can leverage large amounts of data, even social media and other sources to flag potential misinformation, verify the claims that are made by various folks or whatever has been published before.

00:05:44 Speaker_00
So this is sort of the flip side to AI generating things. We can use AI to also validate things.

00:05:50 Speaker_02
Exactly. We're also seeing it being used for hyper-personalization reasons where you can now have personalized news feeds and AI algorithms are able to look at your likes and interests and then curate personalized news feeds just for you.

00:06:08 Speaker_02
And we've seen that a lot. Now you may go, well, that sounds wonderful on

00:06:13 Speaker_02
hand, but you may also say, well, that's terrible because now I'm getting this curated content, so I'm just going to exist in my little echo chamber and I'm not going to be able to see all different sides of different stories or different news articles or content that maybe I wouldn't have liked to see.

00:06:28 Speaker_02
One thing that I always enjoyed about reading a physical newspaper was that I got to read all of the articles, whether or not it was something that I possibly was interested in or not.

00:06:37 Speaker_02
Now, because a lot of people consume content online, it's great, it's super easy. But then also, maybe you're not always getting all of that different opinions.

00:06:48 Speaker_02
Going along with that, it also is able to recommend different articles or videos based on, like I said, your reading history, your different preferences, maybe what others in your social networks are looking at as well.

00:07:00 Speaker_02
So this on one hand can enhance user engagement because maybe you're it's things that you like, those headlines are attractive to you.

00:07:08 Speaker_02
But then on the flip side of it, because we always like to talk about sometimes technology is just neutral, but it's not allowing you to see some of that relevant content that maybe you would enjoy, but don't always look at.

00:07:22 Speaker_00
So let's talk a little bit more about sort of the operational part, if you will, of doing journalism and news. It's not just interviewing somebody for a story or going out there and doing the research.

00:07:32 Speaker_00
Sometimes you need to gather data, and sometimes you need to be able to take things from one different form of media and put into another.

00:07:40 Speaker_00
So in the one hand, we talk a little about data analysis, especially you've seen these reports where they talk about you know, how much money was spent on something or they have these flow charts or these diagrams.

00:07:49 Speaker_00
It's kind of nice now, I think, how websites have gotten a lot more interactive. So you can really see visually how some people it's hard sometimes to read information and really get an understanding of it.

00:08:00 Speaker_00
When you have things like charts with with different geographic locations, with bubbles or colors, or when you have, you know, like flow charts or when you have like diagrams of different types, it really helps you understand the information, charts and graphs and things like that.

00:08:13 Speaker_00
So of course we can use AI to process and analyze large data sets, generate some of those visual outputs to help maybe if not the reader, help the journalist understand, find some patterns, find some hidden things that they may not be aware of, some trends, some stories.

00:08:29 Speaker_00
It's very difficult to find that just by reading a bunch of things. Humans are not that great at it.

00:08:34 Speaker_00
So you can have tools that digest this information, provide that advanced data analysis and really help provide some more understanding of what the story is. As a matter of fact, That's what the definition of data visualization is.

00:08:46 Speaker_00
It's not just taking data and presenting it. It's crafting the story because you can visualize data any of a number of ways. So you have to visualize data in the way that communicates what you are trying to communicate.

00:08:57 Speaker_00
One of the soft skills, right, of AI.

00:09:00 Speaker_00
And sort of related to that, another sort of mechanical, if you will, part of news and journalism is sometimes you're interviewing people, but that has to end up in writing at some point, if that's the way you're communicating.

00:09:12 Speaker_00
So just things like transcription and speech to text, the stuff that we have now, people are honestly taking for granted now. It's kind of crazy if you think about it. People are taking for granted how good machines are at transcription.

00:09:25 Speaker_00
and taking voice, speech, text, and transferring it, if you will, into the written form, but also translating. Now they can do translation.

00:09:34 Speaker_00
It was not that long ago, Kathleen and I will tell you from experience, it was not that long ago when computer-based transcription tools were probably, at the best, 80% accurate.

00:09:44 Speaker_00
And a human, you'd have to still read the whole damn thing just to see if the transcription makes sense.

00:09:50 Speaker_00
probably only within the last maybe year, these tools, these text, speech to text tools have really gotten good enough where you can almost trust them without verifying.

00:10:01 Speaker_00
I'd say you should never unverify anything, but like, I'm just so surprised now how good they are. And we should thank our large language models and all the people who have been producing them at really understanding that.

00:10:11 Speaker_00
So I think those are ways that it could speed up journalism, it could help and provide some insights into the data and get things locked out of whatever format they are in.

00:10:21 Speaker_02
And then another area that we've seen AI really being used is to help with newsroom, you know, the various different tasks and processes that the actual newsroom needs to do.

00:10:31 Speaker_02
So we've seen AI being used to automate and augment and assist with routine tasks such as scheduling social media posts or managing content. workflows, even determining the best time to publish articles.

00:10:44 Speaker_02
It can analyze a lot of data, do some data analysis, and then say when is the best time to publish these articles so that we can get maximum impact, maximum eyeballs on this article. And we've also seen it with image and video recognition as well.

00:10:59 Speaker_02
So AI can identify and tag images and videos, which obviously helps the newsrooms manage that large volume of visual content, especially considering

00:11:09 Speaker_02
how large some of these newsrooms can be, or the volume that it's producing, maybe with the limited number of people that it has.

00:11:16 Speaker_02
And it can also aid in verifying authenticity of visual media as well, which we know is quite easy to make up now with the help of AI, right? So we're using AI to figure out if this is AI generated or not.

00:11:30 Speaker_02
So it's really being impactful in a variety of different ways in news and journalism. And maybe you've experienced some of this yourself.

00:11:38 Speaker_02
You know, a lot of times now in the byline or in a disclosure, it'll say that this article was written with the assistance of AI so that they never fully remove the human from the loop.

00:11:48 Speaker_02
As we had mentioned at the beginning, there's a lot of reasons why maybe you need this. You know, if you're just synthesizing data or reporting on basic, basic facts, it's a small article, you really don't need humans in there to write it.

00:12:00 Speaker_02
You're able to produce more content more quickly and still get the same benefits as if a human were to write it. You know, you don't really need witty commentary to talk about a high school sports game, right?

00:12:13 Speaker_02
You just need a paragraph or two of the data, maybe a few stats, and move on, and everybody's happy, and the sports team's happy that they were covered, and you get a lot out of that article.

00:12:23 Speaker_02
So, you know, AI really is being impactful in a number of different industries, right? That's why we are going to have a number of different use case podcasts.

00:12:31 Speaker_02
And if you haven't done so already, I encourage you to subscribe to AI Today so you can get notified of all of our upcoming episodes.

00:12:37 Speaker_02
We have a lot more podcasts to cover in our AI Use Case Series, and we also have some wonderful interviews lined up as well. Like this episode and want to hear more?

00:12:46 Speaker_02
With hundreds of episodes and over 3 million downloads, check out more AI Today podcasts at aitoday.live.

00:12:53 Speaker_02
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00:13:06 Speaker_02
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00:13:19 Speaker_02
Check it out at aitoday.live slash list. Music by Matsu Gravas. As always, thanks for listening to AI Today, and we'll catch you at the next podcast.