For those who haven’t kept up with technology and still think the earth is flat, artificial intelligence defines itself as “the ability of machines to exhibit intelligence, especially computer systems. AI can automate tasks, analyze data, and make decisions.”
In November, Scripps named several newsers to head up a company AI team in an effort to get ahead of the emerging technology.
One of those hires, Christina Hartman, was named vice president of emerging technology operations, while her counterpart Kerry Oslund was named vice president of AI strategy. Hartman came from the news side. Both report to the company’s chief transformation officer, Laura Tomlin.
The move signaled the company’s attention shift towards AI and what it may hold for local stations.
“Our goal is to quickly and responsibly transform our organization into a nimble environment that fosters innovation at all levels, inspiring revenue growth, efficient workflows and new product development,” Tomlin said in a press release on the move. “AI will play a critical role in reshaping our operating systems and company culture.”
This week, I got the chance to hang out with Hartman on Zoom for a bit and ask about what Scripps meant by the press release on its AI strategy. Will it be friend or foe? Below is the transcript of the conversation.
TVSPY: I wanted to get a little bit of background from you since you came from news. How did you go from news to AI?.
Hartman: My prior role was overseeing standards. So, I issued our guidance around language choice overall ethics policies with regard to news gathering. And so, when chat GPT hit the scene, I was looking at it from a standards perspective, like the team needs guidance here.
But it felt a lot bigger than the sort of guidance that we are typically dealing with solely within standards. And so, at the time, I reached out to our chief ethics officer and said, I really think we need to be thinking about this much more deeply. And so I proposed governance for the organization and overall framework, thinking about trust implications, but also data privacy, security, bias.
So we pulled in from across the organization representatives and specialists within those areas. But I also felt in order to lead governance on AI, I needed to become a practitioner so that I could understand the accuracy, factual accuracy and I became a practitioner.
And so it sort of became a little bit of an assistant to me in thinking about if I had a strategy. If I were looking at a script, I’d pop it in as like a, “what do you think of this?” or basic copy editing. I became seen as, I should say, not became, but became seen as the AI person. But I am no expert.
You know, there are times in fact that I think is a great evil or has potential to be, but I am also really energized by the possibility when paired with the perspective that I come at it with, which is sort of from a responsible use point of view.
TVSPY: So you developed an interest in it, started using it, became seen as the person who was the AI person. How did Scripps go from, “Yeah, that’s kind of a cool little tool that we’re using” to, we need to build a department around it.
Hartman: Yeah. I mean, so there’s no way around the fact that macroeconomic conditions have to be a driving consideration for almost any company trying to engage in developing an AI strategy and trying to understand what AI means for their businesses.
I would say any business that isn’t thinking about that in a really intentional way is making a big mistake. That having been said, you know, Scripps formed the transformation office, which is, overall, looking at the company through the lens of people, process and and technology.
We’re at a place as an organization where through the course of acquisitions we have a number of different systems in use across the organization. And it puts a drag on our operational efficiency.
And so AI as a pillar of the transformation office is how that rolls up. I have a partner, Kerry Oslund. We both report to Laura Tomlin, who is the chief transformation officer. And then reporting to me is Keith St. Peter, our director of Newsroom AI, who is focused very specifically on applications and possibilities in our newsroom.
But Kerry and I are focused on the enterprise.
TVSPY: Got it. It popped in my head while you were talking, that I know Scripps laid off a large chunk of people recently. Is this all kind of part of a reworking of how local news gets done?
Hartman: Scripps implemented the news initiative a couple of years ago to rethink how we produce news.
It came with an investment in more news gathering, manpower, people power. We hired a couple hundred mmjs in all of our markets and streamlined the production piece of our news operations. You know, look, the margins of the television business are changing. The viewing habits are changing and everybody should be thinking about changing the way we do business. Scripps made the choice very intentionally to put more resources into original reporting as sort of the investment choice and then leveraging technology where possible to streamline.
Is that because of AI? No, that was long before anybody except for AI researchers were talking about AI. That was both the economics and the audiences are changing in the business, and so should the business model.
TVSPY: ·Speaking to that, you know, the first thing people think of when they think of AI is, of course, am I gonna lose my job? How do you see AI working in a newsroom?
Hartman: I can tell you what we’re doing today and what our roadmap is in 2025. So long before I looked at a pie chart that looked at the changes over time in a reporter’s day and how a reporter spends their time, particularly a television reporter, and what you see happen over time is an increasingly smaller amount of time spent on source building and actual reporting.
So that really became kind of like a roadmap. Like, okay, what problems can we solve? The biggest one, as we talked to as I was preparing for this role, and as I hired Keith, was that we talked to reporters and digital teams across the company and said what are the most soul crushing parts of your job? And what bubbled up to the top is doing the same story over and over again.
The amount of pressure on a single journalist and a single manager and all the platforms have just absolutely changed.
So that was our first target in terms of solving problems for our newsrooms. And so we are leveraging generative AI to take our originally reported television broadcasts scripts and formatting them for web audiences. There are also tools that are in the testing phase right now to take packages produced for television and version them for social media platforms.
All of this we’re committed to human in the loop. Nothing gets published without a human set of eyes. The ability to have platform specific, social post copy that frankly, we find is more effective in some cases, than what people can do when they’re dashing it out at the end of what is already a long day. It has really been, I think, a boon to our newsrooms. There’s also the reality of newsrooms across the country is that we can’t be everywhere.
They haven’t launched this product in the market, yet. But they’ve developed a tool that allows you to monitor local government proceedings and take the transcript and generate potential news items for journalists to dig into further.
You can set up alerts. If say you’re following potholes, right? You can set up alerts and any time a local government proceeding is posted to YouTube or Vimeo. Any journalist who set up watch lists can get alerts to say, “Hey, they talked about, you know, potholes,” and they get a summary and then make their own decision. Was this newsworthy enough to pursue? But being there in the first place to watch it when it may not yield anything is something that we no longer have to spend the time doing.
TVSPY: So, I’m familiar with the versioning portion of AI and other websites you can use. What platforms are you using and what models?
Because I know that sometimes there’s a bias in the model. I found that when I did an experimental script in my tech job and I asked the Microsoft AI to write a script about one of our products, and it used, because of its knowledge base, it used the Microsoft version of the product to fill out the script, which was wrong for our company.
That’s kind of a two part question: what models are you using and is there a human part making sure that it’s actually doing what you want it to do?
Hartman: Yes. Well, so what I will say, one of the things that we are telling, particularly the senior leadership team, is that in this phase of development and advancements in the technology, we can’t do business in the same way with AI.
Like you run tests rapidly and deploy and there may be some overlap of functionality and even expense as you’re trying to figure out the best model. As an example in December, we launched an internal chat tool, so internally developed and secure. So any prompt output or uploaded document stays within our environment and can’t be used to train LLMs and doesn’t go anywhere. But internally it leverages Open AI and Anthropic only. We are looking at the potential to add other models, but those are the ones for our general use across the organization.
We’re most comfortable with at this, at this stage. That said, I mentioned we have a handful of markets that are testing.
So you can version a script in chat GPT today, right? But the output can potentially be fairly variable depending on your prompt, right? What you ask it to do. And so, we’re looking at from a responsible use perspective, what something that’s a little more controlled from a prompt and model perspective might look like? What we’re finding though is the more controls, the more templatized the output can be.
TVSPY: I worked for a company that was a data storage and protection company. I don’t wanna make your brain explode, but is Scripps focusing a little bit more on cybersecurity and beefing up the IT department now that you’re getting into the cloud and the crazy cyber world out there?
Hartman: So our cybersecurity officer is part of governance and in any demo conversation we have not only a lockstep partner in ensuring that our published guidance to the teams is reflective of the priority that the data security, data privacy, cybersecurity is to us.
TVSPY: Yeah. I’m kind of going off the rails here, but I do know that one of the biggest frustrations at my old company was that I wasn’t able to livestream or do remote video as much as I wanted with people.
I wasn’t able to use certain products because the cybersecurity risk to the company. We couldn’t use them because our IT standards were so high. There were certain security risks to certain live streaming programs, which, you know, broadcasting is, in a sense, live streaming.
What comes to mind for me is like, the more you guys get into having proprietary information in your networks, the more you’re gonna wanna protect it. The more you protect it, the harder it is to do what you’re there to do.
Hartman: Yes. Yes. Yes.
I think what we’re gonna find, you know, quite a bit, is that just because we can do something doesn’t mean we should or will. Or that it’s worth the risk. I am no cybersecurity expert, but very much appreciate those within the organization that are. We share our requirements with any vendor before we even have a conversation. If they can’t meet our standards, we can’t have a conversation.
TVSPY: If you had your unicorn and rainbow world with AI and local TV, I don’t mean that in derogatory way. I mean that actually like, “Wow, one day we’ll be able to do this,” what would it look like?
Hartman: I think a lot of the conversation, misguided parts of the conversation, are overly focused on streamlining and automation. And certainly that’s an opportunity. But I like to think about it from the perspective of what have we always wanted to do that we just couldn’t, right?
To give a couple of examples, I mean, I mentioned, being able to monitor a local government proceedings when you can’t be there as, as one of them. But like, big picture across the organization, we have a gold mine of historical archives that exist in various states whether that’s tape or various forms of hardware storage or on the cloud.
I was talking to someone at one of our stations in Buffalo, and he was showing me all these paper logs from the eighties. And he was like, “how do I get these into a database? Because this is making me…I’m trying to do this by hand. I’ve been working on this for 10 years now, and I’m not making any progress.” And I’m like, yes, yes, yes. There are things we can do. And I got really excited ’cause he was saying, “We’re thinking a lot about as an organization about the concept of connection with our communities.” Take AI out of it and whatever is coming from a technology perspective at the end of the day, and we all do our work as exchanges between people, and this is really the time more than ever to be there for our communities.
And so, this engineer that I was talking to about the archive project was saying, “We get calls all the time from the community that’s like, you know, it’s my husband’s birthday and I have always wanted to find this game in high school where he made this amazing catch and you guys were there and can you help me find it?”
And this engineer in Buffalo has a real passion for helping people find that stuff. We can do that now. Those are the things that I get a real thrill about.
And so, as we’re talking with people, there are a couple of questions we’re asking because these aren’t gonna be top-down initiatives. If it’s a top-down initiative, that’s a mistake because what is a top-down initiative gonna look like? It’s gonna be like, how are we gonna save money? It has to be as much, if not more, a ground up operation of a couple of questions. One, what parts of your job are just killing you that you hate to do? That’s the versioning. There’s a number of other things we could talk about there, but also what have you wanted to do that you can’t do?
Data is another one that comes up a lot from our newsrooms in terms of processing data, monitoring data, flagging anomalies in data for story ideas.
I think the possibilities are really rich when it comes to the opportunity to get people past the initial fear of a conversation about AI and just get to the brainstorming possibilities, right? Like, when’s the last time that people have really had time, I mean in a newsroom, where there’s so, so, so much to do and so little time in a day, to innovate and think differently in a world where the possibilities are not endless, but they’re certainly significantly broader today than they’ve ever been.
TVSPY: It sounds like you are leaning more towards the meme that says something like, I want AI to do the dishes and clean the house so I can do art and photography rather than have AI do art and photography so I can do the dishes and clean the house.
Hartman: Yeah. I mean, I like doing the dishes. But, yeah, I mean, I think this should be exciting, right? The more you play with it, the more excited you are.
