Why is the rise of artificial intelligence (AI) technology so important in the media and entertainment industry?
AI has the potential to dramatically affect the profession and business of news – how journalists can gather and report on the news, how we produce different formats of content and how we deliver it to consumers.
At the AP, we have primarily been interested in how algorithmic techniques can help us make the production of a high volume of news more efficient. That does two things:
1) It helps save our journalists time, freeing them from routine tasks to focus on important storytelling and
2) enables us to create new versions of stories, customizing news formats for more audiences so they engage with it better.
Without automation and AI techniques, doing so would be a drain on resources.
Does AI fundamentally change how the Media/entertainment industry serves the economy?
If we use these technologies properly, news companies can do a better job providing relevant information to consumers, stopping misinformation before it spreads, making its news products more inclusive and diverse and more.
Are current Media practices adequate for overseeing an AI-driven industry?
No. Only a few media companies have sufficient data and technological expertise to properly use and leverage AI.
One of the challenges for the news industry is to figure out how to bring more technological capabilities into the newsroom.
This is why emerging collaborative networks like JournalismAI (London School of Economics) are so important. We must work together to accelerate innovation.
What are the main uses for AI in the media and entertainment industry? Where do you see AI technology headed in your field?
One of the most basic uses of AI technology is also the most common:
Turning simple data into text stories, such as, automatically generating a story about a sports game based on the final scores.
Journalists also are increasingly using algorithms to sift through social media to find perspectives and early detectors of news events, and to sift through thousands of documents looking for patterns that inform a story.
News distribution: algorithms that personalize recommendations for stories and deliver custom feeds, algorithms aimed at increasing paid subscriptions by evaluating customer data and other such business-model uses.
We are still very early in figuring out how to use these technologies effectively and broadly across the industry.
How can the media industry be better prepared to tackle business in the next five years?
Speaking for the news industry, it needs more help in the following:
Data science – gathering and analyzing the data so it can make better decisions about how to deliver successful news products that are engaging and informative.
Talent/technology specialties - it needs people who are “product thinkers” – people who can bring together experts across journalism, technology, strategy, sales and work as a team to innovate.