For journalists and editors, the rise of AI-powered content selection engines is a never-ending string of innovations leading to personal and professional transformations. In this blog post, we’ll look at how AI is impacting journalism as well as the benefits that come with it.
We’ll also discuss emerging trends in the journalism industry and what the future may hold for us in terms of content production. There is no denying the one thing that is powering the journalism industry – people.
The need to produce content that can be consumed by a wide range of audiences has fueled the need for a diverse set of skills. To effectively appeal to viewers, it is important to be aware of what readers want and how those needs will be met.
The availability and calibre of the data fed into these systems determine how effective they are, which is the other side of the coin.
The rise of data-driven articles means better insight into the reader’s wants and needs. There are a number of surveys that indicate changes in consumer behavior in response to shifts in popular culture.
What Is AI In Journalism
Artificial Intelligence (AI) is a field of computer science that is concerned with developing intelligence in machines and software. AI refers to the ability of machines to act intelligently autonomously, in contrast to human intelligence, which is always limited by the resources available for it and can only be as good as the person.
AI can be applied across a wide range of industries, from healthcare to financial services; from retail to transportation; and from power generation to the military. In the past year, Reuters deployed an automatic camera system to cover sporting events, while the BBC just used a synthetic voice to read aloud the stories published on its website.
AI has become very popular within the context of journalism because it allows for automated content selection processes. Here are two different ways how AI works:
1. Machine Learning
Machine learning is a subset of AI that focuses on enabling computers to change in response to training. In simple terms, machine learning involves providing the computer with a set of data and a set of rules that define how the data should be interpreted.
Once these two sets are complete, the computer will be able to make decisions based on the training data provided. The machine learning process is thus, an iterative one where there is an optimization between the amount of data provided and the number of possible ways it can be interpreted.
2. Deep Learning
Deep learning refers to a particular subset of machine learning that uses neural networks (a type of deep network). In neural networks, the connections between units are flexible. One of the best examples used to demonstrate this concept by Stanford University’s CS231n course is that of a neural network being taught to recognize images in place of numbers.
The model is provided with hundreds and thousands of images along with the correct label associated with each image. It then learns to associate certain collections of pixels within an image with numbers by adjusting its internal parameters until it correctly guesses.
This is known as ‘supervised learning’. However, deep learning is not limited to this type of rule-based approach and can be used for unsupervised learning too.
Importance Of AI In Journalism
There are also other powerful tools that can be used to solve journalism-related challenges and problems. For example, blockchain can help with issues of transparency and data ownership, while cloud technology can be used to build the next-generation of software and apps.
Almost four out of ten news organisations have already implemented artificial intelligence policies, according to Charlie Beckett, director of the Journalism AI project, who surveyed 71 news organisations in 32 countries throughout Europe, North America, South America, and Asia in 2019.
One of the ways AI can help journalism is by accelerating the speed of news production — something that is particularly needed in today’s day and age where news cycles are getting shorter.
For example, if a major event unfolds somewhere in the world, by using AI to gather all pertinent data points together as well as producing various angles for video content — all this time-saving functionality can then be used for a follow-up article or story.
Benefits Of AI In Journalism
JournalismAI supports innovation and capacity-building in news organisations to make the potential of AI more accessible and to counter inequalities in the global news media around AI. JournalismAI is a global initiative that empowers news organisations to use artificial intelligence responsibly.
The Tow Centre for Digital Journalism conducted a research in 2017 that found AI technologies should incorporate editorial ideals into their design. Bloomberg was an early adopter using Cyborg, a programme dissecting financial reports and instantly writing news stories with all relevant facts and figures.
AI is being used to source information, produce news articles and identify trends. JournalismAI launched in 2019 to inform media organisations about the opportunities offered by AI-powered technologies. As disinformation exploits new technologies and operates at massive scale, Lisa Gibbs says the news industry must be aggressive in tackling it.
1. Automated Content Production
Content production is a labor-intensive effort that requires a lot of time and resources. With AI, journalists can now focus on developing relevant stories that are directly relevant to the target audience.
Artificial intelligence allows machines to gather and produce data with little or no human intervention, thereby producing credible content in a shorter amount of time.
2. Increased Productivity And Faster News Generation
Another benefit of AI is that it is fast becoming the go-to platform for faster news generation, particularly when it comes to breaking news and the need to generate new content at the speed of light.
More than often, journalists are faced with deadlines they cannot possibly meet without assistance from automation platforms like Google Alerts. On other occasions, it may be the case that a news story has taken off and is being shared by millions of people.
The role of AI in speeding up the ‘news generation’ process by allowing data and content to be pulled from a large pool of sources, without the need for human intervention, is huge. This saves time and resources in terms of news gathering as well as developing new stories.
3. Better E-Commerce Results
AI can also help to increase e-commerce sales on online stores. According to IBM’s recent Market Research Report titled “Worldwide Internet Retailer Operations – Market Engineering 2019”, 56% of global online stores in 2018 had sold more items via mobile than desktop.
AI can be used to automatically populate a store with product details, by storing and retrieving product information from anywhere in the world and then providing them in the correct place on a website.
The key here is using AI to provide more content to the customer, rather than simply augmenting what is available. This improves e-commerce sales as it provides more value to customers.
4. More Engagement Among Readership
AI can also be used by journalists to engage with your readership in a better way. For example, an AI-powered content selection engine might suggest new stories for you or provide real-time trending information related to current events. This is particularly helpful for journalists who are looking to take their readership and news generation to the next level.
5. Branded Content Development
AI can be used for content marketing as well, specifically for branded content development. In this instance, a journalist might need help in making a decision on a certain story and would like to have access to data from their readership.
This could be a quick request sent directly from the journalist’s machine via messaging or an email through their personal account — it all depends on how they wish to interact with the technology.
6. Data And News Analysis
AI can also be used for data and news analysis, a key component of journalism. Artificial intelligence is capable of quickly generating a lot of data points that will eventually lead to bigger and stronger stories.
Data analysis tools can also help journalists understand how their readership is engaging with the content they’re providing. This will, again, allow them to better understand the preferences of their audience, which in turn will help them produce the type of content that the readership wants to see.
7. Use Ai To Generate New Story Ideas
Another good use for artificial intelligence in journalism is as an idea generator for articles or stories. This could be directly on the same website, for example, when a story about your readership’s favourite sport is published, AI could use data points from that article to generate new content ideas such as related players or articles from third-party sources.
8. Improve The UX and UI Of Your Website
A final benefit of using AI in journalism is to improve the user experience (UX) and user interface (UI) of your website. Most websites these days rely on software, whether it’s a content management system or even a blogging platform like WordPress. And while most platforms come with their own inbuilt functionality, they may not be delivering on all fronts.
Risks Of AI In Journalism
The JournalismAI report London School of Economics and Political Science Houghton Street London. In addition to technologies developed to meet the specific requirements of a given media outlet, natural language generation software packages are also available which are not particularly out of reach for a news organisation.
Such tools can also reveal the biggest hit of the day for your competitors and assess the reach of the content generated by media companies. RADAR (Reporters and Data and Robots) in the UK is one such initiative that won financing of €706,000.
The BBC has Juicer, the Washington Post has Heliograf, and nearly a third of the content published by Bloomberg is generated by a system called Cyborg. Subscription model The FT, of course, is an unusual newspaper.
It was one of the first to introduce a paywall successfully, when it became apparent that the old model of display and classified ads were not going to work so well in the new digital world. AI systems can improve journalistic processes and workflows.
1. Lack Of Ethics
There are some ethical concerns when it comes to AI in journalism. The biggest one is that AI might have an unfair advantage over humans, leading to the perception that it’s a game where the advantage goes to the algorithm. This could lead to distrust in information and an increased likelihood of the use of fake news.
2. Loss Of Work Ethic
There could also be a loss of work ethic on the part of journalists as AI may prove more efficient and cost-effective than human journalists editorially at large.
AI may also be used to write stories that are of a wholly different nature than what they should be, and most people will be unaware of this fact because they have no way of verifying the stories.
3. Mass “Fake News” Creation
This is something that could potentially lead to mass “fake news” creation as AI can be designed to produce fake content as well. This could also lead to technological censorship — for example, some countries might decide to censor citizen access to certain websites if the government feels threatened by certain content.
4. AI’s Lack Of “Oomph”
The SESAAB group in Italy got €400,000 to create algorithms that organise content in accordance with internet users’ online behaviours. AI also lacks emotional quotient and flair, which are integral parts of journalism.
It can produce data points and information pretty quickly, but it may not always be able to answer the questions that need answering — as in who, what and why.
5. No Original Thinking
As mentioned above, human-like storytelling is currently not possible with AI. This can lead to journalists facing issues with originality in their work, especially when they rely on AI platforms for data aggregation and news generation.
In this instance, the AI may choose other pre-programmed answers over the questions that need answering, which will lead to lack of original thinking and journalistic solutions.
6. Lack Of Transparency
One might argue that the current technological development of AI will not necessarily lead to human journalists losing their jobs or getting replaced completely by machines. Instead, AI may simply be used to replace certain tasks and functions in journalism, allowing for a more efficient workflow.
However, it is possible that as humans lose their jobs due to AI upskilling and over-qualification they may feel betrayed as they lose “their job” altogether — which could ultimately lead to “lack of transparency” on behalf of AI in journalism.
7. Risk Of Abuse
There are some reports suggesting that AI can be abused by the government for illicit purposes as well. This could be by misuse of the technology by governments who might wish to censor certain content or perform surveillance on their citizens and users, both of which are prohibited under domestic and international laws.
8. The Rise Of The “Journalism Machines”
Finally, the emergence of “journalism machines” could lead to a rise in a bubble of AI that has no idea what real life is and doesn’t have understanding for how humans work. This would affect the perception of how AI performs its duties, which will eventually lead to the development of context and subjective awareness.
That way, AI would be able to consistently report news that is relevant to its readership as well as understand human behaviour patterns better. Considering how many journalists are currently grappling with their purpose in today’s hyper-connected world, this could prove fatal for them.
The future of AI in journalism is uncertain. If you ask Google, they’re betting on AI being the future of everything, from the way we buy groceries to writing articles.
However, many argue that we’re still not ready for an AI revolution. In layman’s terms, AI can be used for good or bad and it’s still not perfect, which means that we shouldn’t fully rely on it just yet.
AI is a powerful tool that can do a lot of good when integrated into day-to-day tasks and functions in journalism.