What’s this about?
A picture of future journalism is moving throughout the world in which it’s being reformed by the advanced concepts of AI-based technology. The idea began flourishing when a survey was conducted in 71 newsrooms from 32 countries by the London School of Economics (LSE). The results depicted a prediction of a wider and more stable impact on the current structure of journalism. The fields are expected to be heavily influenced by AI including data analytics, forecasting, plagiarism detection, fake news detection, NLP and more.
Let’s dive deeper to learn more-
In 2019, ‘The economist’ took an interview with an AI bot. The bot was the GPT-2, a natural language processing model created by OpenAI. In the particular session, the model was able to answer a set of questions regarding the state of the world. One particular question was, ‘What is the future of AI?’ to which GPT-2 responded in this way -
“It would be good if we used the technology more responsibly. In other words, we should treat it like a utility, like a tool. We should put as much effort into developing the technology as necessary, rather than worrying that it’s going to harm us or destroy our lives.”
There were comments that the bot did not understand what it was saying but it had a big thought of the future implied. The statement denoted a future of AI technology built in a manner that it almost mirrored human behaviour and performance.
AI uses in journalism
When the talk on the use of AI arises, it certainly doesn’t just mean the programme or technology is just limited to thinking and interacting like a human being. AI is capable of performing activities that are beyond human possibilities or even by completely accurate computers. The branch of journalism has been carefully observed where the implementation of AI not just fits the best, but also establishes new heights in efficiency. These are a few of the examples where various dimensions of AI use is recognised.
Some vital ways have been explained below to provide stronger understanding of using AI technologies that can lead to big differences.
Data analytic and forecasting: Even with high efficiency, manual observation and analysis of data always save at least a few percent of error possibilities which are unavoidable. The reason is the human brain is naturally unbound to limitations but it has inconsistency in maintaining these capabilities that leads to such unavoidable errors. This is why newsrooms use AI robots for detecting central trends or unusual behaviour from big sets of data. No matter the size of data produced, it is now possible to go through all of it within a comparatively lesser amount of time. This lets them form patterns of events in predictive data analytics that are complicated and time-consuming for normal humans to catch.
Plagiarism check: When information is nearly always available, most of the news and detail based documents come short of originality and ethics. With the help of largely stored data sets from any field, these bots are able to spot the origin of information easily while data mining, in unethically reproduced articles or transcribed interviews. In journalism, authenticity is a must characteristic for any sort of content to be published or it can deeply scar agencies and careers in the subject for lack of such trait.
Fake news detection: Since computers are already highly accurate in data management and calculation, adding its own intellect makes it a great way to enhance the authenticity and safety of news media. False news is enough to stand as destruction for a social community in a virtual generation because it directly influences an individual’s process of thought towards the systems and surroundings.
AI tools in Journalism
As the interest and expectations of AI are exponentially increasing through gaming perspectives in highlights, it has been under-eyes how numerous existing and current news media have already implied a number of AI tools to restructure the functions of journalism. There is an insight that the technology is being prepared in a manner that it would take over certain tasks in the industry of press and media. This creates an idea of journalism being prioritized in the future equal to existing industrial sectors.
· New York Times R&D Lab: Founded in as early as 2006, the NYT newspaper has been working on emerging technologies to evolve the services of journalism. Such parts of research involve studies focused on photogrammetry, media transmission, computer vision, spatial computing, and misinformation. Among all, misinformation was stated as a rise of threat to society in ‘The Rise of AI-Enabled Disinformation’ due to its strong potential of drastic impact.
· Washington Post; One of the Washington post’s new exciting tools is the lead locator. It’s known to provide locations, more specifically appended to political situations for reporters to collect confidential or notable news.
· Academia: To support and broaden the striking role of AI in giving journalism a new face, recently established summits, professional discussions, and conferences as Machine + Media, Computation + Journalism have produced significance in AI technology exploration. Lately, WU Dao 2.0 has been exposed at ‘Beijing Academy of Artificial intelligence’ as the world’s currently largest NLP (Natural Processing Language) model and that is 10times larger than GTP-3.
Possibility of anchor replacement by AI?
In the state of China, Xinhua, a news agency along with the Chinese tech firm, Sogou, released the latest version of its AI 3D anchors named ‘Xinn Xiawei’ which was based on a real anchor of the agency. The facial expressions and speech delivering manner almost mimicked the actual anchor using multi-modal recognition and synthesis, facial recognition, animation and transfer learning. As China is only starting the chapter of building more AI Anchors, there is a presumption that such technologies would be taking over the reporting positions in media due to its indistinguishable resemblance to humans in interaction.
Although the use and new ideas of AI have been gaining quite the attention in journalism and other industries, controversial questions have made their way into the board of attention. These questions are, ‘Is this the future we are moving towards?’. If agreed to, “How much would like listening to the news by an artificial anchor? Would you want them to simply read the news void of emotions following strict operations, or would you rather prefer touch with human emotions? The answer varies from person to person, and the scenario of acceptability can have a mass effect on how the upcoming anchors would perform in the days ahead.
AI in Journalism - Saviour or Destroyer?
The implementation of AI in journalism does not illustrate any damage or disruption in the generic functions of the field so far. At the moment, it rather seems to facilitate most hypothetical and practical designs of execution. But it’s up to how the organisations and roles in charge apply the technologies so that it does not overpower the industry of media with robots.
In 2017, the Tow Centre of Digital journalism in a study suggested editorial values be integrated into the system for audiences who receive AI-enabled news. The design would depict a story put together with the help of technology.
In the EU, the Council for Mass Media in Finland asked the Media Council to immediately address the issues of data processing, choices in computerised procedures and transparency or else ‘others’ will jeopardize the press power and freedom.
With more rising pros entering the field of journalism due to AI development, the cons can single-handedly cause devastation in social infrastructure by manipulating information. The faith of the public is more or less always unstable in media-based organisations and slight exposure of technological misuse can ruin it. If the media working with new yet sensitive technologies don’t move ahead cautiously, it will more seemingly take a negative toll.
Will AI come in as a saviour or destroyer for journalism?
That can only be answered in the future where we will experience a bigger and clearer implication, mass responses, and general impacts other than just experimental prototypes.
Credit - Fatema Tuz Zahara, Intelsense AI