The article you are about to read was written by a human. This kind of disclaimer will become an everyday occurrence as chatbots, or large language models, infiltrate deeper into our media space. Doubts about the veracity of such disclaimers will also become commonplace. With the leaps and bounds registered by machine learning and large language models over the past couple of years, it is becoming increasingly difficult to prove that a human is on the other side of a written or spoken communication. How would I prove to you that these words were the product of human creativity and exertion?

JournalismAI is a global initiative that aims to create opportunities for journalists and media organisations to come together and explore solutions to improve the future of journalism with AI. We are on a mission to inform media organisations about the potential offered by AI-powered technologies and to foster debate about the ethical, editorial, and social impact on AI for journalism. The work of JournalismAI is informed by the global survey that led to the publication of our report in November 2019: New powers, new responsibilities. The report suggests that AI is giving journalists significant new powers, but with those come editorial and ethical responsibilities. We see JournalismAI as a service to the news industry and everyone who's working in and around it.

This FREE online programme offers a deep-dive into the potential of artificial intelligence to journalists and media professionals from small newsrooms. It is designed by the JournalismAI team at the London School of Economics and Political Science (LSE) and powered by the Google News Initiative. The Academy is a 6-week online programme that starts in September 2021 and, in its first pilot edition, it is designed for 20 participants from small news organisations (fewer than 50 employees) in the EMEA region (Europe, Middle East and Africa). In line with JournalismAI's mission to inform media organisations about the potential offered by AI-powered technologies and to foster debate about the ethical, editorial, and social impact of AI on journalism, the Academy aims to support small newsrooms that want to learn how AI can be used to support their journalism. The programme combines a series of masterclasses given by experts working at the intersection of journalism and artificial intelligence with opportunities for discussion among participants.

With the advancements in the field of artificial intelligence, many sectors have been in fear of losing human employees over this advanced technology. And with the rise of machines amid this crisis for business continuity, the fear has started looming in the journalism industry where media houses are publishing automated news for their publications. In fact, Bloomberg News, one of the leading media publishing houses, has claimed that the company has been using automated technology for publishing one-third of their news content on their platform. According to news reports: Editor-in-chief John Micklethwait of Bloomberg News stated in their company memo a few years back, "I think automation is crucial to the future of journalism in a much broader way than many of us realise. Bloomberg already uses automation for customised news and trending stories …" Also, in the recent news, Microsoft has announced laying off a considerable number of journalists from their MSN in order to replace them with artificial intelligence.

IBM has been tweaking the AI-powered highlight picking algorithm it deploys during the Wimbledon tennis championships this year to take into account a wider array of factors to better find and personalise the best points to share with fans around the world. Big Blue is celebrating a 30-year technology partnership with the famous grass court tennis tournament, and in 2017 it unveiled an AI-powered system for picking the best points to insert into a highlights package, with the aim of delivering highlights "better than an international media organisation" as Sam Sneddon, IBM sports and entertainment lead, told Computerworld UK during a tour of its technology bunker on-site at the Championships this year. Whether it was Novak Djokovic and Roger Federer's five-hour epic mens' final, or Simona Halep's swift dismantling of Serena Williams in the ladies' final, IBM was working in the background to map and collect every second of footage before feeding it through a set of machine learning and deep learning algorithms which decide the points that would make for the best 5-10 minute highlight package. The Watson system analyses 39 factors, like player gestures and crowd reactions, from live footage and assigns an'excitement score'. For an idea of scale, IBM collects 4.5 million tennis data points per tournament.