Robot-journalism and copyright – the Indian experience
On AI, NLG and robot-journalism (Péter Mezei)
Artificial intelligence (AI) is a part of our daily life. AI is used in sports, health care, weapon industry, robotics, virtual reality, fintech, retail stores, digital marketing, fashion industry, criminal investigations, the fight against pandemic or humanitarian catastrophes, and it is the holy grail of self-driving cars. Big data would also remain an uncontrollable ocean of information without algorithms. AI has an exponentially growing relevance in the copyright industry as well, including artworks, motion pictures, sound recordings, literature or museums (Mezei, 2020).
One of the most interesting fields of the creative industry, where the “computational turn” (Berry, 2011) seems inevitable is the news industry. “Robot-journalism” is not the future – it is already with us. With natural language generation (NLG) software, media companies can optimize their workload – pass the mechanical, data-intensive workload to algorithms, and leave the creative, editorial (as well as brand new) tasks to the human workforce.
NLG is offered by dozens of corporations on a global level. European and American corporations take the lead – at least with respect the media industry on these continents. It does not, however, mean that corporations offering NLG-based software-as-a-service (SaaS) or content-as-a-service (CaaS) for media organizations are unknown in other parts of the globe – especially in Asia, where China and India are among the major players of the “AI-race”.
As a follow-up project to our AI-related research interests, I teamed up with Alina Trapova to check, whether the European experiences related to robot-journalism need any intervention on the side of legislation. A part of this research is focused on the empirical evidences related to the European NLG service providers. Anushka Tanwar, as my research assistant, has kindly contributed to the collection of relevant data on this field. This gave the idea to Anushka and me to write a spin-off blog post on Anushka’s home country, India. Anushka, in the following part of the post, will introduce the Indian experience related to NLG service providers and journalism.
The Indian experience (Anushka Tanwar)
Indian Prime Minister Narendra Modi has expressed on many occasions, his wish to make India a global hub for AI. He has further launched “SAFAL — AI for all” initiative with the purpose of training students in AI. The scope of AI in India is promising. It has an enormous potential to transform every sector of the economy for the greater good of society.
Journalism is a vast industry and a creative profession. It entails an amalgamation of human characteristics like emotion, judgement, expression, etc. However, there is a new trend of robot-journalism across the world — major media outlets are adopting robot-assisted journalism. For instance, Associated Press uses Automated Insights’ AI technology — Wordsmith to produce corporate earning stories; Xinhua uses its bot called Kuaibi Xiaoxi to produce sports and finance reports; The Washington Post’s Heliograph was used to cover the Rio Olympics and US presidential elections. In 2018, Chinese company Sogou along with Xinhua launched the world’s first artificial intelligence news anchor with human voice, facial expressions and gestures.
While the wave of robot-journalism is picking up fast around the world, India seems to slowly and steadily catch up. There are a few Indian NLG start-ups that are revolutionizing the Indian market. For instance, Phrazor by VPhrase — an industry leader in India, provides AI-powered business intelligence and reporting automation solutions through machine learning and NLG technology. The platform automatically produces content within seconds, after being provided with structured data and statistics. Phrazor has automated commentary on Indian Premier League (IPL) Matches for Hindustan Times — a leading media and publishing company — along with live market commentary for moneycontrol.com, an Indian business news and online trading website.
Other examples include a bot developed by NewsBytes called Yantra which uses machine learning to provide contextual news to readers. Yantra is first provided with inputs regarding what news to search for on the internet, then the information is edited and presented in a question-answer format on the website.
Adziz, formerly known as Contetop, uses NLG to extract meaningful information from raw text. It enables software-as-a-service (SaaS)-based automated AI writing software with no complicated installation or download. It is essentially an article-writing app that employs NLG to reduce writing time.
Stride analyses the existing data to produce meaningful insights that would help businesses to improve their customer experiences. It provides graphical patterns to unstructured data in a structured format in order to understand customer behaviour easily by utilising its NLG capabilities. At the moment, banks and financial institutions are its core customers.
Senseforth.ai provides a human-like conversational platform that is powered by AI and can answer questions quickly. Their product is called A.ware which performs tasks like reading, comprehending, interpreting, and interacting. The entire process makes use of natural language processing (NLP) and NLG technologies. It caters to companies in various sectors such as banking, healthcare, telecom, e-commerce, real estate, education, travel, etc. (Deoras, 2018).
As we can see from the above mentioned examples, NLG has gained a lot of traction in India and abroad within the past few years. When it comes to robot-journalism, even though there are some success stories in India, it could take a while before India truly accepts robot-journalism. There might be a few hurdles on the way, for example, vernacular languages may create a barrier. India is a diverse country with 22 major languages, making it difficult to cater to every community, region, and person in the country through robot-journalism. Furthermore, on the one hand, with such a large and ever-growing population, the labour becomes cheap which benefits the news organizations as they can save costs by hiring people who are ready to work for lower salaries. However, on the other hand, a growing population also results in an increased readership base, making India potentially a great market for robot-journalism and NLG technology. Companies must realise the potential of the unexplored Indian market. I personally believe, if the cost of integrating robot-journalists with news organizations is on the lower end of the scale or on the same level as human journalists, it could become mainstream in India. However, one thing must be clear from the beginning — AI in journalism does not mean replacement of human journalists. Rather, it will provide a helping hand and enhance the work quality of journalists — allowing them to focus on more important issues and tasks, resulting in high quality and in-depth journalism.
David M. Berry: The Computational Turn: Thinking about the Digital Humanities, Cultural Machine, 2011, p. 1-22. (https://culturemachine.net/wp-content/uploads/2019/01/10-Computational-Turn-440-893-1-PB.pdf)
Péter Mezei: From Leonardo to the Next Rembrandt – The Need for AI-Pessimism in the Age of Algorithms, UFITA, Issue 2/2020, p. 390-429.
Srishti Deoras: These 5 Indian Natural Language Generation Startups Are Revolutionising The Sector, Analytics India Magazine, 2018. (https://analyticsindiamag.com/these-5-indian-natural-language-generation-startups-are-revolutionising-the-sector/)
Anushka Tanwar is a law student at University School of Law and Legal Studies in New Delhi. Ms. Tanwar is currently pursuing her internship at AIRecht, Amsterdam. She has published in Transnational Dispute Management, Asia law portal, Kluwer Patent Blog, Kluwer Copyright Blog and has upcoming publications in the European Intellectual Property Review and the ERA-Forum. Her interests lie in Copyright law, Patent law and Artificial Intelligence and law.