What will Artificial Intelligence mean for journalism?
The first wave of this symbiosis was news automation, where artificial intelligence systems generate written stories and alerts directly from data. The goal is not to displace journalists from their jobs — it’s about freeing up their time from labor-intensive tasks so they can do higher-order journalism.
Following the direction set in motion by automation, the next evolution will be about leveraging smart tools that can help journalists augment their own writing. This means AI-powered interfaces capable of providing context to topics in real time and even optimizing a news report based on its dateline and subject matter.
AI will help journalists do more investigative work by analyzing massive sets of data and pointing to relationships not easily visible to even the most experienced reporter. The combination of AI and journalism will contribute to a more informed and efficient society by enabling journalists to conduct deep analysis, uncover corruption, and hold people and institutions accountable. This evolution in journalism comes at a time when fake news seems to cast a shadow over trust in our industry.
These new tools will eventually become prevalent in most newsrooms across the world. However, we should not expect mass adoption without a fight.
Looking at the evolution of successful writing technologies from the past, we can see a very specific cycle emerge, and how long it takes to develop. The first phase is uncertainty; when a new writing technology begins to enter mainstream society, there’s hesitancy to adopt it.
In fact, when the first writing technology was introduced — the act of writing itself on paper — Greek philosopher Socrates argued that
“the written word is the enemy of memory.”
Centuries later, with the introduction of the printing press, Johannes Trithemius, a prolific German cryptographer, worried that the new technology would make monks responsible for transcribing religious books lazy.
Later on, the world witnessed similar resistance to innovation with the introduction of the typewriter and even the word processor in the computers we use today. The transition to augmented writing, where smart machines help journalists create better content, will likely encounter the same barriers to innovation.
Despite promising advances in artificial intelligence, we still know very little about the ethical implications of news augmented by machine learning. While it is clear the integration of machine learning, cognitive analysis and big data will revolutionize multiple aspects of the world, careful consideration is required when extrapolating its benefits to journalism.
As A.I. and cognitive computing quickly evolve, it will be crucial in 2017 for the industry to consider the tradeoffs that will come from increased efficiency and productivity.
Francesco first published this article on LinkedIn. It is reproduced with his permission here.
Francesco Marconi is responsible for strategy and corporate development at the Associated Press, where he is part of the strategic planning team, identifying partnerships opportunities and guiding media strategy. Francesco complements his professional activity with academic research at Columbia University’s Tow Center for Digital Journalism, where he is an Innovation Fellow.
Francesco studied business and journalism at the University of Missouri and completed his post graduate work as a Chazen Scholar at Columbia Business School’s Media Program. In 2014 he joined Harvard University’s Berkman Center for Internet and Society as an affiliate researcher studying the impact of data in journalism. Francesco started his career at the United Nations researching science and technology solutions for developing countries, resulting in the publishing of his first book and TED talk on Reverse Innovation.
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