The meteoric rise of the field of Artificial Intelligence (AI) has had a
remarkable influence on various aspects of our lives, and this influence is
only expected to rise. AI has already disrupted the field of journalism with
the introduction of “Algorithmic journalism” (Dorr,2015). Algorithmic
journalism involves a “software that automatically produces texts in
natural language from structured data.” Various economic reasons are
driving the rise of AI within journalism. First, AI spares journalists the time
to draft articles and news pieces that are relatively uniform such as daily
news reports about the performance of the stock market. AI’s use in editorial
tech helps writers and journalists review their pieces promptly. There’s also
an argument that AI may help reduce the biases in certain stories, but given
that the algorithms drafting the content may itself include the biases of the
person who coded them, this argument still has its flaws.
In its bid to enhance its ability to reap the fruits of AI in journalism,
Reuters has introduced an AI tool called Lynx Insight (Kobie, 2018). This tool
aims to augment journalists and writers rather than replace them by providing
them with analytical tools that synthesize big data in a way that nurtures
their journalistic role. Lynx Insight will analyze a vast amount of data to
identify any interesting patterns or topics that can allow Reuters the
opportunity to publish content that is innovative and pioneering, and at the
same time fits with the readers’ interests. Lynx Insight aggregates the data
and sends the journalist a message with a brief about any interesting patterns
with some background about the story or topic. The App associated with the tool
provides journalists with a live feed of updates regarding any possible
breaking news stories.
AI’s growing influence in the field of journalism may have significant
implications on the future of news and media. AI may help journalists
personalize the news according to the interests of their audience, which may
enhance the appeal of the news and its readability. Its ability to reduce the
cost may allow new news and media outlets to enter the field which supports the
democratization of the field and may provide a competition that can support the
quality of the content. Unfortunately, this competition may also lead to the
deterioration of the content with news outlets fixated on competition and
monetizing content rather than nurturing the field and improving its appeal.
Over-dependence on AI tools such as Lynx Insight may reduce the journalist’s
sense of agency and innovation ability. This dependence may be destructive to
the field of journalism if there are issues with the algorithm, or if the data
used by AI has significant flaws.
Kobie, N. (2018, March 10). Reuters is taking a big gamble on AI-supported
journalism. Retrieved February 12, 2019, from
https://www.wired.co.uk/article/reuters-artificial-intelligence-journalism-newsroom-ai-lynx-insight
Seth, C. (2016). Mapping the human–machine divide in journalism. The
SAGE handbook of digital journalism, 341.
Artificial Intelligence-supported journalism
The meteoric rise of the field of Artificial Intelligence (AI) has had a
remarkable influence on various aspects of our lives, and this influence is
only expected to rise. AI has already disrupted the field of journalism with
the introduction of “Algorithmic journalism” (Dorr,2015). Algorithmic
journalism involves a “software that automatically produces texts in
natural language from structured data.” Various economic reasons are
driving the rise of AI within journalism. First, AI spares journalists the time
to draft articles and news pieces that are relatively uniform such as daily
news reports about the performance of the stock market. AI’s use in editorial
tech helps writers and journalists review their pieces promptly. There’s also
an argument that AI may help reduce the biases in certain stories, but given
that the algorithms drafting the content may itself include the biases of the
person who coded them, this argument still has its flaws.
In its bid to enhance its ability to reap the fruits of AI in journalism,
Reuters has introduced an AI tool called Lynx Insight (Kobie, 2018). This tool
aims to augment journalists and writers rather than replace them by providing
them with analytical tools that synthesize big data in a way that nurtures
their journalistic role. Lynx Insight will analyze a vast amount of data to
identify any interesting patterns or topics that can allow Reuters the
opportunity to publish content that is innovative and pioneering, and at the
same time fits with the readers’ interests. Lynx Insight aggregates the data
and sends the journalist a message with a brief about any interesting patterns
with some background about the story or topic. The App associated with the tool
provides journalists with a live feed of updates regarding any possible
breaking news stories.
AI’s growing influence in the field of journalism may have significant
implications on the future of news and media. AI may help journalists
personalize the news according to the interests of their audience, which may
enhance the appeal of the news and its readability. Its ability to reduce the
cost may allow new news and media outlets to enter the field which supports the
democratization of the field and may provide a competition that can support the
quality of the content. Unfortunately, this competition may also lead to the
deterioration of the content with news outlets fixated on competition and
monetizing content rather than nurturing the field and improving its appeal.
Over-dependence on AI tools such as Lynx Insight may reduce the journalist’s
sense of agency and innovation ability. This dependence may be destructive to
the field of journalism if there are issues with the algorithm, or if the data
used by AI has significant flaws.
Kobie, N. (2018, March 10). Reuters is taking a big gamble on AI-supported
journalism. Retrieved February 12, 2019, from
https://www.wired.co.uk/article/reuters-artificial-intelligence-journalism-newsroom-ai-lynx-insight
Seth, C. (2016). Mapping the human–machine divide in journalism. The
SAGE handbook of digital journalism, 341.