Artificial Intelligence increases gap between rich and poor countries

Image from the report Generating Change A global survey of what news organisations are doing with artificial intelligence
Image from “Generating Change – A global survey of what news organisations are doing with artificial intelligence. Source: https://www.journalismai.info/research/2023-generating-change

Note: This article was run through ChatGPT to help improve the language.
First you will read my version. Below is what ChatGPT suggested.

Artificial Intelligence (AI) is increasing the gap between journalistic news operations in the Global South and news media in the Global North. The two terms are used to roughly distinguish  the economically and technologically advanced countries in the northern hemisphere – e.g. all the Nordic countries – from  the less economically and technologically countries mostly in the South – e.g. all the Asian countries.

The uneven impact of AI in news operations is among the conclusions in a report from JournalismAI.  Generating Change – A global survey of what news organisations are doing with artificial intelligence. JournalismAI is a global initiative established to empower news organisations to use artificial intelligence responsibly.

The Global North/South terminology does not refer to a “geographic region in any traditional sense but rather to the relative power and wealth of countries in distinct parts of the world”

In the executive summary of the report, the researchers conclude that:

  1. Artificial Intelligence (AI) continues to be unevenly distributed among small and large newsrooms and regionally among Global South and Global North countries.
  2. The social and economic benefits of AI are geographically concentrated in the Global North, which enjoy the infrastructure and resources, while many countries in the Global South grapple with the social, cultural, and economic repercussions of post-independence colonialism.

Newsrooms globally contend with challenges related to AI integration, but the challenges are more pronounced for newsrooms in the Global South. Respondents highlighted language, infrastructural, and political challenges.

Some challenges to AI adoption are interrelated. Low internet penetration leads to low digital literacy, which makes it easier for disinformation to thrive. Similarly, resource constraints make it difficult to hire or even find AI experts.

A Philippines-based respondent summarized how resource constraints, knowledge gaps, and language barriers intersect:

AI technologies developed have been predominantly available in English, but not in many Asian languages (with the possible exception of [Mandarin] Chinese). We have to catch up doubly to create AI systems, and AI systems that work with our local languages. There are also limited funding opportunities to allow us to explore using AI systems in our jobs. And lastly, some countries in Southeast Asia (like ours, the Philippines) aren’t as advanced as our neighbours, so there are only a handful of AI experts in the country, much less AI experts in journalism.

Since it takes lots of resources to develop AI applications, the larger media organizations and state owned news operations will have an advantage. it is feared that smaller newsrooms that focus on public interest and accountability journalism will struggle to survive.

“This could have significant implications for the entire news ecosystem,” the report states.

“Even if local AI models were abundantly available, trust would remain an issue. Discussing mobile application “Allam”, a Saudi Government-developed chatbot similar to ChatGPT, one respondent explained how such projects remain tied to political considerations, diminishing user trust in such models:

This is a local model, do we trust the datasets used by Arab state institutions? [One wonders] if the datasets used were balanced or representative or if the data were manipulated? Unfortunately, this is one of the issues we deal with regionally. We don’t have pan-Arab models created by independent Arab institutions whose choices when it comes to training datasets can be trusted. You know how sensitive some of these contexts are … AI requires massive funding to be competitive … Arab political realities raise urgent questions about the reliability of [local AI] models. Are they going to be open source? Are they adaptable to Arab newsrooms’ needs? Can newsrooms add their own datasets, for instance?

The report adds:

“It is important to note that concerns about AI technologies’ enablement of government surveillance and control are not unique to the Global South and have been intrinsic to critical discussions of AI technologies in the Global North as well. As early as 2013, Edward Snowden’s revelations exposed in detail the interdependencies between governments and technology companies.”

“The PRISM program illustrated how the US government utilised the surveillance infrastructure built by technology companies like Google and Facebook using the data they collected for marketing purposes to advance its own surveillance practices.”

Despite the myriad complex challenges newsrooms in Global South countries face, respondents from the region’s newsrooms expressed enthusiasm for building capacity in, and sharing AI expertise. Arguably, they have to if they want to survive as AI is transforming journalism.

This article was run through ChatGPT to help improve the language. Below is what ChatGPT suggested. Do you not – as a reader – agree that the suggested changes would have given you a better reading experience? 

ChatGPT: Here are some suggested language improvements for the text:

Original: “Artificial Intelligence (AI) is increasing the gap between journalistic news operations in the Global South and news media in the Global North.”
Improved: “Artificial Intelligence (AI) is widening the disparity between journalistic news operations in the Global South and those in the Global North.”

Original: “The two terms are used to roughly distinguish the economically and technologically advanced countries in the northern hemisphere – e.g. all the Nordic countries – from the less economically and technologically countries mostly in the South – e.g. all the Asian countries.”
Improved: “These terms are employed to broadly differentiate economically and technologically advanced countries in the northern hemisphere, such as the Nordic nations, from less economically and technologically developed countries primarily situated in the South, including Asian countries.”

Original: “The uneven impact of AI in news operations is among the conclusions in a report from JournalismAI.”
Improved: “The report from JournalismAI highlights the unequal impact of AI in news operations.”

Original: “The Global North/South terminology does not refer to a “geographic region in any traditional sense but rather to the relative power and wealth of countries in distinct parts of the world.”
Improved: “The terminology of Global North/South does not strictly correspond to traditional geographic regions but rather reflects the varying power and wealth of countries across different parts of the world.”

Original: “Artificial Intelligence (AI) continues to be unevenly distributed among small and large newsrooms and regionally among Global South and Global North countries.”
Improved: “The distribution of Artificial Intelligence (AI) remains uneven, both across small and large newsrooms and regionally among Global South and Global North countries.”

Original: “The social and economic benefits of AI are geographically concentrated in the Global North, which enjoy the infrastructure and resources, while many countries in the Global South grapple with the social, cultural, and economic repercussions of post-independence colonialism.”
Improved: “The social and economic benefits of AI tend to concentrate geographically in the Global North, where robust infrastructure and resources are available, while many countries in the Global South contend with the social, cultural, and economic challenges stemming from post-independence colonialism.”

Original: “Some challenges to AI adoption are interrelated.”
Improved: “Certain challenges in adopting AI are interconnected.”

Original: “Since it takes lots of resources to develop AI applications, the larger media organisations and state owned news operations will have an advantage.”
Improved: “Given the resource-intensive nature of AI application development, larger media organizations and state-owned news operations are poised to enjoy an advantage.”

Original: “it is feared that smaller newsrooms that focus on public interest and accountability journalism will struggle to survive.”
Improved: “There is concern that smaller newsrooms dedicated to public interest and accountability journalism may face survival challenges.”

Original: “Even if local AI models were abundantly available, trust would remain an issue.”
Improved: “Even if local AI models were readily accessible, trust would still be a significant concern.”

Original: “The PRISM program illustrated how the US government utilised the surveillance infrastructure built by technology companies like Google and Facebook using the data they collected for marketing purposes to advance its own surveillance practices.”
Improved: “The PRISM program demonstrated how the US government leveraged the surveillance infrastructure established by technology giants like Google and Facebook, using the data collected for marketing purposes to enhance its surveillance capabilities.”

Original: “Despite the myriad complex challenges newsrooms in Global South countries face, respondents from the region’s newsrooms expressed enthusiasm for building capacity in, and sharing AI expertise.”
Improved: “Despite the numerous complex challenges confronting newsrooms in Global South countries, respondents from these regions exhibited enthusiasm for capacity building and sharing AI expertise.”

These improvements aim to enhance clarity and readability while maintaining the original content’s meaning.

– end of ChatGPS text

About Gregers Møller

Editor-in-Chief • ScandAsia Publishing Co., Ltd. • Bangkok, Thailand

View all posts by Gregers Møller

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