By David Stephen
Sedona.AZ– Digital has dominated most aspects of news, and AI has crawled and sprawled the internet. It is probably better for local news publishers and editors to start exploring ways to accommodate AI than to wait it out or expect that it would remain unreliable.
A few paths that may generate revenues:
a.
Have an AI version of regular news. This means that for every news story, there would be an AI-written version. This will not just be a rewrite, but stratified. For example, there could be a historical angle to that story. There could be a lesson or wisdom note to that story. There could also be a highlight of something to learn within that story. Then, there could be a connection of that story to other areas of knowledge, like the relationship between a shipping component and a finance model, or a forestry pattern to an education method, and so forth. There may also be a non-partisan or non-biased mode by AI, for use when reading from some sources. There could be grammar or idiomatic summaries too. These options would be available at premiums, as audiences would benefit more. AI will be working on expanding the depth of stories beyond the mostly one-time or one-use local stories until the next. This may be useful in combating AI-generated news mills.
b.
News could be the best passive way to learn a new language, using the familiarity of words, sentences, and phrases. AI can be used to display news in a second language, word-for-word, text-by-text or paragraph-by-paragraph, in a way to make terms in the second language familiar and, over time, known. It may also extend to voice mode.
In general, the apathy to learning a second language for many adults may sometimes be connected to discouragement from the lack of retention. This could be surpassed by using news, often fresh, different, easily understood, without the burden of rote, to get familiar with a new language. If familiarity is built, it may ease getting seriously into the details of the language, for those that desire to go forward with it. AI may also do a word cloud in the other language, provide reminders, options, and more. It may become something else that technology dependence enhances for cognition. It will also be by subscription.
Local news publishers may form new groups to get these and more done. It may be possible to use open-source large language models [LLMs] to develop this if some groups are unwilling to partner with some frontier AI companies, especially if they rate the platform above the contents.
The goal is for local news to get going as AI development hyper accelerates. Some groups of local news publications may also explore how to derive contents from local libraries as well as the possibility for a neuroplasticity pen, for writing, all in efforts to have some leverage as AI dominates the internet, and digital—that has already dominated human productivity, efficiency, and social life.
Brookings has a commentary, Can journalism survive AI?, stating that, “Last year alone, the U.S. journalism industry slashed 2,700 jobs, and 2.5 newspapers closed each week on average. Despite a 43% rise in traffic to the top 46 news sites over the past decade, their revenues declined 56%. The dominance of less than a handful of privately owned, Silicon Valley-based tech corporations over digital advertising, publishing, audience, data, cloud, and search decimated the business models of journalism worldwide. And now AI is doing it again.”
There is a recent press release, WAN-IFRA and OpenAI Launch Global AI Accelerator for Newsrooms, stating that, “WAN-IFRA, the World Association of News Publishers, has announced today the launch of a broad-based accelerator program for over 100 news publishers in partnership with OpenAI. The Newsroom AI Catalyst is an accelerator program designed to help newsrooms fast-track their AI adoption and implementation to bring efficiencies and create quality content.”
This is an advertisement
