*Researchers at Carnegie Mellon University have come up with AI software that can make your writing sound a lot more polite.
To school their AI in the fine art of etiquette, the team used a half million exceedingly polite messages exchanged by Enron employees.
“Despite the company’s wrongdoing, many of the emails exchanged between employees were — unsurprisingly, if you’ve ever worked in a large corporation — laden with common niceties and politely formed requests and responses,” observes Techcrunch writer Darrell Etherington.
In other AI-generated writing news:
*AI Software Simplifies Radiology Report Writing: AI writing firm Agamon just snagged $3 million in new funding for software that simplifies reports written by radiologists.
The tool is designed to massage writing by radiologists so that is clearer and easier to understand.
Plus, it could help insulate them from communication-related lawsuits.
“In making its case, Agamon on its Website claims that 25% of radiologists in the U.S. are involved in at least one communication-related lawsuit,” observes Radiology Business writer Marty Stempniak.
Plus, “upward of 96% of radiology reports are not understood by the average adult,” Stempniak adds.
*Machines + Media: How Tech is Changing Media: Some key players in media are featured in this one-hour YouTube video, examining tech’s impact on media.
Part of an upcoming video series this summer, the program delves into how AI, machine learning, computer vision and related tech is changing the face of journalism and related media.
“Machines are now part of our media landscape,” says Steven Rosenbaum, managing director, NYC Media Lab.
“So understanding them and finding solutions to make them a force for good is at the core of everything we’re exploring on Machines + Media in the weeks to come,” Rosenbaum says.
The Machines + Media video series is being produced by Bloomberg and NYC Media Lab.
*How One AI-Generated News Service Got it’s Start: Gary Rogers, co-founder of automated news service Radar, says the growing availability of torrents of data from government databases inspired him to experiment with AI-generated writing.
“We could see there was so much data becoming publicly available from the police, the NHS, Public Health England and so on.
“It was just sitting there and never touched.
“We realized very quickly that instead of one story about crime figures, you could easily do it at a borough-by-borough level — and get 33 stories out of it.”
These days, Radar regularly auto-produces thousands of news stories each month using templates and public databases.
The service is currently squired by six journalists, who create AI story templates that reach down into British databases to populate those templates with hyperlocal data.
Using the method, Radar was able to hyperlocalize a government database chronicling crime across Great Britain and come up with a story entitled, “Hackney: The home of bike theft in London.”
Another example of Radar’s AI hyperlocalization: a story examining health trends with the headline, “Figures reveal NHS spends millions prescribing gluten-free food for patients.”
This article takes a look at Radar – as well as a number of other early adopters of AI in journalism.
*Serving-Up AI-Generated Writing for Insurance Agents: Researchers at IBM have come up with a design for a platform that can auto-answer common insurance questions from customers.
The system uses IBM’s natural language processing to understand, classify and retrieve info.
That process enables a text robot to handle common questions ordinarily answered by insurance customers.
“In turn, this allows the agent to tackle more creative and complex problems,” the researchers observe.
*Hollywood Continues Experimentation With AI-Generated Scripts: While critics seem eager to discredit AI-generated movie scripts, Hollywood continues to experiment with the concept.
Over the past few years, it has been discovered that there are computers capable of making valuable film scripts, according to an article in Dataquest.
“This process is relatively recent, since it started two or three years ago.
“Using GAN — Generative Adversarial Neural nets — the creation of this content is speeding its development at tremendously fast rates,” the article author observes.
*Microsoft Prepping ‘Similarity Checker’ for Writing: Tech goliath Microsoft is readying the release of a similarity checker for its AI writing assistant, Microsoft Editor.
The tool essentially smokes-out the plagiarism it finds in documents and helps writers with proper citation.
*OpenAI Still Leary of the Power of its AI Text Generator: While OpenAI is offering a commercialized version of the latest version of its AI text generator – GPT-3 – it’s still wary of its potential use by bad actors.
Access to the commercial version is by invitation only – although it may be more broadly available in months to come, according to Bloomberg writer Ashlee Vance.
“I don’t know exactly how long that will take,” says Sam Altman, OpenAI CEO. “We would rather be on the too-slow than the too-fast side.
“We will make mistakes here, and we will learn.”
The cloud-based service works by taking an inputted sentence and then adding additional sentences it believes should follow — based on its best, AI-aided guess.
OpenAI – as well as many closely following the tech – have expressed fears that the powerful text generator could be harnessed to release a tsunami of fake news across the Web.
While prototypes of the commercialized version were used to auto-generate all sorts of far-fetched musings and often nonsense text, OpenAI sees a number of practical applications for its commercial version.
For example: The system could be trained to auto-generate a list of companies, their stock symbols and foundation dates by first inputting the full data for the first two companies, and then inputting just the names of four additional companies, according to Alex Hern, a writer for The Guardian.
In a perfect world, the commercialized version of GPT-3 would sense a list was being requested and then auto-generate stock symbols and foundation dates for the additional four companies by scanning the Web for the info.
Founded as a nonprofit in 2015, OpenAI became a for-profit in 2018.
It has been funded in part with $1 billion investment from Microsoft, according to Tom Simonite, a writer for Wired.
*Governments Turning to AI-Generated Writing: Local, state and federal governmental agencies will have easy access to AI-generated writing tools – thanks to a new partnership.
Specifically, Automated Insights – a leading AI-generated writing firm – and governmental IT provider Logic Soft have teamed up to proliferate the use of AI-generated writing throughout government.
“Logic Soft is very excited about our partnership with Automated Insights,” says Satish Baraparte, president, Logic Soft.
“They have a great tool – Wordsmith — which will greatly help our customers with automation and simplification to share time-sensitive and relevant information at scale,” Baraparte says.
*AI Tech to Writers: Don’t Worry, Be Happy: An article in the PressGazzette reassures writers that AI-generated writing will augment their jobs – not replace them.
“My instinct is that over time this will start to take on more of the less enjoyable repetitive work — and allow journalists to go out and do the human element of the work,” says Joseph Hook, editor, Radar.
Sounds rosy.
But company’s like Persado are replacing copywriters at slogan writing – once considered a highly creative skill.
And other companies, like United Robots, have added automated interviewing to their AI-generated writing – making the resulting copy ‘appear’ to be more creative.
Moreover, the automated interviewing further eliminates the need for human sports reporters at publishers who use the feature.
United Robots is also giving a talk July 7 at Newsrewired’s virtual conference, which will detail, in part, how its sports-writing AI software replaced freelancers at a major newsmedia outlet.
Perhaps Thomas Kent – a journalism professor at Columbia University interviewed by SourceFabric — says it best: “AI isn’t sentimental, and it isn’t ideological.
“It can be used for good or for evil. It can be used to replace journalists or to strengthen journalists. It can be used to get the truth out, and it can be used for disinformation.
“It’s a neutral piece of technology that can be adapted for almost anything.”
*Special Feature: Company Reports That Write Themselves
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–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.