A.I. in the Newsroom

Goodbye to the Byline? How A.I. May Change Authorship in News

In the world of print journalism, a byline is a coveted commodity. For journalists, it’s recognition of the hard work that goes into developing and writing a solid story. It’s no secret that reporters rely on editors, fact checkers, proofreaders, and automated spelling and grammar programs  for support in producing articles – that’s part of the process. 

But what happens when reporters use Artificial Intelligence (A.I.) to do more – such as produce paragraphs of content for their stories? Will reporters and news outlets disclose what is being produced by machines versus humans? Should the byline change to acknowledge A.I. generated content? 

A.I. Makes Inroads in the Newsrooms

Much has been written recently about the ability of machines and software programs to generate news articles. Tools such as QuillBot, ChatGPT and dozens more can create or paraphrase content. Many print and digital news organizations, faced with economic realities in today’s marketplace, have been quick to adopt A.I. 

News outlets have acknowledged the use of A.I. to generate (non-bylined) stores. The Associated Press states it was among the first news organizations to use AI in the newsroom: “Today, we use machine learning along key points in our value chain, including gathering, producing and distributing the news.”

“Roughly a third of the content published by Bloomberg News uses some form of automated technology,” The New York Times said in its 2019 article, “The Rise of the Robot Reporter.”

And in July, The New York Times reported that Google was testing a new tool called “Genesis” that generates news stories. “Google is testing a product that uses artificial intelligence technology to produce news stories, pitching it to news organizations including The New York Times, The Washington Post and The Wall Street Journal’s owner, News Corp, according to three people familiar with the matter.” 

As A.I. tools continue to be explored and adopted by reporters and the news media, some organizations have been sounding the alarm about the overall impact on the quality of newswriting and reporting created by automated systems. Inaccurate data, bias, and plagiarism – which have happened in human-generated stories – have also been uncovered in A.I. generated content.  

The most recent example of A.I. gone awry in a newsroom occurred last year at CNET. The news outlet issued corrections to more than half of 70 articles created by A.I. for its Money section. The articles, including many “how to” stories, were plagued by inaccuracies and plagiarism.

After correcting the articles, CNET announced it was changing its policies on the use of A.I. in generating news.

“When you read a story on CNET, you should know how it was created,” said Connie Guglielmo, former CNET Editor in Chief in her January 25 blog post. “We changed the byline for articles compiled with the AI engine to “CNET Money” and moved the disclosure so you don’t need to hover over the byline to see it. The disclosure clearly says the story was created in part with our AI engine. Because every one of our articles is reviewed and modified by a human editor, the editor also shares a co-byline. To offer even more transparency, CNET started adding a note in AI-related stories written by our beat reporters letting readers know that we’re a publisher using the tech we’re writing about.” 

(Guglielmo took on a new role in CNET following the A.I. debacle. She is now senior vice president on A.I. strategy.)

Many credible news outlets are letting readers know they are aware of the potential for A.I generated text to include bias and what actions they are taking to avoid it.

“We will guard against the dangers of bias embedded within generative tools and their underlying training sets,” The Guardian’s editor US Editor Betsy Reed states. “If we wish to include significant elements generated by AI in a piece of work, we will only do so with clear evidence of a specific benefit, human oversight, and the explicit permission of a senior editor. We will be open with our readers when we do this.”

Just last week, the Associated Press issued new guidance for use of A.I. in developing stories. “Generative AI has the ability to create text, images, audio and video on command, but isn’t yet fully capable of distinguishing between fact and fiction,” AP advises.

“As a result, AP said material produced by artificial intelligence should be vetted carefully, just like material from any other news source. Similarly, AP said a photo, video or audio segment generated by AI should not be used, unless the altered material is itself the subject of a story.”

Credit: Tesfu Assefa

Use of A.I. as a Tool, Not a Replacement for Human-Generated News

In some ways, the failed experiment at CNET supports the use of A.I. as a compliment to human reporting. Proponents cite the ability of A.I. to take the burden of mundane tasks off reporters and editors, increasing productivity and freeing up time to do what humans do best.

“Social Perceptiveness, Originality, and Persuasion” are cited as the human qualities that would be difficult for A.I. to replicate in newswriting and reporting, according to the website calculator “Will Robots Take My Job.” (Journalists are shown to be at a “Moderate Risk” of 47% of losing their jobs to automation, the site said.)

The new Google tool is designed to do just that, a company spokesperson said to the news outlet Voice of America.

“Our goal is to give journalists the choice of using these emerging technologies in a way that enhances their work and productivity,” the spokesperson said. “Quite simply these tools are not intended to, and cannot, replace the essential role journalists have in reporting, creating and fact-checking their articles.”

That philosophy may sit well with readers, as shown by a recent Pew Research Poll. When asked if A.I. in the newsroom was a major advance for the media, many didn’t see the value.

“Among Americans who have heard about AI programs that can write news articles – a use closely connected with platforms such as ChatGPT – a relatively small share (16%) describe this as a major advance for the news media, while 28% call it a minor advance. The largest share (45%) say it is not an advance at all,” the survey said.

Will Today’s Byline Become Extinct?

As A.I. becomes mainstreamed into the print reporting world, news outlets are faced with choices on how to acknowledge the origins of their content. Will reporters who use A.I. text in their stories acknowledge its source in their byline (‘By York Smith, and Genesis’)? Will they add a credit line at the end of the article? Or will A.I. generated sentences be considered just another tool in the hands of reporters and editors? 

A definitive answer may not be available yet. But credible news outlets that maintain the value of transparency will help the media develop a new industry standard in the world of machine learning.

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Challenging Crypto’s Core: The Impact of Quantum Computing on the Sanctity of the Blockchain

Can Crypto Survive the Quantum Computing Revolution?

In the cryptocurrency world, threats abound. Skeptics and critics cry caution, especially to the millions of people eager to dip their financial toes into the digital currency waters. 

And with good reason. Just like the traditional financial market, the crypto world has its share of challenges. Top of mind is fraud, which was highlighted by the recent FTX Sam Bankman-Fried scandal. The alleged mishandling of customer funds and subsequent lawsuits filed against the Binance and Coinbase exchanges added to its woes. 

But there’s another silent threat to the viability of crypto that many experts fear is the real ticking time bomb: quantum computing. This quickly evolving technology threatens to upend the integrity of the blockchain, which is the crypto engine. Quantum computing’s faster processing could crack the blockchain’s code and potentially steal crypto assets in seconds or less. 

The core of the blockchain is the security of its peer-to-peer transactions, which rely on public and private cryptographic keys for the transfer of assets from one account to another. Once ordered, these transactions are verified through a complex mathematical equation that must be solved by the network. When the equation is solved, the transaction is recorded on the blockchain. These recordings are said to be “immutable” – they are transparent and visible to all on the network. Any attempt to change them would be flagged, and immediately shut down.

Quantum computers, which operate based on quantum theory, are expected to move faster than blockchains to solve these complex mathematical problems. While blockchains rely on classical computer processing using bits (0,1) to solve equations, quantum computers use qubits to run “multidimensional quantum algorithms.”

The speed of quantum computing is seen as a threat to blockchain algorithms. If the quantum computer gets hold of the public cryptographic key and can solve the transaction faster than the blockchain, the assets can be stolen.

“As long as these (blockchain) algorithms are considered to be secure, activities that do not abide by the rules, such as illegitimate cryptocurrency transactions, are discarded, incentivizing actors to behave honestly. They are assumed to be secure against powerful supercomputers, now and for the foreseeable future,” the World Economic Forum reported. “But as quantum computers evolve, this assumption is in danger of being upended _ potentially exposing hundreds of billions of dollars worth of cryptocurrencies to sophisticated cyber criminals.”

Blocking and tackling the quantum computer threat is already in action. 

“Even if everyone takes the same protection measures, quantum computers might eventually become so fast that they will undermine the Bitcoin transaction process,” the firm Deloitte wrote. “In this case, the security of the Bitcoin blockchain will be fundamentally broken. The only solution in this case is to transition to a new type of cryptography called ‘post-quantum cryptography,’ which is considered to be inherently resistant to quantum attacks. These types of algorithms present other challenges to the usability of blockchains and are being investigated by cryptographers around the world. We anticipate that future research into post-quantum cryptography will eventually bring the necessary change to build robust and future-proof blockchain applications.”

New cryptography standards

Credit: Tesfu Assefa

In the US, the National Institute of Standards and Technology (NIST), a division of the US Department of Commerce, is working to finalize cryptography standards that will protect users against quantum computing attacks and hacks.

“It is intended that the new public-key cryptography standards will specify one or more additional unclassified, publicly disclosed digital signature, public-key encryption, and key-establishment algorithms that are available worldwide, and are capable of protecting sensitive government information well into the foreseeable future, including after the advent of quantum computers,” the NIST states.

Blockchain isn’t the only technology that is threatened by attacks from quantum computing. The traditional financial industry could also be impacted by a quantum attack. In its white paper “Quantum Key Distribution and Blockchain,” Toshiba touts the benefits of QKD.

“QKD is the first step toward removing public-key assumptions from blockchain applications. It is used to distribute the secret keys important for protecting highly sensitive data critical to many industries. It protects data confidentiality in the finance, defense, utilities, and health sectors as well as the critical infrastructure that underpins our smart cities and smart energy grid.”

QKD uses photons (particles of light) to conduct the transaction. “Any attempt to read or copy the photons alters their encoding, allowing the secrecy of each key to be tested and guaranteed. A single photon cannot be split into smaller particles and cannot be copied without altering the information that is encoded within it. The latter is prohibited by the no-cloning theorem described above. This enables the high level of security that QKD provides.”

One of the first companies to endorse QKD is the international financial giant JPMorgan, which collaborated with Toshiba on the research.

JPMorgan has embraced digital currencies and blockchains. The bank launched its JPM Coin in 2019 and just launched its euro blockchain transactions on its network.

“At this time, QKD is the only solution that has been mathematically proven to defend against a potential quantum computing-based attack, with security guarantees based on the laws of quantum physics,” the bank said last year. 

While the quantum computing v. blockchain story is often framed for its downside potential, there is another side to the potential relationship between these two technologies.

Charles Hoskinson, CEO and Founder of Input Output Global Inc. and the Cardano blockchain, is bullish on the benefits of quantum computing on the cryptocurrency industry. 

“I don’t feel that quantum computers have a pervasive negative impact on cryptocurrencies, but instead, they can add a lot more utility,”  he said in a recent interview with Inside Quantum Technology. “While these two innovative technologies could synchronize successfully, their coming together could be more of a head-on collision than a collaboration.” 

For the sake of both innovative technologies, working to ensure collaboration versus a head-on collision will drive the future of crypto. 

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