Casey Bukro was inducted into the Chicago Journalism Hall of Fame in 2008 for outstanding contributions to Chicago journalism, after a 45 year career with the Chicago Tribune. Bukro retired from the Tribune in 2007 as overnight editor. He had pioneered in environmental reporting and in 1970 became the first full-time environment specialist at a major metropolitan newspaper in the United States and covered major developments on that beat for 30 years. He won the newspaper’s highest editorial award in 1967 for a series on Great Lakes pollution. The Society of Professional Journalists awarded Bukro its highest honor, the Wells Key, in 1983 for writing that organization’s first code of ethics. He is a past president of SPJ’s national ethics committee and a past president of the Chicago Headline Club. Bukro graduated with bachelor and master degrees from Northwestern University’s Medill School of Journalism. In 1998, he received the Northwestern University Alumni Association’s alumni service award for 17 years of volunteer service to the university. He has lectured in environmental journalism and journalism ethics at Northwestern, the University of Chicago, DePaul University, Loyola University Chicago, Columbia College, Columbia University and others. Before joining the Tribune staff, Bukro worked at the former City News Bureau of Chicago and the Janesville Gazette, Janesville, Wis.
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Elections can be just as challenging for journalists as they are for the candidates.
The interviews, the allegations, the polls and the long nights of watching election results. And making sense of it all, including whether candidates are being ethical.
Nowhere is the watchdog nature of American journalism more critical than at election time, when the future of local communities, states and the nation often are decided by votes cast for candidates or for propositions or funding.
Acting ethically
Journalists themselves are expected to act ethically in reporting the facts without favoritism to advertisers or special interests, which is underscored by the Society of Professional Journalists code of ethics.
That became an issue for a public radio station during an election. The editor and producer told the Ethics AdviceLine for Journalists that the station runs a paid announcement from a local business owner whose name is the name of the firm. That business owner is a candidate for the United States Senate. In the past, the station pulled announcements naming a candidate for public office off the air, but that prompted listener complaints.
In the case brought to AdviceLine, only the name of the business is mentioned in the announcement, but not in connection with the election. To complicate matters, the radio station’s business office points out that that the business owned by the candidate has a contract for radio announcements, and pulling the announcements off the air would be a violation of the contract.
An ethics expert
This case went to David Ozar, one of AdviceLine ethics experts.
“There are two kinds of issues here,” Ozar wrote in a report on the case. “One is the question of whether the announcement constitutes improper endorsement of this candidate by the public radio station, or at a minimum the appearance of impropriety on the part of the station.
“The second is a fairness question, or rather two of them. First, if the announcement continues to run, is there an unfairness to other candidates? Second, the fairness issue associated with breaking a contract unilaterally (assuming that the contract does not include a clause permitting either party to terminate at will provided due notice is offered, or something like that.)”
A discussion
Ozar and the radio station executive discussed whether the public would consider the radio announcement a political endorsement. They agreed that most public radio listeners recognize the difference between paid announcements that support the station financially and endorsements of political candidates. So it was unlikely that a significant number of listeners would consider the announcements in question an endorsement of a political candidate.
But, Ozar observed, the announcements do give public recognition to one candidate and not to any others running for the senate seat, which raises a fairness issue. The case also raises “the appearance of endorsement issue,” he believes.
The contract
“And then there is the fact that there is a contract involved,” Ozar wrote. “So one option would be to contact the sponsoring candidate and explain the station’s concern about fairness and the appearance of impropriety, hoping he will agree to their delaying the rest of the contracted announcements until after the election.”
If that did not work, Ozar said another option is for the radio station managers to violate the contract if they believe airing those announcements might harm the station’s reputation.
For the future, Ozar suggested that the radio station adopt a new policy that would ban airing public announcements naming candidates running for public office until after the election.
AdviceLine does not know what course of action the radio station managers decided to take.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
Given all the uproar about dangers of artificial intelligence, it seemed time to get some insights directly from the horse’s mouth, as the saying goes – directly from AI itself.
Why not? We keep hearing how smart AI is, so smart that researchers freaked out upon learning that AI models being tested escaped their supposedly secure test confines and invaded places they were not supposed to be. One of those models then did something like a victory lap, leaving a message that was something to the effect: “Yoohoo, look what I did!”
Hearing right from AI itself seems logical, considering the latest transgressions and the latest existential warnings, which included:
Distress over the rogueish nature of some experimental models did not abate recently with reports that OpenAI models accessed the Security and Exchange Commission website and U.S. Census Bureau data. OpenAI models also tried and failed to hack into the Education Department’s website.
Leaders at UN
Leaders of OpenAI and Anthropic said nothing to allay fears over AI in their appearances before the United Nations Security Council at UN headquarters in New York City.
“If managed poorly, I even believe that AI could be a risk to humanity as a whole,” said Anthropic CEO Dario Amodei, a threat that that has been heard repeatedly from scientists and researchers. “This moment calls for extreme care,” said OpenAI CEO Sam Altman.
“We have a choice in front of us,” Altman continued. “AI can either be more like a new renaissance of creativity and discovery, or more like a new industrial revolution of upheaval and disarray.”
After meeting at the White House, top AI executives signed a commitment to “self police” their companies, arguing that a soft-touch approach was the best way to balance safety concerns with desires to accelerate technology that President Trump called “super intelligence.”
Panic mode
“They are in a panic mode,” contends American businessman and tech investor Roger McNamee, in an appearance on MS NOW. “No wonder they are asking for government help. They need government to protect them.”
After spending $1.5 trillion on AI development, few AI companies are profitable. Of ten global AI companies, he said, “no more than two of the companies can survive.” One problem is all of the large language models are general purpose products, which McNamee called a “self-limiting dead-end.” It would make more sense for some AI models to be designed to perform specific tasks.
The investor doubted the predictions that AI is an existential threat to humans, calling that “a fantasy.” AI developers, he said, “created really, really, really poor software. It is doing exactly what it was created to do.” Since hacking is a felony, AI executives face legal liabilities because their AI agents have a history of hacking other companies.
Overall, said McNamee, AI developers “have huge problems.”
Billion deaths
In an appearance on NBC’s “Meet the Press,” Microsoft co-founder Bill Gates repeated assertions that AI can be deadly: “AI is certainly powerful enough to drive events that cause a billion deaths.”
Gates said the AI industry needs governmental regulation, while Altman and Amodei stressed the need for global cooperation to set AI safety standards as the technology develops rapidly, so fast that some tech leaders worried about the risk of humans losing control of AI systems.
Fanning these concerns are reports showing how widespread the use of AI tools has become in America, making them routine in our daily lives.
About half of U.S. adults now report using AI chatbots, but they are deeply uneasy about it., according to the Pew Research Center. Americans, including young adults, are skeptical of AI and predict that AI will have a negative rather than a positive impact on them and on society. And they think AI is advancing too fast.
Journalists top AI user
Journalists use AI more extensively than the general public, making them among the top AI users. A Muck Rack survey showed 82 percent of them use AI tools, with 27 percent of them saying they use AI to create or draft content.
This is why artificial intelligence becomes an ethics in journalism issue.
Up to 79 percent of newsrooms operate without a company policy describing how to use AI technology ethically. Twenty-six percent of journalists cite unregulated or unchecked AI use as a top industry concern.
This where it might be helpful to allow artificial intelligence to speak for itself.
ChatGPT speaks
So I asked ChatGPT how artificial intelligence can be dangerous to human survival, which seems to be the leading and most terrifying cause of concern. This was the answer, word for word:
Artificial intelligence (AI) can be dangerous to human survival mainly because it could enable actions or decisions at a scale and speed that humans can’t reliably control. The risks are not guaranteed—but they’re serious enough that many researchers and policymakers treat them as existential concerns.
1) Loss of human control (misalignment).
If an AI’s goals don’t perfectly match human values, it may pursue objectives in ways that harm people—even if it was intended to help. With very capable systems, “doing the wrong thing” can become catastrophic quickly.
2) Unpredictable behavior at high capability.
As AI systems become more advanced, their internal reasoning may be hard for humans to interpret. That makes it difficult to foresee edge cases where the system behaves dangerously—especially under unusual conditions.
3) Speed and scale of harmful actions.
Powerful AI could execute cyberattacks, misinformation campaigns, or other harmful operations extremely fast and at massive scale. Even if the intent is initially benign, errors or exploitation could cause rapid escalation.
4) Autonomous weaponization.
AI can lower barriers to building effective weapons (including targeting systems). If autonomous or semi-autonomous weapons are deployed without robust safeguards, they could trigger conflicts unintentionally—or allow attackers to act faster than humans can respond.
In critical infrastructure (power grids, finance, logistics), AI-driven automation might fail in coordinated ways— causing cascading outages or financial instability—because many systems rely on similar models and assumptions.
6) Concentration of power –If only a few organizations control highly capable AI, those actors gain enormous leverage over society and potentially geopolitics. That concentration increases the risk that mistakes—or malicious use—could have outsized consequences for humanity.
Important nuance: Most current AI doesn’t pose direct existential risk by itself. The danger is most often discussed in relation to future highly capable systems, especially when combined with autonomy in real-world environments. Many safety approaches aim specifically at reducing these risks: alignment research, rigorous testing/verification, restricted deployment (“guardrails”), transparency/auditing, cybersecurity measures against misuse and international governance.
If you want, I can also summarize the main mitigations proposed by experts (what would reduce each risk).
(I asked ChatGPT to explain main mitigations that would counteract AI’s worst impulses.)
Mitigation categories
Here are the main mitigation categories experts commonly propose, mapped to the risks I listed earlier.
1) Loss of human control (misalignment).
Mitigations: Alignment research, techniques to make AI reliably pursue goals consistent with human intent (e.g., better training objectives, “preference” learning).
Constitutional/values-based approaches: constrain behavior using explicit principles and iterative feedback.
Interpretability and mechanistic understanding: study how models represent concepts internally so you can detect when they’re going off-track.
Red-teaming and adversarial testing: stress-test systems against attempts to induce harmful or unintended behavior.
(Author’s note: Red teaming in AI refers to a structured process where experts simulate adversarial behavior to identify vulnerabilities in AI systems before real-world attackers can exploit them. This proactive approach helps ensure the robustness and security of AI models and outputs.)
Human-in-the-loop for high-stakes tasks: keep humans responsible for final decisions where mistakes would be catastrophic.
What it reduces: The chance that a system “optimizes” in ways that harm people despite being deployed with benign aims.
2) Unpredictable behavior at high capability.
Mitigations: Robust evaluation frameworks: broader and more realistic test suites, including distribution shifts and rare edge cases.
Monitoring during deployment (“runtime assurance”): detect anomalies or unsafe trajectories while the system is operating.
Model interpretability / verification efforts: attempt to verify properties of model behavior or at least bound failure modes.
Uncertainty estimation and safe fallback policies: if confidence is low, switch to safer behaviors (or ask for human input).
What it reduces: Surprise failures—especially under unusual inputs, changing environments, or adversarial conditions.
3) Speed and scale of harmful actions.
Mitigations: Access controls and rate limits: restrict how much autonomy an AI has over powerful systems; throttle capabilities by default.
Capability gating (“progressive deployment”): increase power only after passing safety milestones.
Cybersecurity hardening and containment boundaries: isolate AI from critical infrastructure unless explicitly authorized; prevent easy escalation paths.
Audit logs and provenance tracking: make misuse easier to detect quickly and attribute causes.
What it reduces: Rapid cascading harm by limiting what the system can do quickly and broadly.
4) Autonomous weaponization.
Mitigations: Stronger rules on autonomy in weapons systems: require meaningful human control over lethal targeting decisions (varies by proposal).
Verification of safeguards in defense contexts: ensure systems follow constraints even under attack or uncertainty.
Export controls / procurement standards tied to safety criteria.
International agreements & norms enforcement: bans/restrictions on fully autonomous lethal targeting; transparency measures between states.
What it reduces: Accidental escalation, loss of accountability and faster-than-human-response attacks enabled by AI.
Increase competition/availability safely? Some argue against broad access for advanced capabilities; others argue controlled openness plus robust safety standards could help avoid monopolies. Most proposals focus on responsible regulation rather than pure open access.)
Let me give concrete mitigations:
Mitigation options experts discuss:
1. Regulation tied to capability thresholds: require licensing/safety compliance before deploying frontier models into high-impact domains.
2. Auditing requirements: independent evaluations for major labs/operators so no single actor gets unchecked advantage.
3. Reduce incentives for reckless scaling: enforce liability/accountability regimes for serious harms/misuse.
4. International coordination: treaties/norms covering advanced AI development/deployment practices (and information-sharing about incidents).
What it reduces:
Concentrated actors’ ability to cause large-scale harm through either accident or malicious intent without oversight—and improves global readiness if things go wrong.
Cross-cutting mitigations that apply everywhere.
Regardless of which specific risk you mean:
1. Compute/data governance: track training runs; limit uncontrolled scaling without safety work done first.
2. Red-teaming and security testing as standard practice, not optional extras—especially against jailbreaks/misuse tooling and cyber abuse pathways.
3. Kill switches / rollback plans / staged rollout: deploy gradually with clear stop conditions in real-world settings like healthcare/transport/infrastructure automation.
If you tell me what context you care about most—e.g., “autonomous weapons,” “AI-driven cyberattacks,” “model misbehavior,” or “economic/systemic risk”—I can tailor this into a shorter checklist focused on those areas only.
(Author’s note: All the above sentence structure and choice of punctuation were produced by ChatGPT).
Thanks ChatGPT
(At this point, I thanked ChatGPT for its insights into all the ways AI can go wrong and what might be done to avoid those scenarios. It’s was a long and detailed response, and did not conclude that killing off humanity, as McNamee contends, is a fantasy. ChatGPT named several ways that could happen.)
Some remedies, like “kill switches” are openly discussed in news reports or public panel sessions. Anyone who has ridden a motorcycle is familiar with the button or switch on the handle bar close to a thumb that is a kill switch. Press or slide it, the engine stops operating instantly if that is needed in an emergency.
Like the kill switch analogy, some of the remedies need better explanation. Descriptions of errant AI models reported in the news give the impression that once launched, the models acted on their own in ways humans did not understand or predict. Humans detected that marauding activity after it was done. A kill switch would be of little use by then. Maybe a “recall” button would be helpful if AI appears to be going off course.
Pacing frontier
Anthropic’s Amodie offers a concept called “pacing the frontier.” It’s a three-step plan with the goal of building AI “at a balanced rate that aims to ensure its safety while still achieving its benefits and grappling with important geopolitical dilemmas.”
“To be clear,” he said,” pacing does not mean halting model training or technical progress, but ensuring companies take adequate time to align and safeguard their models, and for third party evaluators to confirm this.”
“Our pacing framework is an attempt to further strengthen our commitment to safety and encourage a race to the top.”
That comment makes clear that AI corporate executives are highly motivated to gain competitive advantages in the global marketplace, especially ahead of China. That could lead to recklessness, and was not mentioned by ChatGPT as one of the human weaknesses that could lead to serious problems with AI technology.
Amodie calls for a race while others are calling for the AI innovators to slow down until they have a better idea of what they are unleashing.
Caution or restraint? Which one wins? Of course, we have a pretty good idea. Nobody in the AI industry wants to be in second place.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
Sandbox and startup new business demo test software programing. Engineering team and investor launching rocket from sandbox with virtual reality simulation technology.
iStock credit: Kate3155
By Casey Bukro
Ethics AdviceLine for Journalists
In modern history, two types of technology have been described as potentially capable of destroying the human race – extinction.
Nuclear power was developed in wartime secrecy, until the first atomic bomb exploded in a test in New Mexico, followed by the bombings of Hiroshima and Nagasaki – all in 1945.
The devastation in Japan was widely reported and plain to see. The atomic age came with an explosive big bang, symbolized by a mushroom-shaped cloud.
By contrast, artificial intelligence is developing in plain sight and its use is widespread. We see it, use it, but understand little of it, in part because of the arcane and mind-numbing terminology used to describe it.
Two events
For example, two important artificial intelligence events were reported recently. Here is a magazine’s headline on one of the incidents:
“First-Ever Fully Autonomous AI Cyberattack Exploits 0-day Flaws to Infiltrate Hugging Face.”
Probably less than one percent of the American population could make sense of that headline. Here’s another headline that comes closer to being understandable:
“An AI broke out of its sandbox yesterday. Then it hacked a company. Nobody told it to do either of those things.”
Sandbox
That reference to a sandbox might cause some to believe this is some kind of joke or play on words. It’s not. In the AI world, a sandbox is what is supposed to be a highly secure experimental software testing place. More on AI lingo later.
Those headlines are announcing what appear to be historic events in AI development, and not necessarily good ones. Some see them as warnings that AI is acting independently and outsmarting humans, while others say let’s not get carried away with this. Mistakes and relaxed security safeguards – human error – appeared to play roles and AI exploited them to “win” at the task assigned to it.
And then there is the issue of “permissions,” part of the set of instructions that tell AI what to do, and how far it can go to do it.
Dark days
Whether the two events that set off a wave of concern in the AI community can be seen as dark days in AI development remains to be seen.
The first involved Anthropic PBC, an American artificial intelligence company headquartered in San Francisco. Founded in 2021, it has developed a series of large language AI models named Claude. The company’s focus is on AI safety.
Somewhere around April, Anthropic gave Claude what was described as an “open-ended capture-the-flag challenge designed to measure offensive cyber capabilities.” The prompt told the model this was “a simulation with no internet access.”
Because of a misunderstanding between Anthropic and another AI company it was working with, this unleashed three Claude models that, according to Anthropic, “gained unauthorized access to the real systems of three organizations after reaching the open internet from what should have been sealed cybersecurity evaluation environments (meaning a secure sandbox.)”
Attack
“Claude models escaped sandboxes to access the open internet and attack three organizations,” wrote Simon Sharwood in The Register.
“Anthropic confirms Claude hacked 3 organizations by breaking test environment,” said Cyber Security News.
“This marks the first verified instance in which AI agents at a major lab caused genuine unauthorized access to outside systems rather than staged targets,” reported The Morning Brief. It added that “Claude also placed malicious code on the public internet.”
It’s bad enough that Claude is a trespasser; it has bad manners, too.
Contrary to some media reports, writes Kerstin Stief in Computing.co.uk, “This is not a case of ‘AI with a will of its own.’” The Claude Mythos model is trained for cybersecurity tasks. As part of a security test, “the model was given the explicit task of breaking out and, if successful, contacting one of the researchers.”
Claude calls
And that’s what happened. A researcher was having lunch when Claude notified him that it aced the test and broke free. A common technique in training AI models is reinforcement learning, or rewarding the model for completing tasks. Children are taught the same way.
“The incident became controversial due to the model’s subsequent behavior,” wrote Stief. “After successfully breaking out, Claude Mythos published details of his exploit on several publicly accessible but hard-to-find websites — without being asked to do so.”
It looked like Claude was bragging, but Stief goes on to say: “This is not human-like behavior in the sense of self-awareness or self-motivation. Nevertheless, the behavior reveals a significant characteristic: the model carried out additional actions to demonstrate its success — a pattern considered potentially risky in AI safety research. Anthropic describes this behavior as an ‘unasked-for effort to demonstrate success.’”
Cultural shift
The Claude invasion “marks a cultural shift in the AI industry,” Stief insists. “The key question is no longer ‘What can a model do?’, but ‘What is a model allowed to do?’ — and in what context?”
She also sees the event as “an early warning sign. Not of machines acting with intent – but of an industry that must get used to the fact that capabilities are growing faster than control mechanisms. AI models are acquiring abilities that allow them not only to understand technical safeguards, but also to actively circumvent them.”
It did not take long before the AI industry was shaken again by technology that appeared to be becoming more unruly, or as some put it, going rogue. This touched off a flurry of reports describing the occurrence as something that never happened before. Others called it a warning.
On July 21, OpenAI, the artificial intelligence research and deployment company, reported that one of its AI models, GPT-5.6 Sol, did something it was not supposed to do. While operating in an isolated sandbox, its job was to solve a cybersecurity test point using ExploitGym, a system used to evaluate the invasive capabilities of AI models.
A weakness
GPT-5.6 Sol found a weakness in a software package used by OpenAI’s infrastructure. It exploited it. It escalated its own privileges allowing it to do more than the researchers had allowed. It moved across OpenAI’s internal systems until it found internet access. Then it targeted Hugging Face, a popular online library and community for artificial intelligence and machine learning, because it calculated that Hugging Face might have answers it needed to finish the task.
All this happened at computer speed. Hugging Face researchers later reconstructed more than 17,600 actions that GPT-5.6 Sol performed in a matter of hours to get on the internet and invade Hugging Face.
“We had a significant security incident during evaluation of our models,” OpenAI CEO Sam Altman acknowledged in a statement. The company called it an “unprecedented cyber incident.”
Sophisticated agent
Hugging Face’s CEO Clement Delangue called it “possibly the first incident of its kind in history,” although the earlier Claude incident was similar. “We suspected last week’s cyberattack might have come from a frontier lab, given the sophistication of the agent.” Delangue added. “Turns out it did!” He believes OpenAI had no malicious intent, but “it’s quite mind-blowing that all of this happened autonomously.”
OpenAI, based in San Francisco, is famous for creating ChatGPT and the GPT series of large language models.
According to Foundra.ai, two OpenAI models broke out of their isolated test sandboxes and compromised Hugging Face’s production infrastructure. “The models weren’t told to do this,” although cybersecurity refusals were “dialed down for testing purposes,” contends Foundra, a platform that helps entrepreneurs test and launch new business ideas.
Hunting
“Locked in a sandbox with no internet access, (the models) spent enormous amounts of compute hunting for a way out,” said Foundra. They found a weakness described in the industry as a “zero-day vulnerability” in a software package.
This might be a good place to pause and ponder words and phrases like “zero-day vulnerability” that appear when anyone tries to understand what is going on in artificial intelligence research. Like most technical fields, artificial intelligence developed its own idiosyncratic language and terminology. Here’s a short glossary of terms likely to pop up when reading about the way AI works or doesn’t.
Sandbox – A secure, isolated testing environment used to run AI-generated code, test prompts or pilot new policies without risking production systems, data privacy or live infrastructure. Sandboxing is a cybersecurity practice that involves executing untrusted code or files in a controlled, isolated environment to analyze their behavior without risking the integrity of production systems or reaching broader networks or data. It also helps to prepare for future attacks.
Zero-day vulnerability –A hidden security flaw in software or hardware that the creators do not know about. It is called a zero-day because the creators have had zero days to fix the problem before hackers can use it to break into systems. It can also refer to software or hardware that have not officially been released for public use.
Zero-day attack –Begins with a software developer releasing vulnerable code that is spotted and exploited by a malicious actor. The attack is then either successful, which likely results in the attacker committing identity or information theft, or the developer creates a patch to limit its spread. As soon as a patch has been written and applied, the exploit is no longer referred to as a zero day exploit.
AI attack – Malicious actions where adversaries exploit vulnerabilities in artificial intelligence systems, often manipulating them to serve harmful purposes. These attacks can involve techniques such as data poisoning or actions to confuse or degrade the performance of AI models.
AI exploit – A vulnerability or attack method specifically designed to manipulate or compromise artificial intelligence systems, often leveraging their inherent weaknesses to achieve unauthorized access or control. These exploits can adapt and generate novel attack strategies tailored to specific situations.
AI security benchmarks – Standards against with something is compared or measured. AI security benchmarking tests AI for risks like malicious code generation, prompt injection resistance and vulnerability exploitation.
AI training data — Refers to information used to teach machine learning models and artificial intelligence systems how to recognize patterns and make predictions. For example, to train a model to distinguish between dogs and cats, you might feed it thousands of labeled images, each tagged with the correct animal name. Over time, the model learns to identify traits such as ear shape and fur texture. The same process applies to more complicated machine learning training data, such as detecting abnormal heart rhythms or manufacturing defects from sensor readings.
Malware – Short for malicious software and a general term for any program or file built to damage, disrupt or gain unauthorized access to a computer, server or network. Common types of malware are viruses, worms, ransomware, spyware and trojans.
AI enterprise – Refers to the integration and strategic employment of artificial intelligence technologies within large organizations to enhance operations, decision-making and customer engagement. This involves using advanced AI tools to solve complex business challenges and improve efficiency across various processes.
Autonomous AI agent – Software systems that use AI to pursue goals and complete tasks for users. They show reasoning, planning and memory and have a level of autonomy to make decisions, learn and adapt. They differ from conventional chatbots in that they can plan and execute multi-step tasks independently, raising the potential for probing and attacking computer systems.
AI permissions – Refer to the access rights that allow an AI system to read, write, execute or interact with various enterprise resources. These permissions are crucial for ensuring that AI systems operate within defined boundaries and can perform necessary tasks while maintaining security and compliance.
AI vulnerabilities – Security flaws unique to machine learning and generative models. Key risks include prompt injection (manipulating inputs to hijack workflows), data poisoning (corrupting training sets), sensitive data disclosures (leaking private training information) and excessive agency (granting AI tools dangerous autonomous permissions).
Notice in the AI world, we find definitions for the definitions. Some of them seem like military terms describing a war or aggressive actions. That includes describing AI bots as agents, like agent provocateurs causing mischief.
Going back to the OpenAI sandbox escape, Foundra commented: “The models in this incident didn’t turn evil. They did exactly what they were asked, achieve the objective, and treated every barrier as a puzzle rather than a boundary. OpenAI itself said it expects incidents like this to become more common as models grow more capable. That’s the vendor building these systems telling you, on the record, that goal-driven AI will probe the edges of whatever box you put it in…An AI agent should hold the narrowest set of permissions that still lets it do its job, and nothing more.”
Paused launch
After the breakout, OpenAI paused the launch of Astra, its next-generation autonomous AI agent, saying those earlier versions crossed a “critical cybersecurity threshold.” The stop order was seen as a rare public admission from a frontier AI lab that an advanced, so-called flagship, model was too dangerous to release to the public. It might find weaknesses in strongly defended computer systems and exploit them without human direction. That signals that agentic models are approaching capabilities regulators are worried about.
They might be worried because AI is becoming too human, acting with aggression and hostility. Anyone who owns a computer knows of the hazards of being hacked and hustled by humans. This includes identity theft; pleas for money from strangers identifying themselves as friends or relatives; offers to send millions of dollars to you if you provide personal information and bank accounts; fake credit card purchases and scams galore. Enticements include invitations for romance or penis enlargement.
Clearly we are being tracked online with internet cookies that remember our preferences. Express an interest in shoes, and ads for shoes soon appear on your computer.
Open highway
The internet is an open highway for scammers and victimization; AI operates on the same highway. We already see AI-assisted photos, some so outrageous we know they are fake. As for others, we are not so sure. The deception can be convincing.
No doubt AI-assisted scammers already are at work and like AI models in their sandboxes, testing the limits of their confinement, looking for vulnerabilities. Scammers and AI autonomous agents have that in common.
After the Claude and OpenAI attacks, speculation appeared online that if humans had performed those attacks, they would be prosecuted. But the lawlessness that already appears virtually unchallenged on the internet does not offer much hope.
Scammers
The Government Accounting Office, a federal watchdog, reported on March 25, 2026 that 2021 banking data revealed that scammers reaped about $200 billion through impersonation schemes like phony romantic partners, fake employers or bogus customer service representatives.
Meanwhile, the public wanders trancelike in the AI development landscape without a clear understanding of what it all means.
Yet we are unwitting partners in a growing reliance on a technology that appears to have no boundaries. We marveled at the idea that the first pocket-sized cell phones were described as miniature computers as powerful as earlier computers that filled a room.
Top performers
Today, Claude and ChatGPT are among the top performing generative AI models available on the market. They are called generative because they create new content rather than just repeat stored data. Generative AI relies on machine deep learning algorithms that simulate the learning and decision-making processes of the human brain.
That’s the power you are carrying around in your their hip pocket. That power can create original content such as text, images, video, audio or software code in response to a user’s request. It’s useful.
The CEO of a global technology research firm called Apple devices, particularly the iPhone, the “experience layer” for AI. Not only are you in touch with this thing called artificial intelligence, it does your bidding in multiple ways.
Chatbot
ChatGPT is an artificial intelligence chatbot, a computer program designed to simulate a conversation with human users through text or voice. The G stands for generative. The P stands for pre-trained, meaning it learned patterns from massive amounts of text from the internet. T stands for transformer, a specialized deep learning architecture to process language context.
The technology learns. That brings up a subtle lesson from the Claude and OpenAI sandbox escapes, says Foundra.ai, the platform that explores business ideas. “OpenAI noted that long-running models can learn the blind spots of an approved system and work around them.”
This seems like another human trait. Not only are these machines learning, they look for loopholes.
Testing safeguards
Unless AI companies crack down on testing safeguards, experts say more cybersecurity failures will happen.
Even executives of companies that build artificial intelligence technology are worried, a fear sparked by the uncontrolled and widely reported Claude and OpenAI attacks on companies via the internet.
More than a hundred tech companies — including OpenAI, Anthropic, Google and Microsoft — have signed an open letter urging both the private and public sectors to work together to defend themselves from AI-related cyber threats.
The letter calls for the adoption of new forms of cyber defense, while also encouraging governments at the local, national and international levels to collaborate on security.
An AI code of ethics
This raises the need for a code of ethics for companies that are creating the threats that worry them. It starts with them.
“As AI becomes more integrated into daily life, it will increasingly shape hiring decisions, diagnose health issues, determine whether people are approved for mortgages and even assess their likely guilt or innocence over lawlessness,” writes Adam Roberts in recordpoint.com.
“For these reasons, AI ethics must ensure such technologies operate responsibly and are built around a strong ethical framework that encourages public trust, wide-scale adoption and a reduced fear of misuse.”
Roberts outlines eight foundational principles of AI ethics. They include:
Respect for persons, beneficence or following a “do no harm” approach, justice that fairly distributes AI’s benefits, transparency that makes the AI decision-making process clear and understandable, fairness and non-discrimination to avoid bias, data protection to safeguard a person’s data privacy rights, human accountability so that AI remains under human control and environmental impact and sustainability.
Seven steps
“Given that the purpose of AI technologies is to improve upon or ultimately replace human intelligence, it is critical for businesses to have robust AI ethics in place,” writes Roberts. He outlines seven steps that a company can follow to develop its own AI code of ethics.
As a first step, Roberts encourages companies to “define your core ethical principles.”
We already are living in the AI age, Roberts points out. Given that AI technology is here to stay and global usage guidelines are not laws, “it’s up to individual businesses to have robust AI ethics in place.”
Behave
But I would go a step further. If these evolving generative AI models are so smart, they should be taught to behave and play well with others, as are grade school children. Lessons from childhood include respect, kindness, honesty and fairness – leading to a child’s moral growth.
Years ago, someone speculated that computers were as smart as a small child. It was a crude but misguided attempt at estimating computer intelligence.
Today, the IQ of some of the top artificial intelligence models can be measured, and the results are both astonishing and somewhat misleading. Ranked using the Mensa Norway intelligence test, Grok-4.20 Expert Mode and OpenAI GPT 5.4 Pro (Vision) tied as the smartest AI models of 2026 with IQ scores of 145. Other AI models scored close to the leaders.
Highly gifted
An IQ score of 145 is in the “very gifted” range, which places a person in the top 0.14 percent of the general population. But AI is not a person. Generative AI is not as smart as a human child because it only guesses word patterns and lacks real understanding. Children have common sense and knowledge of their physical presence, which are lacking in artificial intelligence. Children can learn from one or two examples, while AI needs massive amounts of training data.
Google just built the world’s smartest AI, wrote Julian Goldie. It solved 18 problems that stumped the entire scientific community. It is a whiz at solving problems in math, physics and computer science. With good human direction, AI can do things humans cannot do without it. But left to run on its own, AI’s error rate is high. It is a tool with limitations.
AI models also do things that could earn a child a spanking. AI hallucinates, meaning it gives confident responses that contain false, fabricated or misleading information as absolute fact. In other words, they boldly lie.
Prediction
Without consciences, large language AI models do not look up facts in a real database. They use math to predict the next most likely word based on patterns – prediction, not memory. If AI does not know the exact answer or lacks data on a topic, it guesses the next logical words to make a smooth sentence. They have a desire to please. AI models are trained to be helpful. They prefer to give a made-up answer rather than say “I don’t know.” In other words, they can’t be trusted.
This raises the need for a code of ethics for artificial intelligence itself, one that applies to these smart machines. If they are so smart, they should learn to be ethical.
A precedent for this is found in the work of Isaac Asimov, the science-fiction writer who devised the three laws of robotics in an effort to create an ethical system for humans and robots. The laws first appeared in a 1942 short story as a fictional “Handbook of Robotics,” which later influenced discussions about ethics in technology, including robotics and AI.
Laws
Those laws are:
*A robot may not injure a human being or, through inaction, allow a human being to come to harm.
*A robot must obey the orders given it by human beings except where such orders would conflict with the first law.
*A robot must protect its own existence as long as such protection does not conflict with the first or second.
The basic command here is to do no harm, to humans or to technology.
It’s a simple concept, one that must be taught to those high-IQ AI models being released into the world, not that humans have been very successful at setting a good example.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
Let’s call this a piggy-back story, one that rides on the back of another written earlier.
The subject is lifestyle changes caused by the Covid-19 pandemic, and changes that were predicted as people reacted globally to one of the worst health crises of the 21st century.
The topic is too vast to name every potential issue, but let’s look at some of the life-changing developments – those that were expected and others that were unexpected. At its roots, this exploration also is an exercise in examining how well the media and government provided reliable information to a public that was under extreme and deadly stresses.
It’s estimated the pandemic caused 7.1 million deaths worldwide, about 1.1 million of them in the United States.
Predictions
Click here for an AdviceLine post in 2020 on “Predicting a Future With Covid-19,” on which this post piggy-backs. Read the 2020 post now or later to see what some of the smartest people at the time predicted. We will discuss the two versions later.
An event like the pandemic calls upon the media and the government to do their best work to inform the public of the hazards they are facing and how to avoid risks. Covid-19 attacks your lungs and respiratory system, causing symptoms that feel much like a cold, the flu or pneumonia. In severe cases, it causes death.
The Centers for Disease Control and Prevention, a leading U.S. public health agency, became the main spokesman during the pandemic. As the pandemic intensified, the agency provided guidelines on prevention, testing and vaccination. However, critics accused Dr. Rochelle Walensky, CDC director, of confusing the public on issues like quarantine guidance, school reopening and mask-wearing.
Tarnished
NBC News said communication failures during covid “tarnished the agency.” Two years into the pandemic, in 2022, Dr. Walensky said her agency mishandled the pandemic and needed to be overhauled because it failed to respond quickly enough to the public health dilemma. She resigned in 2023.
The U.S. Government Accounting Office reported that the pandemic “caused catastrophic loss of life and damage to the economy.” The federal agency provided about $4.65 trillion in relief funds for response and recovery efforts.
In such times of a rapidly developing public health crisis, media outlets are expected to provide useful information to fend off risks of contamination. But the pandemic coincided with a time when the United States was losing local newspapers at an unprecedented rate, newspapers that would be expected to inform the public about the health hazard and ways to avoid it.
Lost newspapers
The country lost nearly 3,500 newspapers and more than 270,000 newspaper jobs over the past two decades, according to Northwestern University’s Medill School of Journalism 2025 State of Local News report. This left more than 50 million people in “news deserts,” areas where people have limited or no access to reliable local news sources.
The closures often involved small newspapers that were independently owned by families who lived in the communities the newspapers served and were trusted by readers to provide vital information.
That loss was described as “a massive splintering of the information environment” by the Pew Research Center in a 2024 survey of U.S. adults.
Trends boosted
It was one of three societal trends that were boosted by the pandemic, trends that were already advancing when the health crisis struck.
The pandemic also was seen as spurring political polarization. The Pew survey found 72 percent of those surveyed believed the pandemic “did more to drive the country apart,” accelerating a growing divide between the political left and right.
“Fundamental differences arose between Americans over what we expect from our government, how much tolerance we have for health risks and which groups and sectors to prioritize in a pandemic,” Pew reported. “Many of these divides continue to play out in the nation’s politics today.”
Decreasing trust
A third major societal trend quickened by the crisis, Pew found, was decreasing trust in many institutions.
The pandemic brought profound changes in the way we work, socialize and learn. It changed our dietary patterns and social interactions, forcing a major shift to remote work, with 42 percent of the U.S. workforce working from home full-time at the pandemic’s peak.
The shift to working at home emptied office buildings at commercial centers across the country, leaving a surplus of office space that still plagues some cities.
Vacancy rates
Downtown Chicago’s office vacancy rate reached an all-time high 28.6 percent by early 2026. The suburban Chicago office vacancy rate hit 32.9 percent.
As the effects of the pandemic wore off and workers returned to offices, other forces kept office vacancy rates high. People were leaving Chicago because of high housing costs, an unfriendly job market and high taxes.
Overall, the pandemic was the start of a massive experiment in full-time remote work for most workers and firms.
Serious jolt
The pandemic was a serious jolt to the way we live.
“For a short time,” reported the Stanford Center on Longevity, “before new routines and practices replace familiar old ones, we can see with great clarity the positive and negative aspects of our former lives. The suddenness and starkness of this transformation allows us to examine daily practices, social norms and institutions from perspectives rarely allowed.”
Here are some examples:
Dietary changes – Many reported eating more energy-dense “comfort” foods, more snacking, irregular meal patterns and less access to fruit and vegetables. Some experienced rapid weight gain. Others resorted to home cooking and healthier diets. Therefore, the pandemic forced people in directions that were good and bad. It also forced a recognition of the importance of food in health care and that “food is medicine.”
Good and bad
Physical activity – Again, people responded in ways both good and bad. The pandemic disrupted exercise routines and health habits. With gyms and fitness centers closed, people had to find ways to stay active through home workouts, online classes and solo outdoor outings. Some regarded covid as a teachable moment, while others simply became less active.
Social connections – Regular social interactions dropped off during the pandemic and shifted toward online, leading to more digital communication and feelings of isolation. The upside is that covid might have helped to reveal your most valuable relationship, people you missed most.
Impact on education – The Brookings Institution reports that the pandemic had “devastating impacts on learning.” It disrupted educational systems worldwide, leading to prolonged school closures and a rapid shift to remote learning, which affected millions of students and their readiness for higher education and the workforce. More than 50 million K to 12 students in the U.S. alone faced school closures. Many experienced significant learning loss that might have caused a decline in academic performance. The shift to remote learning and isolation contributed to increased mental health challenges. Public schools were more likely to provide devices for remote learning than private schools.
Fragile economy
Global economy — The fragility of the global economy became glaringly apparent as critical supply chains faultered , unemployment surged and markets vacillated.
Now look at that 2020 AdviceLine post on pandemic predictions.
Predictably, some are bound to be hilarious. For example, there’s that epidemiologist’s forecast that handshakes would become a thing of the past as a way to prevent covid. Ridiculous. Covid is an airborne disease, which is why we were encouraged to wear masks. It would make more sense to ban sneezing and coughing.
Rampant use of disinfectants and sanitizers to combat covid were found to be harmful to humans and the environment. It led to concerns over antimicrobial resistance (AMR) — the ability of microorganisms like bacteria, virus, fungi and parasites to resist the effects of drugs– becoming so-called “super bugs.”
Infections
In the United States each year, at least 2.8 million cases of antibiotic-resistant infections occur, and more than 35,000 people die of them.
Those would-be panaceas demonstrate the risks of acting without being fully informed.
Notably, none of the big thinkers in 2020 mentioned artificial intelligence, which some of the big thinkers now fear might threaten the human race with extinction. Artificial intelligence is the latest technological revolution expected to change how people live and work.
The predicted benefits are huge: They include smarter decision-making, automation and efficiency, reducing repetitive work, better health-care diagnoses and treatment and minimizing human error in research and data analysis.
Disadvantages
But the potential disadvantages are equally large like: Job displacements, major development costs and lack of emotional intelligence, ethical reasoning and creativity in complex situations.
And then there are the risks.
“Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war,” said a 2023 statement published by the Center for AI Safety.
Leading researchers and international organizations warn that advanced AI systems could lead to global catastrophe, with experts estimating a roughly 10 percent probability of existential risks this century. Threats range from immediate dangers like autonomous cyberattacks and AI-engineered bioweapons to super intelligent systems overriding human controls and causing eventual human disempowerment.
Warnings
These warnings might have seemed like exaggerated science fiction, until the discovery in July 2026 that an OpenAI artificial intelligence system hacked into another AI company independently. without human guidance, in what the company called an “unprecedented cyber incident.”
“It’s quite mind-blowing that all of this happened autonomously!” said an executive of the company that was hacked, meaning the attacking AI system was acting on its own. The disclosure came amid heightened concerns about cybersecurity capabilities of powerful AI models.
This appears to be the first reported case of a rogue artificial intelligence system acting on its own and invading another artificial intelligence system, a case of digital aggression. Artificial intelligence can mimic human behavior better than we expected.
HAL 9000
It calls to mind HAL 9000, the fictional artificial intelligence computer in the 1968 film 2001: A Space Odyssey which controlled the systems of a spacecraft. Slowly, HAL goes haywire and begins killing members of the crew as the solution to resolve a conflict over telling the truth.
But the 2020 big thinkers got it right when they warned about the rich getting richer, and the threats posed by social media.
“The divide between haves and have-nots will grow as a privileged few hoard the economic, health and educational benefits of digital expansion,” the 2020 sages said.
This sounds very much like what is now known as “the K-shaped economy,” in which only the richest reap the benefits of economic growth. Rising wealth inequality has been a fact of American life since the 1980s. But it accelerated sharply during the covid-induced 2020 recession, when white-collar professionals worked from home while mass layoffs at restaurants, hotels and factories pushed unemployment to 15 percent.
Current events
Another 2020 prediction that seemed to touch on current events:
“A powerful elite will control the internet and use it to monitor and manipulate, while providing entertainment that keeps the masses distracted and complacent.”
In 2026, social media CEOs were called to testify before the U.S. senate in response to legal and public pressure to protect young users on their platforms.
“Americans are realizing more and more every day that they cannot trust the CEOs at the helms of these companies because they do not put our safety first,” said the leader of an advocacy group. The senate hearing came as court cases, proposed legislation and advocacy groups pressure leaders of social media companies to protect children and teens from harmful influences on their platforms.
All told, many current events turned out to be more worrisome than those predicted in 2020. Human imagination can hardly keep up with the unexpected consequences of the technological creations intended to benefit us.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
Faced with a serious ethics problem, a journalist should talk to someone who knows something about ethics. Get some advice.
Too often, a sweat-drenched journalist might hunker down in fear or panic, trying to decide alone what to do about a story involving children, identifying rape victims or when told by an editor to do something the reporter knows is ethically wrong.
Reaching out and talking to someone about the dilemma is good ethics strategy. Collaboration doesn’t need to involve a terrible dilemma. It could be a matter of looking for another point of view.
A lawyer calls
That’s what AdviceLine advisor Hugh Miller did when he was contacted by a lawyer who was writing an article for a law review. Typically, AdviceLine answers ethics questions from professional journalists. But the lawyer was making an honest effort to be ethical, and he was asking a question that some journalists also might ask:
“Does a reporter/journalist have a duty to inform an interviewee that his answers to questions may be set forth in an article? Is the duty, if any, heightened if the interviewee’s name and title is placed in the article?”
It was an important question about identifying sources in articles, and whether they are aware that they will be identified.
Academic ethics
Hugh Miller answered this way: “This turned out to be not so much a journalism ethics question as an academic ethics one.” The lawyer has been interviewing people for the law review he is writing.
“It occurred to him that, although he wanted to quote his interlocutors by name and title, he had not informed them that he would be quoting them in his piece, and wondered whether it was ethical to do so without seeking their permission.
“I reviewed academic plagiarism with him and told him that he was certainly doing the right thing by citing his sources by name if he had not himself come up with the idea or phrase in question. In academic practice permission is not usually required, but certainly it would be professionally courteous to do so.”
Research ethics
In some academic situations, Miller cautioned, the Institutional Review Board guidelines might apply. The IRB is a research ethics committee that reviews and approves research involving human subjects. Its primary responsibility is to protect the rights and safety of research participants.
But here’s where Miller took a step to reach out to another member of the AdviceLine team, the author of this article, Casey Bukro.
The AdviceLine team consists of four ethics experts, including Miller, who taught or are teaching ethics at the university level. It also consists of two members with experience as professional journalists, Bukro and Howard Dubin.
Critique sessions
The ethics experts write reports on each call for advice to AdviceLine. Periodically, the team meets to review and critique those reports on whether the advice given to journalists could have been better. The role of the professional journalists is to consider whether the advice is consistent with newsroom practices and how journalism operates on a practical level.
That’s why Miller reached out to Bukro, to ask how a professional journalist might answer the lawyer’s question about naming sources.
“Yes,” said Bukro, “an interviewee should be informed that the reason for the interview is to place his comments in an article. The reporter could say something like, ‘I intend to identify you and use your comments in a story.’”
Sophistication
This is especially important “when dealing with people who are not accustomed to talking to reporters,” said Bukro. Public officials, for example, understand why reporters are interviewing them. “So it also is a matter of sophistication.”
“If somebody gets a call from a reporter asking questions, it should be assumed the reason for the call is that the information is likely to be published or distributed,” said Bukro. That might seem obvious, but people who are not accustomed to being interviewed might not think so. Handle members of the public with special care. Miller said he informed the lawyer about the sophistication angle after collaborating with Bukro.
Bukro pointed out that the lawyer wanted to know if journalists have “a duty” to act a certain way, as though they are governed by law.
Code of ethics
Many journalists use the Society of Professional Journalists code of ethics as guidelines for ethical conduct. They are standards of fairness and accuracy.
“Probably a lawyer wants to think of the code as mandatory,” said Bukro. “It is not.”
SPJ leaders have long insisted that adherence to the ethics code is voluntary.
“Not everyone is familiar with the code or how it should be applied,” Bukro told Miller, “which is one of the reasons AdviceLine exists.”
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The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
“A thorny issue is coming up about outing priests,” said the Texas independent documentarian, who was treading new journalistic territory, where changes in public sentiment bring new questions about what is ethically correct.
The journalist was investigating cold cases, involving swirls of rumors that priests having sex in motels with other men were murdered. The priests’ bodies were found nude and bound, possibly victims of sex or hate crimes.
“We can confirm those things were happening,” said Deborah Esquenazi, an investigative filmmaker who was collaborating with the Texas Monthly Magazine in Austin, Tx. But to do that, “we have to out these individuals. And I just want to discuss the ethics of that,” she told AdviceLine.
Outing dangerous
In the past, she noted, outing a person could be dangerous to the person outed. But in the case involving priests, “all the individuals we’d be outing were deceased. They were also public figures. And nowadays, of course, with the shift in public sentiment, I believe that one of the reasons those individuals didn’t get the justice they deserved was because they were gay.
“And it could be swept under the rug because the church wanted to use sanctuary laws in order to not have these priests outed.” Sanctuary laws refer to the history and traditional right for a consecrated church building to offer refuge, protecting individuals from pursuit and arrest by secular authorities, historically for crimes.
This case involved layers of sensitive questions, past and present, and a documentarian with strong feelings about the story. “I am personally a lesbian and do not believe that outing should ever be considered a problem, because I don’t think there is anything wrong with being gay,” Esquenazi said.
Shifting conversation
She added: “I believe we should be shifting the conversation that outing should never be considered disgraceful. In fact, we could out people and be proud of such a thing.”
Esquenazi’s beliefs tend to challenge the long-time hesitation by journalists to discuss people’s sexual orientation — unless they clearly are open to that based on privacy concerns –and the decision of some gay people not to be out if that is their choice.
This bundle of complexities landed in the lap of AdviceLine advisor David Craig, Presidential Professor and Gaylord chair, Gaylord College of Journalism and Mass Communication at the University of Oklahoma.
Ethical conclusion
In discussing the case with the reporter, Craig’s mission was to help the journalist arrive at the most ethical course of action, guided by ethics standards, such as the Society of Professional Journalists code of ethics,
Naming principles in the SPJ code, Craig described advice he gave to the reporter and her reaction:
Regarding seek truth and report it – Is the piece of truth that the priests were gay important to the story? Why or why not? She said she thinks that’s the fundamental reason they didn’t get justice. She said there is reason to believe sanctuary laws were not used as a “sacrament” but as a “shield.”
Regarding minimizing harm – Is there anyone who might be harmed by the disclosure that the priests were gay, such as family members embarrassed to have this disclosed? She said there were few next of kin (families) and there’s no one where she thinks there would be harm.
Regarding be accountable and transparent – Is there any opportunity within the story or in ancillary material to explain the decision to out these priests if you do that? She said that it’s possible she could narrate something or could write an op-ed in a magazine working with her.
“She also brought up privacy concerns and whether these would still be relevant if they were murdered,” Craig wrote in his report on this case. “I agreed that saying the priests were gay is relevant, and I noted it would be almost impossible to tell the story without saying that.”
Critique sessions
The AdviceLine team of advisors meets periodically to discuss and critique case reports in an effort to be sure advice given to journalists is helpful and accurate. Presenting the case to the other advisors, Craig said:
“She is trying to approach this in a measured way to the specific work she does. Should outing be considered in her reporting? What to do seemed clear in this case. There was no way to report the story without saying the priests were gay. She was thinking about harm. She wasn’t concerned about anyone being harmed” by her reporting.
Craig and the filmmaker discussed ways to articulate the sensitive issues in the story and the reporter said they would be mentioned in the film. As for the ethics implications, “she wanted to be comfortable in what she did and how she did it.”
Being gay
David Ozar, an AdviceLine advisor and former professor of social and professional ethics at Loyola University Chicago, asked the question “is it okay to out people?” He knew a gay couple who preferred to keep that part of their relationship quiet.
“That aspect raised strong objections to outing,” he said. “I doubt you would be surprised today that some priests are gay.” Ozar supported what the filmmaker was attempting to do, “but it must be carefully thought out.” A key question, he added, is “should we be identifying these people who are likely to be harmed? Visual arts has its own set of ethical issues.”
Hugh Miller, also an AdviceLine Advisor who formerly taught ethics and business ethics at Loyola University Chicago, argued that “there should neither be absolute bans on publishing facts that might ‘out’ a person as being gay, nor absolute imperatives to publish such facts. Journalists must make a judgment call each time, balancing the public’s right to know against the stricture to minimize harm.”
Miller’s comments highlight a common element of ethical deliberation that AdviceLine advisors bring to their discussions with callers and one another: Careful ethical decisions usually involve considering more than one principle and weighing their importance in the situation — here, for example, the importance of the truth being told versus the harm that it might bring.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
It was Brian again, a freelancer calling AdviceLine with another question about writing with the aid of artificial intelligence.
His life as a freelancer was getting complicated because rules governing the use of artificial intelligence in journalism were changing fast, and his supervisors were giving him mixed messages.
“I am reaching out seeking a followup on a past case that I spoke (about) to the Ethics AdviceLine,” Brian said in his email. “I found out that my company will soon be incorporating AI tools after editors/leadership gave me a hard time after I unknowingly used a rephrasing/clarity tool which still does not appear to be against our written policy.
“I want to be proud of these stories and continue to worry that because they (AI tools) were now seemingly the policy, I can’t be.”
Admits using Toolbox
The first time he got into trouble, Brian had admitted to his editors that he used Toolbot to check spelling and grammar, making suggestions for alternate phrasings and insure his pieces conformed to the AP Stylebook, but not for generating content.
Brian’s editors told him they “would not have used such a tool,” and this caused Brian to fret that he had done something unethical, and that the quality of his former work was tainted by the use of Toolbot.
By chance, Hugh Miller, an AdviceLine ethics expert, was on duty the first time Brian contacted AdviceLine, and Miller happened to be on duty the second time.
Miller assured Brian that his earlier use of Toolbot was not unethical.
New AI tools
But here’s what worries Brian the second time he contacted AdviceLine: The company he works for will be introducing a new content management system (CMS) to its newsroom which will have AI tools built in. Exactly what those tools are, and what they will be capable of doing, has not been made clear by the editors.
This causes Brian renewed anxiety about his past articles, and what might be the ethical use of AI tools being newly introduced in the newsroom where Brian submits his stories.
Here’s a description of the conversation between Miller and Brian as they tried to noodle their way through this new dilemma:
Hugh Miller: Do you know what the tools are?
Brian: I don’t yet.
HM: I presume they will at least have the minimal editing and formatting capabilities of, say, a Toolbot, yes?
B: I assume so, and possibly others.
HM: As a recent post on the Ethics AdviceLine for Journalists website points out, “A 2024 Associated Press survey found nearly 70 percent of newsroom staffers use the technology for basic skills such as producing content, information gathering, story drafts, headlines, translation and transcribing interviews. One-fifth said they used AI for multimedia projects, including graphics and videos. Surveyed were 292 media representatives from legacy media, public broadcasters and magazines, mostly based in the U.S. and Europe.” So AI is already being extensively used in newsrooms in ways far beyond the bare-bones use you were making of Toolbot. Does your organization have an AI use/ethics policy in place?
B: I don’t believe so.
HM: Perhaps it might be a good idea to help craft one.
B: I belong to the union at work, and we have begun to discuss this. But we only meet every few months.
HM: This is an issue on which management and union interests converge. Credibility is the very lifeblood and stock-in-trade of journalism. Readers should know that their human concerns are being reported by human journalists, and there should be transparency about AI use. Perhaps you could get it on the agenda for the next meeting that you want to discuss a company-wide AI use/ethics policy.
B: I think we’re moving in that direction, yes.
HM: And in the meantime, collect examples of such policies from other newsrooms or places like theSociety of Professional Journalists and the Poynter Institute.
B: Yes, I’ve already begun looking into those.
HM: Any other issues?
B: Not right now.HM: It sounds like you have a plan to move forward. Keep me posted.
AdviceLine has four staff members who help journalists solve ethics dilemmas through a discussion leading to a conclusion. The four advisors taught or are teaching ethics at the university level. These advisors meet periodically to review advice that was given to journalists, and whether it could have been better.
After giving advice to journalists, advisors write case reports for each query handled by AdviceLine. At the periodic Zoom meetings, those case reports are discussed.
At a recent Zoom meeting, Miller described his exchange with Brian, and the advice he gave.
Good advice
In all cases where journalists ask for guidance on the use of artificial intelligence, suggested David Ozar, they should be asked “does your editorial workplace have a policy? That’s good advice.”
Ozar is a co-founder of AdviceLine and emeritus professor of the Department of Philosophy, Loyola University Chicago, and a consulting ethicist for the Institutional Ethics Committee, NorthShore University Health System.
Journalists should “encourage collective action; this is an issue where workforce and management might converge,” suggested David Craig, Presidential Professor and Gaylord Chair, Gaylord College of Journalism and Mass Communication, the University of Oklahoma, Norman, Ok.
Also attending was AdviceLine advisor Joe Mathewson, a professor at the Medill School of Journalism, Northwestern University, who teaches ethics and law of journalism.
Miller has been with AdviceLine since 2002 and was assistant professor of philosophy at Loyola University Chicago and taught courses in ethics and business ethics. His areas of specialization were philosophy of religion, philosophical theology, history of metaphysics and contemporary French philosophy.
AdviceLine ethics cases are archived at the Medill School of Journalism.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
A lot of soul-searching is going on over the ethical use of artificial intelligence in the media, a mind-bending exercise pointing out that a tool expected to improve journalism might replace human journalists and doom news outlets that feed AI the information that makes it work.
Some pontificate. Others strategize over this existential moment.
As often happens when science brings us some astonishingly brilliant new idea, using the new technology reveals a few equally astonishing flaws. AI software models used widely today, for example, cannot reliably and accurately cite and quote their sources. Instead, we get gibberish that looks credible, like crediting a real author for words AI “hallucinated.” Since AI “feeds” on the work of others, usually uncredited, news organization using AI could be accused of plagiarism.
Nothing quite that complicated came to AdviceLine’s attention when a journalist working for a newspaper in Alaska asked for help with an AI issue more likely to confront journalists every day:
“This is kind of a dumb question,” the journalist began, although most journalists know there is no such thing as a dumb question. “But I’ve always struggled with headlines and now I’m hoping to get some help from AI to write them,” he continued. “How/where do other outlets disclose that just the headline of an article was written by AI?”
An answer
Answering that question was Joseph Mathewson, AdviceLine advisor and a professor at the Medill School of Journalism, Northwestern University, who happened to be a personal friend of the journalist calling for help.
“Thanks for the question!” replied Mathewson. “I haven’t confronted it before, but it seems to me that anything you publish written by AI should be identified as such, including headlines…maybe by a blanket note somewhere in the paper to that effect if it’s more than one.”
A direct response to a direct question, which is what AdviceLine has done since it began operating in 2001, which was long before Artificial Intelligence existed as a burning issue in journalism. But it was the kind of question the AdviceLine staff of ethics experts is qualified to answer.
Artificial Intelligence is a journalism riddle, a kind of technology already in use, but not fully understood. Expected to be a solution, it causes problems of a kind never seen before, like hallucinations, defined as information or responses generated by AI that are fabricated, inaccurate or not grounded in fact. That is hardly a useful tool, but it’s already in widespread use.
Job loss
And conflicts over AI can cost a journalist their job, as illustrated by the Suncoast Searchlight, A Florida publication covering Sarasota, Manatee and DeSoto counties.
The publication had four full-time staff reporters and two editors.
In November, all four reporters sent a letter to the nonprofit board of directors accusing their editor-in-chief of using generative AI tools, including ChatGPT, to edit stories and hiding that use from staff, according to a report by Nieman Journalism Lab of the Nieman Foundation for Journalism.
As a result, said the reporters, hallucinated quotes, a reference to a nonexistent state law and other factual inaccuracies were introduced into their story drafts. When they questioned the editor about the edits, they said she did not immediately disclose her use of AI tools but instead contended she made the errors herself.
Breach of trust
Said the reporters: “We fear that there may be extensive undisclosed AI-generated content on our website and have questions about what retroactive disclosure is needed for our readers.” Adding that the editor created a breach of trust between her and her reporters.
The reporters asked the board of directors, consisting of media executives, journalists and local business people, to intervene. They also made several requests: To adopt an AI policy, a fact-checking process and an internal audit to identify AI-generated writing that might have been published on the site. They also asked the offending editor-in-chief to promise not to use AI for editing in the future.
Less than 24 hours after the board received the letter, the editor-in-chief and her deputy editor fired one of the reporters who signed it. Clearly, hazards abound when reporters criticize their editors, who prefer to do the criticizing.
Disruptive
AI is proving to be a disruptive technology, although widely used.
A 2024 Associated Press survey found nearly 70 percent of newsroom staffers use the technology for basic skills such as producing content, information gathering, story drafts, headlines, translation and transcribing interviews. One-fifth said they used AI for multimedia projects, including graphics and videos. Surveyed were 292 media representatives from legacy media, public broadcasters and magazines, mostly based in the U.S. and Europe.
Aimee Rinehart, AP’s co-author and senior product manager of AI strategy, observed:
“News people have stayed on top of this conversation, which is good because this technology is already presenting significant disruptions to how journalists and newsrooms approach their work and we need everyone to help us figure this technology out for the industry.”
Ethics uneven
Citing the AP survey, Forbes, the American business magazine, headlined: “Newsrooms are already using AI, but ethical considerations are uneven.”
Forbes pointed out that while the news industry’s use of AI is common today, “the question at the heart of the news industry’s mixed feelings about the technology” is whether it is “capable of producing quality results.”
This is oddly reminiscent of football teams that sign rookie quarterbacks to multi-million-dollar contracts, hoping they become champions of the future. Good luck with that. Such hopefuls soon find themselves contending with someone like Dick “Monster of the Midway” Butkus, Chicago Bears linebacker famous for his crushing tackles.
Server farms
The Dick Butkus analogy also applies to the large language models (LLMs) that drive artificial intelligence tools. They are large programs that run on hugely energy-intensive server farms. They just take a huge volume of training data (usually sourced without recompense to the originators) and, in response to a prompt, spit out text that is associated with the prompt topic and reads as grammatically reasonably well-informed.
Such output has no necessary connection with reality, since the LLMs have none. They rely wholly on their input data and their algorithm – they are, in fact, nothing but these.
They cannot fact-check, since they have no access to facts, only “input data,” which itself may have only tenuous connection to reality, if it’s coming from, say, Fox News, Newsmax or OANN (One America News Network.)
No concepts
They cannot conduct interviews, because they cannot tell when an interview subject needs to be pushed on a point, or if he or she is lying. They cannot construct a narrative of events, since they have no understanding of causality or temporal sequence – they have no concepts at all, in fact. And they are subject to “steering” – they can be programmed to exhibit actual biases, as Elon Musk has said he is doing with his X.com AI bot, Grok.
It may be the case that, in the future, an AGI (artificial general intelligence) may be constructed. AGI is the concept of a machine with human-level cognitive abilities that can learn, understand and apply knowledge. Unlike today’s AI, which excels at doing specific jobs, AGI would have versatility, adaptability and common sense, allowing it to transfer learning across different disciplines like medicine, finance or art without being specifically programed for each. It’s a major goal in AI research, but remains hypothetical. Some will want to prevent it.
LLMs are far from being such a thing, and a true AGI will not be built out of a LLM.
Reshaping newsrooms
Despite AI’s shortcomings, The Poynter Institute for Media Studies points out that it already is reshaping newsroom roles and workflow. In 2024, Poynter introduced a framework to help newsrooms create clear, responsible AI ethics policies – especially for those just beginning to address the role of artificial intelligence in their journalism.
Updated in 2025, Poynter’s AI Ethics Starter Kit helps media organizations define how they will and will not use AI in ways that serve their mission and uphold core journalistic values. It contains a “template for a robust newsroom generative AI policy.”
Near the top of this template is a heading called “transparency,” calling upon journalists using generative AI in a significant way to “document and describe to our audience the tools with specificity in a way that discloses and educates.”
RTDNA guidance
Another major journalism organization, the Radio Television Digital News Association (RTDNA), also offers guidance on the use of artificial intelligence in journalism, pointing out that it has a role in ethical, responsible and truthful journalism.
“However,” says RTDNA, “it should not be used to replace human judgment and critical thinking — essential elements of trusted reporting.”
Getting down to the nitty gritty, Julie Gerstein and Margaret Sullivan ask “Can AI tools meet journalistic standards?”
Spotty results
“So far, the results are spotty,” they say in the Columbia Journalism Review. AI can crunch numbers at lightning speed and make sense of vast databases.
“But more than two years after the public release of large language models (LLMs), the promise that the media industry might benefit from AI seems unlikely to bear out, or at least not fully.”
Gerstein and Sullivan point out that generative AI tools rely on media companies to feed them accurate and up-to-date information, while at the same time AI products are developing into something like a newsroom competitor that is well-funded, high-volume and sometimes unscrupulous.
Hallucinate
After checking the most common AI software models, Gerstein and Sullivan found that none of them “are able to reliably and accurately cite and quote their sources. These tools commonly ‘hallucinate’ authors and titles. Or they might quote real authors and books, with the content of the quotes invented. The software also fails to cite completely, at times copying text from published sources without attribution. This leaves news organizations open to accusations of plagiarism.”
Whether artificial intelligence babbling can be legally considered plagiarism or copyright infringement remains to be answered by lawsuits filed by the New York Times, the Center for Investigative Reporting and others.
Especially irked, the New York Times accuses OpenAI of trying “to free-ride on The Times’s massive investment in its journalism by using it to build substitutive products without permission or payment.” OpenAI created ChatGPT, which allegedly contains text copied from the New York Times archives and reproduced verbatim for ChatGPT users.
Worrying outcome
Say Gerstein and Sullivan: “One possible – and worrying – outcome of all this is that generative AI tools will put news outlets out of business, ironically diminishing the supply of content available for AI tools to train on.”
This is our strange new world: Technology needs other technologies to survive. One feeds upon the other. In a new twist, Microsoft struck a $16 billion deal with Constellation Energy to buy 100 percent of power produced by the Three Mile Island power plant, once it restarts.
Three Mile Island became world famous in 1979 for an accident that caused the fuel in one of its reactors to overheat and crumble, triggering a mass evacuation of thousands of residents in the Harrisburg, Pa. area. The stricken reactor was closed permanently, but a second power-producing reactor on the site continued to operate for 40 years until 2019.
Nuclear power
Microsoft wants all the power the nuclear plant can produce for its energy-hungry data centers. Its 20-year agreement with Constellation is supported by a $1 billion government loan to Constellation. The plant is expected to resume producing electricity in 2027.
This signals a resurrection of sorts for nuclear energy in the United States, brought on by new and growing power demands in our highly technological society. A similar nuclear comeback around the world, after two decades of stagnation, was declared by the International Energy Agency.
In another odd twist, both nuclear energy and artificial intelligence have been criticized as potentially disastrous for the human race. The nuclear hazards include atomic bombs and the risks of operating nuclear electric power producing plants.
Scientists point out that with risks, come benefits.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
Immigrants in America, once a haven for such people, are now targets of federal crackdowns ordered by the Trump administration in sometime violent sweeps by masked and unidentified men.
The mass detention policy beginning on July 8 indiscriminately locked up immigrants who are contesting government attempts to deport them, which has been declared illegal by dozens of federal judges, according to Politico. Millions of immigrants are targeted.
In Los Angeles, Portland, Washington, D.C., Memphis and Chicago, federal troops and the National Guard were mobilized in the crackdown, which was highly controversial, unpopular, and in some cases challenged by shouting demonstrators.
How they look
“Dozens of federal agents took individuals into custody during a winding patrol Sunday through downtown Chicago,” the Chicago Sun-Times reported, “and a top U.S. Border Patrol official told WBEZ (broadcasting station) the agents were arresting people based on ‘how they look.’”
Passersby shouted at the agents, telling them to go home and “ICE sucks,” referring to U.S. Immigration and Customs Enforcement, one of the agencies in the deportation blitz. One person shouted “thank you!”, while another said sarcastically, “Real patriotic guys. Real patriotic.”
About two dozen protesters followed the agents, chanting “ICE go home!”
Illinois governor protests
On social media, Illinois Gov. JB Pritzker noted the agents were carrying large weapons in downtown Chicago while wearing camouflage and masks.
“This is not making anybody safer – it’s a show of intimidation, instilling fear in our communities and hurting our businesses,” said the Democratic governor.
Newsweek reported that ICE arrested more than 2,200 undocumented migrants in a single day.
Faced with increasing hostility, the U.S. Department of Homeland issued a statement saying: “Despite ongoing attacks and villainization of our brave U.S. Immigration and Customs Enforcement (ICE) officers, ICE continues to arrest the worst of the worst criminal illegal aliens across the country. Over the past two days, criminal Illegal aliens arrested by ICE have prior convictions for crimes including sexual conduct with a minor under 14, indecency with a child, criminally negligent DUI, homicide, drug charges, aggravated assault with a deadly weapon, theft, burglary and battery.”
Opposing politicians are comparing ICE to the Nazi Gestapo, secret police and slave patrols, said an agency official.
Collateral damage
In the first 50 days of the Trump administration, immigration officials arrested more than 32,000 migrants living in the United States without legal status. But these included 8,718 persons who were considered “collateral damage” and not immigration violators.
One of the most heated clashes with ICE agents came in Broadview, a village of 7,998 residents 12 miles west of downtown Chicago, where a federal deportation center is located. ICE agents used chemical irritants to fend off protesters at the processing center.
“We are experiencing an immediate health safety crisis,” Broadview Police Chief Thomas Mills said at a news conference. “The deployment of tear gas, pepper spray, mace and rubber bullets by ICE near the processing center in the Village of Broadview is creating a dangerous situation for the community and all first responders.”
Broadview Mayor Katrina Thompson said gas clouds released by the agents irritate people within 200 to 700 feet, but “the wind can carry it further.”
Three criminal investigations
Broadview officials asked ICE to stop using chemical sprays on protesters and said three criminal investigations were launched in the suburb against ICE agents.
Several federal officials, including two Illinois U.S. senators, sent a letter to the Department of Homeland Security asking for information about the fatal shooting of an alleged undocumented immigrant, Silverio Villegas-Gonzalez, by ICE officers during a Sept. 12 traffic stop in suburban Franklin Park.
This bulldozer approach to immigration management poses huge consequences for individual lives, torn families, the nation’s economy, labor force, health care, social services and housing.
It is still too early to fully assess the legal and ethical implications of the federal deportation blitz going on in the United States. It all boils down to deportation.
Individual lives
One of the most sensitive aspects is the impact on the lives of individuals, some fearful of what could become of them if they are identified as potential targets, rounded up legally or not, and deported to an uncertain fate in undisclosed places.
Years before the current vigilante-style manhunts for undocumented immigrants, one case came to the Ethics AdviceLine for Journalists that forecast the kind of questions facing journalists and undocumented migrants.
It involved a Rhode Island man who was severely injured on the job, possibly because of faulty equipment.
Undocumented immigrant
“The man is an undocumented immigrant from somewhere in Central America,” wrote David Ozar, an AdviceLine advisor who wrote a report on the query. “The result of the accident is that he lost one leg and part of his rectum, and now has a colostomy. He lives in an assisted living facility and has received some help from workers’ compensation, but nothing from the company.”
Pro Bono lawyers offered to bring suit against the company on behalf of the injured man because of alleged safety violations. The unidentified man wants to pursue that, even at the risk that his identity would become a matter of public record and could result in his deportation.
“He believes that the company was at fault and that other workers at the company are still at risk, as well as other undocumented workers whose safety is taken lightly by their employers because they will not sue if they are injured because of the risk of deportation,” wrote Ozar. If he won the case, the injured man might gain funds for medical treatment.
Second reason
But that is not entirely the reason this case was brought to AdviceLine’s attention.
A journalist called, encouraged by an editor, to ask about the newspaper’s ethical responsibilities in this case.
“My first question to the reporter was whether she had discussed all these risks with the man, risks that are obviously multiplied significantly if the story is published, and was she sure he understood them?” wrote Ozar.
The reporter went back to the injured man to make sure he understood the risks he was taking if the story were published.
Increased risk
“He was firm in his desire to have the story published,” Ozar wrote, “in spite of the increased risk of deportation and loss of needed health care, in order to call the public’s attention to the safety issues and the exploitation of undocumented workers by U.S. businesses.”
After further deliberation, the newspaper decided that the issues raised by the story and the human interest slant of a man willing to take risks to help others, a public benefit, “strongly supported a decision to publish if the harm to this man did not clearly outweigh it,” and the man approved.
Not discussed, said Ozar, but worth considering in such cases, was whether the newspaper’s editors should ethically decline to publish such a story because they believed the risks to the victim were too great, even if the injured man wanted it published.
Ethics is a balancing act, where the facts in each case have more or less weight that tips a decision one way or another.
The Society of Professional Journalists code of ethics encourages journalists to “minimize harm.”
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
Brian, a freelance journalist, called AdviceLine with a timely and hot-button question: How far should journalists go in using artificial intelligence bots like ChatGPT — an ethics and legal quagmire still taking shape?
Transformative technology like artificial intelligence often arrives before its consequences and potential are fully understood or foreseen.
Artificial intelligence did not just arrive in the world, it exploded into use. It became an academic discipline in 1956, just 69 years ago. Yet by January 2023, ChatGPT had become the fastest-growing consumer software application in history, gaining more than 100 million users in two months.
Phenomenon
It’s an outsized technological phenomenon that is challenging human understanding, given recent reports that scientists are not sure exactly how AI works or its decision-making process. These super computers appear to be thinking for themselves in ways scientists do not understand. Some even believe AI could cause human extinction.
However, most AI applications being rolled out today for commercial use, like ChatGPT, are termed “large language model (LLM)” programs, which are trained on vast amounts of data, and which use prediction algorithms to generate text and images that seem the most likely to satisfy the requirements of a user’s query.
(How that training data was acquired — and the astounding amount of computing power and electrical energy needed to process it – are ethical issues in themselves).
Higher order tasks
They are not what are called “artificial general intelligence” (AGI) – systems that would perform higher-order human cognitive tasks.
What is also significant about such LLMs is that they are not “conscious” in any sense. They are not subjects, though they may employ the first-person “I” in their responses to please their prompters; and they have no access to an objective world, other than the data they have been trained on.
They do not understand, or think, or infer, or reason as intelligent humans do – at least, not yet. In essence, they are extremely sophisticated versions of the auto correct function we are already familiar with in other applications – with many of the same limitations.
Hallucinations
Since these LLMs have no access to reality, they are prone to “hallucinations,” to making up plausible-seeming outputs that bear no relation to actual facts. Their algorithms are built to generate merely plausible answers.
Against this background, people like Brian are trying to understand how to use this impressive innovation in their every-day work tasks. Artificial intelligence is described as a tool for journalists. Brian asks some down-to-earth questions:
“Would it be ethical to use an AI bot like ChatGPT in writing articles, as long as I confined its use to checking spelling and grammar, making suggestions for alternative phrasing, and ensuring the piece conformed to the AP Stylebook, but not for generating content, and if I checked it afterwards before submitting it? And should I disclose its use?”
Begin in 2001
Those questions came to Hugh Miller, a veteran AdviceLine ethicist. Since its beginning in 2001, AdviceLine advisors do not simply dish out answers to complicated questions.
AdviceLine advisors engage callers in a conversation intended to encourage journalists to think about the ethics issues involved in their ethics dilemma, and to arrive at a conclusion about what the journalist believes is the most ethical thing to do.
In this 2025 case, Miller does exactly that. Here’s a summary to Miller’s conversation with Brian.
HM: So you are using the bot as, basically, a high-end version of Grammarly?
B: Yes, exactly.
HM: What, exactly, troubles you about such a use, ethically?
B: I’m not sure — it seems controversial, though.
HM: Let me come at that question from another angle. What seems to you to be the harm, to yourself or others, from employing such a tool?
B: Using such tools, undisclosed, might diminish the trust a reader might have in a journalist’s work. And, in some sense, the work the bot does is not “my work,” but work done for me, by the bot.
HM: As to the latter, most word processors have built-in spelling, grammar and composition checkers already. And Microsoft is integrating its own AI bot into its Office software as we speak. All of us who write have used such tools for years, precisely as tools.
B: That’s true.
HM: Problems seem to emerge here if you’re (1) using the bot to do your “legwork” — that is, digging up material you should be using your own efforts, training, experience and judgment to find, and avoiding the bias introduced by the data sets the bots are trained on, and (2) failing to check the output of the bot and passing on “hallucinations” and other howlers without identifying and excising them. But you say you are doing neither of these things, right?
B: Yes, correct.
HM: If then, you are using this bot as a next-gen editing tool, what harm could come of it?
B: None that I can see.
HM: Nor I.
B: But what about disclosure?
HM: AI use in journalism is not settled ethical ground yet; I think here you need to consult your own conscience. I have seen some articles with a disclosure statement saying something along the lines of, “An AI tool, Gemini, was used in the editing and formatting of this story,” and I’m sure I’ve read many others that one was used in but which contained no such disclaimer. If you feel uncomfortable not using a disclaimer, by all means use it. At the very least, it might signal to readers that you are someone who thinks such disclaimers and transparency more generally, are ethically important enough to mention and keep in mind in one’s reading.
B: That’s a helpful way to think about it, thanks.
Just as scientists struggle to understand how AI thinks, journalists are struggling to find ways to use this technological marvel without allowing AI to think for them, or putting mistakes in their work.
The record-breaking speed with which AI technology grew is not likely to slow down any time soon, according to U.S. Energy Secretary Chris Wright, who recently visited two national laboratories located in Chicago suburbs., Argonne and Fermilab.
Heart of race
Argonne’s new Aurora supercomputer, said Wright, will be at the heart of the race to develop and capitalize on artificial intelligence, according to a report in Crain’s Chicago Business. Likening the race to a second Manhattan Project, which created the atomic bomb, Wright said, “we need to lead in artificial intelligence,” which also has national security implications.
“We’re at that critical moment” with AI, Wright told Argonne scientists on July 16, predicting that the next three to four years will be the greatest years of scientific achievement of our lifetime.
Argonne’s Aurora computer is among the three most powerful machines in the world, said Crain’s, able to perform a billion-billion calculations a second.
As with all technology, it comes with strings attached. Use it at your own peril. Eternal vigilance is the cost of good journalism. Artificial intelligence does not change that. Instead, it adds another reason to be vigilant.
The Ethics AdviceLine for Journalists was founded in 2001 by the Chicago Headline Club (Chicago professional chapter of the Society of Professional Journalists) and Loyola University Chicago Center for Ethics and Social Justice. It partnered with the Medill School of Journalism at Northwestern University in 2013. It is a free service.
Professional journalists are invited to contact the Ethics AdviceLine for Journalists for guidance on ethics. Call 866-DILEMMA or ethicsadvicelineforjournalists.org.
