What AI Thinks About AI for Professional Writing

 

As with so many parts of modern life, artificial intelligence (AI) is disrupting professions that rely on the written word. Some people think it’s amazing. Some think it’s overhyped. And some think it’s a dangerous job killer that will reduce humans’ ability to think and communicate for themselves.

I’m not sure where I stand yet, but I was wondering the other day what AI itself thinks about using AI for professional writing, editing and research. Like any good journalist, I reached out to multiple sources for comment. Here’s what I learned from the major AI platforms I consulted that use large language models (LLMs).

ChatGPT and Perplexity kind of hemmed and hawed. Eventually I got tired of waiting for them to formulate a response while “still thinking and processing.” Gemini, sort of hid behind the Google Chrome search results. But Claude to its credit answered my questions swiftly and confidently, but not before telling me: “Hank, the irony of your request has not been lost on me.”

According to Claude: “AI writing tools have swept into newsrooms, law firms, academic institutions, and corporate communications departments with remarkable speed. The pitch is seductive: faster drafts, fewer bottlenecks, lower costs.” No surprise there, but then Claude confided: “For professional writing — where accuracy, credibility, and sourcing are non-negotiable — AI tools introduce a set of risks that should give any serious writer or editor pause.”

Hmmm.

Unprompted by me, Claude then addressed the tendency of AI to come up with make-believe-sources.

The Hallucination Problem

“The most damaging flaw of LLMs in professional writing contexts is what researchers and engineers call ‘hallucination,’” asserted Claude. “It’s the tendency of AI systems to generate false information with complete confidence. This isn't a bug that will be patched in the next update. It is, to a significant degree, structural,” said Claude.

If you’re in a situation or profession that expects you to document the sources for your work, which should give you pause.

As Claude explained during our interview, “language models work by predicting statistically likely sequences of text based on training data. They do not ‘know’ facts the way a database stores records. When asked to produce a citation — a journal article, a court case, a news report — the model generates text that looks like a citation. It follows the correct format, includes plausible author names, and references a real-sounding journal. But the underlying article may not exist at all,” Claude noted.

Personally, I’ve run into the source fabrication problem often and so have many of our clients.

When I asked Claude for an example of AI hallucination, it shared the following story: “This phenomenon gained widespread public attention in 2023 when a New York attorney, Steven Schwartz, submitted a legal brief that cited multiple court cases generated by ChatGPT — none of which were real. The judge was not amused,” noted Claude. “Schwartz faced sanctions, and the case became a widely cited cautionary tale about the dangers of using generative AI in professional legal contexts,” Claude added.

Why Citations Are Especially Vulnerable

According to Claude, “citation requires something AI fundamentally lacks: a reliable, verifiable link between a claim and a specific, retrievable source.” A human researcher, Claude said, “finds a source, reads it, and records it. The citation is downstream of an actual act of retrieval and comprehension. By contrast, AI generates a citation because citations are a pattern that appears in its training data. [AI] has learned that academic sentences tend to be followed by parenthetical author-year references, that legal briefs cite specific case names and dockets, and that journalism includes attributed quotes. So, it produces those patterns — whether or not the underlying source exists.”

To me, it’s amazing the human programmers have figured out a way to mimic academic, legal and journalistic writing style, but you can see how dangerous it can be when mis-used.

As Claude continued: “Even worse Hank, when AI tools do have access to real sources (through retrieval-augmented generation or web search), they can still misrepresent them — paraphrasing inaccurately, attributing quotes to the wrong person, or presenting a source's argument as the opposite of what it actually says.”

Personally, I’ve frequently been frustrated by inaccurate paraphrasing and misattribution of quotes, and it’s something you should double check before you go live with any material AI has generated for you.

The Problem of Confident Vagueness

If you’re still reading this post, or asking your AI assistant to do so, I thank you for your time.

As Claude noted: “Professional writing demands precision. A medical writer cannot say a drug ‘significantly reduces symptoms’ without citing a specific study with a specific patient population and outcome measure,” Claude said. “An investigative journalist cannot attribute a claim to ‘experts’ without naming them. AI prose tends toward what might be called confident vagueness — it sounds authoritative while eliding the specific details that give professional writing its credibility and accountability,” Claude noted.

Agreed. We’re constantly calling out our clients on that.

“This is partly why AI-generated text often passes a casual read but falls apart under editorial scrutiny,” admitted Claude. “The sentences are grammatical, the tone is appropriate, the structure is sound — but when a fact-checker goes to verify the third paragraph, the sources either don't exist or don't say what the text claims.”

In my experience, this is sadly all too accurate.

Accountability

“Beyond sourcing,” continued Claude, “professional writing carries the voice, judgment, and accountability of a named author. A byline is not merely a formality — it represents a human being who can be questioned, who has a reputation at stake, and who made deliberate choices about what to include and what to leave out. AI-generated content erodes that accountability layer entirely,” asserted Claude.

“There is also the question of what gets left out. AI models trained on existing text will reproduce the emphases, omissions, and blind spots of that text,” said Claude. “A professional writer working a beat develops the judgment to know what the data doesn't show, who hasn't been heard from, and what a source has an interest in saying. AI has no such judgment — it optimizes for plausibility, not truth,” stated Claude.

A Tool, But Not a Replacement for Professional Judgment

“None of this means AI has no place in a writer's workflow,” asserted Claude. “Brainstorming, structural outlining, rough drafting, and editing assistance are areas where the stakes of a fabricated citation are low and the efficiency gains are real. But for any writing where sourcing, accuracy, and accountability matter — journalism, legal writing, academic research, medical communication — AI should be treated as a starting point at best, and a liability at worst.”

Even Claude concedes: “The professional writer's value lies precisely in what AI cannot reliably do: find real sources, read them carefully, represent them accurately, and stake their name on the result.”

More tools and resources related to this post can be found on our website.

Conclusion

AI is great for getting started, especially when you’re just staring at a blank screen and can’t get out of first gear. It can be a great help when it comes to brainstorming, structural outlining, rough drafting, and editing assistance. But turning to your work over to AI blindly is not just lazy; it can irreparably damage your reputation and your firm’s.

March Madness and Investing: Why Behavioral Biases Keep Derailing Us

Whether your Final Four picks include Blue Chip mega-caps (Duke, Michigan and Kentucky), or low-cap growth stocks (High Point, Cal Baptist and Prairie View A&M) behavioral biases are on full display when tens of millions of Americans fill out their NCAA men’s basketball tournament brackets.

March Madness is not just a three-week basketball-palooza. It is a classic example of the cognitive biases that derail investors year after year.  Here are four of the most egregious ones:

1. Overconfidence Bias

Ask anyone why they picked a certain team to go deep in the tournament and you will get a confident, well-reasoned answer. They watched three games this season. They read a column about the point guard. Their cousin went to that school. The coach is hot right now. They did well last year.

This is overconfidence bias in its purest form — the tendency to overestimate the accuracy of our predictions based on thin or anecdotal evidence. Behavioral economists have documented this bias extensively. Behavioral psychologist, Daniel Kahneman, described how people consistently overestimate the precision of their forecasts, especially in complex systems with many interacting variables.

Basketball, like markets, is exactly that kind of system. A star player rolls his ankle in warmups. An underdog catches fire from three. A referee misses a call. The outcome is partly skill and partly chaos — and yet tens of millions of people fill out brackets with supreme conviction. Yet no one has ever predicted all 67 games correctly in the same year. In fact, out of 36 million brackets completed on the major online sites in the 2026, NOT ONE bracket remained perfect by  the 44^th game of the 67 game tournament. And there are still four rounds to go.

Investors do the same thing. We read a few earnings reports, catch a segment on financial television, and proceed to make high conviction bets on individual stocks. We forget that we are competing against professionals who do this 12 hours a day with resources and computing power we cannot imagine. The bracket reminds us: confidence and competence are not the same thing.

For many years, Warren Buffett offered $1 billion to anyone who could pick a perfect NCAA bracket and never once paid up. Now Kalshi, the prediction market site is made the same $1 billion offer. They already know they won’t have to pay up in 2026.

2. Recency Bias: Why Last Year's Champion Gets Too Much Love

In bracket psychology, recent events loom far larger than a full body of evidence would justify. The defending champion University of Florida Gators were a No.1 seed in this year’s tournament and a heavy favorite to make the Final Four. Instead, they got knocked out by No.9 seed, University of Iowa in only the second round. University of Nebraska started the season 20-0 and then dropped seven of their last 13 games heading into the post-season. They fell to a No.4 seed and millions of bracketeers overlooked them as a contender. Yet here are the Huskers in the Sweet 16 having just knocked off Vanderbilt, champions of the highly competitive Southeastern Conference.

Recency bias is equally destructive in investing. When markets are rising, investors pile in, assuming the good times will last indefinitely. When they correct, panic selling takes over. We let the last six months of data override twenty years of historical context.

The data on this is sobering. Dalbar's annual Quantitative Analysis of Investor Behavior consistently shows that average investors dramatically underperform the indices they invest in — not because the funds are bad, but because investors buy high and sell low, chasing recent performance. They are filling out their financial brackets based on last week's box scores.

3. Confirmation Bias: Rooting for Your Pick to Be Right

Once you have committed to a bracket pick, something strange happens. You start finding evidence that supports it everywhere. TV analyst Charles Barkley calls your team a “sleeper to watch” and it feels like vindication. But when pundit Seth Greenberg questions them, you instantly dismiss his take on your team, even if his argument is stronger. You are no longer evaluating information objectively — you are prosecuting a case for your predetermined conclusion.

Confirmation bias is one of the most dangerous land mines in investing. Once we own a stock, we unconsciously filter news through the lens of ownership. Good earnings confirm our genius. Bad news gets rationalized as temporary. We stop asking "should I own this?" and start asking "why should I continue to own this?" — a subtle but devastating shift.

Before you finalize a bracket pick, read the case for the other team. Before you double down on a position, write out a serious bear case. The goal is not pessimism — it is intellectual honesty.

4. Loss Aversion

Research suggests most people feel the pain of the loss roughly twice as intensely as the joy of a gain. Kahneman called this “loss aversion,” and he showed it is hardwired into our brains from birth.

In March Madness, loss aversion drives people to pick favorites relentlessly, even when the expected value of an upset pick is higher. We protect our bracket's survival rather than optimizing for winning the pool. We anchor to our initial picks long after they should be reconsidered.

For investors, loss aversion leads to holding losing stocks far too long — hoping to "get back to breakeven" — and selling winners prematurely to lock in gains. Both behaviors sacrifice expected returns in service of emotional comfort. The result is a portfolio shaped more by feelings than by fundamentals.

How March Madness Can Make Us Better Investors

The most successful bracket players — and investors — share a few key traits.

1. They diversify their picks rather than over-concentrating on one narrative.

2. They respect base rates: historically, No. 1 seeds win the national championship more often than all other seeds combined. They manage their downside and stay in the game long enough for their process to pay off.

3. They also know when to trust the structure over the story. The tournament bracket is a process. A well-constructed investment policy statement is a process. Both exist to protect us from ourselves in high-emotion moments.

Before you submit your next bracket or make your next investment decision ask yourself: ”Am I making this pick because the data supports it, or because I watched them play two weeks ago and they outplayed their conference rivals with a better record? Am I buying this stock because I have a thesis, or because everyone on my feed is talking about it?”

Conclusion

March Madness lasts three weeks. The behavioral biases it exposes can last a lifetime. The court just makes it more obvious than a brokerage account does.

#Marchmadness, #NCAAbasketball, #behavioralbias, #investing

Is It Better to Be Published or Quoted?

 

P.T. Barnum, the iconic 19^th century showman liked to say: “All publicity is good publicity.”

That may be true. But I can’t tell you how many financial professionals contact us wanting to do “PR” for them. “We have such a great XYZ, but no one has heard of us,” they lament, assuming media outlets should be breaking down the door to do stories about them.

In today’s era of shrinking newsrooms, that kind of “earned media” coverage is harder and harder to do. It’s simple math. Newsrooms are shrinking at even the best newspapers, magazines and broadcast outlets. The editors and reporters who remain are completely overloaded and don’t have time for coffee, lunch, golf or 15-minute meet-and-greets just to get to know you. They’re under constant pressure to meet tight deadlines with timely, relevant content that will keep the audience engaged and advertisers happy.

And now thanks to crowdsourced pitching services like Qwoted, Source Bottle and HARO (Help a Reporter Out), journalists are receiving more pitches than ever for fewer and fewer coverage opportunities.

That’s why we recommend writing authoritative bylined columns for reputable media outlets cover your industry.

Here are some of the advantages of bylined columns over simply being quoted:

• Recognition and Authority: Publishing establishes you as an expert in your field, whereas a quote often places the spotlight on the person who cited you.
  
  
• Control of the narrative: When you publish a bylined article, you control the narrative. When you’re simply quoted in an interview, your comments are just there to fill in the blanks in the reporter’s story – and there’s always the danger of being misquoted or being taken out of context.
  
  
• Career Advancement: Peer-reviewed publications directly lead to paid speaking gigs, new clients, podcast guest appearances, job opportunities, and consulting opportunities.
  
  
• Professional Development: The process of publishing improves writing and critical thinking skills, forcing the consolidation of complex ideas. After a few articles, you’re presentations and “elevator pitches” will get even better.
  
  
• Greater Impact: A published work allows others to build upon your findings, contributing to the broader development of a field.
  
  
• Validation: Being published means a publisher or reviewers validated the work's quality and value. That’s what cements your status as a bona fide thought leader.
  
  
•  Shelf life. Many of the specialized media outlets we work with build an archive landing page with all of your bylined columns listed, as well as your headshot and professional bio. Most media outlets keep the articles on their archive pages live for several years. You won’t get an archive page just being a source.

 
But I already have a good journalist relationship

If you can build a good relationship with a top journalist who covers your industry or geographic area, that’s great. Those relationships can be an invaluable source of earned media coverage, and you’ll eventually be considered a thought leader. You’ll likely get quoted several times per year – usually on short notice – for stories they’re working on. Just know that you can’t control when they publish, what the story is about, and most importantly, other experts being quoted in the story.

Most good journalists use multiple sources for their report, and you can’t control the order in which you’re quoted or if you’re quoted in the same story as a competitor, former partner or someone who is generally regarded as unethical in your space.

Again, as a source, you can’t control the narrative like you can as a guest columnist or regular contributor.

Conclusion

All PR is good PR, but the right PR is worth its weight in gold. Let me know what you’re doing to garner earned media coverage. I’d like to hear more.

#thoughtleadership, #bylinedarticles, #mediacoverage, #PR