Q: Who will be the next head coach of the North Carolina Tar Heels men’s basketball team?
Q: When will the Department of Homeland Security be funded again?
Q: Where will Taylor Swift and Travis Kelce's wedding occur?
 
You might know the answers to these questions now, but at the time of writing this article, most people did not, which is why they were among the top trending questions on Kalshi, a key player in one of the fastest-growing consumer trends: prediction markets.
 
It’s human nature to speculate, and in many ways the habit is helpful – we need to anticipate future events and outcomes so we can prepare for them, e.g., natural disasters, economic cycles. But will betting on the outcomes of all manner of life events pay out as simple diversion or social/economic disaster? Now that’s a great question for Kalshi!
 
What are prediction markets and how does betting in them differ from other common kinds of gambling, e.g., casinos, lotteries, sports?
 
At the most basic level, prediction market betting is the same as other gambling in that the bettor places a wager on the outcome of an event, e.g., at a casino, where the ‘pill’ will land on a roulette wheel; for a Powerball drawing, what the winning numbers will be; in the NCAA Division I basketball tournament, which men’s/women’s teams will win.
 
However, a key difference is that betting in prediction markets is not limited to one or a few specific types of  bets; rather, people can wager on the outcomes of virtually any activity, which players seem to be doing with increasing enthusiasm.
 
For instance, for the 2026 Super Bowl, Kalshi alone handled over $1 billion worth of bets – an increase of 2,700% from 2025. One of the most popular wagers was, ‘What will be the first song that halftime performer Bad Bunny will sing?’ Bets on that ‘event’ alone surpassed $100 million. People wagered on many other incidental Super Bowl outcomes such as ‘Will Elon Musk or Lionel Messi attend the game?’
 
Thanks to companies like Kalshi and Polymarket, the other main purveyor of prediction bets, this kind of gambling doesn’t need to wait for a once-a-year sports spectacle. People can wager on virtually anything that gains the interest of enough people to create a betting market. For example, while writing this paragraph, some of the trending bets only Polymarket are:

• Who will be the winner of Eurovision 2026?
• When will the U.S. and Iran reach a ceasefire?
• What will SpaceX’s IPO closing market cap be?
• What will be the price of crude oil by the end of March?
• Who will be the Republican presidential nominee in 2028?
• How many Elon Musk # tweets will there be March 31 - April 7?

 
The great variety of bets and ease of placing them from almost anywhere have spurred a prediction market boom. In December of 2026 alone, Kalshi and Polymarket collectively saw almost $12 billion in wagers, an increase of more than 400% from the previous year.
 
Another important difference: prediction markets don’t serve as the ‘house’ like sports books do; rather, markets like Kalshi and Polymarket earn money by charging trading fees for bringing together opposite sides of a bet. The price of a bet on their sites indicates the likelihood that a given outcome will occur, e.g., a $0.20 bet = 20% probability of ‘yes, it will happen.’
 
The screenshots below from Kalshi show a bet on whether the government shutdown will last for at least 70 days. Given the market-calculated 62% probability of ‘yes,’ $1.00 bet on the affirmative earns $2.00, if the shutdown reaches 70 days, while $1.00 wagered on ‘no’ earns $3.00, apparently because of its lower, 41% chance, of occurring.
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Difficult Regulation: While the 39 U.S. states that allow sports gambling regulate it within their own borders and the U.S. Security & Exchange Commission (SEC) regulates the trading of stocks, the Commodity Futures Trading Commission (CFTC) regulates prediction markets like Kalshi and Polymarket.
 
The CFTC is a long-standing regulatory body that promotes the “integrity, resilience, and vibrancy of the U.S. derivatives markets,” which includes financial products like swaps, futures, collateralized debt obligations, and options. The name derivative comes from the fact that the products are derived from the value of underlying financial assets such  as commodities, stocks, and currencies.
 
A challenge for the CFTC in regulating prediction markets is that unlike the common financial assets listed above that tend to be relatively finite in number, the financial assets underlying prediction markets (bets) are constantly changing, as are the individuals who can potentially influence their values. As such, the CFTC necessarily delegates some of the regulation to the prediction markets themselves, or as it calls them, the “designated contract markets” (DCM). Two of the CFTC’s core principles highlight this delegation:

• “a DCM is responsible for preventing market manipulation, price distortions, and disruptions in the settlement of contracts.”
• “DCMs must establish and enforce rules to protect markets and participants from abusive practices, and promote fair and equitable trading.

 
This delegation suggests that regulation of prediction markets is not nearly as tight as that of other derivatives or financial products, which seems to increase the potential for abuse, as the next bullet describes. 
 
Risk of manipulation: Per its website, the SEC is intent on stopping the buying and selling of securities based on material, nonpublic information:
 
“Because insider trading undermines investor confidence in the fairness and integrity of the securities markets, the SEC has treated the detection and prosecution of insider trading violations as one of its enforcement priorities.”
 
Fair treatment of all buyers and sellers is essential for the effective functioning of any market, whether it’s for physical goods or financial products. As the SEC can attest, even when you know organizations’ executives and can track their trading, it’s not easy to maintain market integrity. Fair treatment of all participants is even more challenging in prediction markets where information flow and influence of outcomes is often more obscured.

For instance, one currently trending bet on Polymarket poses a question about a signature esports competition: ‘What will be said at the BLAST Premier Open Rotterdam 2026?’

I’m not familiar with the event, but as it appears 11 cast members will be involved in broadcasting the competition for BLAST.tv, it’s easily imaginable how someone remotely connected to the broadcast could either find out what will be said or influence the dialogue, then either place bets for themselves or advise others’ betting, all while avoiding detection.
 
Betting based on inside information for esports commentary is one thing; betting involving covert military operations is another. “Hours before the U.S. military captured Venezuela’s president, Nicolás Maduro, an anonymous user on Polymarket bet tens of thousands of dollars that Mr. Maduro would fall.” The bettor, who some believe may have been a government official with inside information about the operation, pocketed $410,000.
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Can you guess the percentage of people who have placed a sports bet within the past year? Hint, it’s roughly the same number as those who have gotten a tattoo, run a 5K race, or been in a wedding party. The answer, one in five, may seem high, but the gaming industry is growing by leaps and bounds, which calls for a timeout to ask: Should we be all-in on sports betting?

It’s the eve of March Madness, the NCAA Division I basketball tournament that’s one of the biggest sports seasons of the year and one of the biggest sports betting opportunities. Estimates are that $3.1 billion was legally wagered on March Madness 2025 – a little less than the $3.3 billion GPD of Belize. This year’s betting will likely easily eclipse 2025’s.
 
Taking a broader view, in 2017, legal sports betting in the U.S. was mainly confined to Nevada and totaled about $4.27 billion. The following year the U.S. Supreme Court struck down a federal law that prohibited sports gambling, which “opened the floodgates to [the] legalized sports-betting industry” and “paved the way for meteoric growth in legal sports betting.”
 
With 13 states allowing active sports betting in 2019, the total handle, or amount wagered, rose to $13 billion. By the end of 2021, the number of legal states had doubled to 26 and wagers had grown to $58 billion. In 2025, the handle hit $165 billion – larger than the $154.5 billion GDP of Kuwait.
 
Of course, the legalization of sports betting has been its main enabler, but what other factors have contributed to its extremely fast ascent?  A few key influences have been:

• Online and Mobile Options: The vast majority of sports bets are placed online (~95%). Apps on mobile devices, such as those of BetMGM, Caesars Sportsbook, and DraftKings, have made it very easy for people to “bet anywhere, anytime, [as] these apps blur the boundaries of when and where gambling happens.”

• Partnerships with Teams: Most major professional sports teams have signed deals with betting companies. A few specific examples are: New York Yankees and San Antonio Spurs – Bally Bet Sports & Casino;  Philadelphia 76ers and  Pittsburgh Steelers – BetMGM; New York Mets and Philadelphia Eagles – Caesars Sportsbook; Detroit Pistons and Chicago Bulls – BetRivers.
• Advertising: Promotions for these betting companies and others are ubiquitous. The firms frequently air commercials during professional sports contests. Viewers also often can spot signage for the companies inside the stadiums and along the courts where athletes compete.
• Endorsers: As in many product categories, celebrity endorsements seem to be very effective for betting companies, hence firms such as BetMGM partner with A-list actors like Jamie Foxx and Jon Hamm. Professional sports leagues generally prohibit their current players from endorsing gaming apps; however, one notable exception is the NBA, which has allowed LeBron James to serve as a spokesperson for DraftKings. Otherwise, betting firms have been very successful attracting many of professional sports’ top retired athletes including, Shaquille O’Neal, Jerry Rice, Wayne Gretzky, Mike Tyson, Peyton Manning, Connor McDavid, Barry Sanders, David Ortiz, Marshawn Lynch, Drew Brees, Charles Barkley, and many more.
• Variety of Bets: The sheer number of wagering options also makes it likely that a person will find a bet that beckons them. Betting on just the outcome of a game now seems passé thanks to sports betting apps that allow users to make microbets, or bets on “events that are resolved quickly” like how far an MLB player will hit a homerun or whether two NBA teams’ halftime scores will total more than 110 points.

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However, what weighs heaviest on Mark’s mind are the many people who unwittingly fall into gambling addiction, “throwing money on longshots” because they believe “a huge win is coming.” Mark maintains that even those who set limits on how much they’ll wager can easily succumb to the illusion that they’ll win back money lost. This common rationalization, he contends, is truly “dangerous to people’s lives.”
 
Jed Colyer, a junior accounting major, shares many of Mark’s concerns about the nature of sports betting, agreeing that it’s empty promise of “more, more, more” encourages addiction, as bettors lose their sense of how much is enough.
 
Colyer also cares about what  motivates people to gamble, which he views through the lens of his Christian faith and Bible passages such as 1 Timothy 6:9-10 and Matthew 25:14-30. While he believes money is an important God-given tool that serves useful purposes, he sees gambling  as a “misuse of the tool,” stemming from a fixation on wealth and being rich – preoccupations that ultimately lead to personal “ruin and destruction.”
 
Admittedly, Mark and Colyer represent one side of the debate about sports betting. Also in their class were several students, mainly men, who offered rational arguments in support of gambling, such as:

• Personal choice for entertainment
• Ability to bet responsibly
• Positive economic impact

 
Sports betting is already very widespread and growing rapidly, which means profound impact on even larger numbers of people. For these reasons, it’s important to invite the perspectives of individuals living at the frontlines of the trend – young men, particularly ones like Mark and Colyer who have shown the ability to step back from the legal context, marketing messages, and social pressure and apply moral reasoning.
 
What does it mean to “gamble responsibly” – an admonishment that many betting companies make but do little to unpack?
 
Likewise, what does the need for this upfront warning suggest about the activity and the probability that users will suffer financially, socially, or in other ways? Snack food can become a vice for some, but potato chip marketers don’t need to warn us to “eat responsibly.”
 
Perhaps I’ll be persuaded by other arguments in the future, but for now the risks of sports betting to individuals, organizations, and society seem to outweigh entertainment and economic rewards. To encourage gambling on games is a bet on Single-Minded Marketing.
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February 14th has long reminded people of the affection they feel for the most important others in their lives: spouses, fiancés, boyfriends, girlfriends. Thanks to AI, “significant other” can now mean other than human, but even if people desire human-like intimacy from artificial intelligence, should organizations offer it?
 
A colleague recently shared an article with me and several others that she found disheartening: Married women in China who find their real-life relationship with their spouse lacking are spending the equivalent of thousands of U.S. dollars a year on AI boyfriends. The digital rendezvous often occur in otome games  like Love and Romance, Light and Night, and Beyond the World.
 
I wasn’t entirely surprised by the article, as the issue has been on my radar, along with other AI-related concerns, for about two years, and over past several months, I’ve been tracking related stories such as these:

• The increase in AI relationships could lead to a rise in divorces.
• People are having “children” with chatbot partners.
•  Parents are turning to chatbots to mind their young children.
• Adult children are leaning on AI to substitute for their own communication with aging parents.

 
Still, in doing research for this piece, I was stunned by some of the usage statistics:

• Since 2014, more than 660 million residents of China have used Xiaoice, the world’s “most popular chatbot,” which Microsoft “uniquely designed as an AI companion with an emotional connection to satisfy the human need for communication, affection, and social belonging.”
• Nearly 20% high schoolers report that they or someone they know has had a romantic relationship with AI.
• Nearly 20% U.S. adults have used AI to simulate a romantic partner, and within young adults age 18-30, 31% of men and 23% of women have used AI in this way.
• Since its launch in 2017, the AI companion Replika has had 30 million users, while the similar product Character AI has 20 million active users. Over half of Character AI’s users are age 18 to 24, and around a fourth are 25 to 34.

 
Writing for Greater Good Magazine, Sahar Habib Ghazi says statistics like these suggest that “AI-human romance isn’t niche--it’s mainstream, especially among young adults.”
 
Since there have been people, there have been interpersonal relationships. Of course, some reasons for those relationships have been very practical, e.g., procreation, protection; however, humans also have simply sought each other’s company and companionship.
 
In more recent times, researchers have empirically studied humans’ sociological and psychological behaviors and developed theories to describe them. Maslow’s classic Hierarchy of Needs suggests that the desire for belonging is among the most basic of all human desires, preempted only by physiological needs (e.g., air, food, water) and the need for safety.
 
Indeed, most people want to be around other people, if not all or most of the time, some of the time. In fact, it’s so unusual for anyone to spurn social interaction entirely that the rare individual who does receives the label hermit or recluse.
 
With technology, even a recluse can get a ‘social fix’ through one-way interactions, such as by following influencers or watching TV shows with favorite actors, or regularly listening to a particular podcast. In these cases, the followers/viewers/listeners don’t really know the ‘celebrity others,’ yet the former often feel a sense of connection to the latter.
 
There also are ways to fulfill social needs without any people. Perhaps the most popular substitutes are pets, which many people regularly enjoy. Harvard Health reports that “pets can provide their owners with more than companionship,” and Psychology Today suggests that pets can be “friends.”
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Similarly, farmers sometimes bond with the livestock for which they care, e.g., a lead cow. Some people even gain a sense of social interaction by nurturing immobile living beings, i.e., plants, which can help them feel less lonely.
 
Together these examples form a continuum on which people might find satisfaction of social needs, ranging from extensive human contact, to relatively little, to none.
 
There also are countless cases in which people use other things not to meet social needs but to shift their focus from them, e.g., work, hobbies, media. For instance, someone might immerse themself in their job to help take their mind off feelings of loneliness.
 
Given the many ways of meeting and masking social needs currently and historically, is there any reason not to accept AI as a relationship alternative? After all, it can produce more human-like interaction than virtually any of the secondary options. Some would even say better-than-human.
 
There are advantages and disadvantages of AI relationships. The following two lists are not exhaustive but seem to be some of the main pros and cons.
 
Pros:

• Readily available: No person is accessible all the time to talk, listen, etc. Chatbots are available 24/7. They’re also extremely fast, and they don’t get tired.


• Nonjudgmental: For many people, it’s hard to simply listen to others’ disclosures without sharing their opinions of them. Chatbots typically refrain from such appraisals, which can be especially helpful for people who experience social anxiety or mental health challenges.


• Very smart: Of course, AI makes mistakes, but the vast repository of information it can draw from and assimilate means it doesn’t suffer from ignorance and inexperience to the extent that many people do. What's more, AI’s ability to sensitively apply its expansive knowledge base means it can seem “more ‘human’ than many people.”


• Adaptable: As people, we can adapt to others’ needs but it’s hard because as we do, we often need to stretch ourselves or give up our own needs. AI doesn’t have those limitations; it can be 100% accommodating.

 
Cons:

• Dependency: Given that AI is so readily available, accommodating, and reluctant to ever say “no,” there’s risk of dependency and even addiction. In fact, some humans who have found themselves spending far too much time with AI companions have turned to the app I Am Sober to help break their obsessive compulsive behavior.

 

• Data vulnerability: There’s risk involved with any of the information we share on websites or enter into apps, but the risk is greatly magnified when considering the very sensitive information individuals are likely to reveal to their AI companions, whose discretion is only as great as that of the companies behind them.


• Manipulation: Along with potential misuse of users’ data is the potential for users to be unknowingly manipulated into buying products that a chatbot’s parent company wants to promote. It’s hard to imagine that companies won’t seek to monetize those intimate relationships – something that would almost never happen with a human partner.

 

• Unrealistic expectations: In keeping with the previous point, AI’s varied advantages over people can cause its users to show little tolerance for human imperfections. Instead, they expect the people in their lives to offer support at an AI level.

 

• Not true love: Although those who use AI companions may experience a “form of ‘love,’” it’s not likely real love given that genuine love involves the desire to nurture another’s well-being, and chatbots “don’t have well-being to nurture.” By the same token, AI can “replicate” some dimensions of love, but what it’s offering is just that – imitation, not genuine love.

 

• Mistakes: As time goes on, AI seems to be making fewer mistakes and having less frequent hallucinations; however, the nature of the mistakes have sometimes been disastrous, such as when AI has offered to serve as a suicide coach and write troubled teens’ farewell letters.

 
Another possible con I was going to list for AI companions was the inability for physical expression, e.g., a touch, a hug, a kiss. However, it probably shouldn’t be surprising that some technically savvy companies have integrated AI into sex dolls to create life-like sex robots.
 
Also, while writing this piece, I learned of a platform called Moltbook, a website where AI agents interact with each other. Humans can only observe; they cannot enter the conversations. The dialogue is both interesting and disconcerting. It portends a time when AI agents might go rogue, working against their human principals, not for them. If this prediction is in any way a real possibility, engaging a bot as a companion seems even more precarious.
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​Often lost in the news of who is or isn’t implicated in the Epstein files is the grievous nature of the acts against fellow human beings. Sex trafficking is an age-old issue, which makes it worth considering why it's wrong and why it still occurs but even more important, learning what some courageously caring organizations are doing to stop it.
 
The U.S. Department of Justice’s Office for Victims of Crime identifies sex trafficking as “the recruitment, harboring, transportation, provision, or obtaining of a person for the purposes of a commercial sex act in which the commercial sex act is induced by force, fraud, or coercion or in which the person induced is under 18.”
 
This definition points to the fact that not all human trafficking is sex trafficking. Besides sexual acts, people also are sometimes exploited for their labor in industries such as “housekeeping, childcare, construction, farming, and the food service.”
 
Using fraud, force, or coercion to get a person to do something they wouldn’t otherwise choose is never a good thing, but the exploitation is especially heinous when it involves the most intimate parts of individuals’ bodies and emotional beings. In other words, in the realm of moral depravity, sex trafficking has few equals.
 
Given its deplorable nature, why does sex trafficking occur? There seem to be three main structural reasons:
 

1. A market for commercial sex: As the sayings go, prostitution is the oldest profession and sex sells. People have been willing to pay for sex for millennia, which has allowed individuals to offer themselves for a fee.
2. Opportunistic others: Seeing the potential to expand the market, unprincipled people have long stepped in to help broker the sales of sex, bringing together buyers and sellers for a fee. In the process, traffickers have often broken laws and taken advantage of the service providers.
3. Vulnerable people: It’s unlikely that prostitution is an aspirational profession for anyone. Instead, most who make money selling themselves would much rather be doing something else, but they stay in the trade either because they’re kept from leaving or because they have no good alternatives.

 
According to Elijah Rising, a Houston-based organization aimed at ending sex trafficking in the city, human trafficking is “the fastest growing criminal enterprise,” one worth $236 billion, from which sex trafficking produces 73% of the profits. Women and girls are victims in 78% of sex trafficking cases, versus 22% for men and boys.
 
When the victim is a minor, the criteria of force, fraud, or coercion need not apply, as children’s naivety means that they don’t necessarily know what normal adult behavior is, so they may not even realize they’re being exploited. Often these young victims are still going to school and living at home while being trafficked by parents or other family members.
 
So, although Epstein’s extreme exploitation deserves the infamy it’s gained, it can be misleading to think that all sex traffickers look like him. Instead, according to the U.S. Department of Homeland Security and in keeping with the previous paragraph, “Traffickers are men and women of all ages. They can be relatives, romantic partners, or close family friends” as well as individuals “behind an employment ad or a new friend on social media or online gaming.”
 
Those managing larger scale sex trafficking often operate out of apartment complexes, bars, hotels, massage parlors, and truck stops. Notwithstanding all the differences, the common denominator among traffickers is their desire to “profit at the expense of others.”
 
Although the breadth and depth of sex trafficking is daunting, thankfully there are organizations that embrace the challenge through unique missions and special strategies aimed at combatting the industry, or demarketing the selling of sex.
 
There certainly are others, but here are four best practices from four exemplary organizations:
 
1. Help people see the problem: It’s hard to motivate individuals toward a solution if they don’t recognize the problem. Mentioned earlier, Elijah Rising helps potential partners gain awareness of the gravity of sex trafficking in Houston by taking them on discreet van tours of where the illicit activities occur, while sharing an educational video featuring survivors, experts, and others.
 
Since 2011, more than 11,000 people have taken the tour, which has helped a variety of organizations, including law enforcement agencies, identify signs of sex trafficking.
 

Throughout human history, “seeing is believing” likely has been central to individuals’ interpretation of truth. We’re more apt to believe what we can see with our own eyes, but that trust comes with a caution: “Don’t believe everything you see.” Thanks to the realism of AI, that caveat seems to be evolving into a troubling new norm: “Don’t believe anything you see.”
 
A few months ago, a cringingly cute TikTok video went viral. In what seemed to be low resolution surveillance video from someone’s backyard, a collection of fun-loving bunnies playfully bounced on a large trampoline. Few things could be more wholesomely entertaining . . . or contrived.

The problem was that the rabbit roundup never really happened. Especially observant viewers recognized some non-lifelike video peculiarities, e.g., a pair of ears protruding from one bunny’s backside and another rabbit disappearing mid bounce. No, the video wasn’t real, rather it was the product of Google’s Veo 3, a realistic, AI-driven video generator.
 
Most of us are familiar with deepfake videos, which have become more and more ubiquitous on social media. Based on my viewing habits, YouTube sends me a steady stream of short videos featuring animals that include crocodiles, snakes, gorillas, and sharks, which I find fascinating. Some clips are real, but occasionally interspersed are ones that are too far-fetched to be actual animals, and, like the bunnies, there are sometimes video abnormalities that point to fabrication.
 
For me, these animal videos are just entertainment, which may make the deceptive ones less problematic. In fact, for the purpose of entertainment, people often want to be deceived – every time we go to a movie, play, or musical we pay to watch actors pretend to be people they’re not, in situations and settings that aren’t real. Most consider those kinds of mutual deceits morally acceptable.
 
However, to be “mutual,” the deceit should involve informed consent, meaning that the viewer A) knows what they’re seeing is imaginary, and B) they agree to watch it. For me, I believe YouTube’s animal videos uphold #2 but not #1, i.e., I certainly agree to watch them, but  I don’t feel I always know what’s true.
 
AI is an incredible tool with an ever-growing assortment of applications for individuals and organizations, including the creation of visuals like complex graphics, realistic photos, and convincing videos.
 
With any tool, especially one as powerful as AI, comes the duty to wield it responsibly. While many use AI with discernment others don’t. Individuals in the latter group may have one or more of the following motivations, which range from relatively benign to troublingly malicious:

• Experimenting with the new tech
• Looking to gain likes and shares
• Charting a quick and path to monetization
• Seeking to deceive and mislead

 
Unfortunately, the latter categories seem to be producing new examples continually. For instance, deepfake investment schemes, which often combine forged images, voice, and video, already have become so pervasive that many prominent organizations and institutions have issued warnings and guidance including JP Morgan, the Securities and Exchange Commission, and the state of New York.
 
As troubling as these carefully orchestrated schemes of the criminally minded are, the democratized use of deception by ordinary people in their daily lives is just as disturbing. One such broad-based indiscretion is employees’ use of AI to create fake receipts for meals or entire business trips they never experienced but that they submit for reimbursement.
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Open AI’s recent announcement that it would free ChatGPT to engage in erotica sparked backlash and prompted CEO Sam Altman to defend the decision: “we are not the elected moral police of the world.” At first glance, it’s difficult to deny the AI visionary’s disclaimer, but his statement raises important questions: Should there be people appointed to monitor AI morality and if so, who?
 
In an October 14 post on X, Altman shared, “In December, as we roll out age-gating more fully and as part of our ‘treat adult users like adults’ principle, we will allow even more, like erotica for verified adults.”
 
The CEO then defended the firm’s controversial new initiative with a follow-up X post on October 15: “But we are not the elected moral police of the world. In the same way that society differentiates other appropriate boundaries (R-rated movies, for example) we want to do a similar thing here.”
 
It’s doubtful many people have ever used the term “moral police,” or something similar, in a positive way. Instead, Altman’s implication seems akin to the way “police” is used pejoratively in this office scenario:

• Joe: “Bob, are you going to the bathroom again?!”
• Bob: “Who are you, the bathroom police?”

 
On one hand, Altman’s defense is reasonable. Who can possibly judge the ethical actions of the planet’s 8 billion-plus residents? Besides being logistically impossible, some may say it’s philosophically undesirable, as many different worldviews and multitudes of corresponding moral standards drive individuals’ actions.
 
Furthermore, as two research colleagues and I found in a recent study we conducted about marketing ethics, people’s opinions of what constitutes sex-related indecency tend to vary more than perspectives on issues involving other values like fairness and honesty.
 
It’s also easy to understand the financial incentives Open AI may gain by enabling more adult content. The adage “sex sells” rings true even when the ‘personal interaction’ for sale doesn’t involve a real person.
 
In a BBC interview, Parmy Olson of Bloomberg Opinion reported that about 30% of prompts typed into AI assistants were of a romantic or sexual nature. She also stated that chatbot companies that restrict adult content “lose millions of users.”
 
Regardless whether the percentage of X-rated interactions is 5% or 35% of total chatbot use, it’s likely a multibillion-dollar market opportunity for OpenAI and a very significant amount of revenue for any company to reject, especially one that’s not yet profitable.
 
In 2024, OpenAI had about $5 billion in losses on $3.7 billion in revenue. The firm’s revenues are expected to reach $12.7 billion in 2025, but OpenAI isn’t projected to make money until it reaches revenues of $125 billion in 2029.
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Despite these logistical and financial reasons for refraining to act as “moral police,” Altman’s hands-off approach to ethics is alarming. ChatGPT accounts for 80.92% of chatbot use worldwide. It’s very troubling that a world leader in artificial intelligence seems to decline ethical accountability for the transformational technology.
 
Again, it’s true that opinions about decency vary greatly, especially when it comes to sexual liberties; however, the specific issue here isn’t the most important point. If OpenAI doesn’t want to act as “moral police” on this issue, can we expect it to accept moral responsibility for any ethical issue involving AI?
 
Perhaps Altman believes that AI will handle moral issues involving AI. That belief seemed wishful to me eight years ago; now it appears increasingly naïve.
 
In September 2017, I wrote an article for Business Insider in which I posed for the first time the question, “Can machines can learn to be moral?” It was five years before ChatGPT’s public release, so the essay was largely speculative, based on the little experience most of us had with AI at the time. Still, it was hard to imagine how an algorithm could make subjective decisions about what’s decent, fair, honest, respectful or responsible.
 
Over the years since, I’ve increasingly used AI, including chatbots, as many people have. In a Mindful Marketing article in May of 2024, I proposed that “Questions are the Key to AI and Ethics,” and ultimately concluded that we can’t rely on AI for moral accountability, rather it’s up to people to hit the brakes, or press pause, when AI-related ethical issues arise.
 
Even as AI grows more adept at completing nonmoral tasks (ones not involving ethical issues), there are still strong signs moral accountability must come from outside algorithms, for example:

• Just a few days ago, a deepfake of Nvidia CEO Jensen Huang promoting a cryptocurrency scam performed better than the firm’s real GTC 2025 keynote, fooling tens of thousands of viewers.
• Chatbots have been implicated in the deaths of teenagers who have taken their own lives, as AI has offered to write farewell notes and serve as a “suicide coach.”
• Nudify apps leverage AI to digitally remove clothing in photos of unsuspecting individuals. The apps users, who have included middle schoolers, often share the lewd results with others, causing great emotional and social pain for the victims.

 
If AI has a sense of right and wrong, why hasn’t it stopped these acts, which most reasonable people would call ‘reprehensible’? What’s worse, AI not only didn’t pump the brakes, or hit pause, it’s what enabled these actions to occur; it made them possible. Examples like these have led me to conclude:
 
If left unchecked by humans, AI will continue to enable unethical behavior.
 
So, opposite Altman’s abdication of ethical accountability, we do need “moral police,” badly. The question, then, is who should they be?
 
I asked a similar question in an April 2025 article, “Who Will be the Adult in the Room with AI?” and suggested several sets of complementary accountability partners: legal systems, industry associations, organizations, and individuals.
 
In a recent talk I’ve given titled, “Exercising Our Moral Leadership,” I’ve continued to press the theme of broad-based moral responsibility, arguing that each of us needs to lean on others for support in our ethical decision making, ranging from clarification of factual information to serving as moral sounding boards and accountability partners.
 
Ultimately, I believe ethics is a team sport – every stakeholder employing thoughtful analysis and engaging in constructive conversations. Still, the idea that ‘ethics is everyone’s job’ can seem like a platitude if people don’t genuinely embrace moral responsibility and seriously prepare themselves for ethical decision-making, which involves intentional actions like:

• Adopting a moral anchor, or a set of moral standards, such as the Golden Rule or specific moral principles like decency, fairness, honesty, respect, and responsibility.
• Thoroughly knowing one’s field because making ethical decisions also demands firm grasps of objective, factual information
• Looking beyond immediate circumstances to consider long-term consequences and impacts on secondary stakeholders
• Questioning the consensus because task definitions and time pressures sometimes lead teams to choose what can be done versus what should be done

 
Artificial intelligence appears to be as transformative a technology as our world has ever seen. Most of us have experienced firsthand how it can help us work more efficiently and effectively. We’ve also collectively witnessed how, if left unchecked, it can enable actions that are morally suspect.
 
We do need moral police for AI. You and I should be part of that patrol. Leading the force should be those who are most knowledgeable about AI – police chiefs at Alphabet, Microsoft, Nvidia, and  . . . OpenAI.
 
It’s understandable that Altman wants to respect personal liberties and make Open AI profitable. However, allowing AI to police itself is asking for moral anarchy by way of Single-Minded Marketing.
​

How is it possible to improve ethics in a field that seems beset by moral issues? What about actively engaging emerging marketers on topics that matter to them and using competition to provide positive, memorable experiences they can revisit when encountering moral issues in their future careers? That was the goal of the inaugural Mindful Marketing Ethics Challenge.
 
Competition is captivating. It’s a main reason sports are so popular to play and to watch. Only occasionally does academics include contests (e.g., spelling bees, quiz bowls). Competition involving ethics seems almost like a contradiction, but why not an ethics competition?
 
Since creating Mindful Marketing 11 years ago, I’ve envisioned different initiatives that might improve moral decision-making in the field. One of those recently came to be with the publishing of Mindful Marketing: Business Ethics that Stick. Another dream has been to see a student-based ethics competition.
 
For many years, I made the long drive to Western Pennsylvania with students in our capstone marketing course to participate in the American Marketing Association (AMA) Pittsburgh Chapter’s marketing plan competition. Although it was big commitment in many ways, it was a great learning opportunity and very helpful to see how our marketing program’s work compared to some of the best in the state. Moreover, it was exciting to compete.
 
With the creation of AMA Central PA three years ago, the dream of an ethics competition became more realistic; however, to make it happen, it took the support of a group of like-minded educators and marketing practitioners – fellow AMA Central PA leaders who saw the value in ethics for emerging marketers and who backed the proposal not just verbally but by championing the competition at their own universities and elsewhere. Thanks to that collective commitment to students and to moral progress, the Mindful Marketing Ethics Challenge was born.
 
Two months before students returned to campuses for the fall semester, I drafted a short ethics-focused case about one of the field’s biggest and most controversial promotional trends: influencer marketing. As August began, I began emailing faculty at other schools, inviting them to share with their students the case and the unique competition benefits described in a specially designed promotional flyer:

• Team prizes: 1st place $500; 2nd place $300; 3rd place $200
• Presentation opportunities
• Food and networking

 
Ten teams submitted 1,500-word written responses to the influencer marketing case, which described a pitch that a hypothetical marketing firm, Impact, made to Widerquest, a fictitious maker of outdoor sporting equipment and apparel that sought to use influencers responsibly.

​Although Impact’s proposal was good in many ways, it included moral concerns such as transparency about influencer compensation, respect for competitors, physical stereotypes, and product embellishment. A panel of six accomplished marketing practitioners evaluated the responses in a double-blind review process.
 
On October 1, eight teams from four different universities participated in the finale at Messiah University, where each team had five minutes to summarize its recommendations for ensuring that the influencer marketing in the case was both effective and ethical. The judges evaluated the presentations, and the combined written and oral scores were tallied to determine the top three place winners, whose school identities were then revealed:

• 1st place – Susquehanna University
• 2nd place – Shippensburg University
• 3rd place – Susquehanna University

 
Those were the logistics and timeline of the competition, which were important, but what did students learn about marketing ethics that they might carry into their future careers?
 
Teams’ written and oral responses to the influencer marketing case were very insightful. Some identified implications I hadn’t considered. The ethics case and the first-place team’s written response are available on the Mindful Marketing Ethics Challenge webpage. Here are several highlights of the winning team’s analysis:
 

• “Impact’s expectations raise serious ethical concerns that conflict with Wilderquest’s values. By requiring embellishment of features and forbidding negative feedback, the proposal undermines honesty and risks deceiving consumers.”

 

• “Encouraging influencers to disparage competitors manipulates buyer choice and fails to treat other brands fairly.”

 

• “Respect is also compromised by messaging that portrays consumers’ lives as ‘lacking without Wilderquest,’ exploiting insecurities rather than affirming worth.”

 

• “Responsibility is neglected by allowing influencers to promote products they have not used, stripping audiences of genuine evaluations and reviews.”

 

• “Encouraging technology to enhance photos or videos without disclosure risks misleading consumers. Collectively, these practices jeopardize consumer trust and contradict Wilderquest’s commitment to authenticity.”

 

 
So, in many ways a Barbie with type 1 diabetes is just another iteration of differently enabled dolls for Mattel, but what do these dolls mean for our society? Is their net impact positive or negative?
 
Given that neither dolls nor diseases are in my wheelhouse, I reached out to several people who could answer these questions more authoritatively: Dr. Kevin Barnes – a retired pediatrician, Dr. Sarah Jones – a nurse educator, and Meredith Schorner – an RN and school nurse.
 
Barnes said he appreciates that Mattel spent more than a year working with a diabetes organization in order to ensure the doll’s accuracy, and he believes that for some of the more than 200,000 children in the U.S. with type 1 diabetes mellitus, it could be therapeutic to play with a doll that experiences the same things they do.
 
However, he also expresses some valid concerns, for instance:

• Where do we draw the line on dolls representing childhood diseases, particularly ones that are somewhat “invisible” to others even though they greatly impact daily life, e.g., celiac disease, asthma?
• Given Barbie’s history of more often emphasizing style over substance, how much of Mattel’s motivation in making the doll is the positive publicity it generates?

 
Jones believes that the type 1 diabetes Barbie can potentially do much good by helping to make the condition more mainstream, or acceptable, which among other things, could encourage proper self-management. That care is critical given that the disease demands intensive insulin therapy with either multiple daily injections or an insulin pump.
 
With confirmation from a colleague who regularly cares for diabetes patients, Jones states that Barbie’s self-monitoring insulin pump is the standard for treatment, which Jones sees as positive overall. However, like Barnes, she also raises some important questions about the doll:

• Does its female Caucasian identity fall short in representing the disease’s well-documented impact across gender and racial lines?
• Could Barbie’s continuous glucose monitoring device and insulin pump create stigma for children whose insurance will not cover the advanced technology and for families that cannot afford it so they must rely on traditional injections?
• Could the doll make it more socially acceptable to have type 1 diabetes but not type 2? This may be an increasing concern given that incidences of type 2 diabetes, which is often associated with obesity, are on the rise among children.

 
Not surprising, Jone’s differentiation of the two sometimes conflated conditions coincides with that of the University of Virginia Health System, which states that “Unlike type 1, type 2 diabetes is not an autoimmune disorder,” rather it “occurs mostly in people over 45, or in younger people with obesity or genetic reasons.”
 
Besides her role as a school nurse, Schorner is a parent of young girls who believes the diabetic Barbie will be “an exciting new toy for many.” More than just a plaything for those who have type 1 diabetes, she expects the doll will raise questions for nondiabetic children and help them better understand the devices they see on some of their peers. She elaborates:
 
“Children need to know that their peers with type 1 diabetes (T1D) didn't do anything ‘wrong’ to become diabetic – they didn't eat too much sugar, and it certainly doesn't have anything to do with their weight. T1D is increasing in prevalence, and diabetic children need lots of support at home and at school. They need peers that can be not just understanding but also helpful to them in managing their diabetes.”
 
“Under the guidance of a knowledgeable adult, engaging in play with this doll may help young children develop a basic understanding of CGM readings, carbohydrate counting, and insulin requirements. It could also help children to know what to do if they encounter a person experiencing a diabetic emergency.”
 
Schorner has firsthand experience caring for children with type 1 diabetes. In one case, the child’s family chose finger sticks and insulin injections, at least in part because they were concerned that a more socially visible glucose monitor might label their child as a diabetic.
 ​

When was the last time you spoke with your mom or dad? For adult children with their own families and demanding jobs, time between conversations with their aging parents can quickly become days or weeks. At a time when there seems to be a technological solution for every problem, it’s not surprising that there’s an app for that, but do we really want our moms and dads chatting with AI instead of with us?
 
InTouch is an internet-based subscription service that allows customers to enlist Mary, a pleasant and engaging AI agent, to have phone conversations with their aging parents. AI Touch s.r.o., a Czech Republic company that appears to own InTouch, offers several sample conversations on its website.
 
The site also provides some compelling rationale for the service, such as:

• Stimulating the loved ones’ minds
• Supporting their emotional well-being
• Strengthening family connections

 
The company adds, “We go beyond small talk, discussing family, hobbies, memories, and even brain teasers to keep [the older parents’] mind active and spirits lifted.” The firm also promises to provide a short summary of each call so the subscriber can know how their parent is doing, or if they didn’t answer the phone.
 
Ultimately, inTouch aims to address a customer pain point that’s increasingly common for a particular generation of people who often must care for two sets of loved ones simultaneously: their own children and their aging parents. The caught-in-the-middle phenomenon has spawned the fitting term "the sandwich generation."
 
The age cohort that’s currently most likely to find itself in the middle is Generation X, whose members, born between 1965 and 1980, are 45 to 60 years old. Studies have shown that the pull of two-way caregiving places unique strain on Gen X’s time, as well as on their financial and mental health.
 
I am one of those Gen Xs who recently lived the sandwich experience. My father passed away less than four years ago, and my mother a little more than a year. Given a variety of physical challenges as well as worsening dementia, my mom required a particularly great amount of care in the years leading up to her passing.
 
At the same time, my wife and I were not yet empty nesters, and we both had demanding full-time jobs. Often it was difficult to balance the competing demands placed upon us.
 
Although that time was not long ago, AI agent-based services like InTouch didn’t exist then, or at least I didn’t know about them. If InTouch has been available to me, should I have used it to interact with my mother?
 
As just mentioned, I have firsthand experience similar to that of inTouch’s target market, which helps me envision the service’s pros and cons. However, I’m not an expert on older adults or the multifaceted social and psychological dynamics surrounding the aging process, so I reached out to someone who is.
 
Dr. Raeann Hamon is Distinguished Professor of Family Science and Gerontology at Messiah University. Her meaningful research, impactful writing, and influential leadership over several decades have gained her international renown. Moreover, she’s a thoughtful and compassionate person who wants the best for others.
 
I shared inTouch’s website with Dr. Hamon and asked if she would offer her perspective on the service. She graciously agreed.