Is AI Better Than Nothing? In Mental Health, Probably Yes

 In medical trials, "termination for benefit" allows a trial to be stopped early when the evidence of a drug’s effectiveness is so strong that it becomes unethical to continue withholding the treatment. Although this is rare—only 1.7% of trials are stopped for this reason—it ensures that life-saving treatments reach patients as quickly as possible.

This concept can be applied to the use of AI in addressing the shortage of counsellors and therapists for the nation's student population, which is facing a mental health crisis. Some are quick to reject the idea of AI-based therapy, upset by the notion of students talking to a machine instead of a human counselor. However, this reaction often lacks a careful weighing of the benefits. AI assistance, while not perfect, could provide much-needed support where human resources are stretched too thin.

Yes, there have been concerns, such as the story of Tessa, a bot that reportedly gave inappropriate advice to a user with an eating disorder. But focusing on isolated cases does not take into account the larger picture. Human therapists also make mistakes, and we do not ban the profession for it. AI, which is available around the clock and costs next to nothing, should not be held to a higher standard than human counselors. The real comparison is not between AI and human therapists, but between AI and the complete lack of human support that many students currently face. Let's also not forget that in some cultures, going to a mental health professional is still a taboo. Going to an AI is a private matter. 

I have personally tested ChatGPT several times, simulating various student issues, and found it consistently careful, thoughtful, and sensible in its responses. Instead of panicking over astronomically rare errors, I encourage more people to conduct their own tests and share any issues they discover publicly. This would provide a more balanced understanding of the strengths and weaknesses of AI therapy, helping us improve it over time. There is no equivalent of a true clinical trial, so some citizen testing would have to be done. 

The situation is urgent, and waiting for AI to be perfect before deploying it is not much of an option. Like early termination in medical trials, deploying AI therapy now could be the ethical response to a growing crisis. While not a replacement for human counselors, AI can serve as a valuable resource in filling the gaps that the current mental health system leaves wide open.

Where is the work? AI and Creativity

For ages, we have blurred the lines between ideation and execution, treating them as inseparable parts of creativity. Craftsmanship was tightly bound to originality. Think of Michelangelo working on the Sistine Chapel, a project that spanned nearly a decade. Where does his genius truly lie? In envisioning those profound images, or in the labor of painting them? What, exactly, is the essence of the work?

The rise of AI forces us to untangle these ideas and reconsider what it means to produce "human" work. Take a recent story I heard from from the audience of one of my talks: a person described how he fed an AI every detail about a retiring colleague, and the AI generated a speech so moving that it brought the retiree to tears. But the retiree, upon learning the speech's origin, was dumbfounded.

What is interesting is not the retiree’s reaction, but the storyteller's own oversight. He failed to see his own critical role in the process. By gathering the details, curating moments that best captured the retiree’s essence, he performed the most human part of the creative act. He mistook the act of turning those ideas into words as the creative work, but that is not the case.

AI, ironically, is pushing us to be more human, not more like machines. It is forcing us to recognize that our true contribution lies in the ability to think, to create, and to feel. As AI takes over the mechanical aspects of tasks we once considered integral to creativity—whether that is writing, painting, or coding—we are left with the more uniquely human roles: original thinking and emotional depth.

This shift reshapes our understanding of creativity and work. It shows that human value does not lie in production—the technical aspect of turning an idea into a product—but in the deeper conceptual and emotional layers that AI still cannot reach.

As we move forward, we are compelled to rethink productivity itself. The future will not belong to those who can outdo AI in execution, but to those who can combine AI’s strengths with our unique capacities for innovation, empathy, and insight.

The challenge we face is not to resist AI, but to fully embrace our humanity—to cultivate the traits that machines cannot replicate. With AI taking over the drudgery, we are freed to focus on higher-order thinking and those creative leaps that define human ingenuity.

Ironically, the more we develop artificial intelligence, the more we learn about what human intelligence really is. And in that discovery lies our future—a future where AI does not replace creativity, but elevates it to new possibilities.

Is the college essay dead?

The college essay, once a revered academic exercise, is now facing an existential crisis. It used to be a good tool—a structured way for students to demonstrate their understanding, showcase their critical thinking, and express ideas with clarity . The college essay was not merely about content; it was a skill-building process, teaching students to organize thoughts, develop arguments, and refine language. Yet today, AI  has made the traditional essay feel outdated, as it can generate polished, formulaic essays effortlessly. Policing AI use in these assignments is nearly impossible, and the conventional essay’s value is rapidly diminishing.

Not all essays are created equal, however, and the future of the college essay might depend on the type of skills we emphasize. The expository essay, designed to see if students understand material or can apply concepts, is on its last legs. When AI can churn out a satisfactory response in seconds, it is a clear sign that this form of assessment is no longer viable. The AI does not just pass these assignments; it excels at them, raising an uncomfortable question—if a machine can do it, why are we still teaching it? For these kinds of essays, the challenge is that they often assess recall rather than thinking. They were already on shaky ground; AI is just the final push. 

The essays that may survive, though, are those that demand novelty, creativity, and genuine problem-solving. AI may help in drafting, structuring, or even generating ideas, but it does not replace the kind of original thinking needed to solve real-world problems. It cannot fully simulate human intuition, lived experience, or deep critical evaluation. AI's writing is wooden, and often devoid of true beauty. Essays that require students to synthesize information in new ways, explore original ideas, exhibit artistic talent, or reflect deeply on personal experiences still have value. These essays are not about whether you know a theory; they are about what you can do with it. This is where the human element—the messy, unpredictable spark of creativity—remains irreplaceable. 

The deeper issue is not AI itself but the way we have been teaching and valuing writing. For decades, the emphasis has been on producing “correct” essays—structured, grammatically precise, and obedient to the format. We have been training students to write well enough to meet requirements, not to push the boundaries of their creativity. It is like teaching students to be proficient typists when what we really need are novelists or inventors. We have confused competency with originality, thinking that writing formulaic content is a necessary step before producing meaningful work. This is a misunderstanding of how creativity works; mastery does not come from repetition of the mundane but from risk-taking and exploration, even if that means stumbling along the way.

The real future of the essay should start with this recognition. Imagine if instead of book reports or basic expository pieces, students were challenged to write for real audiences—to draft scientific papers for journals, craft poems for literary contests, or propose solutions to pressing social issues. Sure, many students would not reach the publication stage, but the act of aiming higher would teach them infinitely more about the writing process, and more importantly, about thinking itself. This would not just be about mastering the mechanics of writing but developing a mindset of curiosity and originality. AI could still play a role in these processes, helping with the technicalities, leaving the student free to focus on developing and articulating novel ideas.   

The problem with the book report or the “explain Theory A” essay is not just that they are boring; it is that they are irrelevant. Nobody in the professional world is paid to summarize books or explain theories in isolation. These are stepping stones that lead nowhere. Excelling at pointless, terrible genre does not prepare to succeed ad an authentic genre. Instead of teaching students to write these antiquated forms, we should ask them to write pieces that demand something more—something they cannot copy-paste or generate easily with a prompt. Authentic, context-rich, and creative assignments are the ones that will endure. If there is no expectation of novelty or problem-solving, the essay format becomes an exercise in futility. 

AI’s rise does not have to spell the end of the essay. It might, in fact, be the nudge needed to reinvent it. We have the chance to move beyond teaching “correct” writing toward cultivating insightful, original work that challenges the boundaries of what students can do. AI’s presence forces us to ask hard questions about what we want students to learn. If writing is no longer about mechanics or regurgitating content but about generating ideas and engaging critically, then AI becomes a collaborator, not a competitor. It can help with the structure, but the essence—the thinking—must come from the student.

In the end, the college essay is not dead; it is just in need of reinvention. The conventional model of essays as rote demonstrations of knowledge is no longer viable. But the essay that challenges students to think, create, and solve problems—those essays will survive. They might even thrive, as the focus shifts from the mechanics of writing to the art of thinking. The key is to evolve our teaching methods and expectations, making room for a new kind of writing that leverages AI without losing the human touch. Raising expectations is the main strategy in dealing with AI in education. 

Four Myths About AI

AI is often vilified, with myths shaping public perception more than facts. Let us dispel four common myths about AI and present a more balanced view of its potential and limitations.

1. AI Is Environmentally Costly

One of the most persistent claims about AI is that its use requires massive amounts of energy and water, making it unsustainable in the long run. While it is true that training large AI models can be energy-intensive, this perspective needs context. Consider the environmental cost of daily activities such as driving a car, taking a shower, or watching hours of television. AI, on a per-minute basis, is significantly less taxing than these routine activities.

More importantly, AI is becoming a key driver in creating energy-efficient solutions. From optimizing power grids to improving logistics for reduced fuel consumption, AI has a role in mitigating the very problems it is accused of exacerbating. Furthermore, advancements in hardware and algorithms continually reduce the energy demands of AI systems, making them more sustainable over time.

In the end, it is a question of balance. The environmental cost of AI exists, but the benefits—whether in terms of solving climate challenges or driving efficiencies across industries—often outweigh the negatives.

2. AI Presents High Risks to Cybersecurity and Privacy

Another major concern is that AI poses a unique threat to cybersecurity and privacy. Yet there is little evidence to suggest that AI introduces any new vulnerabilities that were not already present in our existing digital infrastructure. To date, there has not been a single instance of data theft directly linked to AI models like ChatGPT or other large language models (LLMs).

In fact, AI can enhance security. It helps in detecting anomalies and intrusions faster than traditional software, potentially catching cyberattacks in their earliest stages. Privacy risks do exist, but they are no different from the risks inherent in any technology that handles large amounts of data. Regulations and ethical guidelines are catching up, ensuring AI applications remain as secure as other systems we rely on.

It is time to focus on the tangible benefits AI provides—such as faster detection of fraud or the ability to sift through vast amounts of data to prevent attacks—rather than the hypothetical risks. The fear of AI compromising our security is largely unfounded.

3. Using AI to Create Content Is Dishonest

The argument that AI use, especially in education, is a form of cheating reflects a misunderstanding of technology’s role as a tool. It is no more dishonest than using a calculator for math or employing a spell-checker for writing. AI enhances human capacity by offering assistance, but it does not replace critical thinking, creativity, or understanding.

History is full of examples of backlash against new technologies. Consider the cultural resistance to firearms in Europe during the late Middle Ages. Guns were viewed as dishonorable because they undermined traditional concepts of warfare and chivalry, allowing common soldiers to defeat skilled knights. This resistance did not last long, however, as societies learned to adapt to the new tools, and guns ultimately became an accepted part of warfare.

Similarly, AI is viewed with suspicion today, but as we better integrate it into education, the conversation will shift. The knights of intellectual labor are being defeated by peasants with better weapons. AI can help students better understand complex topics, offer personalized feedback, and enhance learning. The key is to see AI as a supplement to education, not a replacement for it.

4. AI Is Inaccurate and Unreliable

Critics often argue that AI models, including tools like ChatGPT, are highly inaccurate and unreliable. However, empirical evidence paints a different picture. While no AI is perfect, the accuracy of models like ChatGPT or Claude when tested on general undergraduate knowledge is remarkably high—often in the range of 85-90%. For comparison, the average human memory recall rate is far lower, and experts across fields frequently rely on tools and references to supplement their knowledge.

AI continues to improve as models are fine-tuned with more data and better training techniques. While early versions may have struggled with certain tasks, the current generation of AI models is much more robust. As with any tool, the key lies in how it is used. AI works best when integrated with human oversight, where its ability to process vast amounts of information complements our capacity for judgment. AI’s reliability is not perfect, but it is far from the "uncontrollable chaos" some claim it to be.

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AI, like any revolutionary technology, invites both excitement and fear. Many of the concerns people have, however, are rooted in myth rather than fact. When we consider the evidence, it becomes clear that the benefits of AI—whether in energy efficiency, cybersecurity, education, or knowledge accuracy—far outweigh its potential downsides. The challenge now is not to vilify AI but to understand its limitations and maximize its strengths.