Curiosity, Adaptability and Kindness
No one is future-proof, the better ambition is to become future-capable
“Tell me, what is it you plan to do with your one wild and precious life?” ~ Mary Oliver
Curiosity is the refusal to let yesterday’s competence become today's cage. Adaptability is the dignity to change your methods without losing your soul. Kindness is the choice to remain human when the system offers a thousand reasons to be a machine.
The Human Job
On 30 November 2022, OpenAI released ChatGPT to the public. The service answered questions, drafted letters, wrote code, summarized documents, and produced fluent prose in seconds. Office workers tried it first for experiments they did not report to their managers. Students tried it for essays. Lawyers, consultants, programmers, journalists, recruiters, bankers, and teachers tried it for work that had once shown professional competence. By January 2025, the World Economic Forum was asking employers about the skills they expected to need by 2030. More than one thousand employers, representing over fourteen million workers, took part in that survey. Analytical thinking remained at the top. Creative thinking followed. Resilience, flexibility, agility, curiosity, and lifelong learning rose in importance. The list was not sentimental. It said, in the language of payroll and planning, that the human future at work would depend on habits not easily reduced to a repetitive procedure.
The central error in most conversations about artificial intelligence is that we prioritize intelligence over character. We ask whether a machine can write, reason, plan, diagnose, advise, persuade, and remember. These are useful questions, but they push us too quickly into a contest of functions. They encourage a humiliating little sport in which the human being is invited to race the machine across a field chosen by the machine’s owners. The result is predictable. We lose at speed, volume, storage, pattern extraction, and cheerful indifference to boredom. A person who tries to defeat AI by becoming a cheaper, slower, more anxious version of AI has already accepted the wrong job description.
Can a Machine Think?
The better question is not whether AI can think. The better question is what kind of person grows in its presence.
The answer begins with curiosity, adaptability, and kindness, not as decorative virtues, but as practical strengths. They are the old words people use when they have run out of new jargon. They sound soft until one notices that they are the exact qualities needed when the rules change, the tools change, the firm changes, the client changes, and the old professional status no longer guarantees useful judgment. Curiosity keeps a person from being trapped inside yesterday’s competence. Adaptability lets a person revise a working life without surrendering dignity. Kindness preserves trust when systems become faster than relationships can bear.
This is not a retreat from excellence. It is a stricter definition of it.
The worker of the near future will not be asked only, “What do you know?” That question is becoming less interesting by the month. A machine can provide a first answer. A machine can provide ten. A machine can produce an answer with footnotes, a counterargument, a tone adjustment, a risk register, and a fake air of calm. The harder question will be, “What do you notice?” Which is exactly where curiosity begins. It begins not with the possession of information, but with irritation at the insufficiency of the available answer. It is the raised eyebrow in the meeting. It is the quiet refusal to accept that the dashboard knows the client, that the score knows the applicant, that the AI model knows the child, that the prediction knows the life.
The International Labour Organization has been careful on this point. Its work on generative AI does not describe one simple future in which jobs either vanish or survive. It examines occupational exposure at the level of tasks, and its recent work refines that measurement because the impact of AI depends on the composition of work, the design of institutions, and the choices made around adoption. People do not lose “jobs” in the abstract. They lose tasks, status, entry points, discretion, confidence, training routes, and sometimes the right to be inexperienced in public.
Novices
That last loss may be the most dangerous. AI may not begin by replacing the expert. It may begin by consuming the novice.
A junior analyst once learned by doing poor first drafts. A junior lawyer learned by reading too many documents slowly. A young teacher learned by facing a classroom with a plan that did not survive the first ten minutes. A young manager learned by making a small mess of a meeting and then discovering, with some embarrassment, that authority is not the same thing as volume. These were not inefficiencies. They were the cost of forming judgment.
If AI removes all of that early clumsiness, it also removes the evidence by which a person learns what competence feels like from the inside. The novice does not only need the correct answer. He needs the memory of having been wrong in a recoverable way. He needs to learn why the first sentence of a report is bloated, why the client question is not the client problem, why a legal clause that looks standard may alter the whole bargain, why a classroom goes silent when a teacher has mistaken coverage for understanding. These things are not absorbed through polished output. They are learned in the friction between attempt and correction.
Recovered novice-learning will therefore have to be designed. It will not happen by nostalgia. A firm using AI well should still ask junior staff to produce a rough first version before the machine is invited in. A law office should let a trainee mark up a contract unaided, then compare that reading with the AI’s version, then ask where both failed. A school should let students draft, stumble, revise, and only then use the tool to test structure, evidence, and tone. A hospital should teach younger clinicians not merely to read a prediction, but to state what would make it wrong. A newsroom should ask a young reporter to write the first five questions before any system generates fifty. The point is not to ban the tool. The point is to preserve the apprenticeship of attention.
This is where curiosity becomes discipline. The useful worker asks, “Why did the system suggest this?” The serious student asks, “What would I have missed without the tool?” The doctor, banker, engineer, civil servant, teacher, or journalist asks, “What kind of person would be harmed if this answer were wrong?” These are not ornamental questions. They are the beginning of professional judgment.
For twenty years, businesses trained employees to suppress curiosity. Follow the template. Stay in your lane. Escalate only through approved channels. Now those same executives announce, with the exhausted surprise of men discovering snow, that curiosity is essential. The employee may be forgiven for noticing the timing. An institution that spent twenty years rewarding obedience cannot summon independent judgment by adding it to a slide.
Adaptability
Adaptability is the second word, and it is often abused. In corporate language, adaptability can mean “please absorb the consequences of our poor planning.” It can mean relocation without support, retraining without time, flexibility without security, or resilience offered as a scented candle for institutional failure. I do not mean that. I mean adaptability as an adult capacity to revise one’s methods while retaining one’s standards.
The difference is vital. A person without standards changes too easily. A person without adaptability changes too late. The first becomes fashionable and hollow. The second becomes principled and unusable. The task is to remain teachable without becoming formless.
AI makes this difficult because it tempts us into two equally foolish poses. The first is panic. The second is smugness. Panic says everything human is finished. Smugness says everything important is safe. Both are lazy. Panic flatters the machine. Smugness flatters the speaker. Reality is less obliging. In “Generative AI at Work,” Erik Brynjolfsson, Danielle Li, and Lindsey Raymond studied the deployment of a generative AI assistant in customer support and found productivity gains averaging about 14 percent, with the largest gains among less experienced and lower-skilled workers. That is not the end of the human worker. It is also not a bedtime story. It means the novice may be helped, monitored, accelerated, and compared in the same motion.
Adaptability cannot be a weekend course in prompt engineering. It has to be a habit of intellectual refitting. A person must learn how to work with a tool, then learn when not to trust it, then learn how the tool changes the expectations of colleagues, then learn how clients respond to faster work, then learn which old skills have become rarer and therefore more valuable. The adaptable worker does not simply learn the new system. She studies the social rearrangement produced by the system.
This will separate the serious from the merely busy. The merely busy person asks, “How do I use this?” The serious person asks, “What does this make easier, what does this make harder, who gains authority, who loses practice, and what should I now learn by hand?”
Kindness
Kindness is the third word. A company using AI in hiring can process more candidates, but it can also reject more people without ever noticing them. In schools, automated feedback may return comments faster than any teacher could, while quietly training children to write for systems that have no interest in their courage. In hospitals, predictive systems can help allocate scarce resources, but they can also allow a score to acquire the emotional status of fate. Newspapers publish, banks screen, and government offices decide at a velocity that outruns reflection. Speed is useful. But we have granted it a moral authority it has not earned.
Kindness in the age of AI is not niceness. It is disciplined attention to the human consequences of increased power. It slows the hand at exactly the point where the system invites acceleration. It asks for the name, the exception, the appeal, the conversation, the second look. It does not reject systems. It prevents systems from becoming alibis.
The OECD’s recent work on AI and skills makes clear that adoption is limited not simply by the existence of technology, but by skills, training, and organizational capacity. The future is not being delivered as a sealed package by engineers in California, Shenzhen, London, Paris, or Zurich. It is being negotiated in procurement meetings, classrooms, HR departments, clinics, banks, ministries, kitchens, studios, warehouses, and family conversations at 9:30 p.m., when someone says, “I do not know whether my job will exist in five years.”
At that hour, kindness is not a mood. It is leadership.
I have come to distrust the phrase “future-proof.” It flatters our desire for insurance against history. No one is future-proof. Not the coder, not the professor, not the consultant, not the novelist, not the executive with the expensive watch and the calendar full of strategy sessions. The better ambition is to become future-capable. That means able to learn without humiliation, change without panic, and succeed without becoming cruel.
Working Ethic
This is why curiosity, adaptability, and kindness belong together. Curiosity without kindness can become predatory. Adaptability without curiosity can become mere obedience. Kindness without adaptability can become helpless sympathy, good-hearted and ineffective. Together, they form a working ethic for a time in which competence is being unbundled and sold back to us as software.
There is an old professional bargain that AI is now breaking. It promised that if one acquired a credential, learned the rules, entered a field, and performed reliably, one could expect a long period of usefulness. That bargain was never available to everyone, and many workers lived without its protections. But for the professional classes, it had the force of weather. Now it is weakening. The credential still counts. The rules still count. Reliability still counts.
Some days this is already tiring. There is a fatigue peculiar to the present moment, the fatigue of permanent adjustment. New tool, new update, new warning, new opportunity, new acronym, new expert, new panic, new reassurance, new invoice. The future now arrives with release notes. Even the apocalypse, one suspects, would ask us to accept cookies.
And yet I do not think despair is justified. Despair is often vanity in dark clothing. It assumes we know enough to give up. We do not. We know that AI will alter tasks. We know that some workers will gain and some will be exposed. We know that employers say analytical thinking, creativity, resilience, flexibility, curiosity, and lifelong learning are rising in value. We know that institutions are not ready enough. We know that training is uneven. We know that policy will lag behind practice, as policy usually does, arriving at the station with a briefcase after the train has left.
But we also know something older. People grow under pressure when they are not abandoned to it. They learn when someone gives them room to try. They adapt when they can retain dignity. They become brave when courage is made ordinary by the conduct of others. They become kinder when kindness is not treated as weakness by the ambitious.
The AI conversation has been dominated by strange extremes. On one side are those who speak as if machines will soon absorb every human gift. On the other are those who insist that nothing fundamental has changed, usually from positions buffered by tenure, capital, reputation, or all three. I do not trust either camp. The first lacks faith in people. The second lacks sympathy for those without shelter. A better view begins with the worker sitting at a desk, opening a tool that can do part of her job, wondering whether to feel relief, shame, anger, or curiosity.
I want her to feel curiosity first. Not because curiosity solves everything, but because it keeps the door of agency open. I want her to ask what the tool can do, what it cannot do, what it hides, what it assumes, what it cheapens, what it makes newly possible. I want her employer to give her time to learn rather than pretending that adoption is instant. I want her colleagues to share discoveries rather than hoard advantage. I want her school, firm, union, profession, and government to treat adaptation as a public responsibility, not a private burden placed on the already tired.
Lifelong Learners
Above all, I want us to stop speaking of human beings as obsolete components in a technical system. A person is not a legacy device. A person is a learner, a judge, a witness, and a keeper of obligations. This is not romantic language. It is a description of what institutions require when anything goes wrong. When the system fails, no one asks to speak to the workflow. They ask for a person.
The work ahead is therefore not to become less human in order to survive intelligent machines. It is to become more deliberately human, with higher standards for attention, better habits of revision, and deeper obligations to one another. The machine can answer. The person must ask why the answer is being sought, who will use it, who may be harmed by it, and whether a faster answer has made us better or merely quicker.
On a good morning, this future does not look like surrender. It looks like a meeting after the first difficult question has been asked. Someone has stopped pretending to understand. Someone else has admitted uncertainty. A third person has opened a notebook. The room is quieter than before, but not defeated. Work has begun.
Stay curious
Colin
Image - Kevin Grieve on Unsplash
A comment from email and my reply =. Dear Colin,
You have mentioned three important qualities, for none of which we have demonstrable tests or quantitative measures.
I was born, or emerged from the innocence of infancy, with deficiencies in each. It took me nearly sixty years to discover what was “wrong” with me, when I read in a newspaper about the newly- and vaguely-defined “Asperger Syndrome,” and I donned it like a glove. I hope that in the three decades since I have become kinder and more curious. But now, spurred by what you have written here, I cling to my inadaptability like a shield.
Adaptability is conducive to survival, approval, and prosperity, but I ask, “Adaptable to what?”
As the youngest grandchild of an Hasidic rabbi (well, actually, he acquired two more grandchildren after he died) I was raised on stories from the Bible. Not that my mother neglected Hansel and Gretel entirely, but my steady died of bedtime stories consisted of Adam and Eve, Cain and Abel, Abraham and Isaac, Jacob and Esau, Joseph the Dreamer and his cruel brothers … up to and including Moses and Aaron, Samuel and Saul, David and Solomon, and of course Daniel in the Lion’s Den (with whom I could not help but identify).
Jacob and Esau was a turning point. Before them, there was only mankind. After them, there were Jews and Gentiles. I was a Jew, one of the good guys as assumed in the Bible. Until, spurred by just a smidgeon of curiosity, I learned enough about the world to infer that much of what I had been taught were lies. Instantly I became an atheist, which I have remained throughout my life except for a brief interlude of deism after reading Thomas Paine’s The Age of Reason.
Some things have remained with me from the Bible, now viewed as fable. Gideon’s recruitment of an army. The kindness of Joseph, who overfilled the sacks of his cruel brothers when they came to buy grain, not recognizing the vendor. And the cruelty of Jacob.
I had been brought up to honor Jacob, the patriarch of the tribe … or the 12 tribes. This Spring I had occasion to argue with a rabbi about the fable (which he of course regards as fact) of Jacob and Esau. He said that Esau bribed Jacob by offering to trade his birthright for a mess of pottage, I said that Jacob demanded that trade.
I looked up the relevant all-too-brief passage in the Bible. I found two versions, one in the Christian version, the other in a volume of The Anchor Bible with a better translation by E.A. Speiser. Both agreed. It was Jacob who proposed and insisted upon the bribe. Esau accepted the bribe. He was famished, and realized that his birthright was worthless if he starved before he could inherit from Isaac. Both translations ended the story with a thinly-veiled criticism of Esau … for undervaluing his birthright.
But I see Esau as blameless and Jacob as cruel. I wonder now: why didn’t I renounce Judaism at age two when I first heard the fable? And I wonder now, why did the priests and rabbis, the followers of Jesus, and good Christians like Saint Francis and William Blake, let the cruel sin of Jacob slip by without denunciation and renunciation of primogeniture, the original sin, itself?
Adaptation? Adaptation to what? Adaptation to injustice? Adaptation to lies? Adaptation to cruelty? “We, the good Germans, followed orders and survived the Holocaust”
---but did not risk anything to oppose or prevent it.
Give me curiosity. Give me kindness. But keep adaptation on the shelf as at best an often necessary expedient.
My reply:
"The Jacob and Esau reading stops me in my tracks, not because it is surprising, but because it is obviously correct and I had never paused long enough to notice. The text does what you say it does. The editorial gloss blames the hungry man.
You are right and have the precise flaw in my argument, and I want to sit with it rather than defend around it. True, adaptability without a fixed moral object is not a virtue at all. It is a mechanism. 'Adaptable to what' is the question I should have asked inside the essay, not left for a reader to ask in the comments.
What I meant, and did not say clearly enough, was adaptability in method, not in standard. The person who changes how they work while refusing to change what they will tolerate. But I concede that distinction is easier to draw on paper than to hold in a life, especially when the pressure to conform arrives dressed as common sense, institutional loyalty, or survival.
Esau was famished. That is not a moral failure. That is a human condition being exploited by someone with the luxury of patience.
Thank you for sixty years of inadaptability on the things that mattered. The essay is better for your reading it.
Stay well"
Deep thoughts here. “the fatigue of permanent adjustment” well describes the constant feeling of driving a stick shift automobile on steeply sloping and curving terrain. It explains why automatic is restful and agency is surrendered to idle one’s attention energy. Your insights provide a template to study as to what standards need to be chosen.