Temper the Past to Divine the Future

I want to start with a document written a hundred and seventeen years before I was born.

In 2013 I found out I had a right to a citizenship I had never heard of, through a great-grandmother born in Luxembourg in 1896. In 2014 I became a Luxembourgish citizen. A single piece of paper, filed in a European archive long before anyone in my family had thought about me, reorganised what was available to me across thirty countries. I spent the decade that followed building a firm that helps other people find the same thing in their own past; it has since guided more than 3,500 Americans onto that path.

I mention it because it is the reason I am qualified to talk about the future. My entire working life has consisted of going backwards in order to move forwards. And when demand for that work stopped behaving like a business and started behaving like weather, we turned to artificial intelligence to keep up — and immediately ran into ethical questions that no amount of engineering answered.

So I went looking for older tools. That is what this is.

We are living through a time of dizzying change. Every day brings a new technology, a new ethical problem, a new question about the future. Most of us ask: where is this going? Where is AI taking us?

I want to invert the question. Where did we come from, and what can we learn from that? Because as George Santayana put it, those who cannot learn from history are condemned to repeat it. If we do not look to the past for the lessons, we risk tripping over exactly the same mistakes, only wrapped in modern technological packaging.

Confucius said it more usefully: 溫故而知新 — revisit the old in order to understand the new. I translate it a little more loosely. Temper the past to divine the future. Not nostalgia, not heritage as decoration. A method, in five movements.

溫Wēn

Revisit With Purpose

Picture the First Industrial Revolution, at the end of the eighteenth century. Steam engines replacing craft work, factories appearing, cities growing and filling with smoke. A time of wonder and of fear. In England there were people who picked up sticks and stones and broke the machines — the Luddites, textile workers who saw the mechanical looms as enemies that would steal their jobs. It was understandable: suddenly one machine did the work that ten people had been doing. The shock was so great that intelligent people concluded progress meant the end of human work.

What happened next is that society transformed. New jobs appeared. New skills became valuable. It was not the end of work — it was a change.

In fact, historical studies show that across the last two hundred years technology itself was not the main culprit in mass unemployment. Very often it is other things — badly designed economic policy, a lack of educational preparation — that determine the social impact. And with every wave of innovation, professions were born that nobody had imagined. Twenty years ago there were almost no mobile app developers, no data analysts, no social media specialists. Today they are ordinary careers.

So the lesson is double. First: history teaches perspective. Every technological revolution brought difficulty, and also brought adaptations and solutions nobody had predicted. Second: people find ways to reinvent themselves. Our capacity to create and to learn is what carried us through.

Take the Second Industrial Revolution, at the turn of the twentieth century — electricity, mass production, cars and aeroplanes. Again fear and euphoria walked side by side.

There is a detail I love from that period. When the Brazilian emperor Dom Pedro II tested Graham Bell’s telephone at the 1876 Exposition in Philadelphia, he exclaimed in astonishment: “My God, it speaks!” He ordered a hundred of them, and Brazil became the second country in the world to officially adopt the telephone, in 1877.

Now hold that next to the rest of the era. Electric light frightened people — there were those who thought it far too dangerous to light the streets at night. The automobile was called a noisy, polluting invention that startled horses.

Same decade, same category of novelty, opposite reaction. One man hears a machine speak and is delighted; other people look at a lamp and see a hazard. The technology does not determine how it is received. Wonder and dread were both available in 1876, and neither was unreasonable — which means the response was a choice then, and it is a choice now.

故Gù

The Old as Solid Ground

And yet those revolutions also produced serious imbalances. Industrialisation created factories, and it created the exploitation of workers and the poisoning of the environment. It took decades to understand that economic development has to walk hand in hand with labour rights and with sustainability.

That is the other historical lesson, and it is the one people skip: not every advance is good for everyone straight away, and it falls to society to correct the course. The pattern in the history of technology is consistent. We advance, we get it wrong, we learn, we adjust the direction, and we advance again.

Which brings us to the Third and Fourth Industrial Revolutions — the digital era of the late twentieth century, and the era of artificial intelligence we are living in now. The internet, personal computers, smartphones: in fifty years all of it radically changed how we work, how we speak to one another, and how we think. AI, often called the heart of the Fourth Industrial Revolution, produces enthusiasm and dread simultaneously — exactly as steam did.

The difference is that now the change is faster and global. In a handful of years AI came out of the laboratories and into daily life, from the navigation app in traffic to the assistant on a phone. We have seen extraordinary things — who would have said a machine could diagnose disease in seconds, or write text almost like a person? But alongside them come the old questions in new form. Will AI take our jobs? Will it control us? Are we going to lose control of our own creations?

It is almost an echo. In the 1990s, when the commercial internet arrived, there were people predicting the collapse of human interaction, that we would all end up isolated in front of screens. A few months of working from home during the pandemic nearly proved them right. But what also appeared were opportunities nobody had costed: global collaboration, distance education, access to information.

At every great technological transformation, we learned the same three things: adapt, regulate where necessary, and make sure the benefit is collective. The question is not “how do we stop innovation?” Innovation is part of human nature, and once released it goes forward. The question is what we are going to do with it.

而Ér

The Bridge Between Worlds

When I talk about ancestry I do not only mean the history in books. I mean the cultural and spiritual roots we each carry — from our grandparents, and from the first peoples of whatever land we live on. Every one of us carries the accumulated judgement of those who came before, and that old knowledge can be, and should be, a compass for innovation with purpose.

The indigenous leader Txai Suruí, speaking to an international audience about the environment, put it in a sentence I have not been able to improve on: the future of innovation must be ancestral.

Look at how far that goes. In the middle of all this futurism, she is pointing out that the key to the future is also in the past. Her example: it is far easier to preserve the waters of a river than to invent machines to clean them once they are already polluted. Obvious, isn’t it? Prevention is better than cure — a maxim our great-grandmothers were already preaching, applied to advanced technology. The most sophisticated solutions very often turn out to run through the recovery of old practices of care and restraint.

Indigenous peoples of the Amazon have been running for centuries what we now market as sustainable technology. Agroforestry — cultivation systems integrating trees, plants and food — is applauded today as ecological innovation, and it has existed in indigenous cultures for generations. Or consider phytotherapy: how many modern drugs began in the traditional knowledge of healers and midwives? Technologies that sound brand new have often existed for millennia in traditional knowledge. We simply did not recognise them as technology, because they do not arrive on a silicon chip.

Why does this matter? Because innovation with purpose means creating the new without discarding what brought us here. It means asking: does this improve people’s lives? Does it respect nature? Does it honour human dignity? Our ancestors did not know about artificial intelligence, but they knew cooperation, balance and respect — and those values do not expire.

Three inherited ideas make the point better than any argument I could construct.

An indigenous teaching says: when you make an important decision, think about the next seven generations. Imagine if our technological decisions had to account for their effect on our great-great-grandchildren. How differently would we design a city, a product, an AI policy?

From the African philosophy of Ubuntu comes the idea that I am because we are — the good of the individual and the good of the community are the same object seen from two angles. Applied to technology, it says there is no point in an innovation that serves a few and harms many, or that excludes the people who most need it.

And there is a Brazilian word, gambiarra, for the ability to solve a problem with whatever is actually to hand. It is usually said with a smile, but it describes something serious: invention born of necessity, refined and passed down. Every culture has its own version. That is ancestry working as engineering.

Recovering ancestry is also an antidote to dehumanisation. When technology advances too fast, there is a risk of losing the human connection. But if we remember our own stories and traditions, we keep a foot on the ground. Innovation acquires identity and soul; it stops being generic. And looking inward, at roots, is not being trapped in the past — it is drawing nourishment from it in order to flower.

To be clear: valuing ancestry is not rejecting modern science, and I am not proposing we abandon computers and live as people did five hundred years ago. This is about integrating the old and the new. It is the humility to recognise that not all knowledge was born in Silicon Valley — a great deal of wisdom was born in villages, in monasteries, in deserts, over thousands of years.

This is where the phrase comes alive. Revisiting the old means listening to the voices of those who came before in order to guide what we create. It means that when we design an AI, we ask ourselves ethical questions that were already present in the first human societies.

知Zhī

Knowledge Turned Into Wisdom

In the middle of algorithms and automation, how do we not lose the human element? How do we make sure artificial intelligence serves us instead of subjecting us? This is not science fiction. It is current.

Look at where we already are. AI is already making decisions that affect lives. It can select who gets a bank loan, who is called for a job interview, what a security camera flags. Built without care, these systems do not remove injustice — they automate it. There have already been cases of facial recognition failing more often on Black people because of bias in the training data: historical prejudice reproduced in the twenty-first century.

And when an algorithm decides and nobody can explain why — the black box — what happens to accountability? We cannot accept “sorry, that’s what the computer said.”

Keeping the human element means two things. First, humans close to the decisions, supervising and holding the final word. Second, human values — empathy, fairness, respect — embedded in the technology itself rather than bolted on afterwards.

We cannot delegate our values to code.

新Xīn

What Is Genuinely New

The world has, to its credit, woken up to this. In 2021 UNESCO adopted the first global Recommendation on the Ethics of Artificial Intelligence. One hundred and ninety-three countries agreed on a guide to ensure emerging AI benefits humanity rather than harming it. In practice that means defining principles: transparency — AI has to explain its decisions as far as possible; accountability — someone answerable for what the system does; privacy; and, fundamentally, non-discrimination. An ethical AI should reduce inequality, not deepen it.

And on inequality: real innovation has to include everyone. A third of the world’s population still has no internet access. Take one country as an illustration: in Brazil, 36 million people did not use the internet in 2022, and of those, 17 million self-declared as Black or mixed race and 17 million belonged to the lowest income classes. More than half of the children in its public school system leave the second year unable to read and write properly. Every country has its own version of those figures, and most of them are worse than their governments admit.

That is a warning. If we do not bring along the people at the margin, AI will widen the gap rather than close it. A world where only an elite understands and controls the technology while millions have no voice is not a just future — and it is not a stable one.

So keeping the human at the centre is also a question of inclusion. The equation is simple: if only a few people program and decide, they put their view of the world into the machine. The more diverse the team building an AI — in gender, in race, in culture, in language — the more human and the more complete the result.

The same applies regionally, and this is the part that gets least attention. There is a serious debate about decolonising AI: not letting a Global North perspective alone set the rules of the game. Researchers point to the risk of simply absorbing ready-made foreign solutions and assuming they fit every context. Every country and every culture needs to shape the technology to its own values and needs.

Some people now argue for slow AI, by analogy with slow food: developing these systems with more reflection, more care, at a human pace, instead of the blind rush of ship first and fix later.

Keeping the human element, in the end, is remembering that technology is a means and not an end. We define the purpose. And it works: a programme using AI to help children develop their writing won a UNESCO award — technology applied with sensitivity to education, amplifying human talent instead of replacing it. Or AI supporting doctors in diagnosis, not dispensing with the doctor but giving back the time to actually care for the patient.

There is no neutral algorithm. Every line of code, every product decision, carries an ethical choice. So ask, always: who might be helped, and who might be harmed, by the thing I am building? Am I accounting for the range of people who will actually use it? If this is misused, how would I prevent it?

Sun Tzu said the greatest victory is the one won without fighting. The same applies here: the best way to face the potential problems of AI is to avoid them at the start rather than treat them afterwards. Build the ethics in at conception, instead of fighting the consequences later.

Balance, and Humility

Many Eastern traditions emphasise harmony between opposing forces — yin and yang reminds us to look for the balance in everything. Read that today as the balance between innovation and tradition, between technology and humanity, between speed and reflection. A sustainable future requires exactly that: neither paralysing technophobia nor blind fascination with the machine.

Sun Tzu offers lessons that carry directly into the management of innovation. Know the enemy and know yourself, and you will obtain victory without danger. In our context the enemy is not a person — it is the ethical challenge and the risk. And “yourself” is our own human nature: our values, our fears, what we need. Understand the technology deeply, its capabilities and its limits, and understand ourselves, and we can navigate any storm of innovation without fear.

These traditions also value patience and the long view. Against the anxiety for immediate results, philosophies like Taoism suggest flowing with the natural rhythm, doing things at the right time. Sustainable innovation can be incremental and careful. We do not have to reinvent the world every week — small consistent steps produce great change without chaos. A journey of a thousand miles begins with a single step.

And finally, the thing this field is shortest of: humility. Confucius preached humility in learning — knowing there is always something more to learn. Applied here: the humility to acknowledge that we do not know everything about the future, that AI is not infallible, and neither are we. The humility to listen to different voices. And humility in the face of nature — in Eastern cultures and in indigenous ones alike, there is an awareness that the human being is only part of a larger whole.

Strategy with empathy. Efficiency with ethics. Power with compassion. It sounds almost like a koan, but I believe it is entirely possible.

So look back at everything we have covered. History gave us prudence. Our ancestors gave us values and purpose. Ethics gave us direction. Old strategy gave us balance. What remains is for us, in the present, to put it into practice.