Thousands of years ago, human life expectancy probably did not exceed 20–25 years. Only in the last two centuries, with advances in medicine, science and technology, have we reached a point where average life expectancy has crossed 80 years and continues to climb. As of 2019, average life expectancy for men and women in Israel stood at 82.8 years, and according to World Bank figures the country ranked among the world’s top ten in the preceding three years. Today artificial intelligence is accelerating that progress: it analyses vast quantities of biological data to shorten drug development, enable personalised medicine, predict health risks and even investigate the mechanisms of ageing itself — heralding the next leap in human longevity.
A similar pattern exists in almost every area of our lives. The domestication and cross-breeding of plants and animals thousands of years ago were, in effect, humanity’s first attempts at genetic engineering; and genetic engineering still feeds us today, because the species we depend on supply our needs, food above all. AI-driven gene-editing technologies — CRISPR combined with predictive AI models, for example — are advancing that “domestication revolution” with unprecedented precision and speed: designing disease-resistant, high-yield varieties, creating new biomaterials, and ultimately redesigning the blueprint of life itself. The difference between domesticated fruits and vegetables and their wild counterparts is already striking — and AI is now designing the next generation of domesticates, beyond anything we imagined.
As humanity advances, future generations will ultimately be more prosperous. Streets will be cleaner, essential resources will be purified in dedicated facilities, we will cope better with extreme events such as disasters, we will have free time, we will build broader and more varied relationships, and creativity and self-fulfilment will be within reach. There is no doubt that we have suffered significant setbacks along the way — protracted wars, species extinction, poverty, disease and environmental crises. And yet, despite the periodic downturns, it is fair to say that the line of human success trends steadily upward. AI will be the central engine of the next “prosperity” phase: optimising resource allocation through smart grids and smart logistics, enabling a circular economy through intelligent sorting and recycling, predicting and mitigating disaster damage, automating tedious work to free human creativity, assisting scientific breakthroughs, and even helping to address complex problems of governance and society. Of course, AI also brings new challenges — radical shifts in employment structures, algorithmic bias, autonomous-weapons risk — but as with previous technological revolutions, the aggregate effect points toward deeper progress.
We have eliminated some of the most terrible diseases, more than once with the help of animals we feared would go extinct. The remedy for smallpox was found in the scabs of British cows; in the late 1790s a physician named Edward Jenner used the cowpox virus to develop an inoculation — and ever since, all vaccines have been called “vaccination”, from the Latin vacca, cow. Jenner, incidentally, was mocked at the time by people who claimed he was trying to turn human beings into beasts. We eradicated smallpox and other devastating plagues that had claimed hundreds of millions of lives (the Black Death remains the deadliest in history); we created technologies that would have been inconceivable 200 years ago; our life expectancy has more than doubled and continues to rise, which brings new problems that demand creative solutions, new survival mechanisms, and the construction of the largest communication and information network in history — the internet. AI is the newest and most powerful member of that creative-solutions arsenal: accelerating the development of drugs and treatments in months rather than decades, monitoring and predicting epidemics in real time, analysing medical imaging, and tailoring individual treatment plans. It is not merely a product of the internet — it is an exponential amplifier of its capabilities.
The revolution intensifies
If Gutenberg’s printing revolution made most of the world’s population literate — at its peak influence an estimated 85% of the global population — the internet and the digital revolution raised literacy to a new level. Now generative AI, in the form of ChatGPT, Gemini and their peers, is igniting a “cognitive revolution”. Never, in all the thousands of years of recorded history, have we accumulated so much information; today the volume of data held in cyberspace already reaches tens or hundreds of petabytes (one petabyte equals 1015 bytes). AI does not merely store and process that information — it understands, summarises, creates and infers, turning information into actionable insight. In practical terms, the volume of text published online in a single day is equivalent to 170 years of the New York Times — an unimaginable quantity that AI is learning to digest and distil in an instant.
To achieve all this, you have to know how to seize opportunities. Opportunities help us understand ourselves and almost always open doors to new worlds. What entrepreneurs do changes the way we, as individuals and as groups, perceive everything. Google was founded in 1998, Facebook in 2004. Nobody can claim the world has not changed since. Today AI companies such as OpenAI with ChatGPT, DeepMind with AlphaFold, and Anthropic — together with established giants embedding intelligence into their businesses, Google and Microsoft among them — are reshaping how we work, learn, create and communicate. More than that, the sheer scale of information and communication resources now available to us, without needing mainframes the size of a room, is the real revolution. AI is making intelligence itself accessible and ubiquitous.
There is a paradox here that deserves its own discussion: data that exists but is not accessible. In most organisations the data is not missing — it is trapped.
But to create this revolution, the technology companies must also earn money. That is understandable: most of us do not work purely out of altruism, devoting time, skills and abilities without compensation. It means there is an unwritten agreement between users, who enjoy almost everything free of charge, and the companies that supply all these remarkable things. In the age of AI, the core of that agreement is data. Users provide data — text, images, speech, behaviour — to train and improve the models, and in return receive powerful services free or at low cost: search, creative tools, intelligent assistants.
Email, search, video and music streaming, work and commerce platforms, dating — all of it is “free”. At first we did not understand the price we were paying: privacy. Today those battles have reached centres of power in every country and on every continent, all attempting, quite reasonably, to impose regulation and privacy law on the octopuses threatening to take over everything. The rise of AI, with its insatiable appetite for high-quality data and its capacity for deep analysis of individual behaviour, has escalated the debate over privacy and data sovereignty to unprecedented levels of complexity.
And if we widen the lens and place this moment on the timeline — from the dawn of history to a bright and unknown future — we may conclude that it is a pointless struggle. Not because we will lose to the technology companies, but because from a broad historical perspective the whole episode is a passing chapter that will ultimately contribute to great human progress; those companies, after all, are themselves creations of nature. The development of AI and the data economy accompanying it may be a necessary path to a more efficient society, stronger human–machine collaboration, and solutions to global challenges such as climate change and disease. Data is the fuel of the new era.
Consider that when Einstein concluded in 1917 that particles of light could amplify one another, it was pure scientific research. Only in the 1960s did scientists succeed in building the first functioning laser — the practical product of the theory. Today you have probably encountered dozens of items processed by lasers, and possibly been treated by one. Millions have undergone laser procedures, right down to hair removal. Nobody then knew what tomorrow would bring, which is precisely why research and development could not be restricted. In the same way, today’s basic research into transformer architectures and deep learning is incubating tomorrow’s artificial general intelligence, which will surpass even the laser in impact and reshape every corner of civilisation — from scientific breakthroughs to artistic creation, from interstellar exploration to understanding consciousness itself.
Information and knowledge come at a price
The Cambridge Analytica affair is considered one of the largest breaches of user privacy, preceded by Edward Snowden’s revelations about the NSA, which one could argue touched on national security. Using the information of nearly 100 million Americans, a large-scale exercise in “psychological engineering” was conducted with a single goal: securing the election of a particular presidential candidate, who was indeed elected. We cannot truly know how much the company’s activity influenced that outcome, but Facebook had already run a similar experiment on 60 million people back in 2010. AI will take this kind of psychological engineering to alarming dimensions of scale and precision: deepfake video and audio, hyper-targeted persuasion models trained on personal data, and automated disinformation campaigns — AI-driven tools that pose a serious challenge to democracy and social trust.
On one hand, the severity of the harm to privacy is clear and comprehensible. On the other, once we remember that every technological advance ultimately advances human culture, the debate over privacy and “we are the product” becomes less significant. In the age of AI it may be more accurate to say: we are data — but we are also partners in shaping the future. And if we pause to examine how badly privacy has actually been harmed, we find that matters are less severe than we imagine. True, advertising can be targeted at us by thousands of parameters, but ostensibly all of that information is anonymous. Google and Facebook have no idea who the anonymous person is; they hold a digital profile with general, anonymous characteristics for advertising. The trouble is that AI’s powerful correlation and inference capabilities make that anonymisation increasingly fragile. Connections between seemingly unrelated fragments of information make it possible to reconstruct personal details with high confidence. Anonymity in the age of AI is eroding at an unprecedented rate.
More troubling than any “surveillance” by Google or Facebook is the risk of breaches of government databases and identity theft. While digital tracking is used mainly for advertising — even if advertising can shape consciousness — the consequences of breaching biometric databases or population registries are many times more serious. Someone who steals an identity can commit crimes without being detected. AI-driven intrusion, with automated vulnerability discovery and convincing phishing generation, together with deepfake technology, makes identity theft, financial crime and political incrimination easier, at larger scale and harder to detect. A breach of government databases by AI-equipped hackers could be catastrophic.
So why do we focus mainly on Google and Facebook rather than on the more sensitive databases of governments, medical institutions and financial bodies? Perhaps because it is more fashionable to criticise the rapacious capitalism of Google and Facebook, which expand endlessly and appear insatiable for the foreseeable future. That raises a philosophical discussion about their intentions, particularly when their controlling shareholders hold every material resource a person could want, from private islands to private flights to the moon. AI development is pushing that hunger for data and the concentration of capital into a new dimension. Training leading models demands astronomical computing power and data that only the giants can afford — a concentration of power that is intensifying. The race to AGI further fuels philosophical debates about control, alignment and existential risk to humanity. The lords of big tech are trying to be the gods who shape humanity’s future.
And yet we have a choice. As the familiar saying goes, we can simply stop at any moment — but then we would discover that we are paying other prices. Giving up the internet, the smartphone that tracks us with unprecedented precision, and other digital spaces, all so that we can be targeted a little less. Meanwhile, I do not see many people throwing away their phones and heading into the desert to live without street cameras watching every step. In a future where AI is deeply embedded in infrastructure — smart cities, autonomous vehicles, the internet of things — “stopping” would mean complete disconnection from society, forgoing convenience, services and essential opportunities. Sensors everywhere and AI-driven analysis will make a life without surveillance a luxury.
So yes, we are paying a price in data, privacy and attention. But is it really as bad as it seems? The key in the age of AI is balance: does the price in data that we pay buy transformative value that improves lives and advances society as a whole? Just as humanity traded sweat for agricultural progress, coal for the industrial revolution and privacy for the convenience of information, are we now trading data and a measure of autonomy for AI-driven future prosperity?
How to maximise your personal benefit
How do you extract the most value from this field — and perhaps become a “product” of it on your own terms? In the age of AI:
- Deepen your AI literacy. Understand what AI can and cannot do. Learn to use the tools effectively, including how to prompt models well.
- Prioritise data sovereignty. Know what information you are sharing. Grant permissions carefully. Use privacy settings.
- Focus on capturing value. Use AI to improve efficiency through workplace automation, learning through adapted instruction, creativity through assistive tools, and health through monitoring and guidance.
- Develop skills that are hard to replace. Critical thinking, complex problem solving, creativity, emotional intelligence, ethical judgement and interpersonal collaboration.
- Take part in shaping the future. Follow AI ethics and policy. Support responsible development.
Yes, at the level of data we remain “products” or “fuel”. But in the wider picture we are joint partners and ultimate beneficiaries in an unprecedented AI revolution that is shaping the future of humanity. The key is to ensure that the costs are controlled, that the benefits are shared, and that core human values and agency remain in the driver’s seat. The rewards of the future — health, prosperity, knowledge and the ability to solve global problems — may be on a scale far exceeding anything we can imagine today, just as ancient peoples could not have imagined lasers, certainly not lasers that intercept missiles, or the internet.
If we really are “data”, the question is who makes it accessible. In most organisations the data is trapped, not missing. And in a world where a trillion agents will act on our behalf, access to data will determine who thrives and who is swallowed up.