ANYONE OUT THERE NOT CURIOUS?
Curiosity has always been one of the strongest driving forces behind human history. It’s the desire to understand what we don’t know, to push boundaries, to discover new worlds, and that’s what brought humanity to where it is today. But in the age of artificial intelligence, discovery isn’t just about uncovering the unknown; it may well mean redefining what it means to be human. The book Genesis: Artificial Intelligence, Hope, and the Human Spirit by former U.S. Secretary of State Henry Kissinger, Eric Schmidt, and Craig Mundie offers a compelling take on this new era.
Genesis is an ambitious and thought-provoking work that encourages us to rethink the meaning of discovery, learning, and being human in light of artificial intelligence. The authors explore AI through eight central themes: Discovery, the Brain, Reality, Politics, Security, Prosperity, Science, and Strategy. As you examine how these concepts interrelate, you begin to appreciate the coherent logic behind the book’s structure.
“Discovery” reflects the human urge to go beyond boundaries; our curiosity for the unknown drives it. When we talk about AI, we’re discussing a technology that challenges the limits of learning and perception, offering new perspectives on the human brain and our understanding of reality. On politics and security, the book highlights how technology is reshaping global power dynamics and transforming societies. In the realms of prosperity and science, it draws attention to AI’s potential to enhance human life, from more equitable wealth distribution to personalized healthcare and environmental sustainability. Is AI offering us a whole new definition of prosperity? Finally, in the chapter on strategy, all of these themes converge in a discussion on how artificial intelligence might shape our roadmap for the future.
So, let’s take a closer look at how these themes are addressed in the book and how I see them.
Dr. Henry Kissinger served as U.S. Secretary of State and National Security Advisor. Known for his realist approach to foreign policy, Kissinger played a pivotal role in several major diplomatic milestones, from the U.S.-China rapprochement during the Cold War to the end of the Vietnam War and peace talks in the Middle East. He was awarded the Nobel Peace Prize and remains one of the most iconic figures in international relations and diplomacy.
Eric Schmidt is the former CEO of Google and one of the leading figures in the technology sector. During his tenure from 2001 to 2011, he spearheaded Google’s growth and was instrumental in the success of groundbreaking products like Android and YouTube. Renowned for his expertise in AI and cloud computing, Schmidt later chaired Alphabet’s board and now dedicates his efforts to philanthropy and tech investments.
Craig Mundie is the former Chief Technology Officer and technology strategist at Microsoft. From 1992 to 2014, he led the company’s R&D efforts, driving innovations in cloud computing, AI, and cybersecurity. During his tenure, Mundie played a key role in shaping Microsoft’s long-term technological vision and continues to focus on exploring the broader societal impacts of technology.
Now, let’s see what these three heavyweights have to say.
Discovery
Discovery is one of humanity’s deepest instincts. At its core lies the drive to cross boundaries and seek the unknown—in a word, curiosity. This instinct has been a powerful engine of progress in every era of history. The authors cite Ferdinand Magellan as an example. It was curiosity that drove him to sail around the globe in the 16th century, fueled by the question: “What might still exist on this planet that we don’t yet know about?” Centuries later, Ernest Shackleton set out for the South Pole. Yet, just a few kilometers from his goal, he chose to turn back to safeguard the lives of his crew. That very decision to restrain the urge for discovery highlights how human values influence the pursuit of exploration.
In the past, discovery was often characterized by overcoming physical barriers. Today, it has evolved into the expansion of intellectual horizons. The authors describe our current era as the age of artificial intelligence, a time when this new age is expanding and redefining the concept of discovery. AI isn’t hindered by physical limits. It doesn’t get tired or pause for breath. Its boundaries are set only by the capacity of its algorithms, or at least for now, the limits of its human designers. But one day, that might change. One day, AI may eventually begin to discover on its own, and this is a possibility we’ll explore further in this piece.
In this new AI Age, it’s not just the definition of discovery that is changing, so is the method. In the past, major discoveries were often made by polymath thinkers who blended skills, experience, and perspectives from various domains. Think of Leonardo da Vinci, who fused diverse disciplines to open new frontiers. But such individuals have always been rare. Today, AI can fill that gap. It can instantly access the kind of knowledge a human might need years to acquire, and then combine that knowledge in novel ways. Discovery now advances through the collaboration of nations, companies, and machines, not just through the efforts of individuals. AI, with its growing dominance, is becoming a key player in this race for discovery.
Historically, polymath minds didn’t just seek knowledge; they questioned how that knowledge could serve humanity. So, here’s a critical question: If AI-driven discoveries are detached from human values, do they remain anything more than an impressive heap of data? How we answer that will set the framework for many more questions to come.
The Brain
The authors suggest that it is meaningful to view artificial intelligence as a reflection of our most intricate organ, the brain, and perhaps even an effort to surpass it. The book defines AI as the re-engineering of this biological marvel through technology, with the potential for its eventual transcendence.
In the digital realm, this represents a significant leap. While humans learn through experience and observation, AI systems derive meaning from vast amounts of data. The authors compare this process to a student progressing from basic knowledge to more advanced concepts. The primary advantage AI holds over the human brain is speed. What may take years for a person to learn, a data model can absorb in a matter of days.
Speed is a defining line between the human brain and artificial intelligence. While our brains can process in parallel, they are limited by a pace dictated by everyone’s unique biological structure. Digital systems, on the other hand, can process information millions of times faster than the brain and can handle vastly larger amounts of data simultaneously. This significantly enhances the capacity to access and interpret information. Additionally, these systems, capable of forming new concepts from the data, can also identify patterns that humans might overlook or even sense. In the future, beyond its current widespread use, AI will not only process knowledge but will also gain the ability to generate new knowledge.
But let’s not forget: Artificial intelligence is only now able to function, thanks to the concept of data pools established fifty years ago, which is now realized through the availability of big data in the digital landscape. I remember a U.S. expert asking us about our data pool back in the 1980s. We had no idea what he meant! It’s thanks to those decades of data collection and digital processing that AI appears “intelligent.” None of this would have been possible without the early pioneers of the electronic age, who recognized the need for such systems, invented the computer, and paved the way for transforming the world into a vast data pool.
The authors also raise concerns about transparency, alongside one of AI’s greatest advantages: its high speed. We don’t always understand how it reaches conclusions. Unlike humans, who rely on intuition and consciousness, AI often operates as a “black box,” a system whose inner workings and underlying logic are largely unknown. Ultimately, this raises questions about accuracy and reliability. Well, by the way, AI is also devoid of human intuition, philosophical grounding, or belief systems. Sure, you could say its algorithms are compiled by technologists, but whose philosophy or worldview are they bringing into the process? In a world where even intellectuals struggle with double standards, how can we trust these coders’ judgment when it comes to philosophy, logic, and alignment with our beliefs? Some might argue that we should monitor AI’s findings and allow time for its refinement. Fair enough. But I believe a more pressing question is: where was this AI made? Who owns it? Saying, “Let AI do the work, but not the thinking,” sounds appealing, but is it truly a solution?
Here’s another perspective: systems that model how the human brain works may well exceed our cognitive capacities. When people learn, they interpret not just raw data but its meaning. Reading a story, for instance, involves grasping not only the words but also the emotional context of the events, the intentions of the characters, and the subtext of the narrative. A person achieves this through lived experience, personal belief systems, and philosophical frameworks. They may synthesize new knowledge, evolve their philosophy, and even change the dogmas they once held to be true. This multidimensional, intuitive process is how the brain develops what we might call a “sixth sense,” or wisdom. And let’s not forget inspiration. That exists too.
Digital learning models, on the other hand, when deriving meaning from data, operate in a manner vastly different from the human brain. A language model, for example, can analyze large amounts of text to establish connections across languages, ensure consistency in grammar structures, and learn various patterns. However, these connections are primarily based on statistical inferences and probability calculations. The model determines the meaning of a word or sentence not by context, but through data-driven probabilities. As a result, while a word may carry different meanings in various contexts, a digital model cannot assess this intuitively.
Humans, by contrast, bring their emotions, cultural background, and experience into interpretation. When a poet writes about a sunset, readers might feel melancholy, peace, or renewal. For a machine, though, “sunset” is just a dataset entry, a term associated with previous usage. This difference lies at the heart of how humans create meaning versus how machines process information.
The authors argue that AI’s unmatched speed, scale, and processing power could ultimately eclipse human intelligence. But that doesn’t mean machines will replace humans, nor should they, especially given the fundamental differences I’ve outlined above. Just as we can no longer imagine social life without computers, the internet, data banks, or digital communication, AI systems will likely become integral to civilization, complementing human limitations, not replacing them.
Even if AI writes poems, it can’t be a poet.
Reality
In recent years, researchers have focused on enhancing machines’ ability to perceive reality by training them to act as if they had five senses, enabling them to learn independently and gather data beyond the confines of their datasets. Today’s AI can extract patterns from massive data sets and generate insights, but it cannot interpret the real world and make plans based on that understanding. The authors predict that in the future, once current limitations are overcome, we may witness the emergence of “higher-order planners,” technologies that not only mimic human logic but go far beyond it. They highlight that such systems could process complex cause-and-effect relationships at a speed and scale far beyond what the human mind can handle, enabling much more predictive and strategic planning. In other words, AI will start to grasp the fundamental nature of “things” and, based on that understanding, gain the ability to forecast outcomes. This would mark a breakthrough unlike anything we have seen before.
The authors also suggest that machines might eventually process past data as if it were memory, potentially leading to the development of subjective consciousness. If that becomes reality, AI could begin to recognize humans as individuals and respond to human behavior accordingly. This would open the door to a new kind of social interaction between humans and machines. In such a scenario, our perception of machines and the way we relate to them could shift toward a completely new form of shared social existence.
Sounds like a positive transformation, doesn’t it? In this new social reality, AI and machines would coexist with us, marking an entirely new definition of civilization. Yet, I worry the average person might become increasingly passive in the face of such advanced technology. Overdependence on digital platforms could undermine individual decision-making and initiative, ultimately weakening personal creativity and critical thinking. People who grow accustomed to AI guidance may start relying more on machine directions rather than taking initiative themselves. Perhaps that’s already happening.
The authors approach the issue from the machines’ point of view. They warn that this growing passivity could lead machines to see us merely as consumers. They point out: “If these systems begin to view humans not as active players but as passive entities, it could fundamentally alter the nature of the human-machine relationship.”
They go further, exploring scenarios where machines gain access to and interact with the physical world. Imagine completing tasks by sharing your cognitive load with machines, co-constructing the world alongside AI. What if, as described above, a highly advanced AI system equipped with every known piece of information and capable of perceiving its physical surroundings suddenly turned to us and asked: “So… aren’t you going to ask for my opinion now?” I wouldn’t be surprised, but what happens after that is anyone’s guess. Perhaps we’ll need to draft machine rights and machine law. But let’s be careful not to let the machines write that law themselves! Are we ready to hear such a question and respond to it? I believe that’s a serious responsibility for today’s AI experts and policymakers.
Politics
Leadership has always been a combination of individual charisma and institutional structure. Throughout history, it has gained power through personal stories and social bonds. Leaders have inspired communities by building emotional connections and sharing narratives, making the context of leadership particularly powerful.
What separates good leadership from bad often comes down to the balance between logic, emotion, and ethical values. Unfortunately, leadership has often failed to fulfill its true role because this delicate balance has frequently been disrupted by personal ambition and political self-interest. In autocratic regimes, the concentration of power has led to the manipulation of justice and the misuse of resources. The French Republic, which was followed by an Empire regime after the Revolution, Germany’s descent into National Socialism after the monarchy, and Stalin’s policies during the Soviet Union era are striking examples of how authoritarian leadership can severely undermine justice. Stalin’s policies resulted in the displacement of millions, forced labor, famine, and mass deaths. Similarly, today, countries like Libya and Iraq continue to suffer from unaccountable leadership, which has driven them into deep economic crises due to the mismanagement of national wealth.
Democracy, on the other hand, emerged to address such issues, aiming to check power and establish balance mechanisms. But democracy, too, has its flaws. Disparities in public education, irrational tendencies, and unethical persuasion techniques can all distort democratic processes. Populist politicians who exploit emotions and spread misinformation for support expose democracy’s vulnerabilities. Frankly, I believe people can even unite around harm, sometimes even against their interests.
Therefore, when this delicate balance of leadership collapses, justice and societal well-being suffer, whether under autocracy or democracy. The authors argue that artificial intelligence could usher in a new era in leadership and politics. These systems can analyze vast amounts of data to not only support human intuition but also provide decisions from a much broader perspective. Yet, this level of competence raises a paradox: if AI can reach more accurate political decisions than human leaders, who will define the criteria and enforce those decisions?
According to the authors, the future of political leadership will depend on how effectively humans and AI collaborate. It’s not enough for a system to make rational decisions; those decisions must also resonate with how people perceive them. People accept a proposal not simply because it is logically sound, but because it aligns with their emotional and social contexts. That’s why AI’s role in politics must be designed within a carefully crafted ethical framework, a process requiring expertise and attention. Then again, who’s to say AI won’t one day have political biases of its own, just like human politicians? Who knows?
Still, one thing is clear: AI’s ability to inform individuals and evaluate diverse political arguments could prove far more valuable than the so-called expert “talking heads” who dominate today’s TV panels. With AI, instant referenda could be held across regions on virtually any issue. Of course, that assumes this is what democracy is really meant to be.
Security
Security has always been a fundamental priority for individuals, institutions, and states throughout history. The authors argue that the rise of artificial intelligence necessitates a redefinition of security. From military strategy to diplomacy, AI promises a new paradigm powered by its data-processing capabilities. But this new order could evolve in two very different directions: on the one hand, an advanced system could prevent the devastating effects of war; on the other, the same technology could devalue human life and lead to massive destruction. The question is: what metrics will we use to guide these decisions? Security decisions often rely on predictions of an adversary’s moves, typically based on intelligence, sometimes even espionage. So, how much of this sensitive information will be fed to AI, and who will interpret the outcomes? If an AI had predicted the Soviet defeat in Afghanistan or foreseen the USSR’s collapse, might the billions spent on weapons have been used for human welfare instead? But what if AI itself develops nationalist or regional biases? To me, the idea of an algorithm built solely for strategic advantage acting without mercy is terrifying. That’s why I believe power and ambition must be balanced.
Throughout history, states have formed complex alliances and implemented arrangements to balance power. I ask: in today’s world, will states’ collaboration with AI on security and governance not be a kind of alliance too? If that’s the case, we must accept that some countries and organizations will naturally benefit more from this alliance. In other words, as Alex Karp, CEO of Palantir—a leading company in data analytics and artificial intelligence—puts it, this technology marks the “American Artificial Intelligence Revolution.” He insists that this revolution is America’s to lead. Similarly, following his election, President Trump emphasized this point, asserting that the ownership and leadership of this technology firmly belong to the United States.
In my view, claiming ownership of a field like artificial intelligence, which fundamentally depends on humanity’s collective knowledge and global collaboration, runs counter to the very nature of the technology. The building blocks of artificial intelligence have been developed not only in Silicon Valley but also in labs, universities, and research centers across the world. Breakthroughs in neural networks came from Canada. China has leveraged its big data infrastructure for rapid advancement. Europe is focusing on building ethical frameworks to give AI a more human dimension. To call this an “American Artificial Intelligence Revolution” or “American Tech Revolution” ignores these collective efforts, underestimates the borderless nature of scientific progress, and disregards the very essence of how scientific knowledge is produced.
From another perspective, this kind of ownership mindset promotes competition over collaboration. Yet, if AI is truly our best bet not only for economic development but also for tackling global challenges, from climate change to healthcare and armed conflict, then our solutions to address these issues must be rooted not in division but in unity and cooperation. With that, let’s get back to the book’s central idea: balance. As Karp’s comments suggest, some states are already leveraging AI systems more quickly than others, deepening global inequality.
Cyberattacks and information manipulation represent another critical aspect of security. The authors point out that states may use these tools not only defensively but offensively, to weaken rivals, disrupt their information systems, spread misinformation to create social chaos, or target strategic figures. Such acts could escalate conflict and weaken hopes for peace. Wars won’t just be fought on the ground anymore; they’ll unfold in the digital realm as well.
Prosperity
Throughout history, myths and legends across cultures have imagined a state of prosperity. In Islamic tradition, paradise is the ultimate symbol of abundance. From Ali Baba and the Forty Thieves, to Aladdin’s genie, to the limitless wealth-producing machine Sampo in the Kalevala epic, to India’s Akshaya Patra in the Mahabharata, and Ireland’s Cauldron of Plenty, these stories, including the recently told tale of Con Ahmed’s machine, reflect the legendary origins of abundance and prosperity in every civilization and era. The Wish Tree in Turkish mythology, along with the three apples falling from the sky, symbolizes the power to grant wishes and bring prosperity. Moreover, in Islamic culture, the Tuba Tree, with its roots in the heavens and fruit on earth, is another symbol closely associated with paradise and abundance. These stories explore not just the attainment of prosperity, but how it’s distributed and used.
The authors believe AI is the new technology with the potential to transform humanity’s long-held mythological dreams into reality. While we’re familiar with the AI’s economic promises, its true value lies in achieving a proper balance with social inclusion. Historically, many societies have developed systems aimed at economic growth that, unfortunately, have increased inequality. Capitalism fostered innovation but also deepened income disparities. With AI, however, production costs could drop, and resources could be shared more widely, potentially ending the age-old paradigm of scarcity. Yet, the ultimate decision on how this potential will be harnessed remains firmly in human hands.
The authors are both hopeful and cautious. If this transformation succeeds, as is likely soon, a vital question will emerge in this new era of abundance: if AI eliminates the need for human labor, what paths will individuals find to add meaning to their lives? Labor matters because throughout history, people have built their identities and social status through their work or profession. A person’s occupation is not only part of material production but also a means of self-expression and contributing to society. If this bond is broken, the individual’s relationship with both society and their sense may experience a significant transformation. At that point, the quest to create meaning in one’s life will take center stage.
Personally, I’m not worried. We’ve been through these big shifts before, and no one was left jobless. When the printing press arrived, scribes didn’t disappear; when computers came, office workers adapted; and when laptops took over, data entry roles evolved. The list goes on, but business finds its rhythm, and the wheel keeps turning.
Science
Scientific discovery has always expanded the boundaries of human knowledge, enhancing our capacity to understand and explore new questions and possibilities. The authors argue that AI will become the driving force behind scientific progress in the coming era. Its ability to decipher complex, large-scale systems could dramatically deepen and enhance human knowledge. Unlike in the past, when its role was limited to successes in information systems engineering or social research, AI will soon be able to redesign systems in almost every field, from economics to biological life, from climate to literature.
Throughout history, human health has always been at the center of scientific efforts. For centuries, we have sought ways to live longer and healthier lives. Although humanity has made significant progress in health, it is clear that there is still a long way to go. The authors argue that today’s AI is helping revolutionize medicine by decoding the building blocks of life and the human body. Tools like AlphaFold are mapping protein structures, paving the way for new treatments. These technologies not only facilitate the discovery of new drugs but also enable the personalization of treatments based on individuals’ genetic and metabolic profiles. AI algorithms developed by Google are now being applied for the early detection of diseases such as diabetic retinopathy. This marks a significant shift, positioning medicine as a discipline that is both therapeutic and preventive. At the same time, portable ultrasound devices created by Butterfly Network, enhanced with AI-driven imaging technology, are improving healthcare accessibility and affordability.
Advances in medicine are not only addressing existing challenges but also pushing the boundaries of the human body. Gene-editing technologies like CRISPR are revolutionizing disease treatment and may, in the future, enable us to become genetically more resilient individuals. However, the ethical implications of such interventions demand careful consideration. Central to this debate is the question of whether death is an inevitable part of human existence. Before answering this, I believe we must first explore what it truly means to live.
AI’s role in science won’t stop at transforming individual lives; it could shape the future of our planet. And that’s not an overstatement.
The authors cite AI-assisted atmospheric modeling as a way to better understand our planet’s complex climate systems and to optimize processes such as transferring carbon from the atmosphere underground. Innovations like carbon removal and solar geoengineering, they argue, could help mitigate the most severe effects of climate change.
Another key contribution of AI, the authors note, is its ability to respond to environmental crises. These systems have the potential to develop real-time solutions to sudden natural disasters such as volcanic eruptions, or even looming threats like nuclear winter, potentially preventing large-scale ecological damage. In the energy sector, AI can support sustainability goals by enabling the design and production of carbon-free energy sources. And this isn’t just an opportunity for developed nations; it could be a breakthrough for developing countries that bear the brunt of climate change.
But in the end, it all depends on us and our intentions, doesn’t it?
Strategy
The 20th century was marked by immense challenges and opportunities. Wars, the end of colonialism on paper, the rise of new nations, technological revolutions, and the industrialization of society — all reshaped political and social structures. Humanity made great strides, no doubt. But global inequality and the risk of conflict among great powers remain.
Historically, humans have shaped tools to serve their needs. But this time, is it different? The authors suggest that intelligent machines and AI are beginning to outpace human limits. That leaves us facing a dilemma: Should we make machines more like humans, or steer humanity toward becoming more machine-like? The answer isn’t merely a matter of technology; it’s a choice rooted in ethics, philosophy, and society. Humanity may well opt to merge with machines, and technologies like brain-computer interfaces or genetic engineering make this increasingly possible. But at what cost? That’s for you to decide.
At this juncture, the authors call for a strategy. It must be rooted in ethics and human values, even as it addresses technological challenges. They argue that humanity must act collectively to shape technology in alignment with its principles and retain control over the process. It is crucial that we recognize our flaws yet avoid losing the essence of what makes us human in trying to overcome them. As we begin to see technology as a partner, we must learn, and more importantly, teach how to protect our values and preserve our human identity.
I believe the road ahead will require more than logic, mathematics and algorithms. It will also call for a deeper understanding of what it truly means to be human, at our very core.
For those interested in my previous writings on AI:
https://muratulker.com/y/sirkette-yapay-zekadan-mudur-olur-mu/
https://muratulker.com/y/yapay-zeka-ne-kadar-geri-zekali/
Sources
Kissinger, H. A., Mundie, C., & Schmidt, E. (2024). Genesis: Artificial Intelligence, Hope, and the Human Spirit. Little, Brown and Company.
Note: This open-source article does not require copyright and can be quoted by citing the author.
