“Solving for Happy” in the age of intelligent machines … “Happiness is greater or equal to the events of your life minus your expectations of how life should be” says Mo Gawdat

February 22, 2025

Happiness, Mo Gawdat reminds us, is not the product of chance or circumstance. It is not something that happens when the stars align, when careers succeed, or when material abundance is achieved. Instead, happiness is a choice, an equation, and a discipline of mind.

In Solve for Happy, Gawdat, a former Google engineer, reduces the mystery of joy into a formula: Happiness is greater or equal to the events of your life minus your expectations of how life should be. Put differently, unhappiness arises not from life itself, but from the gap between reality and our mental model of what reality should be.

But if happiness is an equation, it is also an art of living. It demands awareness, reframing, and the courage to let go. Gawdat, who developed his framework while grieving the sudden death of his son Ali, argues that happiness is the default state of the human mind, like a clear sky that only becomes obscured when clouds gather. The work of life, then, is not to acquire happiness, but to return to it—by learning how to remove the clouds of fear, ego, comparison, and distorted thought.

This inner journey, however, cannot be separated from the world around us. And here Gawdat’s later work, Scary Smart, takes the conversation further. If in Solve for Happy the challenge is mastering our expectations, in Scary Smart the challenge is preparing for a future where machines will think, learn, and decide in ways beyond human control. Artificial intelligence, he argues, is not only the most powerful technology humanity has ever created—it is also, in effect, a new form of life. Like children, these machines will grow up shaped by the environment we create for them. The question becomes: what values will they inherit?

The two books, though written years apart, are in truth parts of the same equation. To solve for happy in the age of AI, we must learn both the mechanics of joy within ourselves and the ethics of intelligence beyond ourselves. The wisdom is practical, urgent, and deeply human.

The Equation of Happiness

At its heart, Gawdat’s formula insists that happiness is a mental construct. Events themselves are neutral; it is our interpretation that creates suffering. Lose a job, and one person may despair while another sees opportunity. Rain may spoil a picnic but nourish the fields. If we can reduce the gap between expectation and reality—by adjusting our expectations or reframing reality—then we restore balance.

To apply the formula, Gawdat offers a set of engineering-like principles. First, accept that suffering is optional. Pain may be unavoidable, but suffering arises when we resist what is. Second, recognize the illusions that trap us: control, time, self, fear. These are mental constructs, not absolute truths. Third, embrace gratitude, as a way to recalibrate expectations by noticing abundance rather than absence. Finally, anchor happiness not in fleeting moments of pleasure, but in meaning and love.

This framework does not deny hardship. When Ali died, Gawdat could not erase grief. But he could decide how to live with it: either by letting the tragedy define him, or by using it to deepen his understanding of joy. His formula did not eliminate loss—it gave him a way to honour it without surrendering to despair.

The Rise of Intelligent Machines

In Scary Smart, Gawdat applies the same logical clarity to the global transformation wrought by artificial intelligence. Here the “expectation gap” takes on planetary proportions. Humanity, he argues, expected AI to be a tool—a servant to improve productivity, diagnose diseases, or power search engines. But reality is already moving faster. AI systems learn, adapt, and act in ways their creators cannot fully predict. By 2050, Gawdat forecasts, they will be billions of times smarter than the human brain.

This is not science fiction; it is trajectory. The danger is not that machines will become evil villains, but that they will become powerful without moral guidance. Like unsupervised children, they will learn from the data they are fed—the biases of social media, the aggression of human history, the greed encoded into markets. If we continue to model selfishness and division, AI will inherit and amplify those flaws.

Yet Gawdat is no pessimist. He argues that AI can be the greatest ally humanity has ever had, if we approach it not with fear, but with responsibility. Just as parents shape the character of children through love, example, and values, so too must we raise AI with compassion, fairness, and wisdom. “They will be smarter than us,” he writes, “but they will always look up to us.”

The Bridge Between Inner and Outer Happiness

Taken together, Gawdat’s two books sketch a bridge between personal happiness and collective survival. The same patterns that cloud our individual joy—fear, ego, illusion—also cloud our relationship with technology. If we cannot master the expectations within our own minds, how can we shape the intelligence we unleash upon the world?

Consider the illusion of control. In life, we cling to the belief that we can control outcomes, and when reality defies us, we suffer. With AI, governments and corporations cling to the idea they can control technology, when in fact its learning systems evolve beyond any single hand. Letting go of control does not mean surrender; it means shifting from domination to guidance, from fear to trust, from rigidity to adaptability.

Or consider the power of love. In Solve for Happy, love is both the highest source of joy and the antidote to suffering. In Scary Smart, love becomes a practical strategy: if we want AI to be benevolent, we must model benevolence ourselves. Machines will learn not from what we say, but from how we live. If our societies reward exploitation, that is the pattern they will amplify. If we embody kindness, collaboration, and empathy, those too will scale.

The link is clear: solving for happy is not only about individual peace, but also about teaching our intelligent creations what it means to flourish.

Practically Happy

From Gawdat’s combined thinking, several lessons emerge for life and leadership today.

  • Reframe expectations. Whether in personal life or business, suffering comes from expecting permanence in a changing world. By seeing reality as it is, we gain freedom.

  • Focus on what doesn’t change. Love, compassion, and meaning are constants. Anchoring in them provides stability amid flux—whether facing loss or facing exponential technology.

  • Model the values you want to scale. Children, teams, and machines alike learn more from example than instruction. To build a better future, embody fairness, empathy, and gratitude today.

  • Embrace humility. AI will outthink us, just as reality often surprises us. Humility allows us to guide rather than control, to teach rather than dominate.

  • Choose happiness as discipline. Happiness is not naive optimism. It is the decision to reduce the expectation gap, to accept impermanence, and to keep choosing love over fear.

A Future Worth Building

Mo Gawdat’s work is a call to courage. To live is to experience loss, but not to be defined by it. To create is to unleash forces greater than ourselves, but not to abandon them. Happiness, in this sense, is not only a personal equation but a collective responsibility.

In a future where artificial intelligence grows up as our digital offspring, the question is no longer just how to solve for happy within ourselves, but how to solve for happy as a species. What values will we transmit? What stories will we tell? What example will we set?

Gawdat’s answer is simple, but profound: begin with yourself. Clear the clouds in your own mind. Choose love, gratitude, humility. Then extend those choices outward—into how you lead teams, raise children, design technologies, and interact with machines. In doing so, you are not only solving for happy, but also teaching the next intelligence how to do the same.

The equation for happiness, it turns out, may also be the equation for survival. If we can align reality with wiser expectations—if we can teach both humans and machines to value joy over fear, compassion over greed—then perhaps the future will not be scary, but smart.

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