Introduction
Summary of the book AI Needs You by Verity Harding. Before moving forward, let’s briefly explore the core idea of the book. Artificial Intelligence isn’t a distant possibility; it’s woven into your present, influencing what you see, how you learn, and the choices you make. Yet it doesn’t simply happen to us—AI is shaped by our input, values, and demands. Over time, public voices can guide AI’s evolution, ensuring it benefits everyone rather than a privileged few. From balancing innovation with fairness to reflecting the diversity of our world, AI’s path depends on decisions we make today. As with previous breakthroughs like IVF, we can learn, debate, and refine our principles as technology matures. This book invites you to step forward, question the status quo, and speak up. Your perspective can help design more responsible AI, making sure it respects human dignity, protects freedom, and nurtures creativity. The future of AI needs you—your curiosity, your insight, and your courage.
Chapter 1: Glimpsing a World Transformed: How Artificial Intelligence Weaves Into Our Lives Each Day .
Picture stepping out of your front door each morning and entering a world invisibly guided by tiny, tireless minds made of code. Your smartphone offers personalized recommendations before you’ve even asked, identifying the music that best suits your mood, the quickest route to school, or the news stories you’re most likely to read. These digital assistants operate with remarkable speed, crunching oceans of data to tailor experiences that feel almost handcrafted for you. Beneath these everyday conveniences lies artificial intelligence (AI), a force reshaping how societies function. While you’re aware that voice assistants can recognize your speech or that video apps suggest new shows, it might be easy to forget the vast web of logic and learning behind these tools. They are quietly transforming your life, ensuring that daily decisions—whether big or small—are influenced by patterns, predictions, and calculations beyond your direct control.
This transformation isn’t happening in a distant laboratory; it’s unfolding right in your pocket, your living room, and your neighborhood. Take traffic signals: many cities now rely on AI to adjust light cycles, reducing congestion and improving travel times. Online, streaming platforms apply intelligent filtering to help you discover new movies or songs that mirror your interests. Healthcare apps might analyze symptoms you input and swiftly offer potential diagnoses or healthy living tips. Even your favorite sports teams use AI-driven analytics to refine strategies and outsmart opponents. Step by step, AI is stitching itself into the fabric of daily life, making complex decisions appear simple and personalized. However, this power doesn’t just pop into existence. It emerges from intricate algorithms, data sets, and relentless machine training—a vast and often hidden network that continually reshapes your world.
As AI weaves into countless aspects of your routine, it’s important to remember that behind every smart suggestion or automated action are human choices and priorities. Researchers, developers, and corporate strategists decide which problems AI should tackle first, how much data to feed into models, and what goals these systems aim to achieve. Their decisions influence what you see, whom you interact with, and even which events you learn about. Moreover, because AI adapts from past examples, it can sometimes inherit and strengthen biases hidden in historical data. If overlooked, these biases can influence search results, job recommendations, or news feeds, potentially skewing how you understand the world. Simply put, AI’s infiltration into everyday life isn’t neutral. It’s shaped by human hands and guided by the values, hopes, and blind spots of those who design it.
This invisible transformation challenges you to think differently about the tools you use. When your social platform suggests a new friend or a video series, consider that an AI-driven judgment guided that choice. It’s not necessarily malicious or manipulative, but it can subtly nudge your tastes, beliefs, and behaviors. Over time, these nudges shape society’s discussions, influence cultural trends, and affect how communities form and evolve. Recognizing AI’s fingerprints in your daily life is the first step toward becoming an informed participant in the conversation about its future. Instead of passively absorbing what AI systems offer, you can learn to question and understand how these systems work. By doing so, you gain the power to push for AI that aligns with your values, respects your privacy, and promotes a fair, open, and vibrant society.
Chapter 2: Unmasking the Hidden Shadows: Understanding AI’s Complexities That Lie Beneath Its Promise .
Beneath AI’s dazzling possibilities lurk unexpected challenges and contradictions—its shadow side. Imagine a city known for brilliant innovation and wealth, yet also plagued by homelessness and despair. This stark contrast, like the famed technology hubs that shine in skyscrapers while struggling souls rest in their doorways, mirrors AI’s dual nature. On one hand, you see algorithms capable of spotting diseases in medical scans or optimally routing delivery trucks. On the other, these same technologies can reinforce prejudice, exclude disadvantaged communities, or deepen existing inequalities if not carefully monitored. AI is never just about flawless efficiency and clever solutions; it’s equally about unintended consequences and overlooked populations. Recognizing these hidden shadows is vital. It ensures that while we unleash AI’s power, we remain alert, so it doesn’t magnify our darkest tendencies or leave vulnerable people behind.
The complexity comes from how AI learns. Most systems rely on mountains of past examples, patterns drawn from real-world data. If that data is skewed—perhaps biased toward certain groups, cultures, or viewpoints—then the AI will dutifully replicate those imbalances. Think of a hiring tool trained on decades of job applications that favored a narrow demographic. Without careful design, such a tool might continue to prefer that same demographic, ignoring equally qualified candidates who break the mold. This subtle reproduction of old injustices can harden inequality into a new digital standard. In doing so, AI risks becoming not only a mirror of our flawed histories but also a magnifier of them. Understanding this risk allows us to shine a light into these shadowy corners and encourages efforts to promote more balanced, fair, and inclusive data sets.
Unmasking AI’s hidden pitfalls also involves examining its role in shaping social behavior. Personalized feeds and recommendations might feel comfortable and reassuring, but they can create echo chambers. Inside these digital bubbles, differing opinions vanish, replaced by a chorus of agreement. Without exposure to alternative viewpoints, communities can become fragmented, each group convinced it holds the entire truth. This subtle isolation can foster polarization, making it harder for people to find common ground. By acknowledging this issue, we’re better prepared to push for AI designs that encourage curiosity, empathy, and a broader perspective. After all, a healthy society thrives on a diversity of voices, experiences, and opinions, not a narrow loop of repetition. Illuminating AI’s shadow side helps us understand that these systems must be continuously guided by human values and responsible oversight.
Disentangling AI’s complexities also means facing ethical questions head-on. Should law enforcement rely on facial recognition if it sometimes misidentifies minorities? Should credit assessments powered by opaque algorithms decide who gets a loan? Answers are not straightforward, and the stakes are high. The goal isn’t to abandon AI but to steer it responsibly. This may require diverse teams of developers who bring fresh perspectives, regulators who set strict standards, and informed citizens who demand fairness. By confronting the uncomfortable truths about AI—its hidden shadows, biases, and vulnerabilities—we lay the groundwork for progress. We create space for meaningful debate, public input, and constructive criticism. Only then can AI evolve from a tool that sometimes amplifies human flaws into one that highlights human virtues. This journey begins with courage: the courage to face the shadows and strive for better solutions.
Chapter 3: Building Ethical Bridges Through Past Innovations: IVF’s Lessons Guiding AI’s Responsible Growth .
When thinking about AI’s ethical debates, it may help to recall another remarkable technology that once stirred intense controversy: In Vitro Fertilization (IVF). Before IVF became a widely accepted medical procedure, it raised deep moral, religious, and societal questions. Critics viewed test-tube babies as unnatural, fretting over the notion that humans dared to create life outside the human body. Proponents, however, celebrated the newfound hope for couples who longed for children. This clash of opinions forced policymakers, doctors, and the public to define acceptable uses for a technology that was rapidly evolving. Over time, discussions, regulations, and cultural shifts allowed IVF to become mainstream. Today, it’s not only a common fertility solution but a window into how societies learn to guide transformative breakthroughs. AI, in many ways, stands at a similar crossroads, inviting us to shape its ethical path.
The IVF story teaches that public engagement matters. Once people recognized that IVF was not just an abstract concept, but a source of joy, relief, and familial connection, resistance softened. Widespread conversations helped set boundaries, guide policy decisions, and implement safeguards. Laws formed around embryo handling, donor anonymity, and treatment access. Different communities struck their own balances, reflecting local moral values and cultural beliefs. In the same manner, AI’s future needs active public involvement. Rather than surrendering AI’s direction to a handful of experts, societies can ask hard questions: How can we prevent AI-driven hiring from amplifying discrimination? What rules should govern AI in healthcare to ensure fairness and accuracy? By drawing on lessons from IVF’s journey, we see that open dialogue and negotiation between citizens, experts, and authorities can forge a path that respects human dignity.
IVF also illustrated how ethical principles must evolve with technological progress. Early concerns centered around the unnatural creation of life, but as IVF matured, new ethical puzzles emerged: genetic screening of embryos, decisions about unused embryos, and opportunities for single parents and same-sex couples to build families. Each turn forced society to revisit its moral compass. Similarly, AI will not remain static. New capabilities—like advanced language models, predictive policing tools, or AI-assisted scientific research—will demand fresh ethical appraisals. The key lesson: as AI pushes the boundaries of what is possible, our ethics must stretch and adapt to keep pace. Instead of fixed, one-time solutions, we need ongoing dialogue, flexible standards, and a readiness to update regulations. This approach ensures that as AI matures, it does so guided by values that reflect a society’s current understanding.
Perhaps most importantly, IVF showed that addressing ethical debates early and earnestly can prevent fear and misunderstanding from dominating public opinion. By allowing multiple voices—clinicians, ethicists, families, religious leaders, and everyday citizens—to join the conversation, IVF regulations emerged that balanced innovation with respect for human life. For AI, this means involving diverse communities now. If we wait until the technology is too widespread or deeply entrenched, it may become harder to correct harmful patterns or reverse biased decisions. Through timely involvement, people can shape AI’s trajectory to honor fairness, uphold privacy, and nurture trust. Just as IVF came to be seen not as a monstrous intervention but a compassionate tool, AI, guided by transparent oversight and inclusive ethics, can become a force that uplifts rather than undermines the societies that choose to embrace it.
Chapter 4: From Hope to Hurdles: Navigating Societal Values, Cultural Norms, and Rapid Technological Adoption .
As AI ripples through cultures worldwide, it encounters countless value systems, traditions, and norms. Some societies might eagerly embrace AI’s efficiency, seeing it as a way to modernize industries and expand knowledge. Others may fear its disruptive potential, worried that AI-powered automation could upend jobs, economies, or established social hierarchies. Consider how differently countries approached IVF decades ago: while some supported the technology as a solution for loving families, others imposed strict limits or bans based on moral or religious views. AI’s adoption may follow a similar path, revealing that no single ethical framework can neatly fit all contexts. Recognizing this diversity helps us understand why global conversations on AI’s governance are challenging. Ultimately, solutions must reflect a tapestry of viewpoints, acknowledging that ethical debates cannot simply be universalized without careful consideration of local sensitivities.
Navigating these differences requires a willingness to listen, learn, and compromise. Imagine a global forum where policymakers, religious leaders, human rights advocates, engineers, business owners, and everyday users gather to discuss AI’s future. Each participant brings unique priorities—some emphasize economic growth, others stress privacy and autonomy, still others focus on justice and equity. Through honest conversation, participants can identify common ground. Perhaps everyone agrees that facial recognition should never be used to target vulnerable minorities, or that healthcare AI must be tested rigorously before deployment. These shared values become anchor points, guiding the development of international guidelines or industry standards. Although reaching consensus is difficult, this process mirrors how IVF regulations arose through sustained debate. The hope is that through careful deliberation, societies can set thoughtful boundaries, ensuring AI’s growth aligns with varied cultural principles.
However, cultural understanding alone isn’t enough. Rapid adoption of AI demands proactive thinking. If we wait until issues become too large—until bias in credit scoring devastates families or AI-driven surveillance erodes civil liberties—the damage could be difficult to undo. Instead, a forward-looking approach encourages scenario planning: imagining different futures and identifying which paths lead to prosperity, fairness, and freedom. Decision-makers can use these insights to craft laws, incentives, and safeguards in advance. This anticipatory approach borrows from how countries learned to manage medical advances over time, shaping policies before crises arose. By doing so, we ensure that AI’s integration occurs with careful intention rather than reckless speed, making it more likely that innovations will serve, rather than harm, the societies embracing them.
A crucial factor in this journey is transparency. Without understanding how AI decisions are made, people can’t meaningfully weigh in or hold systems accountable. Just as IVF clinics operate under clear medical guidelines and oversight, AI developers must explain their tools, methodologies, and goals. Transparency isn’t only about publishing code—it’s about ensuring that non-experts can understand how their data is used or how decisions affecting their lives are reached. This fosters trust, reducing the suspicion that AI is an inscrutable black box controlling human destiny. With clear communication, individuals feel empowered to question outcomes, propose improvements, or challenge unfair practices. When combined with cultural sensitivity, anticipatory governance, and sustained dialogue, transparency becomes another pillar that supports a just and beneficial integration of AI into daily life, ultimately making the technology less alien and more genuinely human-centered.
Chapter 5: Flickering Screens and Hidden Eyes: AI Surveillance, Privacy, and Freedom at Crossroads .
Imagine strolling down a busy street lined with shops, cafés, and offices. Unseen by you, cameras embedded in lampposts and storefronts scan faces, cars, and movements. AI-driven tools match this data against vast databases, predicting behavior, identifying patterns, and even rating trustworthiness. In some places, such technology is a reality rather than a fantasy. AI-powered surveillance can help locate missing people or protect public safety, but it can also stifle freedom, fueling unjust profiling and suppressing political dissent. As AI systems become more adept at analyzing behavior, the question arises: How much surveillance is too much? Finding a balance is tricky. We must weigh the benefits of catching criminals or averting threats against the cost of living under a digital microscope. At its core, this debate asks what kind of society we want to inhabit.
In authoritarian regimes, AI surveillance may serve as a tool of oppression. Governments monitor citizens to silence dissent, filtering public conversations, blocking undesirable information, and scoring individuals on their loyalty. Even in more open societies, corporations leverage similar data-gathering strategies for profit, tracking your clicks, purchases, and browsing habits. When combined with AI’s analytical power, these records allow businesses to predict your desires, influence your buying decisions, and shape your experiences without your explicit knowledge. While not always sinister, this subtle manipulation infringes on personal autonomy, placing corporate interests above individual freedoms. Understanding these implications encourages more nuanced discussions. Where do we draw the line between needed safety measures and invasive intrusion? If we fail to set boundaries, AI surveillance could remodel the public sphere into a place where every action is recorded and judged.
The power of AI surveillance lies partly in its hiddenness. Unlike a police officer patrolling the street, AI can watch silently, tirelessly, and simultaneously in countless locations. This invisibility makes it harder to question. Instead of seeing a uniformed figure, you encounter only your daily routines, unaware that intricate software constantly sifts through your data. Without transparency or accountability, this creates an environment where trust erodes. If people suspect they’re always monitored and rated, they may self-censor, avoiding open debate, protest, or unconventional ideas. Over time, creativity and innovation could wither, replaced by conformity and fear. Balancing these concerns is complex. We cannot ignore genuine benefits—like AI’s potential to detect fraud or warn of epidemics—but we must ensure that these advantages never justify sacrificing fundamental human rights and freedoms we hold dear.
Achieving this balance requires action from many fronts. Policymakers should develop clear legal frameworks that limit data collection and mandate oversight, ensuring surveillance tools aren’t misused. Citizens must stay informed, understanding how their data is gathered and used so they can demand accountability. Ethical designers and engineers can incorporate privacy protections from the start, building systems that secure personal information. Even grassroots movements can advocate for tighter privacy laws and fairer data policies. Collaborative efforts, open forums, and public consultations can guide how far surveillance technology should reach. Just as the debates around IVF shaped how life-creating technology would be regulated and accepted, so too can robust discussions about AI surveillance steer society away from oppressive extremes. By thoughtfully setting safeguards, we can enjoy AI’s advantages without surrendering the personal freedoms we cherish.
Chapter 6: Voices Unheard, Perspectives Needed: How Ordinary People Shape AI’s Evolving Shared Destiny .
Though experts might dominate headlines when discussing AI’s future, ordinary people’s experiences hold invaluable insights. Picture a delivery driver who relies on AI navigation tools to streamline her route. She notices how certain areas are consistently avoided, possibly limiting her business. Her real-world observations reveal that the algorithm’s assumptions could be unfair. Imagine students whose language-learning apps adapt to their difficulties, yet sometimes fail to recognize regional dialects. Their feedback can highlight overlooked cultural nuances. By sharing such perspectives, everyday users bring ground-level understanding to a technology often discussed only in lofty, abstract terms. This is crucial because AI isn’t just an engineer’s puzzle—it’s a living, evolving force in communities. When people speak up about what they see, feel, and fear, they help shape AI’s direction, ensuring it responds to human reality rather than theoretical perfection.
Public input doesn’t only spot flaws; it guides AI toward inclusivity and fairness. Consider a citizen panel meeting to discuss a city’s new AI-driven traffic system. Parents might worry about school crossings, elderly pedestrians about reliable crossing times, and shop owners about ensuring steady customer flow. Their combined voices can prompt changes to the algorithm, making it safer for children, more considerate for seniors, and supportive of local businesses. This collective approach recalls how IVF regulations emerged—not solely from medical experts but from people who cared deeply about human values. Similarly, AI must be refined through dialogues that connect developers with users. By listening to these voices, tech creators gain insights that cannot be gleaned from code alone. It’s a process that grounds innovative technology in everyday life, ensuring AI’s path aligns with broad, human aspirations.
Fostering this dialogue requires making AI understandable. Too often, discussions remain locked behind technical jargon or presented in ways that intimidate non-experts. But if you can learn the basics of a smartphone’s functions or a streaming app’s recommendations, you can also grasp core ideas about AI: it learns from data, spots patterns, and applies these lessons. By demystifying AI, educators, journalists, and community leaders help ordinary people feel confident in raising questions or expressing concerns. When users feel empowered to ask why a certain recommendation appears, why a loan application was denied, or how a face recognition system works, they encourage transparency. Their curiosity pressures companies to explain themselves and justifies regulations that insist on fairness. Over time, this continuous exchange of knowledge transforms people from passive subjects into active contributors steering AI’s direction.
This participatory process doesn’t require everyone to become a coder or an AI researcher. Your lived experiences—whether as a student, worker, artist, caregiver, or farmer—are a form of expertise. They reflect how AI interacts with your realities, informing whether its decisions uplift or hinder. By sharing observations with neighbors, local representatives, or online forums, you add momentum to the push for responsible AI. You can even influence AI indirectly through consumer choices, favoring services that respect your privacy, transparency, and diversity. These actions send signals that society values ethical AI, encouraging companies to adapt. Just as democratic systems rely on every citizen’s voice, AI governance thrives on broad participation. It’s through countless individual contributions, big and small, that AI’s evolving destiny can become something we shape together, ensuring its growth benefits everyone rather than a privileged few.
Chapter 7: Crafting Fair and Inclusive Algorithms: Diverse Teams, Bias-Free Data, and Human Oversight .
At the heart of responsible AI lies a fundamental question: How can we ensure these technologies reflect our best qualities, not our worst? One answer starts with the teams building them. A diverse group of engineers, ethicists, sociologists, and everyday users can spot blind spots more easily. When people from different backgrounds, cultures, and life experiences contribute to AI design, they are more likely to identify biases and prevent them from becoming embedded in systems. Imagine a voice assistant trained only on voices from one region—it might struggle with accents, leaving some users feeling excluded. By involving a multicultural team, developers can address such issues early on, crafting products accessible to broader populations. Diversity in design ensures AI’s benefits aren’t limited to a lucky few but are more evenly shared across society.
However, team diversity is just one piece of the puzzle. Data—the fuel that powers AI—is another critical factor. If historical data mainly represents one gender, one ethnicity, or one socioeconomic class, the AI can inherit biases and reinforce them over time. Overcoming this challenge involves careful data selection, cleansing, and expansion. Developers must think: Are we representing all ages, regions, and walks of life? Are we acknowledging that the world’s complexity cannot be captured by narrow samples? Achieving balanced datasets can be tough, but it’s a vital step to ensure fairness. This process echoes lessons from IVF regulation, where attention to cultural, moral, and individual factors shaped guidelines. For AI, balanced data ensures that its decisions don’t just favor the majority or the familiar, but consider the world’s rich and varied humanity.
Beyond diverse teams and balanced data lies the importance of human oversight. AI can accomplish impressive feats—predicting diseases, optimizing logistics, or assisting in scientific research—but it can also make errors. Sometimes these errors arise from poor data, other times from situations the AI wasn’t trained to handle. Human experts must monitor these systems, ready to step in when something goes wrong. Think of a self-driving car encountering a sudden obstacle it’s never seen before. In that moment, human judgment might be critical. Likewise, a judge relying on AI-generated recommendations must retain the power to question and overrule them if they feel the output is unjust. Human oversight guarantees that we don’t surrender control to an automated process devoid of empathy, critical thinking, or ethical reasoning. It ensures that AI remains our tool, not our master.
All these measures—diverse creators, balanced data, and human oversight—are part of a larger strategy to keep AI aligned with human values. This alignment isn’t automatically guaranteed. It must be built intentionally, updated continuously, and enforced vigilantly. The process resembles pruning a garden: we remove weeds of bias and injustice, nurture seeds of fairness, and shape the growth of AI into something beautiful and sustainable. By embracing these principles, AI can move beyond its shadow side. It can become a technology that lifts people up rather than pushing them down. This demands ongoing effort, public pressure, and thoughtful policies. Yet, as history shows with IVF and other major scientific breakthroughs, societies can find ways to guide technology toward a future that respects dignity, promotes fairness, and enhances the well-being of all.
Chapter 8: Co-Creating Tomorrow’s Intelligent Tools: Embracing Active Participation to Steer AI’s Course Forward .
As we peer ahead, it’s clear that AI’s future isn’t set in stone. Instead, it’s a canvas waiting to be painted by all of us who live with, benefit from, and challenge these technologies. While industry leaders and governments influence AI’s trajectory, no single authority should hold absolute sway. Your voice, along with millions of others, can shape how AI tools evolve. This might seem like a grand idea, but it can start small. Simply questioning why a recommendation popped up on your screen or why certain ads follow you is the first brushstroke. Over time, these everyday inquiries accumulate, pushing developers, regulators, and communities to respond. Just as public debates steered IVF into a more ethically navigated practice, collective involvement can ensure AI develops into a force for good, guided by human values rather than narrow interests.
Embracing active participation means finding accessible channels for your input. Maybe you join a local workshop on AI and ethics, share your thoughts online, or support initiatives that promote digital literacy. Maybe you engage with policymakers, urging them to adopt clear rules about data handling and algorithmic transparency. Public consultations, citizen assemblies, and community forums can provide platforms for meaningful exchange. Over time, these efforts accumulate into a powerful counterweight against the idea that experts know best. Instead, they affirm that lived experiences matter and that ethical technology must reflect the wisdom and hopes of ordinary people. Your involvement is like a feedback loop, continuously correcting AI’s course, making sure it truly serves human progress. As more individuals participate, we move closer to a future where AI thrives under the steady guidance of collective insight.
Consider how you can help shape such a future. Perhaps you’ll support privacy-friendly apps, indirectly encouraging companies to respect user data. Maybe you’ll demand clearer explanations when an AI tool influences a decision about your credit score or university admissions. Each act of engagement, big or small, adds weight to the idea that AI must earn our trust. And earning trust means delivering fairness, acknowledging mistakes, and accommodating different cultural values. Over time, these incremental changes accumulate, just as small streams feed mighty rivers. Eventually, policymakers respond by creating robust frameworks, companies rethink their strategies to emphasize ethics, and researchers design AI systems more transparently. It won’t happen overnight, but consistent participation ensures AI’s evolution won’t drift aimlessly. It will be anchored by public understanding, collective scrutiny, and a shared vision of human-centered progress.
Ultimately, co-creating tomorrow’s intelligent tools is about believing in our ability to influence technology’s course. By remembering the lessons of IVF, we know controversial breakthroughs can be guided responsibly when many voices contribute. By studying AI’s shadow side, we see the dangers of ignoring public input. By embracing a culture of inclusivity, fairness, and accountability, we give ourselves the power to chart AI’s path. This means showing up when difficult questions arise, not shying away from ethical debates just because they are complex. It means caring about the data we share, the regulations we support, and the communities we build. If we accept this responsibility, we can welcome AI as a partner in solving problems, expanding knowledge, and enriching lives—an intelligent ally shaped by humans who dared to engage, question, and dream of a better future.
All about the Book
Explore the transformative power of AI in ‘AI Needs You’ by Verity Harding. This compelling read unpacks innovations, ethical concerns, and the future of technology, making it essential for anyone interested in AI’s impact on society.
Verity Harding is a visionary tech expert and author, renowned for her insights into artificial intelligence and its societal implications, inspiring readers to engage with technology responsibly.
Data Scientists, Software Developers, Tech Entrepreneurs, Ethics Consultants, Business Strategists
Technology Enthusiast, Reading Science Fiction, Participating in Hackathons, Writing about Tech Trends, Attending AI Conferences
Ethical Implications of AI, AI Accessibility, Impact of AI on Employment, Sustainability in Technology
The future of AI is not just about technology; it’s about the choices we make today.
Elon Musk, Sheryl Sandberg, Neil deGrasse Tyson
Best Technology Book of the Year, Innovation in Literature Award, Readers’ Choice Award
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