In a world buzzing with visions of humanoid robots strolling through our homes and artificial intelligence reshaping every corner of society, it’s easy to get swept up in the excitement. Billions of dollars flood into startups promising autonomous everything, from self-driving cars to AI companions that think like us. But what if the real revolution isn’t in flashy demos but in quiet, human-centered innovations that solve everyday problems? That’s the grounded perspective offered by Rodney Brooks, the legendary founder of iRobot, creator of the Roomba vacuum, and a veteran of robotics and AI. In a recent interview with tech journalist Om Malik, Brooks cuts through the hype, sharing insights from his decades-long career that blend optimism with realism. Drawing from his journey from a working-class kid in Australia to MIT professor and serial entrepreneur, Brooks argues that true progress in tech comes slowly, messily, and often in unsexy forms. His message? Humans will thrive alongside machines, but only if we temper expectations and focus on what actually works.
Brooks’ story begins in Adelaide, South Australia, where he grew up in the 1950s in a family without much formal education. By age four, his innate mathematical talent earned him the nickname “the professor” from his parents, who nurtured his curiosity with books on electricity and computers. These sparked a lifelong passion for building circuits and dreaming of robots, even as he tinkered with wires and batteries in a time when personal computers were science fiction. This hands-on ethos carried him to MIT, where he became a professor and pioneered work in robotics, including a seminal 1985 paper on Simultaneous Localization and Mapping (SLAM), a technique that allows robots to navigate and build maps of their environments in real time. SLAM, which started as a probabilistic method for merging observations, evolved through decades of refinements by countless researchers, highlighting Brooks’ key lesson: groundbreaking ideas demand relentless engineering to become reality. What began as a theoretical fix for mobile robots now powers everything from autonomous vehicles to warehouse bots, but it took 40 years of incremental advances in computation and sensors to get there.
Today, at Robust.AI, Brooks channels that pragmatism into practical tools like the Carta cart, a smart warehouse assistant that exemplifies his human-first approach. Picture vast fulfillment centers where workers trudge 30,000 steps a day, equivalent to 15 miles, pushing heavy carts loaded with orders. Human hands excel at picking items, far surpassing any robot’s grasp, so Carta doesn’t try to replace them. Instead, it uses cameras and simple AI to navigate aisles, locate products, and reduce physical strain. When a worker finishes a task, they say “done,” and the cart autonomously delivers the load, avoiding ladders or politely yielding to people while rerouting around immovable obstacles like pallets. This isn’t glamorous; it’s not a humanoid butler from a sci-fi flick. But it’s reliable, easing cognitive and physical loads in a $4 trillion market. Brooks notes that his ventures, from Roomba’s simple disc design to Rethink Robotics’ teachable arms, have always empowered humans, letting them grab a handle to take control like a “Superman” with amplified strength. In an era of automation anxiety, Carta shows how tech can augment workers, making jobs more efficient without erasing them.
Yet, Brooks is quick to pour cold water on the humanoid robot craze that’s captivating investors and headlines. The human form, he explains, makes a seductive promise: a machine that can do anything we can. But appearance deceives. The Roomba’s low-profile disc promised only floor cleaning, not window washing, setting realistic expectations. Humanoids, by contrast, evoke unlimited potential, fueling hype despite glaring limitations. We still can’t replicate the dexterity of human hands, an evolutionary accident stemming from ancient sea creatures with five-boned fins. Future manipulators might resemble sea anemones with tentacles and cilia, Brooks muses, better suited for tasks than mimicking our biology. This mismatch explains why flashy demos dazzle in controlled settings but falter in the “messy reality” of the real world. Take autonomous vehicles: Brooks attended his first talk on them in 1979, and by 1990, prototypes zipped along highways. Yet, nearly half a century later, services like Waymo operate in limited areas and still rely on human interventions, often clumsily executed. Brooks is skeptical of bolder claims, like Tesla’s robotaxi ambitions, which he sees as more charade than breakthrough, complete with remote safety drivers. The lesson from PCs and smartphones, which took decades to mature from clunky prototypes to seamless tools, is clear: true adoption demands time to conquer the “long tail” of unpredictable scenarios.
This patience extends to artificial intelligence, where Brooks urges a rethink of education to match the technology’s demands. Generative AI, he admits, surprised even him with its language prowess, challenging philosophical ideas like John Searle’s Chinese Room thought experiment, which argued machines couldn’t truly understand without consciousness. When Brooks fed Chinese characters about artist Ai Weiwei into ChatGPT and got a coherent biography back, it upended assumptions about intelligence. But rather than fearing AGI (artificial general intelligence) as an imminent overlord, Brooks views these tools as sophisticated information interfaces, not brain duplicates. He warns against overhyping them as paths to godlike machines, suggesting AGI might be centuries away because we may be using the wrong metaphors, like assuming computation alone mirrors human thought. Just as Isaac Newton wasted years on alchemy, unaware it required nuclear physics, we might be barking up the wrong tree with purely computational models of mind. Instead, Brooks advocates for diverse educational paths, distinguishing intellectual pursuits from job training. He praises systems like Germany’s, with targeted diplomas for trades, over one-size-fits-all degrees that regurgitation facts without context. In a question-driven AI era, success hinges on asking why, connecting dots across disciplines, much like Brooks’ MIT students who only grasped concepts when building real systems. Journalism, Malik adds, taught him more about tech’s human impact than any classroom, emphasizing practical learning over rote answers.
Looking to the future, Brooks envisions a transformed manufacturing landscape, one that challenges America’s nostalgia for factory jobs while embracing global shifts. With China dominating scaled production, as seen in Brooks’ partnership with Foxconn for Robust.AI robots, the U.S. lags in making things. But emerging technologies like 3D printing could disrupt this, turning supply chains from component networks into raw material flows, democratizing production much like mobile payments leapfrogged in developing nations. AI-driven material science, predicting properties without endless testing, promises further innovation. Brooks provocatively predicts that by century’s end, Nigeria, with its booming population and pressing problems, will become a tech epicenter, much as China’s scale propelled its rise. This isn’t doom for the West; it’s a call to adapt. Politicians tout manufacturing jobs for votes, yet, as Brooks observed at a Brown University talk, elite parents rarely want their kids in factories. Real progress, he insists, lies in rethinking work: factories like BYD’s in China, vast as San Francisco but staffed by just 40,000 amid robots, signal a future where automation creates new roles, not just eliminates old ones. Quantum computing, too, will likely shine first in simulating physical systems, aiding materials and fusion energy, rather than revolutionizing classical tasks overnight.
Brooks describes himself as a realist, having weathered multiple AI hype cycles where trends like neural networks rose and fell, only to return improved. The current boom, fueled by massive investments, will yield breakthroughs, but much will be wasted, leaving overbuilt data centers ripe for the next innovative “kid in obscurity” to repurpose, just as excess fiber optics enabled Google’s search empire. His vision is human-centered: robots and AI should serve us, not duplicate us, in forms optimized for efficiency, not anthropomorphic appeal. This pragmatic optimism counters both breathless hype and dystopian fears, reminding us that technology’s true value emerges slowly, enhancing lives in the messy real world.
References
- IEEE Spectrum on SLAM Technology: https://spectrum.ieee.org/slam-robotics-navigation
- The Verge on Waymo’s Autonomous Vehicle Development: https://www.theverge.com/2023/7/12/23792594/waymo-self-driving-car-expansion-san-francisco-los-angeles
- World Bank Projections on Nigeria’s Population and Economy: https://www.worldbank.org/en/country/nigeria/publication/nigeria-economic-update
- MIT Technology Review on 3D Printing in Manufacturing: https://www.technologyreview.com/2022/05/25/1052664/3d-printing-future-manufacturing/
- Nature on AI in Materials Science: https://www.nature.com/articles/d41586-023-02592-5