Modern AI-powered robots are showcasing impressive capabilities, yet researchers indicate they are still years from replacing humans due to their inability to adapt to changing conditions. According to Cointelegraph, AI robotics company Figure recently demonstrated humanoid robots performing basic tasks like cleaning, while a group of robots worked for nine consecutive days sorting packages, sparking discussions on the potential for robots to replace human jobs.
Oliver Obst, an associate professor of robotics at the University of New South Wales, highlighted that repetitive jobs in structured environments are most at risk of automation. However, he noted that humanoid robots are unlikely to see widespread deployment soon, as they are not more efficient or less error-prone than existing robotic manufacturing methods. Obst emphasized that robots face challenges with reliability, speed, safety, cost, and recovery from unexpected situations, particularly in environments requiring more variation and judgment than package sorting.
Despite advancements, Obst believes that mass replacement by humanoid robots is not imminent. Instead, selective automation of specific tasks is more likely. While AI software is rapidly impacting information work, physical robots face greater challenges. In a recent demonstration, a human worker outperformed a team of Figure's robots in sorting packages, highlighting the current limitations of robotic efficiency.
Markus Levin, co-founder of decentralized data network XYO, acknowledged that AI models and automation software excel in repetitive tasks but require charging, maintenance, and supervision. A report from the International Federation of Robotics noted a doubling in global demand for factory robots over the past decade, with warehouses and logistics being key growth areas. Levin believes that broad human replacement remains years away due to barriers such as reliability, safety, regulation, infrastructure costs, and trust.
Dr. Francisco Cruz Naranjo, a senior lecturer at the University of New South Wales, stated that robots are highly efficient in controlled environments but struggle in dynamic settings. He noted that while robots excel in repetitive tasks, humans are better at adapting to changing conditions. Naranjo suggested that the replacement of repetitive jobs in less static settings depends on research advancements and societal adaptation to robot-friendly spaces.
Both Naranjo and Obst see potential benefits in a mass rollout of robots, such as improving work-life balance and addressing workforce shortages in dangerous environments. However, they caution that societal implications, such as the impact on economies built around individual wages, need careful consideration. Obst warned that while robots could make dangerous work safer, they might also lower the perceived cost of conflict, posing ethical challenges.
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