Elon Musk's recent announcement of an upcoming Tesla Bot -- complete with a human form, "human-level hands" and a characteristically optimistic delivery date -- has garnered a healthy serving of criticism for good reason. Among other capabilities, Musk says, the robot will eventually be capable of running errands such as going to the grocery store alone. Boston Dynamics, which has developed the most advanced humanoid robot ever created, has spent more than a decade working on its Atlas platform. While progress has been impressive, with Atlas running, jumping and even dancing in front of tens of millions of YouTube viewers, the company is quick to acknowledge that the robot is a long way from performing complex tasks autonomously. One of the best examples of evolutionary robotics potential -- and unfulfilled promise -- goes as far back as 2010 to a study published in the PLOS Biology journal.
Rapid developments in evolutionary computation, robotics, 3D-printing, and material science are enabling advanced systems of robots that can autonomously reproduce and evolve. The emerging technology of robot evolution challenges existing AI ethics because the inherent adaptivity, stochasticity, and complexity of evolutionary systems severely weaken human control and induce new types of hazards. In this paper we address the question how robot evolution can be responsibly controlled to avoid safety risks. We discuss risks related to robot multiplication, maladaptation, and domination and suggest solutions for meaningful human control. Such concerns may seem far-fetched now, however, we posit that awareness must be created before the technology becomes mature.
This article provides an overview of evolutionary robotics research where evolution takes place in a population of robots in a continuous manner. Ficici et al. (1999) coined the phrase embodied evolution for evolutionary processes that are distributed over the robots in the population to allow them to adapt autonomously and continuously. As robotics technology becomes simultaneously more capable and economically viable, individual robots operated at large expense by teams of experts are increasingly supplemented by collectives of robots used cooperatively under minimal human supervision (Bellingham and Rajan, 2007), and embodied evolution can play a crucial role in enabling autonomous online adaptivity in such robot collectives.
The biobot developed at the University of Illinois at Urbana-Champaign couples engineered skeletal muscle tissue to a 3D printed flexible skeleton. Although robotic humanoids now perform backflips and autonomous drones fly in formation, even the most advanced robots are relatively primitive when compared with living machines. The running, jumping, swimming, and flying creatures that cover our planet's surface have long inspired engineers. Yet a subset of researchers are not just taking tips from living creatures. These roboticists, computer scientists, and bioengineers are combining artificial materials with living tissue, or making machines entirely from living cells.
Worms, mammals, even bees do it. Every living thing on Earth replicates, whether that be asexually (boring) or sexually (fun). Robots do not do it: The machines are steely and very uninterested in reproduction. But perhaps they can learn. Scientists in a fascinating field known as evolutionary robotics are trying to get machines to adapt to the world, and eventually to reproduce on their own, just like biological organisms.