From Star Trek's Data and 2001's HAL to Columbus Day's Skippy the Magnificent, pop culture is chock full of fully conscious AI who, in many cases, are more human than the humans they serve alongside. But is all that self-actualization really necessary for these synthetic life forms to carry out their essential duties? In his new book, How to Grow a Robot: Developing Human-Friendly, Social AI, author Mark H. Lee examines the social shortcomings of the today's AI and delves into the promises and potential pitfalls surrounding deep learning techniques, currently believed to be our most effective tool at building robots capable of doing more than a handful of specialized tasks. In the excerpt below, Lee argues that the robots of tomorrow don't necessarily need -- nor should they particularly seek out -- the feelings and experiences that make up the human condition. Although I argue for self-awareness, I do not believe that we need to worry about consciousness.

For a field that was not well known outside of academia a decade ago, artificial intelligence has grown dizzyingly fast. Tech companies from Silicon Valley to Beijing are betting everything on it, venture capitalists are pouring billions into research and development, and start-ups are being created on what seems like a daily basis.

For a field that was not well known outside of academia a decade ago, artificial intelligence has grown dizzyingly fast. Tech companies from Silicon Valley to Beijing are betting everything on it, venture capitalists are pouring billions into research and development, and start-ups are being created on what seems like a daily basis. If our era is the next Industrial Revolution, as many claim, A.I. is surely one of its driving forces. It is an especially exciting time for a researcher like me. When I was a graduate student in computer science in the early 2000s, computers were barely able to detect sharp edges in photographs, let alone recognize something as loosely defined as a human face. But thanks to the growth of big data, advances in algorithms like neural networks and an abundance of powerful computer hardware, something momentous has occurred: A.I. has gone from an academic niche to the leading differentiator in a wide range of industries, including manufacturing, health care, transportation and retail.

For a field that was not well known outside of academia a decade ago, artificial intelligence has grown dizzyingly fast. Tech companies from Silicon Valley to Beijing are betting everything on it, venture capitalists are pouring billions into research and development, and start-ups are being created on what seems like a daily basis. If our era is the next Industrial Revolution, as many claim, A.I. is surely one of its driving forces. It is an especially exciting time for a researcher like me. When I was a graduate student in computer science in the early 2000s, computers were barely able to detect sharp edges in photographs, let alone recognize something as loosely defined as a human face.