If you Google "care bots", you'll see an army of robot butlers and nurses, taking vital signs in hospitals, handing red roses to patients, serving juice to the elderly. For the most part these are just sci-fi fantasies. The care bots that already exist come in a different guise. These care bots look less like robots and more like invisible pieces of code, webcams and algorithms. They can control who gets what test at the doctor's office or how many care hours are received by a person on Medicaid. Increasingly, human caregivers work through and alongside automated systems that set forth recommendations, manage and surveil their labor, and allocate resources.

With the ever-increasing volume, variety, and velocity of available data, scientific disciplines have provided us with advanced mathematical tools, processes, and algorithms enabling us to use this data in meaningful ways. Data science (DS), machine learning (ML), and artificial intelligence (AI) are three such disciplines. A question that frequently comes up in many data-related discussions is what the difference between DS, ML, and AI is? Can they be compared? Depending on who you talk to, how many years of experience they have had, and what projects they have worked on, you may get widely different answers to the above question. In this blog, I will attempt to answer this based on my research, academic, and industry experience; and having facilitated numerous conversations on the topic.

"He's my baby," she tells me over Zoom, holding up a puppy to the camera. I laugh and say, "Who's a good robot?" Lucky barks again, and the sound is convincing, as if it's coming from a real dog. He's got a tail that wags, eyes that open and close, and a head that turns to face you when you talk. Under his synthetic golden fur, he has sensors that respond to your touch and a heartbeat you can feel. LeRuzic, who lives in a rural area outside Albany, is fully aware that her pet is a robot. But ever since she got him in March, he's made her feel less lonely, she says.

With the ever-increasing volume, variety, and velocity of available data, scientific disciplines have provided us with advanced mathematical tools, processes, and algorithms enabling us to use this data in meaningful ways. Data science (DS), machine learning (ML), and artificial intelligence (AI) are three such disciplines. A question that frequently comes up in many data-related discussions is what the difference between DS, ML, and AI is? Can they even be compared? Depending on who you talk to, how many years of experience they have had, and what projects they have worked on, you may get widely different answers to the above question. In this blog, I will attempt to answer this based on my research, academic, and industry experience; and having facilitated numerous conversations on the topic.

John Markoff covered technology for The New York Times for 28 years. He is currently a Berggruen Institute fellow at Stanford's Center for Advanced Study in the Behavioral Sciences. "You don't get it," he said. "In China, they'll be lucky if the robots come just in time." For the previous decade, I had been reporting on the rapid expansion of new AI technologies into the workplace and how they were about to displace not only blue-collar manufacturing jobs but, for the first time, white-collar knowledge workers like lawyers and doctors. But that night, Kahneman alerted me to a largely unexamined aspect of the AI-fueled automation debate.

"As my father lost the ability to do things for himself, my mother would give him gentle prompts to keep him on track," recalled Kautz, associate professor in the University of Washington's Department of Computer Science & Engineering. "So at a stage of the disease where, according to the clinical scales, it would seem he couldn't do anything for himself, he could still perform many of the functions of life. He could shower, get dressed, and so forth because my mother would monitor him and give a prompt when needed." It's a recollection that has guided Kautz in initiating a research effort at the UW to explore ways in which computer science can compensate for diminished mental capacity. The Assisted Cognition Project is a collaborative effort by the UW, Intel Computers and Elite Care, a private company developing a state-of-the-art retirement community in the Portland area that utilizes so-called ubiquitous computing to keep tabs on residents' needs.

To address the burgeoning "loneliness epidemic" and the demands of an aging population, some think that we should deploy robotic caregivers. A new ad titled "B.E.N. (Biologically Engineered Nursing)," however, suggests that this is a dreadful idea. This five-minute ad was produced by the Society of Saint-Vincent-de-Paul (SSVP), an international Catholic voluntary organization that provides assistance to those in need. When the short story opens, we see a woman, Claudine, dancing with her robotic caregiver, BEN. From there, we travel back to the previous day, and we come to see how the pair came to their gloomy embrace.