Much virtual ink gets spilled each week enumerating the many horrors that could be ours in an AI-filled world, but top researchers in the field are already thinking ahead and making plans to ensure none of that happens. In particular, the importance of making artificial intelligence "human-aware" has come to be viewed as a top imperative for the field, earning it special status as an official theme of the International Joint Conference on Artificial Intelligence taking place this week in New York. "It's crucial that we design smart systems to work well with people," said Harvard professor Barbara Grosz during a panel discussion at the conference on Tuesday. AI should be a complement for human intelligence, not a replacement, Grosz said. As such, an ability to understand who it's interacting with and respond accordingly -- such as by explaining the decisions it makes -- is essential.

Even though we are social animals, managing relationships is not an easy task. Everyday interactions with people around us can become tricky as stress, anger, exhaustion, and other emotions start affecting the way we and others react to different situations. The inability to correctly "read" other people and understand how we should treat them causes disagreements and even fights. All these struggles have led to numerous investigations about humans' interactions, resulting in the creation of a term researchers Peter Salavoy and John Mayer coined Emotional Intelligence (EQ or EI). Recently, conversations about the relationship between EI and artificial intelligence have developed.

The Internet of Things will create a vast surge in the amount of data that we – and our devices – generate. To make sense of this trove of information will require the use of algorithms and artificial intelligence by researchers, firms, and government. Digital sifting creates both promise and peril, and is certain to clash with important social norms. For example, it may force us to revisit norms around privacy, ownership, prediction, and the public-private boundary. The Section on Internet and Computer Law welcomes submissions for papers about this clash.

Much virtual ink gets spilled each week enumerating the many horrors that could be ours in an AI-filled world, but top researchers in the field are already thinking ahead and making plans to ensure none of that happens. In particular, the importance of making artificial intelligence "human-aware" has come to be viewed as a top imperative for the field, earning it special status as an official theme of the International Joint Conference on Artificial Intelligence taking place this week in New York. "It's crucial that we design smart systems to work well with people," said Harvard professor Barbara Grosz during a panel discussion at the conference on Tuesday. Nominate your analytics project today! AI should be a complement for human intelligence, not a replacement, Grosz said.

It is the nature of humankind to constantly strive toward innovation and bring forth new inventions. Creativity, imagination and conscious reflection are distinguishing features of the human brain which cannot be copied by machines. However, the use of neuronal networks in machines such as AlphaGO is a prime example that demonstrates the extraordinary speed of development in the area of artificial intelligence (AI). The research and development relevant to AI represents a truly remarkable achievement in human culture. In the years ahead intelligent computers will improve the quality of life: They will diagnose illnesses, recommend therapies, protect the environment, support education and transform the way we work.

At the International Symposium on Biomedical Imaging in Prague, a Harvard-based artificial intelligence system won the Camelyon16 challenge, a competition comprised of participants introducing their individual AI systems and its ability to facilitate automated lymph node metastasis diagnosis. Referred to as PathAl, the computing system identifies cancerous cells through a mechanism referred to as deep learning--an algorithmic technique that accumulates copious amounts of unstructured data and organizes it into clusters, before analyzing it for patterns. Deep learning is predominately utilized in speech recognition systems like Apple's Siri and Microsoft's Cortana. According to one of the challenge's organizers, Jeroen van der Laak of Radboud University Medical Center in Netherlands, the technology featured in the competition went "way beyond" his expectations, as the AI's accuracy proved strikingly close to that of human beings. In addition, van der Laak said AI technology has the propensity to intrinsically redefine the way histopathological images are handled in the medical community.

Everyone who gets going in Machine Learning (and Deep Learning) gets overwhelmed by the plethora of MOOCs available. Here, I try to give a comprehensive survey of such courses available freely on the internet. You can take this post as an complementary to this and this previous posts. I will try to highlight some important pointers such as the difficulty of the courses, the correct order in which these should to be completed, the right audience for these courses. You will get a feel of how these courses give you a stack of skills in your arsenal and how you can use them to develop practical machine learning systems.

Jeff Lesser, Twitter's Head of Social Customer Service, at the recent Corporate Social Media Summit New York said that customer service is the top reason why people follow brands on Twitter. Using social for customer care provides users with personalized service and is a great opportunity for brands to improve their image. Personalized customer service is harder to create with chatbots and this has created a large resistance to their growing popularity. Chatbots, better known as bots, are computer programs that conduct a conversation with auditory and/or textual methods. These programs attempt to mirror the personality and knowledge of a human.

Access Facebook from the western half of North America and there's a good chance your data will be pulled from a computer cooled by the juniper- and sage-scented air of central Oregon's high desert. In the town of Prineville, home to roughly 9,000 people, Facebook stores the data of hundreds of millions more. Rows and rows of computers stand inside four giant buildings totaling nearly 800,000 square feet, precisely aligned to let in the dry and generally cool summer winds that blow in from the northwest. The aisles of stacked servers with blinking blue and green lights make a dull roar as they process logins, likes, and LOLs. Facebook has lately added some new machines to the mix in Prineville.

Artificial intelligence is making miracles happen. A group of researchers at Massachusetts Institute of Technology (MIT) recently developed an AI that predicts social interactions. The core algorithm of their research is able to predict whether a person will go for a hug, handshake, high-five, or kiss. Like every AI, this algorithm also needs some data to train itself. The researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) used television shows like "Desperate Housewives" and "The Office" to train the algorithm.