Tom Simonite in MIT Technology Review: “Software trained to know the difference between an honest mistake and intentional vandalism is being rolled out in an effort to make editing Wikipedia less psychologically bruising. It was developed by the Wikimedia Foundation, the nonprofit organization that supports Wikipedia. One motivation for the project is a significant decline in the number of people considered active contributors to the flagship English-language Wikipedia: it has fallen by 40 percent over the past eight years, to about 30,000. Research indicates that the problem is rooted in Wikipedians’ complex bureaucracy and their often hard-line responses to... (More >)
Robots Will Make Leeds the First Self-Repairing City
Emiko Jozuka at Motherboard: “Researchers in Britain want to make the first “self-repairing” city by 2035. How will they do this? By creating autonomous repair robots that patrol the streets and drainage systems, making sure your car doesn’t dip into a pothole, and that you don’t experience any gas leaks. “The idea is to create a city that behaves almost like a living organism,” said Raul Fuentes, a researcher at the School of Civil Engineering at Leeds University, who is working on the project. “The robots will act like white cells that are able to identify bacteria or viruses... (More >)
How Satellite Data and Artificial Intelligence could help us understand poverty better
Maya Craig at Fast Company: “Governments and development organizations currently measure poverty levels by conducting door-to-door surveys. The new partnership will test the use of AI to supplement these surveys and increase the accuracy of poverty data. Orbital said its AI software will analyze satellite images to see if characteristics such as building height and rooftop material can effectively indicate wealth. The pilot study will be conducted in Sri Lanka. If successful, the World Bank hopes to scale it worldwide. A recent study conducted by the organization found that more than 50 countries lack legitimate poverty estimates, which limits... (More >)
The importance of human innovation in A.I. ethics
John C. Havens at Mashable: “….While welcoming the feedback that sensors, data and Artificial Intelligence provide, we’re at a critical inflection point. Demarcating the parameters between assistance and automation has never been more central to human well-being. But today, beauty is in the AI of the beholder. Desensitized to the value of personal data, we hemorrhage precious insights regarding our identity that define the moral nuances necessary to navigate algorithmic modernity. If no values-based standards exist for Artificial Intelligence, then the biases of its manufacturers will define our universal code of human ethics. But this should not be their... (More >)
Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots
Book description: “Robots are poised to transform today’s society as completely as the Internet did twenty years ago. Pulitzer prize-winning New York Times science writer John Markoff argues that we must decide to design ourselves into our future, or risk being excluded from it altogether. In the past decade, Google introduced us to driverless cars; Apple debuted Siri, a personal assistant that we keep in our pockets; and an Internet of Things connected the smaller tasks of everyday life to the farthest reaches of the Web. Robots have become an integral part of society on the battlefield and the... (More >)
How Africa can benefit from the data revolution
Neil Lawrence in The Guardian: “….The modern information infrastructure is about movement of data. From data we derive information and knowledge, and that knowledge can be propagated rapidly across the country and throughout the world. Facebook and Google have both made massive investments in machine learning, the mainstay technology for converting data into knowledge. But the potential for these technologies in Africa is much larger: instead of simply advertising products to people, we can imagine modern distributed health systems, distributed markets, knowledge systems for disease intervention. The modern infrastructure should be data driven and deployed across the mobile network.... (More >)
The Future of the Professions: How Technology Will Transform the Work of Human Experts
New book by Richard Susskind and Daniel Susskind: “This book predicts the decline of today’s professions and describes the people and systems that will replace them. In an Internet society, according to Richard Susskind and Daniel Susskind, we will neither need nor want doctors, teachers, accountants, architects, the clergy, consultants, lawyers, and many others, to work as they did in the 20th century. The Future of the Professions explains how ‘increasingly capable systems’ – from telepresence to artificial intelligence – will bring fundamental change in the way that the ‘practical expertise’ of specialists is made available in society. The... (More >)
Algorithms and Bias
Q. and A. With Cynthia Dwork in the New York Times: “Algorithms have become one of the most powerful arbiters in our lives. They make decisions about the news we read, the jobs we get, the people we meet, the schools we attend and the ads we see. Yet there is growing evidence that algorithms and other types of software can discriminate. The people who write them incorporate their biases, and algorithms often learn from human behavior, so they reflect the biases we hold. For instance, research has shown that ad-targeting algorithms have shown ads for high-paying jobs to... (More >)
A Visual Introduction to Machine Learning
R2D3 introduction: “In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions. Keep scrolling. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco…./ Machine learning identifies patterns using statistical learning and computers by unearthing boundaries in data sets. You can use it to make predictions. One method for making predictions is called a decision trees, which uses a series of if-then statements to identify boundaries and define patterns in the... (More >)
AI tool turns complicated legal contracts into simple visual charts
Springwise: “We have seen a host of work related apps that aim to make tedious office tasks more approachable — there is a plugin that can find files without knowing the title, and a tracking tool which analyzes competitors online strategies. Joining this is Beagle, an intelligent contract analysis tool which provides users with a graphical summary of lengthy documents in seconds. It is a time-saving tool which translates complicated documents from elusive legal language into comprehensive visual summaries. The Beagle system is powered by self-learning artificial intelligence which learns the client’s preferences and adapts accordingly. Users begin by... (More >)
