Artificial Intelligence, or AI, is a branch of computer science that has been important since 1930s when the first computer was built. We've seen many AI applications in both the social and technological areas of our life over the years, yet most people are still unaware of a large portion of this fast-developing subject. We'll go through 7 facts you didn't know about Artificial Intelligence that might have an immediate impact on your life. Do you ever wonder why you have to solve so many CAPTCHAs to prove your identity? Sir Alan Turing created a test in 1950 to identify whether the user performing the exam is a machine or a human.

There are many recent examples of Artificial Intelligence (AI) systems being used for vulnerable people in humanitarian and disaster response contexts, with serious ethical and security-related implications. In particular, vulnerable populations are put at further risk through biases inherently built into AI systems. There are security concerns regarding their personal information being exposed and even used for persecution purposes. Yet rarely do they have a choice when it comes to the consent of surrendering such information. Now, as AI adoption grows rapidly, this report aims to develop AI principles and recommendations that would be specific to vulnerable people in the humanitarian field.

How to engage with a vibrant community of like-minded learners. How to develop and present a final programming project. The entry-level course is taught by David J. Malan and the computer science learners get to learn the following programming languages through this course - C, PHP, and JavaScript plus SQL, CSS, and HTML. What makes this course more interesting is that the problem sets included in the course curriculum are inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. Mentioned below are important details of the course.

Members of the National Association of Insurance Commissioners (NAIC) have agreed unanimously to adopt an Artificial Intelligence Guiding Principles. The NAIC's AI Working Group based the document on a set of AI principles developed by the Organisation for Economic Co-operation and Development (OECD). The United States is one of the 42 countries that has adopted the OECD AI principles. The NAIC is a Kansas City, Missouri-based group for the top insurance regulators in the states, the District of Columbia and U.S. territories. At the NAIC, regulators and representatives for consumer groups have said careful oversight of AI-based systems is important, because of concerns that insurers or other entities could use AI systems to hide illegal forms of discrimination, such as race-based discrimination.

An automated service will no longer label people as male or female, according to a report from Business Insider. Google's Cloud Vision API, a "computer vision" product that has the ability to "[a]ssign labels to images and quickly classify them into millions of predefined categories," might be making some changes to two specific labels. Business Insider claimed to have seen a Feb. 20 email from Google to developers, which stated that the company would avoid using gendered labels for its image tags. Business Insider claimed that this was a direct quote from the email: "Given that a person's gender cannot be inferred by appearance, we have decided to remove these labels in order to align with the Artificial Intelligence Principles at Google, specifically Principle #2: Avoid creating or reinforcing unfair bias." In the Artificial Intelligence Principles published by Google AI, Principle #2 states: "We will seek to avoid unjust impacts on people, particularly those related to sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability, and political or religious belief."

Artificial Intelligence principles define social and ethical considerations to develop future AI. They come from research institutes, government organizations and industries. All versions of AI principles are with different considerations covering different perspectives and making different emphasis. None of them can be considered as complete and can cover the rest AI principle proposals. Here we introduce LAIP, an effort and platform for linking and analyzing different Artificial Intelligence Principles. We want to explicitly establish the common topics and links among AI Principles proposed by different organizations and investigate on their uniqueness. Based on these efforts, for the long-term future of AI, instead of directly adopting any of the AI principles, we argue for the necessity of incorporating various AI Principles into a comprehensive framework and focusing on how they can interact and complete each other.

We're in a golden age for hollow corporate statements sold as high-minded ethical treatises. Last year, in the thick of its fake news scandal, Facebook released a 5,000-word document outlining, well, I'm still not sure exactly. The letter attempted to pull the company out of its public opinion black hole by posing probing questions, including the head-scratcher: "How do we help people build supportive communities that strengthen traditional institutions in a world where membership in these institutions is declining?" The answers were generally of the "build more Facebook" variety. It was a masterstroke in corporate pablum, though not so masterful that it saved the company from the onslaught of bad press.