When you think about Artificial Intelligence (AI) and war, you might find yourself thinking about killer robots, like those we have seen in movies such as The Terminator. In reality, AI and warfare looks quite different from these popularized images, and today we see many countries around the world exploring the use of AI and implementing AI systems into their militaries and defense programs. With this increased interest in AI, there has also been a growing debate about the ethics and legality of using AI in warfare. While there are many concerning aspects about AI being utilized in warfare, one that is particularly troubling, but has also received less attention, is that of biased AI systems. Certain lessons can be learnt by looking at examples of biased AI in non-military settings. It has become increasingly clear from a number of investigations and studies that the biases that exist within our society will also become embedded into AI.

Some image recognition programs would not recognize this image as a bride. But not all brides wear white. Bias and discrimination are often used interchangeably. But they are not the same. Bias is a point of view or a preference for one thing over another.

At some point last year, Google's constant requests to prove I'm human began to feel increasingly aggressive. More and more, the simple, slightly too-cute button saying "I'm not a robot" was followed by demands to prove it -- by selecting all the traffic lights, crosswalks, and storefronts in an image grid. Soon the traffic lights were buried in distant foliage, the crosswalks warped and half around a corner, the storefront signage blurry and in Korean. There's something uniquely dispiriting about being asked to identify a fire hydrant and struggling at it. These tests are called CAPTCHA, an acronym for Completely Automated Public Turing test to tell Computers and Humans Apart, and they've reached this sort of inscrutability plateau before. In the early 2000s, simple images of text were enough to stump most spambots.

Facial recognition technology has progressed to point where it now interprets emotions in facial expressions. This type of analysis is increasingly used in daily life. For example, companies can use facial recognition software to help with hiring decisions. Other programs scan the faces in crowds to identify threats to public safety. Unfortunately, this technology struggles to interpret the emotions of black faces.

Facial recognition technology has progressed to point where it now interprets emotions in facial expressions. This type of analysis is increasingly used in daily life. For example, companies can use facial recognition software to help with hiring decisions. Other programs scan the faces in crowds to identify threats to public safety. Unfortunately, this technology struggles to interpret the emotions of black faces.

An image from the product page of Amazon's Rekognition service, which provides image and video facial and item recognition and analysis. SAN FRANCISCO -- The Orlando Police Department in Florida is planning to continue its test of a facial recognition program from Amazon, despite outcry from civil rights and privacy groups that law enforcement and government agencies could abuse the technology. OPD announced last month that the trial proof of concept run of the software had expired, but OPD public information officer, Sgt. Eduardo Bernal, said in a release Monday that the department will continue its testing of the program. Two years ago, Amazon built the facial and product recognition tool, called Rekognition, as a way for customers to quickly search a database of images and look for matches.

In an effort to explain to my Italian grandma what machine learning is, I delved deep into the subject and decided to write up an introduction to Machine Learning. The essay will be translated in Italian of course as English is not her forte. You may have probably heard of "Artificial Intelligence", a term that is now part of mass culture thanks to science fiction movies and books. In recent years though, other terms have surfaced such as "Machine Learning" and "Robotics". So what is Artificial Intelligence?

This is the second installment in a three-part series exploring the impact of artificial intelligence (NYSE:AI) on investment management. I want to thank the speakers at the AI and the Future of Financial Services Forum, hosted by CFA Institute and CFA Society Beijing, for inspiring this series. The first installment offered a primer on the AI technologies that are relevant to investment professionals. Artificial intelligence (AI) is coming to the investment world. With the help of deep learning techniques, AI researchers have made significant strides in natural language processing (NLP), speech recognition, and image recognition.

This is the second installment in a three-part series exploring the impact of artificial intelligence (AI) on investment management. I want to thank the speakers at the AI and the Future of Financial Services Forum, hosted by CFA Institute and CFA Society Beijing, for inspiring this series. The first installment offered a primer on the AI technologies that are relevant to investment professionals. Artificial intelligence (AI) is coming to the investment world. With the help of deep learning techniques, AI researchers have made significant strides in natural language processing (NLP), speech recognition, and image recognition.

When you upload photos to Facebook, have you noticed that the website already seems to know who's in them? It's remarkable, and you can give the credit to big data. Face recognition software, like fraud detection and ad matching algorithms, draws on deep libraries of content in order to deliver the correct results. And these data collections are hard at work across the web and in many of your favorite apps. It comes as no surprise that developers have been hard at work on face recognition software since it's an integral part of security programs.