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"But with all of the successes of AI, it's also important to pay attention to when, and how, it can go wrong, in order to prevent future errors. A recent paper by Roman Yampolskiy, director of the Cybersecurity Lab at the University of Louisville, outlines a history of AI failures which are "directly related to the mistakes produced by the intelligence such systems are designed to exhibit." According to Yampolskiy, these types of failures can be attributed to mistakes during the learning phase or mistakes in the performance phase of the AI system."

"It is also self-improving. The 10-year-old grading software leverages deep learning algorithms to "compare notes" with human teachers' scores, suggestions, and comments. An engineer involved in the project compared its capabilities to those of AlphaGo, the record-breaking AI Go player developed by Google subsidiary DeepMind."

"Concerns have been growing about AI's so-called "white guy problem" and now scientists have devised a way to test whether an algorithm is introducing gender or racial biases into decision-making."

"In October, American teachers prevailed in a lawsuit with their school district over a computer program that assessed their performance. The system rated teachers in Houston by comparing their students' test scores against state averages. Those with high ratings won praise and even bonuses. Those who fared poorly faced the sack. The program did not please everyone. Some teachers felt that the system marked them down without good reason. But they had no way of checking if the program was fair or faulty: the company that built the software, the SAS Institute, regards its algorithm a trade secret and would not disclose its workings."

"To what extent do the decisions of these types of algorithms reflect the conscious or unconscious biases of their creators?"

"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"Instead, the new work shows our brains rely on the kind of maths that an algorithm might use to perform the task. In fact, Tsao and her colleague, Steven Le Chang, stumbled on their discovery while working on computer vision. The pair had initially set themselves the challenge of coming up with a way of reliably converting facial images into a numerical representation."

"The point of creating this vast portfolio of digital gun art is to feed an algorithm made to detect a firearm as soon as a security camera catches it being drawn by synthetically creating tens of thousands of ways each gun may appear. Arcarithm is one of several companies developing automated active shooter detection technology in the hopes of selling it to schools, hotels, entertainment venues and the owners of any location that could be the site of one of America's 15,000 annual gun murders and 29,000 gun injuries."

"Facebook announced late Friday that it had eliminated jobs in its trending module, the part of its news division where staff curated popular news for Facebook users. Over the weekend, the fully automated Facebook trending module pushed out a false story about Fox News host Megyn Kelly, a controversial piece about a comedian's four-letter word attack on rightwing pundit Ann Coulter"

"Cellebrite, the Israeli-founded and now Japanese-owned company behind some of the software, claims a wider rollout would solve problems over failures to disclose crucial digital evidence that have led to the collapse of a series of rape trials and other prosecutions in the past year. However, the move by police has prompted concerns over privacy and the potential for software to introduce bias into processing of criminal evidence."

"high-frequency trading that you hear a lot is that it destabilizes markets, because all the computers trading with each other don't have the common sense famously possessed by stock exchange floor traders, and so they sometimes do dumb stuff like sell stock for a penny or buy it for $99,999.99, and then later when you yell at them they just point to their algorithms and shrug. "

"The platform's automated tools may have mistaken the visuals of the burning building for 9/11 footage, according to Vagelis Papalexakis, an assistant professor of computer science and engineering at the University of California, Riverside who studies machine learning used in similar systems."

"The Bank of England has previously highlighted the impact of trading algorithms. "Some markets appear to have become more fragile, as evidenced by episodes of short-term volatility and illiquidity over the past couple of years," Threadneedle Street said last December, warning of a move towards "fast, electronic trading." "

"Then came the algorithm, which used automatic speech recognition to detect specific features and patterns in each of the 48 recordings. It was clear from examining the waveforms of the cries that each category had a specific pattern."

"That can include statistical or machine learning algorithms that rely on police records detailing the time, location, and nature of past crimes in a bid to predict if, when, where, and who may commit future infractions. In theory, this should help authorities use resources more wisely and spend more time policing certain neighborhoods that they think will yield higher crime rates."

"The performance of LipNet compares incredibly favorably to human lipreading experts on GRID corpus, the largest publicly-available sentence-level lipreading dataset. In fact, where human experts got just 52 percent, LipNet scored 93 percent. Its sentence-based approach to lip-reading also smashed the best previous attempt by a machine, which managed 79.6 percent accuracy on the same dataset."

"Automated decision-making is appealing to businesses as it can save time and eliminate human emotional volatility. "People have a bad day and it then colors their perception of the world and they make different decisions. In a hedge fund that's a big deal," he added."

"The report cited a recent academic analysis of studies on how people interpret moods from facial expressions. That paper found that the previous scholarship showed such perceptions are unreliable for multiple reasons."

"The results may seem similar to what you'd get if you'd searched WebMD, Mayo Clinic, etc. The difference is that Dr. A.I. pulls in many more data points than those sites do, then combines artificial intelligence with a massive database to pinpoint the most likely results in your specific case. It doesn't just find all possible ailments and list them for you to explore further on your own."