There is no question that artificial intelligence (AI) and automation are entering the workplace in many graduate level jobs, and this trend is likely to continue and quicken. Times Higher Education recently asked whether universities needed to rethink what they do and how they do it, given that artificial intelligence is beginning to take over many post-university careers. The implications and – most importantly – the potential benefits for education are significant, and perhaps not yet appreciated by higher education leaders. With that in mind, here are four examples of how AI can benefit universities. First, there is a new role for higher education, which is to equip graduates to work effectively alongside artificially intelligent systems.

DESCRIPTION Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon's customers? Do you want to build advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify?

The idea of automated customer service is nothing new – from speech recognition technology on dreaded call center phone lines, to Apple's groundbreaking Siri personal assistant system, AI has been in our lives and in our pockets for a while now. Yet, young as 2016 still is, it's already defined itself as the year of the Chatbot – from Microsoft's experimental and indeed controversial (more on that later) attempt to engage millennials with the creation of'Tay', a chatbot designed to imitate a teenage girl, in March, to April's recent inundation of announcements from companies eager to trial Chatbots, this year could be the year Chatbots go mainstream. But in a world where the search for authenticity seems increasingly futile and more and more of our meaningful interactions take place via a screen, will the public really welcome Bots? Are they even ready for widespread release? And how are businesses going to capitalize on them? Put simply, a Bot is a piece of software which performs automated tasks and simple, time-consuming or repetitive errands, and this is exactly what a ChatBot does – except (you guessed it), it simulates human interaction.

We've talked before about the prospects of artificial intelligence (AI) and how it will likely disrupt things like we've never seen before with some estimates predicting that up to 80% of all service jobs will be impacted. Healthcare is one area where AI is receiving a good chunk of funding. We looked before at one example of an artificial intelligence company called Enlitic that uses machine learning technology to read X-rays better than your average radiologist who makes 286,000 a year on average. There are actually quite a few artificial intelligence companies in healthcare and CB Insights recently identified 65 of them at various stages of funding. Founded just last year, Chinese company iCarbonX has taken in nearly 200 million in funding from investors that include the 200 billion Chinese internet giant Tencent.

WASHINGTON – Donald Trump and Hillary Clinton spelled out their economic visions in high-profile speeches in Michigan this week. They delved into taxes and regulations, trade deals and job growth. Yet perhaps most notable about their speeches is what they left out. Mostly unmentioned were major challenges that have slowed the U.S. economy and made good-paying jobs harder to find, particularly in struggling pockets of the country. Automation and increasingly high-skilled jobs that require technological know-how that many people lack. They are problems that analysts say require a transformative vision.

SpaceX launched a Japanese commercial communications satellite Saturday night. The Falcon 9 rocket lifted off at 10:26 p.m. PT from Cape Canaveral, Fla., carrying the JCSAT-16 satellite into a geosynchronous transfer orbit. At 10:40 p.m., the first stage landed on a platform floating several hundred miles off the Florida coast. The secondary objective of landing the first stage of Falcon 9 on the drone ship -- named Of Course I Still Love You -- is key to the SpaceX mission of reusing rockets. The satellite, operated by SKY Perfect JSAT Corp., will serve as a backup transmitter for the rest of the communications company's satellite fleet.

The market is a massive, irrational, and fluid amalgamation of all information available in the public domain, at least according to the efficient market hypothesis. The famous quote, that "the market can remain irrational longer than you can remain solvent," holds significance, because it illustrates the perpetual struggle that we face in trying to understand its inner machinations. The market is both a byproduct of human innovation, as well as a microcosm of the world we live in. Just as we can't definitively know how the market will move, we can't definitively know how the choices we make will affect the world we live in. Therein lays the real challenge, in which we take everything we think we know and make an analytical decision, because afterward all that is left is to wait and see if it was the right call.

Drone safety, from privacy issues to crashing over unsuspecting pedestrians, has been a concern since, well, the dawn of the drone. But one startup is working to use artificial intelligence to help drone pilots pick the safest route. Flock, an artificial intelligence company formed out of Imperial College London, Oxford University and Cambridge University, is currently developing a risk analysis program for commercial drones, from aerial photographers to drone use on a larger scale, such as delivering Amazon packages. The program uses real-time weather information and the location of buildings. But what's perhaps even more impressive is that the system can also predict what areas will be full of people so it can choose a route around congested areas or a time when those areas will be less crowded.

In the world of machine learning, deep learning neural networks (DLNN) is the fastest growing field. World Scientific's latest book "Deep Learning Neural Networks: Design and Case Studies" shows how DLNN can be a powerful computational tool for solving prediction, diagnosis, detection and decision problems based on a well-defined computational architecture. The applications in this field serve as a major decision tool in Big Data applications. DLNN successfully applied to a broad field of applications ranging from computer security, speech recognition, image and video recognition to industrial fault detection, medical diagnostics and finance. Their range of applications covers almost any problem whose input data, performance evaluation and target decision can be numerically expressed.

When Bloomberg first built the terminal system, back in the early 1980s, most of its customers -- mainly finance professionals -- didn't have computers on their desks. The internet was not yet a commonly-accepted technical protocol for networking and hardware of the terminal's kind hadn't been seen before. So Bloomberg's engineers had to go about inventing the tech themselves -- from the set of instructions to carry data across a network, to custom-built hardware so traders could use a keyboard, and monitors you could stack. It created a great culture of invention at Bloomberg, which has more software engineers than journalists. But cultivating that culture to create new products within came at a small cost.