This post presents my personal views. Note I could not discuss all of the below due to time constraints. So, what could we do about it? Cristoph Molnar's free book on interpretable ml explains this well Have I missed any strategies?

Artificial intelligence works better than human lawyers in accurately spotting risks in everyday business contracts. That's the conclusion of a landmark study pitting 20 experienced US-trained corporate lawyers against Tel Aviv based LawGeex, which makes artificial intelligence (AI) software for contract review and approval, in spotting issues in everyday contracts. Both the lawyers and the LawGeex AI analyzed five previously unseen non-disclosure agreement contracts, containing 153 paragraphs of technical legal language under controlled conditions. This is the first time that AI software has been tested with a typical task undertaken by lawyers on a daily basis. The result: LawGeex software achieved a 94 percent accuracy rate at identifying risks in the NDAs.

In this interview recorded at the Open Source Leadership Summit, Azure CTO Mark Russinovich and The New Stack's founder Alex Williams discussed how Microsoft builds on and contributes to open source for Azure's artificial intelligence (AI) and machine learning. As Russinovich -- who had just given a keynote suggesting that AI owes its current strength to the combination of open source and the cloud -- explained, "Fundamentally a lot of AI, machine learning and analytics is built on top of open source and it's a key part of our strategy to build with and use that open source, as well as to contribute back and to add to open source." Examples of that range from Microsoft contributing its own enhancements and fixes to existing projects like YARN (which is used in Azure Data Lake Analytics), to supporting the R open source community, to working with Facebook and AWS on the ONNX project to exchange models between Caffe, MXNet and CNTK, Microsoft's own deep learning framework -- which is also open source. "CNTK is our own intellectual property; it's a differentiated convolutional neural network framework… that we developed internally for Bring. We use that internally for a lot of our cognitive APIs… and we contributed that to [the] open source [community]," Russinovich explained.

Over the past few years there has been dramatic rise in the use of data, analytics, and most recently, artificial intelligence (AI). With AI rapidly moving into the daily operations of a rising number of uses and enterprises, the disruption to human capital and the labor workforce of tomorrow is inevitable. What's more, this change mostly likely will be amplified by innovation and commoditization that AI brings as it enters every aspect of the modern workplace. Modern industry stands on a precipice between platforms and automation. Uber, Lyft, Gigster, Deliveroo, and the multitudes of other platforms are still heavily dependent on human labor, but all are aggressively investing in artificial intelligence to automate processes and decrease risk in business operations.

The world is being battered by technological disruption, as innovations such as big data analytics, artificial intelligence (AI), robotics, the Internet of Things, blockchain, 3D printing, and virtual reality change how societies and economies work. Individually, each of these technologies has the potential to transform established products, services, and associated support networks. Taken together, they will upend old business models and institutions, heralding a new era of economic, social, and political history. Major economic transformations typically produce far-reaching change. During the first Industrial Revolution, in the 18th and 19th centuries, new manufacturing processes eventually led to huge improvements in human well-being.

This article was originally published in March 2017. During my time as a graphic designer, I've experienced nearly everything – short of physical violence – that working life can throw at you: recessions, legal disputes, defaulting clients, and of course, the thrill that comes with completing a successful project. But two events – both of which turned the practice of graphic design on its head – stand out as life changing. The first was the arrival of the Macintosh computer. For all practising designers at the time, computerisation necessitated an extensive rethink of the craft: no more mechanical artwork, no more paste-up, no more typesetters, no more expensive retouchers.

Google has just started to fund computer software which will write local news. A short story written by Japanese computer software made it to second rounds of national literary prize. And an artificial intelligence company called deep mind has created software that can generate music by listening to music. All these foregoing flashy news stories are evident of the benefit and popularization of Artificial Intelligence in the modern world. Earlier, the computer generated works relied heavily upon the input provided by the programmer, the software was very much like a tool or a mechanism like brush or canvas.

The Federal Trade Commission (FTC) confirmed Monday that it is investigating Facebook's privacy practices following reports that the company allowed personal data to be extracted from users without expressed permission. The investigation was spurred by reports that Facebook allowed political data analytics firm Cambridge Analytica to gain access to the personal information of more than 50 million Facebook users and use that data to craft targeted political advertising campaigns. "The FTC takes very seriously recent press reports raising substantial concerns about the privacy practices of Facebook," Tom Pahl, Acting Director of the Federal Trade Commission's Bureau of Consumer Protection, said in a statement. "Today, the FTC is confirming that it has an open non-public investigation into these practices." The FTC previously declined to comment on an investigation into Facebook.

A new Apple patent may be hinting at the inclusion of Face ID in upcoming Apple Watch installments. The document mentions a camera and "user identification" -- two things that are strongly linked to the TrueDepth camera system of the iPhone X. Late last week, the U.S. Patent & Trademark office published another patent application from the Cupertino giant. The document is centered on the Apple Watch and new features in the pipeline. The patent mentions a lot of sensors and a camera that are expected to enhance the user experience.

Recently, AAAI coordinated and The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) cosigned a statement with CRA, and the Thirty-First Conference on Innovative Applications of Artificial expressing concern about the proposed Intelligence (IAAI-19), will be held in Honolulu, Hawaii, USA, January tax bill and its ramifications for graduate 27 - February 1, 2019. The technical conference will continue its student stipends. Other organizational 3.5-day schedule, preceded by the workshop and tutorial programs.