Marc Kaufman typically needs 20 hours to create one patent application for a software innovation. But the Washington-based patent attorney says he's saving valuable time with a little high-tech help. Kaufman, a partner at Rimon PC, has been using an artificial intelligence tool called Specifio that analyzes claims--words that define an invention--and generates a bare-bones draft with a description and illustrations in a couple of minutes. He says the tool he started using six months ago has given him five extra hours to fine-tune his clients' applications to boost their likelihood of approval. "Saving hours allows me to really understand the client's business and be very strategic with the patent application, while coming in at a price that clients are willing to pay," Kaufman said.

In Part One of Vision publisher David Hulme's interview with Seán Ó hÉigeartaigh, the AI expert had much to say about the pros and cons of artificial intelligence. Part Two is a continuation of that discussion. Where is the developing technology leading us? DH At the end of the Second World War, Albert Einstein wrote a famous editorial in the New York Times. He's obviously regretting that the nuclear genie is out of the bottle. Scientists sometimes get to this point.

It's the buzzword that's taken over most human resources (HR) conferences. At last year's HR Technology Conference and Expo in Las Vegas, several companies touted the integration of artificial intelligence (AI) into their recruiting products. Back home, the 2018 SHRM HR Tech Conference, held in Hyderabad in April, saw key sessions on how AI is going to be a driving force in HR functions. Their next conference in Chicago, held in June, had sessions on how to use AI to better understand employees. AI, or the ability of machines to imitate the human mind, is invading the workplace.

Explanation in machine learning and related fields such as artificial intelligence aims at making machine learning models and their decisions understandable to humans. Existing work suggests that personalizing explanations might help to improve understandability. In this work, we derive a conceptualization of personalized explanation by defining and structuring the problem based on prior work on machine learning explanation, personalization (in machine learning) and concepts and techniques from other domains such as privacy and knowledge elicitation. We perform a categorization of explainee information used in the process of personalization as well as describing means to collect this information. We also identify three key explanation properties that are amendable to personalization: complexity, decision information and presentation. We also enhance existing work on explanation by introducing additional desiderata and measures to quantify the quality of personalized explanations.

Artificial intelligence (AI) is changing the way we work and play, but did you know it's also being used to help couples break up quickly and cheaply? Almost half of all marriages in the US and Canada end in divorce, so it's no wonder an app like Wevorce would be popular. Co-founded by former attorney Michelle Crosby and marketing executive Jeff Reynolds, Wevorce basically acts as a tax software for divorce. It also aims to alleviate the pain of messy divorces, which Crosby personally experienced when she was only nine years old. She was put on the stand by her parent's divorce lawyer and asked: "If you were stranded on a desert island, which of your parents would you choose to live with?" Wevorce works by prompting users to answer questions about their ideal outcome regarding the division of assets, co-parenting plan, and other important decisions.

But "trying to draw a line between what is military and what is commercial is exceedingly difficult," said R. David Edelman, a technology policy researcher at the Massachusetts Institute of Technology. It is difficult to put a "made in America" label on artificial intelligence. Research on the technology is often done collaboratively by scientists and engineers all over the world. Companies rarely hold on to the details of their A.I. work, as if it were a secret recipe. Instead, they share what they learn, in hopes that other researchers can build on it.

A growing number of organizations are turning to algorithms to "score" their customers. Understanding customers and rewarding the best has always been at the center of running a successful business. However, thanks to big data and analytics, the concept is changing. A growing number of organizations are turning to algorithms to "score" customers and determine what price they pay, how long they must wait on hold, and whether they can return items they have purchased. "Digital technology has enabled consumers to be more knowledgeable about prices, and online shopping has made it easier for them to hunt for bargains," explains Sunil Gupta, Edward W. Carter Professor of Business Administration and chair of the General Management Program at Harvard University.

File photo - An employee holds an iPhone Apple XR during the press visit of the new Apple Store Champs-Elysees on Nov. 15, 2018 in Paris, France. There aren't many ways 2018 could have gone worse for the tech industry. It felt like every week, Facebook CEO Mark Zuckerberg and friends were apologizing for some major privacy blunder or platform manipulation. Self-driving cars proved they weren't ready to hit the road and Elon Musk nearly self-destructed on Twitter. Electric scooters swarmed cities only to be vandalized in droves.

In almost equal measure, the year 2019 promises to be a challenging and positive one for the IT industry. The tech landscape in particular will be dominated by conversations around edge computing, artificial intelligence (AI) and the holy grail, work/life balance. As a concept, edge development and definitions have been discussed and analyzed in depth for years. Now we're at the point where edge computing is entering production and becoming "live." For enterprise users and consumers, edge data centers will be visible through the services they provide.

The video showed the woman in a pink off-the-shoulder top, sitting on a bed, smiling a convincing smile. But it had been seamlessly grafted, without her knowledge or consent, onto someone else's body: a young pornography actress, just beginning to disrobe for the start of a graphic sex scene. A crowd of unknown users had been passing it around online. She felt nauseous and mortified: What if her co-workers saw it? Would it change how they thought of her? Would they believe it was a fake?