What kind of skills does a company most need these days? Those are probably a lot closer to the mark. But here is one that no one is expecting: philosophers. Do businesses really need a bunch of pointy heads sitting around scratching their beards and quoting Kant or John Stuart Mill halfway through a board meeting? Commerce is about action, not talking, right?

Dubbed "the world's first robot lawyer" by its 19-year-old creator, Joshua Browder, DoNotPay has now successfully contested over 160,000 parking tickets in London and New York. The program attempts to glean information from a simple survey to determine whether an appeal is possible by asking questions that could lead to a dismissal in court, questions like: "were there clearly visible parking signs?" From there, the AI attempts to guide users through the appeals process while aiming for a dismissal. To date, it's been successful in 64 percent of attempts, successfully defending 160,000 of 250,000 offenders in the 21 months it's been active. That's a cool 4m the bot has saved drivers in just under two years.

Artificial intelligence (AI) will make society smarter, leaner and more efficient. But first, startups and businesses must enable the workforce of the future and pivot business models to incorporate AI. Mundane tasks such as driving, scheduling and logistics will all be handled by an AI assistant with multiple input points, such as microphones around your house and smartphones. The AI assistant will be the central nervous system of your life and connected smart home. In the future, when you summon a shared autonomous car from your phone to go out to dinner, your AI assistant will automatically notify the restaurant of your ETA and dietary restrictions.

THE ORIGINAL MACHINERY question, which had seemed so vital and urgent, eventually resolved itself. Despite the fears expressed by David Ricardo, among others, that "substitution of machinery for human labour…may render the population redundant", the overall effect of mechanisation turned out to be job creation on an unprecedented scale. Machines allowed individual workers to produce more, reducing the price of many goods, increasing demand and generating a need for more workers. Entirely new jobs were created to oversee the machines. As companies got bigger, they required managers, accountants and other support staff.

Artificial intelligence is creeping into everyday life in the form of intelligent personal assistants (IPA). Question-answering applications aim for human-like responses, but it's tough to live up to that standard.

Google's DeepMind artificial intelligence (AI) technology has proven to be very smart. DeepMind's AlphaGo system got worldwide attention for beating top-ranked Go player Lee Sedol earlier this year. Previously it has played Breakout and navigated a Doom-like maze. But now the DeepMind software is looking more versatile. Today the Google DeepMind lab unveiled another feat that looks off the wall but is actually evidence of the strength of Google's AI.

"Front-facing robots play an important role in data gathering, and can then make connections. For instance, they can store a query and intelligently offer relevant information to a guest in future," says Pemberton. Crucially, such data can be amassed in a centralized location and delivered on demand locally, so the preferences of a guest staying in a hotel in Miami will be captured and reapplied when she checks into a hotel belonging to the same chain in say, London.

In the construction industry, many projects involve remodeling or refurbishing existing buildings, and such jobs often face delays or cost overruns when hidden problems emerge. "Renovation projects live and die by the quality of information," according to Martin Fischer, a Stanford professor of civil and environmental engineering. New software can analyze this point cloud to automatically extract details to plan a remodel or other purposes. Newer buildings often have computerized blueprints and records, including details such as the number of rooms, doors and windows, and the square footage of floors, ceilings and walls. But such information may not exist for older buildings, necessitating the time-consuming and difficult task of collecting these details manually.

In relation to Bayesian statistics, the sensitivity and specificity are the conditional probabilities, the prevalence is the prior, and the positive/negative predicted values are the posterior probabilities.

The way we are used to do things and draw decisions is about to change with the oncoming digital evolution. Software and hardware are converging in the Internet of Things and devices driven by machine learning will bring in machine-like accuracy and speed to support data driven human decisions and actions. In today's world, we need to designs solutions for customer engagement in the digital age, and regularly rework our industry scenarios to stay ahead of the game. There is a call for design of data driven, machine learning enabled enterprise software to run on state-of-the-art connected devices. As the amount of data continues to grow, it is essential to utilize the power of deep learning to urge better decisions throughout the customer engagement process, and to run on the next generation of connected devices.