In many respects, 2016 was the year of artificial intelligence (AI). Innovations such as big data, advances in machine learning and computing power, and algorithms capable of hearing and seeing with beyond-human accuracy have brought the benefits of AI to bear on our daily lives. By working together with machines, people can now accomplish more by doing less. Yet the power of AI can address far bigger challenges than helping organise our calendars, order our groceries or play games. In collaboration with AI, people can help to solve some of the world's most urgent and difficult problems.

A survey by Personetics shows that the financial services industry is getting a closer to supporting conversational commerce, supporting projects that use chatbots to improve the overall customer experience. Research reveals that most banking providers will be using automated chatbots to handle a significant volume of customer conversations in the near future. Some are doing it already. Powered by chatbots, conversational commerce (Voice-First Banking) allows organizations to interact with customers over digital and messaging platforms, providing answers to questions, advice and offers in real-time. A survey conducted by Personetics shows that over three quarters of financial institution respondents view chatbots as a viable commercial solution now or within the next 1-2 years, and almost half of the companies already have active chatbot projects in place. A majority of the respondents see a substantial share of customer conversations handled by bots within 3-5 years.

In the Marvel universe, billionaire Tony Stark/Iron Man has Jarvis, a personal AI to anticipate his needs and streamline his life. When I mention this to Collie Brown, founder and CEO of Arghon, a personal AI company, he gives a knowing smile. A moment before he described his AI product as a "life assistant." "There's the Watsons of the world, geared towards large scale data and the like," Brown said. "Arghon's about you, what's happening in your life from the time you wake up to the time you go to bed. Our goal is to manage what happens in between that."

If the basics of retail are elementary, then it should be no surprise that a technology named Watson is leading what may be one of the biggest trends in 2017. Watson is the name of an artificial intelligence technology (AI) by IBM; many may remember Watson for its $1 million winning streak on "Jeopardy." Today, several major retailers -- from Macy's to 1-800-Flowers.Com -- are using or testing the supercomputer's cognitive computing capabilities to more acutely predict (and serve) customer wishes. Most recently, Staples announced plans to implement Watson technology to bring to life its Easy Button. Infused with the technology, the button can now take Staples orders by voice, text, email, messaging app or mobile app.

Consider the tragedy of a child killed by neglect and abuse. Now consider the tragedy of a child taken from parents who would not have criminally abused her. Computer algorithms might soon help humans make such difficult decisions -- but only if we recognize the myriad ways in which they can go wrong. In countless cities across the nation, child welfare services make extremely tough calls every day. With limited resources and information, they must often rely on gut instinct in predicting who is most vulnerable.

I know how terrible healthcare records theft can be. I myself have been the victim of a data theft by hackers who stole my deceased father's medical files, running up more than $300,000 in false charges. I am still disputing on-going bills that have been accruing for the last 15 years. This event led me on the path to finding a solution so others would not suffer the consequences that I continue to be impacted by, but hospitals and other healthcare providers must be willing to make the change. The writing is on the wall.

The advocates of machine learning are known to be a fiercely contentious lot, each asserting that its own approach is superior to all others, and that any evidence adduced to the contrary is propaganda, fake news of the worst sort, stemming from jealous advocates of inferior approaches. The closest approximation to the internecine warfare of the machine learning field is the human learning field, in which advocates of public, government-run and union-staffed schools exchange harsh words with advocates of charter schools, with a level of invective and passion that indicates that someone is strongly in favor of hopelessly uneducated machines and/or humans.

Do you think AI will decrease human labor? So if foreseeable technologies materialize, then then the need for human labor could decrease. Technology always puts existing jobs under strain. This doesn't immediately mean that human labor as a whole is under threat. Generally, other professions grow to fill the loss, often creating more jobs than the ones that are lost.

Intel may have cut ties with Android on smartphones and tablets, but the company's partnership with Google on Android for the internet of things is growing stronger. Google's Android Things, a slimmed down version of Android for smart devices, will be coming to Intel's Joule 570x computer board. The combination will allow makers to cook up Android-based gadgets or smart devices for use in home, retail, or industrial settings. The Intel board adds a lot of processing and graphics muscle to projects. With 4K graphics capabilities, the 570x is good for devices with screens or computer vision, like robots and drones.

A true genius, Alan Turing was played brilliantly by Benedict Cumberbatch inThe Imitation Game -- the movie about his life and role in ending WWII -- which introduced him to a whole new generation of admirers. It was Turing who predicted machine learning would play a big role in modern computing in his article the "Turing Test," way back in 1950. Indeed, Turing was way ahead of his time, which was a major theme in the movie, but now the world has caught up. The major advancements in readily accessible computing power, the quantity of data available, and algorithms that truly make machine learning possible are driving our ability to process data, analyze it, and act on it in ways that would make Mr. Turing proud. These advances have completely changed the machine learning game: The fundamental concept remains the same, but now it's far more sophisticated, efficient, and easily deployable. Beyond the big headline-grabbing examples of how machine learning will impact our lives -- such as through driverless cars -- it has exciting potential to put an end to the bland and sometimes ineffective customer experiences that many retailers are delivering to their customers.