Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.
Its impact is drastic and real: Youtube's AIdriven recommendation system would present sports videos for days if one happens to watch a live baseball game on the platform ; email writing becomes much faster with machine learning (ML) based auto-completion ; many businesses have adopted natural language processing based chatbots as part of their customer services . AI has also greatly advanced human capabilities in complex decision-making processes ranging from determining how to allocate security resources to protect airports  to games such as poker  and Go . All such tangible and stunning progress suggests that an "AI summer" is happening. As some put it, "AI is the new electricity" . Meanwhile, in the past decade, an emerging theme in the AI research community is the so-called "AI for social good" (AI4SG): researchers aim at developing AI methods and tools to address problems at the societal level and improve the wellbeing of the society.
Are you a KDnuggets reader? If not, let me introduce you to the premier data science informational website. We're actually an awful lot like Netflix (legal disclaimer: we are nothing like Netflix). At least, that's what people having been saying lately -- I'm sure you've heard the chatter. Here are the ways we are hearing others making the connection between these 2 powerhouses of industry.
As a tech writer, I sometimes feel about new technology the way I suspect military historians must feel about war: You just can't say you love every aspect of your subject. My default model for "tomorrow" is built on the bright and exciting images of yesterday's tomorrow, from "Star Trek" and Flash Gordon, Buck Rogers and Tom Swift. As naïve as it may sound, I inherited from the books, films and TV shows of my childhood a basically progressive view: Despite bumps and missteps occasionally setting us back along the way, technology ultimately would lead to a better future. And I believe it has. Despite the anxiety we seem to thrive on these days, this is a safer world than the one I was born into nearly 70 years ago.