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.
Artificial intelligence, defined as intelligence exhibited by machines, has many applications in today's society. More specifically, it is Weak AI, the form of A.I. where programs are developed to perform specific tasks, that is being utilized for a wide range of activities including medical diagnosis, electronic trading, robot control, and remote sensing. AI has been used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, and more. AI for Good is a movement in which institutions are employing AI to tackle some of the world's greatest economic and social challenges. For example, the University of Southern California launched the Center for Artificial Intelligence in Society, with the goal of using AI to address socially relevant problems such as homelessness. At Stanford, researchers are using AI to analyze satellite images to identify which areas have the highest poverty levels. The Air Operations Division (AOD) uses AI for the rule based expert systems. The AOD has use for artificial intelligence for surrogate operators for combat and training simulators, mission management aids, support systems for tactical decision making, and post processing of the simulator data into symbolic summaries.
Over 111.8 million people in the U.S. talk to voice assistants like Siri, Alexa, and Google Assistant every month, eMarketer estimates. Tens of millions of those people use assistants as data-finding tools, with the Global Web Index reporting that 25% of adults regularly perform voice searches on smartphones. But while voice assistants can answer questions about pop culture and world events like a pro, preliminary evidence suggests they struggle to supply information about elections. In a test of popular assistants' abilities to provide accurate, localized context concerning the upcoming U.S. presidential election, VentureBeat asked Alexa, Siri, and Google Assistant a set of standardized questions about procedures, deadlines, and misconceptions about voting. In general, the assistants fared relatively poorly, often answering questions with information about voting in other states or punting questions to the web instead of answering them directly. In light of historic misinformation efforts around the election, the shortcomings have the potential to sow confusion or hamper get-out-the-vote efforts -- especially among those with accessibility challenges who rely heavily on voice assistants.
One day in 2017, Alexa went rogue. When Martin Josephson, who lives in London, came home from work, he heard his Amazon Echo Dot voice assistant spitting out fragmentary commands, seemingly based on his previous interactions with the device. It appeared to be regurgitating requests to book train tickets for journeys he had already taken and to record TV shows that he had already watched. Josephson had not said the wake word – "Alexa" – to activate it and nothing he said would stop it. It was, he says, "Kafkaesque". This was especially interesting because Josephson (not his real name) was a former Amazon employee.