If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
A team of University of Illinois researchers estimated the mortality costs associated with air pollution in the U.S. by developing and applying a novel machine learning-based method to estimate the life-years lost and cost associated with air pollution exposure. Scholars from the Gies College of Business at Illinois studied the causal effects of acute fine particulate matter exposure on mortality, health care use and medical costs among older Americans through Medicare data and a unique way of measuring air pollution via changes in local wind direction. The researchers - Tatyana Deryugina, Nolan Miller, David Molitor and Julian Reif - calculated that the reduction in particulate matter experienced between 1999-2013 resulted in elderly mortality reductions worth $24 billion annually by the end of that period. Garth Heutel of Georgia State University and the National Bureau of Economic Research was a co-author of the paper. "Our goal with this paper was to quantify the costs of air pollution on mortality in a particularly vulnerable population: the elderly," said Deryugina, a professor of finance who studies the health effects and distributional impact of air pollution.
This week Bett, the education show that brings together over 800 education providers, takes center stage in London. Educators, developers, and ecosystem players come together to share what is new, connect and learn. Microsoft is the worldwide partner for Bett, but most platform providers and hardware vendors use the event to launch their latest devices and software solutions aimed at education. As in years past, we have announcements aimed at making life in the classroom easier for the teacher, whether it is about saving time on managing students, assets, or content. Microsoft added new indicator lights at the back of the computers the students are using so teachers can quickly glance at the class and make sure all machines are powered and connected.
Does your company have an AI ethics officer? In 2014, Stephen Hawking said that AI would be humankind's best or last invention. Six years later, as we welcome 2020, companies are looking at how to use Artificial Intelligence (AI) in their business to stay competitive. The question they are facing is how to evaluate whether the AI products they use will do more harm than good. Many public and private leaders worldwide are thinking about how to address these questions around the safety, privacy, accountability transparency and bias in algorithms.
The past year has seen many businesses question exactly how transformational digital transformation really is. The answer, as with all IT initiatives, depends on the scope of the ambition, the skill of the leadership, and the ultimate degree of business impact. Yet we've seen a pattern emerge: Those with transformational aspirations discover that boil-the-ocean schemes seldom meet their objectives, while carefully planned and targeted initiatives often have broader benefit than even the original instigators imagined. The latter is particularly true of initiatives that reform fundamental processes. Transformation usually implies moving from one fixed state to another, yet digital transformation at its best involves a journey from inflexibility to a "permanently agile" condition.
UPDATE Oct, 2019: We just added a new season with 4 new podcasts focused on artificial intelligence, machine learning, data science, and data orchestration. Building a data foundation is essential to driving innovation. This is just as true for mid-market companies as for large enterprise companies. Mid-market and large enterprise companies have different challenges, so we've brought together experts from each size company to discuss key trends that are reshaping the way successful companies use their data: from data management and data foundation to spatial and machine learning to data-based process and information excellence. Listen to this chat series on all things data!
On January 9, the World Health Organization notified the public of a flu-like outbreak in China: a cluster of pneumonia cases had been reported in Wuhan, possibly from vendors' exposure to live animals at the Huanan Seafood Market. The US Centers for Disease Control and Prevention had gotten the word out a few days earlier, on January 6. But a Canadian health monitoring platform had beaten them both to the punch, sending word of the outbreak to its customers on December 31. BlueDot uses an AI-driven algorithm that scours foreign-language news reports, animal and plant disease networks, and official proclamations to give its clients advance warning to avoid danger zones like Wuhan. Speed matters during an outbreak, and tight-lipped Chinese officials do not have a good track record of sharing information about diseases, air pollution, or natural disasters.
During the kind of virus outbreak that China and other nations are now contending with, time is of the essence. Such was the case in 2002 and 2003, when Chinese authorities were accused of covering up the SARS epidemic that eventually claimed over 740 lives around the world. With the current outbreak, involving a coronavirus that originated in Wuhan and has so far taken over 40 lives, the Chinese government is being more transparent, as Germany's health minister noted to Bloomberg yesterday on the sidelines of the World Economic Forum in Davos.
At the IBM Watson Experience Center, digital and physical worlds meet in a futuristic-looking lounge overlooking San Francisco's Financial District. "Regardless of the industry you're in, there's likely an application for AI … even as a chef," said IBM's data and AI engagement lead Euniq Nebo, as he stood before a 32-foot digital screen displaying human-size images of various professionals. A chef on the screen stepped forward and came to life. Nebo spoke of questions facing a restaurant chef, such as which cutting-edge tools to invest in, or whether to incorporate local produce into a cuisine. But IBM is betting its AI can "extract the insights" from data to help its clients stay ahead of the curve, Nebo said.