Companies around the world are expecting to apply artificial intelligence (AI) within their companies in the next few years but are lagging in discussions of the ethics around it, research from Genesys finds. More than half of the employers questioned in a multi-country opinion survey say their companies do not currently have a written policy on the ethical use of AI or bots, although 21% expressed a definite concern that their companies could use AI in an unethical manner. "As a company delivering numerous customer experience solutions enabled by AI, we understand this technology has great potential that also comes with tremendous responsibility," said Steve Leeson, VP UK & Ireland, Genesys. "This research gives us important insight into how businesses and their employees are really thinking about the implications of AI – and where we as a technology community can help them steer an ethical path forward in its use." The research findings stem from opinion surveys sponsored by Genesys (www.genesys.com),

What is your role and who do you work for? I am the CTO and chief scientist at Jumio. We are a biometric identity verification provider that uses computer vision technology, machine learning, augmented intelligence and live verification experts to verify government-issued documents (e.g. As CTO and chief scientist, part of my job is to make sure that our major technology initiatives are successful. One of our current, large-scale initiatives is our cloud migration process, where we're moving all of our applications from being hosted on-premise to a microservices-based cloud deployment.

Robotic Process Automation (RPA) has been quite a buzzword for few years and when I say "robotic",I still see people misconnecting it to the physical "robots" but it actually refers to the software bots which are capable of automating the series of steps without human intervention. So, in this article I would like to explain what RPA is and how it is different from other automations and how do businesses get accelerated by augmenting the skills of their employees with digital co-workers. The roots of automation dates back to the age of Mayans wherein they automated water transportation through aqueducts which was followed in the later stages by means of automating the assembly line by Henry Ford. In the 20th century, the data driven jobs needed people to fortify the processes supported by technology which gave rise to the establishment of Enterprise Resource Planning systems. With ERP being not customizable Business Process Management came into existence which is customizable and API driven.

This has given rise to an extreme theory that either AI or robots will replace humans in many jobs, pushing the unemployment rate close to 50 percent. Although the jobless rate reaching 50 percent may be an exaggeration, it appears all but certain that the rate of technological unemployment -- loss of employment caused by technological progress -- will reach 10 to 20 percent. This means that unless some steps are taken, the Fourth Industrial Revolution driven by AI, the "internet of things" and big data will lead the human race to a dystopia rather than to a utopia. What measures could be taken to lead us to an utopia instead? Gross domestic product, the total value of income earned in a country over a given period of time, is distributed to capital and labor.

In the initial phase I would not be worried about healthcare job cuts. AI implementation will constitute a great opportunity for healthcare specialists to improve the way we perform our duties and collaborate in the development of a new technology. As a cardiac imaging specialist, one of the great advances could be the automatisation of routine and time-consuming tasks that, with the help of AI, could become more efficient and consistently accurate. At the end of the day, this will save a lot of time that could be used on other activities by the healthcare workers. In the first phase, the healthcare worker will confirm the work of the machine, but from my point of view, probably, in a second phase, the results will be accepted without human intervention.

As we enter new frontiers with the latest technology trends and enjoy the many positive impacts and benefits it can have on the way we work, play and live, we must always be mindful and prepare for possible negative impacts and potential misuse of the technology. The British, Chinese, and United States armed forces are testing how interconnected, cooperative drones could be used in military operations. Inspired by a swarm of insects working together, drone swarms could revolutionize future conflicts, whether it be by overwhelming enemy sensors with their numbers or to effectively cover a large area for search-and-rescue missions. The difference between swarms and how drones are used by the military today is that the swarm could organize itself based on the situation and through interactions with each other to accomplish a goal. While this technology is still in the experimentation stage, the reality of a swarm that is smart enough to coordinate its own behavior is moving closer to reality.

As we enter new frontiers with the latest technology trends and enjoy the many positive impacts and benefits it can have on the way we work, play and live, we must always be mindful and prepare for possible negative impacts and potential misuse of the technology. The British, Chinese, and United States armed forces are testing how interconnected, cooperative drones could be used in military operations. Inspired by a swarm of insects working together, drone swarms could revolutionize future conflicts, whether it be by overwhelming enemy sensors with their numbers or to effectively cover a large area for search-and-rescue missions. The difference between swarms and how drones are used by the military today is that the swarm could organize itself based on the situation and through interactions with each other to accomplish a goal. While this technology is still in the experimentation stage, the reality of a swarm that is smart enough to coordinate its own behavior is moving closer to reality.

Bias is a prejudice in favor or against a person, group, or thing that is considered to be unfair. But as machine learning becomes more of an integral part of our lives, the question becomes will it include bias? In this article, I'll dig into this question, its impact, and look at ways of eliminating bias from machine learning models. Machine learning has shown great promise in powering self-driving cars, accurately recognizing cancer in radiographs, and predicting our interests based upon past behavior (to name just a few). But with the benefits from machine learning, there are also challenges.

This implementation programmatically optimizes for the number of clusters (k) and at the end of clustering process stores the clusters to disk. You can test the code with San Francisco crimes data in "inputs" folder (i.e. Note that if you want to test with your own location data, you need to copy your location CSV format file into "inputs" folder first. Next, pass your filename as a parameter to the clustering program as shown below. Your CSV file should have "Lat,Lon" format.

"Every year we're developing new technology -- like deep learning, which has improved the performance of pattern recognition," he added.