Jobs traditionally done by women are more vulnerable to the impact of artificial intelligence than those done by men, especially in high-income countries, a report by the United Nations' International Labour Organization showed on Tuesday. It found 9.6% of traditionally female jobs were set to be transformed compared with 3.5% of those carried out by men as AI increasingly takes on administrative tasks and transforms clerical jobs, such as secretarial work. Human involvement will still be required for many tasks -- and roles are more likely to be radically changed rather than eliminated, the report said. Jobs in the media, software and finance-related roles are also at the forefront of change as generative AI expands its learning abilities. "We stress that such exposure does not imply the immediate automation of an entire occupation, but rather the potential for a large share of its current tasks to be performed using this technology," the report said. It called on governments and employers' and workers' organizations to think about how AI can be used to enhance productivity and job quality.

Compounding the danger is the lack of any AI regulation. Instead, unaccountable technology conglomerates, such as Google and Meta, have assumed the roles of judge and jury in all things AI. They are silencing dissenting voices, including their own engineers who warn of the dangers. The world's failure to rein in the demon of AI--or rather, the crude technologies masquerading as such--should serve to be a profound warning. There is an even more powerful emerging technology with the potential to wreak havoc, especially if it is combined with AI: quantum computing.

PUNDITS in the US are arguing over a technology that is used almost exclusively for elections and pornography. I am referring to deepfakes, videos manipulated with simple apps to swap out faces, distort words and make it look like politicians are starring in hot XXX movies. The fate of deepfakes could change the course of democracy. And that feels very on-brand for the US right now. Technologists first warned about the power of machine learning to create convincing doctored videos back in 2017.

This February, China's best-known contemporary actress, Yang Mi, surfaced in a video of a 1983 Hong Kong television drama The Legend Of The Condor Heroes. Given the prevailing China-Hong Kong friction, the fake video wherein the original actress' face was replaced with Yang garnered almost 240 million views before it was removed by Chinese authorities. Similarly, videos of US President Donald Trump mocking Belgium for joining the Paris Climate agreement, or a video of Facebook CEO Mark Zuckerberg boasting that the social network owns its users, were widely circulated until they were found to be fake. Known as deepfakes, this new breed of fake videos first surfaced back in 2017 with fake porn videos of some Hollywood celebrities. While initially simple open source video editing tools were used to manipulate audio and video, criminals are now using more sophisticated machine learning (ML) tools like generative adversarial networks, or GANs, that use a pair of contrasting unsupervised ML algorithms to create a deepfake.

BOSTON and BANGALORE, India, September 15, 2018 /PRNewswire-PRWeb/ -- Independent analyst firm, rpa2ai has released RPA50, the first in a series of in-depth research reports on Robotic Process Automation (RPA). RPA50 is the industry's most comprehensive listing of RPA vendors to-date. The RPA50 infographic lists the top 50 global vendors within the Robotic Process Automation (RPA) marketplace. It also identifies eight different vendor categories and provides guidance on when to consider which category of vendors. In addition to vendor summaries, the research analyzes the RPA ecosystem and marketplace development, examines the impact of RPA, highlights implementation challenges and the role of professional services.

Artificial intelligence could outsmart and enslave humanity, but our species' future could turn out even worse if we don't advance in the field. That's according to Tomas Mikolov, a research scientist at Facebook A.I. Research, who believes that catastrophic events could have a detrimental effect on society, and it may be machines that save humans from themselves. "There are these arguments that maybe we should not develop A.I. because it's going to destroy us," Mikolov said at the Human-Level Artificial Intelligence conference in Prague, Czech Republic on Saturday, describing this scenario as resulting from science fiction drama. "What if actually not achieving A.I. is the biggest existential threat for humans? As the technology is getting increasingly complex, we are producing more artificial substances that could get into the environment. We as humans are actually very bad at making predictions. What will happen in some distant time, 20, 30 years from now if we make some bad decisions? Maybe actually it will be A.I. that will help us to become much smarter."

Researchers at the University of Chicago have trained a neural network, or artificial intelligence (AI) system, to write fake reviews on Yelp and have found the AI-generated reviews to be virtually the same as those written by humans. The AI-software learned how to mimic writing a review from publicly-available Yelp restaurant reviews. A customization process, which included feeding in details on specific restaurant dishes, tailored the review for a specific restaurant. The AI-generated reviews were found to be "effectively indistinguishable from those produced by humans" by test subjects and were rarely identified by plagiarism detection software. On usefulness, the test subjects gave an average score of 3.15 for AI reviews versus 3.28 for genuine reviews.

For many Americans, the threat of a nuclear missile strike from North Korea feels very real at the moment. Much more real than being attacked by an intelligent robot, say. But according to Elon Musk, the rise of artificial intelligence (AI) poses a much greater threat to humanity than Kim Jong-un's belligerent regime in Pyongyang. Elon Musk, CEO of SpaceX and Tesla, speaks during the International Space Station Research and Development Conference at the Omni Shoreham Hotel in Washington, D.C., on July 19. The Tesla and SpaceX chief executive has long warned of the dangers of AI and issued his latest opinion after a bot from OpenAI defeated some of the world's best players in in a professional gaming competition.

I've read a lot of articles suggesting that AI will take away a large chunk of sales roles by 2020. Technology is now rapidly changing the way people buy with the internet and artificial intelligence creating more online based transactions thus slowly removing the need for physical sales people. Whilst we are already seeing AI transform the buyer journey I can't help but think.... Is AI a bigger threat to sales managers? If you look at how AI is being used within the sales industry itself it appears to be taking on the tasks of a sales manager and in doing so, removing the need for them all together. Let's look at some of the ways AI is being used and could be used in a sales management function: Now I sit in 2 minds on whether I think AI will take away the role of a sales manager.

Cloud diversity: How 10 companies use the cloud 10 different ways How Amazon is planning for the second decade of the cloud revolution IT will spend more than one-third of its budget on cloud in 2017, says new report Subscribe to TechRepublic's Cloud Insights newsletter Google has been running a distant third in the cloud computing wars, with first-mover Amazon Web Services and enterprise darling Microsoft Azure outpacing it in the infrastructure-as-a-service market. But what if, as Stratechery analyst Ben Thompson has posited, infrastructure (or platform) isn't really the big deal, but rather is democratizing the ability to make sense of big data? In that battle, Google has more than a fighting chance, but new moves from AWS to democratize machine learning will make it hard to gain ground. Machine learning is a hot topic, but it's also a particularly thorny one to navigate. Put simply, most enterprises lack the technical chops to be able to master machine learning.