Google, Facebook, Amazon, IBM and Microsoft are joining forces to create a new AI partnership dedicated to advancing public understanding of the sector, as well as coming up with standards for future researchers to abide by. Going by the unwieldy name of the Partnership on Artificial Intelligence to Benefit People and Society, the alliance isn't a lobbying organisation (at least, it says it "does not intend" to lobby government bodies). Instead, it says it will "conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology". There will be equal representation between corporate and non-corporate members on the board of the partnership, and it hopes to invite "academics, non-profits and specialists in policy and ethics" to join. Each of the five founding corporate members has strong AI research teams, some of which have become household names, such as IBM's Watson and Amazon's Alexa.

When it comes to policing artificial intelligence, technology leaders think there is safety in numbers. A new organization called the Partnership on Artificial Intelligence to Benefit People and Society will seek to foster public dialogue and create guidelines for developing AI so that systems do not misbehave. The companies involved include Google and its subsidiary DeepMind, Facebook, Amazon, Microsoft, and IBM. The partnership is founded on eight tenets or principles, including the idea that AI should benefit as many people as possible; that the public should be involved in its development; that research should be conducted in an open way; and that AI systems should be able to explain their reasoning. That such fierce rivals would come together in this way shows how important the companies feel it is to head off public concern and speculation over the potential impacts of AI.

The regular engagement of experts across multiple disciplines (including but not limited to psychology, philosophy, economics, finance, sociology, public policy, and law) to discuss and provide guidance on emerging issues related to the impact of AI on society.

I am a Post-Doctoral Associate in the Computer Science Department at Courant Institute of Mathematical Sciences, New York University. I am working in the Laboratory of prof. Since January 2017 I will be an Assistant Professor in the Department of Electrical and Computer Engineering at NYU Tandon School of Engineering. I received my PhD from the Department of Electical Engineering at Columbia University in the City of New York, where I was also the Fu Foundation School of Engineering and Applied Science Presidential Fellowship holder (in years 2009-2012). I was co-advised by prof.

We've been naughty at Basecamp. Since before the launch of version 3, almost a year ago, we've had an internal API for chatbots. This allowed us to pipe in GitHub commits and control our operations infrastructure from Campfire. It was a quick, hackish version, but it was enough to make it work -- well, work for us. Finally it's time to atone and bring chatbots to everyone!

Today a new nonprofit organization called the Partnership on Artificial Intelligence to Benefit People and Society announced its establishment. Participants include Amazon, Google (and Google's DeepMind) Facebook, IBM, and Microsoft. Those companies will put up money and research resources (that could mean talent, open-source code, or data). Company representatives will sit on the organization's board alongside people from academia, the nonprofit world, and policy and ethics experts, according to a statement. Plans call for discussions, studies, reports, best practices, and public outreach in general.

The world's largest technology companies hold the keys to some of the largest databases on our planet. Much like goods and coins before it, data is becoming an important currency for the modern world. The data's value is rooted in its applications to artificial intelligence. Whomever owns the data, effectively owns AI. Right now that means companies like Facebook, Amazon, Alphabet, IBM, and Microsoft have a ton of power.

Researchers have developed machine learning software that can accurately diagnose a patient's breast cancer risk 30 times faster than doctors, based on mammogram results and personal medical history. The system could help doctors give better diagnoses the first time around -- which means fewer mammogram callbacks and false positives. "This software intelligently reviews millions of records in a short amount of time, enabling us to determine breast cancer risk more efficiently using a patient's mammogram," said one of the researchers, Stephen Wong, from Houston Methodist Research Institute. "This has the potential to decrease unnecessary biopsies." A mammogram is a breast X-ray that aims to spot any potentially cancerous cells before symptoms arise.

At Experian DataLabs in Carmel Valley, a team of scientists is thwarting bad guys with math. A top-five U.S. credit card issuer recently dumped about 6 billion transaction records on Experian DataLabs to see if its fancy machine learning mathematical formulas could do a better job of rooting out credit card fraud than the bank's existing system. Experian scientists used neuro-embedding/natural language processing techniques to understand the "syntax" of the credit card data, said Honghao Shan, a Ph.D. computer scientist. "We thought we had figured it out and went back to them," said Eric Haller, head of Experian DataLabs. "They said, how did you do that? You identified fraud that we can't identify ourselves. And it turns out we reduced their false positives by half."

Let's face it: artificial intelligence is scary. After decades of dystopian science fiction novels and movies where sentient machines end up turning on humanity, we can't help but worry as real world AI continues to improve at such a rapid rate. Sure, that danger is probably decades away if it's even a real danger at all. But there are many more immediate concerns. Will automated robots cost us jobs?