Just like much of the content on the internet, fake news is funded largely by advertising.  Therefore, this week Facebook announced that pages that share “fake news,” or false stories masquerading as truth, will no longer be allowed to advertise on its platform.  The goal is straightforward:  to punish pages that link to stories that are marked as “false” by third-party fact-checkers from making money. 

Terrorists and other hate groups like al-Qaeda, ISIS, white supremacists, and neo-Nazis use social media and video streaming platforms to publish and spread their hateful and offensive content for radicalization, propaganda, or organizational purposes. After the recent tragic events in Charlottesville, the tech community has been figuring out ways to respond.  Platforms have increased the rate of which they either take down white supremacist content or make it harder to find.  But, many companies and platforms have been flagging and taking down such harmful for a long while, especially pertaining to terrorist content.

According to the Environmental Protection Agency, a majority of rivers and streams in America cannot support healthy life with the number of rivers being polluted trending upwards.  55 percent of waterways in America are currently listed as “poor” and another 23 percent are listed as “fair.”  Additionally, millions of Americans drink water that contains unsafe levels of industrial chemicals according to Environmental Science & Technology Letters.  When it comes to water pollution specifically, AI technology can help detect the sources of pollution for clean-up. This week’s AI spotlight is on a robot called Envirobot which uses AI technology to find sources of pollution in bodies of water.  Developed by scientists at the Swiss research institute, École Polytechnique Fédérale de Lausanne (EPFL), Envirobot is a four-foot long eel-like robot that is made up with small compartments attached to each other.  Ea ...

Suicide is ranked as the third leading cause of death among people ages 10 to 14 and second among people ages 15 to 24 according to the Center for Disease Control and Prevention.  Obviously, suicide and depression are a serious problem facing society. People who are contemplating suicide often feel helpless and reach out, but hearing and acting on cries for help doesn’t always happen in time. Tragically, many people who have struggled with depression and/or suicidal thoughts have used social media to post notes about their intentions to take their own lives or even live stream their suicides. In response, Facebook announced a few months ago that it would be taking more initiative in using its platform for social good.  One of Facebook’s tools to aide with suicide prevention is artificial intelligence. Facebook has developed algorithms that recognize patterns in user’s posts to flag them in case they are at risk of committing suicide.  Critics hav ...

My recent InfoWorld blog took aim at Elon Musk’s recent call for regulation of AI research.  While a deregulation-minded Washington is unlikely to set up a new federal AI agency to oversee AI applications and research, Musk insists that he wants exactly that. In remarks after his comments to the National Governors Association meeting, Musk clarified that “the process of seeking the insight required to put in place informed rules about the use and development of AI should start now. Musk compared it to the process of establishing other government bodies regulating use of technology in industry, including the FCC and the FAA. “I don’t think anyone wants the FAA to go away,” he said.” But this is even more worrisome.  He is proposing establishing an agency with full regulatory authority over every use of AI.  After setting up such an omnibus regulatory structure, then he wants the agency to figure out what it should do! But this ...

 Towards the conclusion of many legal investigations, lawyers typically find themselves mired in paperwork, documents that span several years if not decades of information pertaining to a specific issue.  Legal teams are then tasked with the seemingly insurmountable challenge of sifting through millions of these spreadsheets, emails, and other documents and sorting them into the necessary categories.  Not only is this process extremely inconvenient and inefficient, it is also incredibly costly and runs the risk of missing important information that is relevant to a case, information that could show that fraud has taken place. A few weeks ago, SIIA published an AI Spotlight on the benefits of FICO’s AML Threatscore tool which uses artificial intelligence to detect for irregular financial activities like money laundering, terrorist financing, and fraud.  In that same vein, this week’s Spotlight is on AI technology that intuitively aids in the sifting an ...

You probably have gotten a call or email from your credit card issuer asking if you made a particular transaction. Ever wonder what triggered it?  Turns out it is a form of artificial intelligence called a neural network.  Instead of creating general rules about what transactions are likely to be fraudulent, a neural network just looks at all your transactions and figures out your very own individual pattern of usage. If a new transaction is significantly out of pattern, that’s when you get the call or the email.

U.S. companies have been bringing manufacturing home, and with this has come almost a quarter of a million jobs since 2010. And more are on their way — Deloitte reports that about half of U.S. manufacturing executives plan to bring home some portion of their operations by 2020. But there’s a hard truth beneath this positive trend: While domestic manufacturing is near all-time highs, America is not fully prepared to fill the jobs of the future.

"I'm afraid for all those who'll have the bread snatched from their mouths by these machines. ... What business has science and capitalism got, bringing all these new inventions into the works, before society has produced a generation educated up to using them?" —Henrik Ibsen, a character in his play The Pillars of Society

Gavyn Davies writes in an April 30, 2017 Financial Times piece that “there have been some signs that productivity growth may be starting to recover from the low points reached a few years ago.”  Davies notes that Jan Hatzius from Goldman Sachs shows somewhat improving labor productivity growth starting in 2016 – Hatzius used official data and numbers from the Institute for Supply Management (ISM) purchasing manager’s index.  And Juan Antolin-Diaz is slated to publish work in the Review of Economics and Statistic next month showing an increase in trend productivity growth from 0.3% in 2012 Q2 to 0.7% now.  Davies himself, however, concedes that these numbers are tentative.