As Artificial Intelligence (AI) technologies proliferate, concern has centered around the long-term dangers of job loss or threats of machines causing harm to humans. All of this concern, however, detracts from the more pertinent and already existing threats posed by AI today: its ability to amplify bias found in training datasets, and swiftly impact marginalized populations at scale. Government and public sector institutions have a responsibility to citizens to establish a dialogue with technology developers and release thoughtful policy around data standards to ensure diverse representation in datasets to prevent bias amplification and ensure that AI systems are built with inclusion in mind.

Bogota - Carmenza Gomez was planning a surprise Christmas dinner in the winter of 2008 to celebrate having her eight children back together under one roof in their home in an impoverished suburb in Bogota, the capital of Colombia. That summer, the family had finally been reunited after years apart due to the sons' military service. It was months away, but Carmenza wanted to throw an elaborate dinner to share their first Christmas together in years. But just days after the last of her sons arrived home, 23-year-old Victor Fernando, her third youngest, disappeared. "I didn't tell any of them what I was planning [for Christmas]," Carmenza recalled nearly a decade later.

One candidate fled the violence of Colombia with her mom at age nine. Another fled the Taliban at age six. A third says his parents were almost deported from the United States. Catalina Cruz and Safiya Wazir won their primary elections in New York and New Hampshire respectively last week, while William Tong is campaigning to become Connecticut's first Asian American attorney general. They're representative of a surge of minority candidates in this year's midterm elections, in which more women and people of color are not only running for office--but also winning votes and unseating entrenched politicians.

Chinese internet giant Alibaba is doubling down on its chip manufacturing with a dedicated subsidiary, co-founder and chairman Jack Ma said at an event in Hangzhou this week. The company wants to launch its first self-developed AI inference chip in the second half of 2019, supporting its move into self-driving vehicles and smart products. The move follows the company's announcement back in April that it had begun testing its own autonomous vehicle technology. China's government has been pushing to raise the standard of its home-produced chips -- particularly for use within the transport and healthcare sector -- in a bid to raise its profile as a leading tech innovator, but also to avoid over-reliance on US imports, which are continually under jeopardy due to ongoing trade tensions. Back in June, for example, President Donald Trump levied a 25 percent tariff on $50 billion worth of Chinese goods.

Companies and cities all over world are experimenting with using artificial intelligence to reduce and prevent crime, and to more quickly respond to crimes in progress. The ideas behind many of these projects is that crimes are relatively predictable; it just requires being able to sort through a massive volume of data to find patterns that are useful to law enforcement. This kind of data analysis was technologically impossible a few decades ago, but the hope is that recent developments in machine learning are up to the task. There is good reason why companies and government are both interested in trying to use AI in this manner. As of 2010, the United States spent over $80 billion a year on incarations at the state, local, and federal levels. Estimates put the United States' total spending on law enforcement at over $100 billion a year. Law enforcement and prisons make up a substantial percentage of local government budgets.

One of the most common refrains about fighting in cyber space is that the offense has the advantage over the defense: The offense only needs to be successful once, while the defense needs to be perfect all the time. Even though this has always been a bit of an exaggeration, we believe artificial intelligence has the potential to dramatically improve cyber defense to help right the offense-defense balance in cyber space.

It sounds eerily similar to the plot of an episode of Charlie Brooker's popular dystopian science fiction series Black Mirror. But China's controversial social credit system – in which all of its 1.4 billion citizens are'ranked' on their behaviour in real-time – is on track to launch by 2020. Completing community service and buying Chinese products is thought to improve your social standing, which is given as a score out of 800. Those rated'top citizens' get VIP treatment at airports, discounted loans, waived deposits on hotel and car rentals and fast-tracking to elite universities. Fraud, tax evasion and smoking in non-smoking areas can drop your ranking, as well as buying items in supermarkets that the government doesn't approve of - such as alcohol or video games.

As businesses struggle to combat increasingly sophisticated cybersecurity attacks, the severity of which is exacerbated by both the vanishing IT perimeters in today's mobile and IoT era, coupled with an acute shortage of skilled security professionals, IT security teams need both a new approach and powerful new tools to protect data and other high-value assets. Increasingly, they are looking to artificial intelligence (AI) as a key weapon to win the battle against stealthy threats inside their IT infrastructures, according to a new global research study conducted by the Ponemon Institute on behalf of Aruba, a Hewlett Packard Enterprise company HPE, 1.66% This press release features multimedia. The Ponemon Institute study, entitled "Closing the IT Security Gap with Automation & AI in the Era of IoT," surveyed 4,000 security and IT professionals across the Americas, Europe and Asia to understand what makes security deficiencies so hard to fix, and what types of technologies and processes are needed to stay a step ahead of bad actors within the new threat landscape. The research revealed that in the quest to protect data and other high-value assets, security systems incorporating machine learning and other AI-based technologies are essential for detecting and stopping attacks that target users and IoT devices.

Elon Musk is one of the world's most prominent business figures. His latest headline-grabber is the announcement of the first paying passenger his SpaceX venture plans to fly around the Moon. There are also his extraordinary pioneering achievements include creating online payment platform PayPal, running electric car maker Tesla, as well as SpaceX. His innovative and wide-ranging interests include solar energy and artificial intelligence, and he has promised the Hyperloop, a super-high speed magnetic train travel, in an underground tube and he has designs on Mars. But this year, things seem to have turned sour for the tech entrepreneur.

SAP has created an AI ethics panel to guide its use of machine-learning technology. If only it had a similar committee for fraud allegations: it might have avoided the corruption scandal engulfing it in South Africa. The German ERP giant – which is accused of kicking back $2m to secure state contracts – claimed it is the first European biz to create a external artificial intelligence ethics board: a five-person committee that includes technical experts and specialists in public policy, ethics, and bioethics. However, while several of them possess solid IT credentials, there's no one with a background in AI. Rather, expertise in the evolving field will come from inside SAP.