Much work on social media opinion polarization focuses on identifying separate or orthogonal beliefs from media traces, thereby missing points of agreement among different communities. This paper develops a new class of Non-negative Matrix Factorization (NMF) algorithms that allow identification of both agreement and disagreement points when beliefs of different communities partially overlap. Specifically, we propose a novel Belief Structured Matrix Factorization algorithm (BSMF) to identify partially overlapping beliefs in polarized public social media. BSMF is totally unsupervised and considers three types of information: (i) who posted which opinion, (ii) keyword-level message similarity, and (iii) empirically observed social dependency graphs (e.g., retweet graphs), to improve belief separation. In the space of unsupervised belief separation algorithms, the emphasis was mostly given to the problem of identifying disjoint (e.g., conflicting) beliefs. The case when individuals with different beliefs agree on some subset of points was less explored. We observe that social beliefs overlap even in polarized scenarios. Our proposed unsupervised algorithm captures both the latent belief intersections and dissimilarities. We discuss the properties of the algorithm and conduct extensive experiments on both synthetic data and real-world datasets. The results show that our model outperforms all compared baselines by a great margin.

The European Commission is in consultation with EU data protection authorities following the news that US technology firm Clearview AI has scraped more than three billion facial images from social media sites including YouTube, Facebook and Twitter, without obtaining the permission of users. It has also transpired following an investigation by Buzzfeed news that the company wants to expand its service to the European market, with nine European countries including Italy, Greece, and the Netherlands as potential partners. Meanwhile, EURACTIV has been informed by a US official that Clearview AI is not a member of the 2016 EU-US Privacy Shield agreement, which obliges American companies to protect personal data belonging to EU citizens, according to EU standards and consumer rights. Clearview AI has not as yet disclosed whether any of the images have been harvested from EU citizens. If this were to be the case, the software may violate the EU's General Data Protection Regulation, Article 4 (14) of which covers the processing of biometric data.

If you're uncertain whether AI is the best or worst thing to ever happen to cybersecurity, you're in the same boat as experts watching the dawn of this new era with a mix of excitement and terror. AI's potential to automate security on a broader scale offers a welcome advantage in the short term. Yet unleashing a technology designed to eventually take humans out of the equation as much as possible naturally gives the industry some pause. There is an undercurrent of fear about the consequences if things run amok or attackers learn to make better use of the technology. "Everything you invent to defend yourself can also eventually be used against you," said Geert van der Linden, an executive vice president of cybersecurity for Capgemini.

The European Union won't issue a ban on facial recognition tech, as it once proposed, the Financial Times reports. In a previous draft of a paper on artificial intelligence, the European Commission suggested a five-year moratorium on facial recognition, so that the technology's impact could be studied, noting that it can be inaccurate, used to breach privacy laws and facilitate identity fraud. In a new draft, seen by the Financial Times, that moratorium has been removed. Instead, it seems the European Commission will encourage individual member states to set their own facial recognition rules. The latest draft suggests that independent groups assess each proposed public use of the technology.

After the messy reporting of the Iowa caucus results, some who build tech for progressive causes say the approach to software development in this space needs rethinking. After the messy reporting of the Iowa caucus results, some who build tech for progressive causes say the approach to software development in this space needs rethinking. Democrats could avoid another tech meltdown like the one that afflicted the Iowa caucuses with a better strategy for building the tools they need, progressive technology specialists say. The origins of the Iowa debacle are in a boom-and-bust cycle that places technology in competition with other priorities as time-crunched campaigns grapple with how best to spend as they hurtle toward an election. "The easy way to spend money, that's reliable, is on advertising," says Evan Henshaw-Plath, a technologist who has built applications for progressive causes and was an early employee at Twitter.

Positive, reliable and human-centric artificial intelligence (AI) relies on the willingness of Europe as a whole to design a balanced and inclusive governance framework that would allow it to become a leader in the development of trustworthy AI technologies worldwide. That was the main conclusion reached in the frame of the high-level workshop organised by the Panel for the Future of Science and Technology (STOA) on 29 January 2020 at the European Parliament in Brussels. The first STOA event for this parliamentary term (2019-2024) drew a full house with Members of the European Parliament, European Commission leaders, academic experts and representatives of international organisations debating how to strike the right balance on AI. Harnessing the numerous benefits that the transformative power of AI can bring needs to also take account of the necessity to mitigate a number of potential risks – from hampering people's fundamental rights, such as privacy or non-discrimination – to undermining European values such as democracy, human dignity and the right to assemble. The event proved to be a timely occasion to discuss how Europe could maximise the benefits and address the challenges of AI in a human-centric way, coming only a few days before the publication of the European Commission's legislative plans on AI in the form of a White Paper on 19 February 2020.

Within the next two years, annual spending on AI would rise to more than $2 billion and funding for quantum computing would increase to $860 million, according to the White House plan. The proposed increases in AI spending include more than $850 million at the National Science Foundation, $125 million at the Department of Energy's Office of Science and $100 million at the Agriculture Department, among other agencies. The budget also proposes $50 million in AI and quantum education and job training initiatives, including partnerships with community colleges. "Early-stage research is a high priority," Kelvin Droegemeier, director of the White House Office of Science and Technology Policy, said about proposed AI and quantum funding on a media conference call Monday. U.S. Chief Technology Officer Michael Kratsios, also speaking on the call, said the country is facing a "global power competition" for AI, quantum computing and other critical technologies.

Artificial Intelligence is seen by many as the latest solution to a growing threat: the rise of cyber attacks in recent years. Machine learning and other AI applications can be embedded within algorithms in basically any software. Given the fact that today's world pretty much runs digitally, AI seems to be the answer to cybercrime damages that will cost the world $6 trillion every year by the time we reach 2021. However, while AI can exponentially boost cybersecurity, it can also make the task even more complex. AI can be used and modified by hackers, who are always eager to evolve and use the last available tech in the market to cause harm.

If Hoan Ton-That is feeling the pressure, he isn't showing it. Over the last month, fears about facial recognition technology and police surveillance have intensified, all thanks to Ton-That's startup, Clearview AI. First came a front-page investigation in The New York Times, revealing Clearview has been working with law enforcement agencies to match photos of unknown faces to people's online images. Next, cease-and-desist letters rolled in from tech giants Twitter, Google and Facebook. Lawmakers made inquiries and New Jersey enacted a statewide ban on law enforcement using Clearview while it looks into the software.

Today's global sanctions regimes have arguably never been more challenging for organisations to ensure they remain compliant and have the required screening processes and procedures in place. Over the past decade, trade and economic sanctions have become an ever more popular tool of foreign policy in an increasingly uncertain geo-political climate. Aside from country-specific sanctions, such as those against Iran, Russia, North Korea, etc, more targeted regulations focus upon particular businesses or individuals. As a result, national and international AML, screening and anti-fraud obligations have increased in both scope and complexity. Failure to comply with sanctions and money laundering obligations, can result in severe financial and reputational costs.