Cryptographic algorithms are what keep us safe online, protecting our privacy and securing the transfer of information. But many experts fear that quantum computers could one day break these algorithms, leaving us open to attack from hackers and fraudsters. And those quantum computers may be ready sooner than many people think. That's why there is serious work underway to design new types of algorithms that are resistant to even the most powerful quantum computer we can imagine. Read our emerging journalist fellow Tammy Xu's full story on how quantum-resistant algorithms are being developed--and what comes next.

The Federal Circuit recently held as a matter of statutory interpretation that an artificial intelligence system cannot be named as an inventor on a US patent application. This holding, which effectively excludes AI systems from the category of "individuals" eligible to be named as inventors, may complicate the intellectual property strategies of innovators who use advanced AI for research and development. Here's what happened and why it matters. The Federal Circuit was asked to determine whether an AI system called DABUS could be named as the inventor on two separate patent applications. The first disclosed a light source that was calibrated with a specific frequency corresponding to, among other characteristics, certain human brainwave activity.

Today, major healthcare companies are investing heavily into various AI-powered devices. For example, Zimmer Biomet and the New York City-based Hospital for Special Surgery recently inked a three-year deal to create the HSS/Zimmer Biomet Innovation Center for Artificial Intelligence in Robotic Joint Replacement. "The collaboration aims to develop decision support tools--powered by data collection and machine learning -- to assist surgeons planning and predicting outcomes for robotic-assisted joint replacements." Additionally, Johnson & Johnson have gone on record saying that they see "a huge opportunity to harness data, machine learning and artificial intelligence to help drive decision-making at all levels of healthcare." As artificial intelligence starts playing a larger role in the modern healthcare space, a critical question will need to be answered: Are AI-powered solutions products or services?

We propose and explore the possibility that language models can be studied as effective proxies for specific human sub-populations in social science research. Practical and research applications of artificial intelligence tools have sometimes been limited by problematic biases (such as racism or sexism), which are often treated as uniform properties of the models. We show that the "algorithmic bias" within one such tool -- the GPT-3 language model -- is instead both fine-grained and demographically correlated, meaning that proper conditioning will cause it to accurately emulate response distributions from a wide variety of human subgroups. We term this property "algorithmic fidelity" and explore its extent in GPT-3. We create "silicon samples" by conditioning the model on thousands of socio-demographic backstories from real human participants in multiple large surveys conducted in the United States. We then compare the silicon and human samples to demonstrate that the information contained in GPT-3 goes far beyond surface similarity. It is nuanced, multifaceted, and reflects the complex interplay between ideas, attitudes, and socio-cultural context that characterize human attitudes. We suggest that language models with sufficient algorithmic fidelity thus constitute a novel and powerful tool to advance understanding of humans and society across a variety of disciplines.

The growing interest in developing corpora of persuasive texts has promoted applications in automated systems, e.g., debating and essay scoring systems; however, there is little prior work mining image persuasiveness from an argumentative perspective. To expand persuasiveness mining into a multi-modal realm, we present a multi-modal dataset, ImageArg, consisting of annotations of image persuasiveness in tweets. The annotations are based on a persuasion taxonomy we developed to explore image functionalities and the means of persuasion. We benchmark image persuasiveness tasks on ImageArg using widely-used multi-modal learning methods. The experimental results show that our dataset offers a useful resource for this rich and challenging topic, and there is ample room for modeling improvement.

Companies with employees in the European Union (EU) could be affected by a landmark proposal to regulate the use of artificial intelligence (AI) across the region. The EU Artificial Intelligence Act, now working its way through the legislative process, is expected to shape technology and standards worldwide. The act comprises a broad set of rules seeking to regulate the use of AI across industries and social activities, noted Jean-François Gerard, a Brussels-based attorney for Freshfields Bruckhaus Deringer. The AI regulation proposes a sliding scale of rules based on risk: the higher the perceived risk, the stricter the rule, he said. The proposal would classify different AI applications as unacceptable, high, limited or minimal risks, according to a client briefing Gerard helped produce.

In the law, sometimes there is a need to craft a somewhat fictional aspect for purposes of allowing the wheels of justice to spin freely and not get unduly gummed up. That's where legal fiction can handily come to play. Per the definition of the Cornell Law School's Legal Information Institute (LII), a legal fiction is formally denoted as "an assumption and acceptance of something as fact by a court, although it might not be, so as to allow a rule to operate or be applied in a manner that differs from its original purpose while leaving the letter of the law unchanged." This is done ostensibly in the pursuit of justice, but for which can also be more modestly employed in the interests of convenience or for other jurisprudential benefits. I am reminding you about the nature of legal fiction to provide a bit of a potential surprise or some might say a mind-bending bombshell about a loosely proposed legal fiction regarding AI. Some experts suggest that we might need to concoct a legal fiction associated with ascribing a form of legal personhood to AI systems.

Companies are increasingly adopting automated systems to support, and sometimes even replace, humans in key steps of their hiring and employee management processes. According to Forbes, all Fortune 500 companies report using some form of automation in their HR pipelines. And it's not just large companies that are jumping on this trend: industry surveys have shown that at least 25% of all US-based companies plan to increase their use of automated systems in hiring and talent management over the next few years. From an economic perspective, it's not difficult to understand why companies are embracing automation. Automated systems offer a highly-scalable way to add efficiency to HR, and remove many critical bottlenecks when it comes to identifying and hiring new talent.

If you are ready to join a leader in the Retail and Technology space, please apply and Randstad will be more than happy to assist in helping you land your next role.

Dover, DE, Sept. 13, 2022 (GLOBE NEWSWIRE) -- Metatron Inc. (OTC Pink: MRNJ), a mobile and web technology pioneer having developed over 2,000 apps on iTunes and Google Play, is pleased to announce the Company is presently working to restructure corporate debt obligations in addition to the Company officially launching an Artificial Intelligence Application Division within Metatron, Inc. The Company is presently working in good faith with debt holders to consolidate, restructure and improve the Company's debt obligations. The more favorable terms and consolidation will assist the Company to improve and streamline the Company's balance sheet and financial reporting. Details of the restructuring will be announced upon final completion and execution. Having years of success in the mobile and web technology sectors, the Company views Artificial Intelligence (AI) as the unbridled beast of future technology growth.