Artificial Intelligence (AI) is a fascinating technological development that is significantly impacting our present-day lives. Given AI's potential, there is a need to carefully examine what is being entrusted to the AI system and to build mechanisms to obtain the advantages of AI and to avoid its disadvantages. AI is a potent digital computational reality and even though AI-driven applications are widespread, still there seems to be limited appreciation of the role AI is playing in our lives. However, recent technological advances in designing self-driving vehicles have helped focus attention on AI and have helped people better understand the powerful potential of AI. The prospect of safe self-driving or autonomous vehicles is quite amazing, and this possibility has justifiably attracted much attention.

The high expectations of AI have triggered worldwide interest and concern, generating 400 policy documents on responsible AI. Intense discussions over the ethical issues lay a helpful foundation, preparing researchers, managers, policy makers, and educators for constructive discussions that will lead to clear recommendations for building the reliable, safe, and trustworthy systems6 that will be commercial success. This Viewpoint focuses on four themes that lead to 15 recommendations for moving forward. The four themes combine AI thinking with human-centered User Experience Design (UXD). Ethical discussions are a vital foundation, but raising the edifice of responsible AI requires design decisions to guide software engineering teams, business managers, industry leaders, and government policymakers.

Carter shook her head and stared at the combined camera and microphone that surveyed the corridor. Lipcott's words seemed to float in front of her eyes. What she did next could determine not just Lipcott's future, but her own. She walked on to the corner, to a dead spot between cameras, took a deep breath, and mouthed, "Don't ask questions.

Nearly 1,000 current and former Activision Blizzard Inc. employees have signed a letter calling the company's responses to a recent discrimination lawsuit "abhorrent and insulting." The new letter, which was reviewed by Bloomberg, was circulated Monday following a turbulent week for the publisher behind games like Call of Duty and World of Warcraft. Last week, the California Department of Fair Housing and Employment filed an explosive lawsuit against Activision Blizzard that alleged sexual discrimination, harassment and retaliation. In response, an Activision Blizzard spokesman called the allegations false and distorted. A subsequent email from Activision executive Frances Townsend described the suit's claims as "factually incorrect, old and out of context."

A new alliance of professional and research organisations is aiming to deliver a set of professional standards for data scientists. If widely adopted, the framework could go a long way to ensuring those working on advanced AI and machine learning systems (AI/ML) do so in a way that mitigates the emerging technology's risk to society. It could eventually lead to anyone unethically implementing AI being'struck off', or banned from the profession, one expert told Tech Monitor. The Alliance for Data Science Professionals has been formed by organisations including the BCS, the chartered institute for IT, and the Alan Turing Institute for AI research, along with the Royal Statistical Society, the Institute of Mathematics and the National Physical Laboratory. It aims to set the standards "needed to ensure an ethical and well-governed approach so the public, organisations and governments can have confidence in how their data is used".

Motion blur caused by the moving of the object or camera during the exposure can be a key challenge for visual object tracking, affecting tracking accuracy significantly. In this work, we explore the robustness of visual object trackers against motion blur from a new angle, i.e., adversarial blur attack (ABA). Our main objective is to online transfer input frames to their natural motion-blurred counterparts while misleading the state-of-the-art trackers during the tracking process. To this end, we first design the motion blur synthesizing method for visual tracking based on the generation principle of motion blur, considering the motion information and the light accumulation process. With this synthetic method, we propose \textit{optimization-based ABA (OP-ABA)} by iteratively optimizing an adversarial objective function against the tracking w.r.t. the motion and light accumulation parameters. The OP-ABA is able to produce natural adversarial examples but the iteration can cause heavy time cost, making it unsuitable for attacking real-time trackers. To alleviate this issue, we further propose \textit{one-step ABA (OS-ABA)} where we design and train a joint adversarial motion and accumulation predictive network (JAMANet) with the guidance of OP-ABA, which is able to efficiently estimate the adversarial motion and accumulation parameters in a one-step way. The experiments on four popular datasets (\eg, OTB100, VOT2018, UAV123, and LaSOT) demonstrate that our methods are able to cause significant accuracy drops on four state-of-the-art trackers with high transferability. Please find the source code at https://github.com/tsingqguo/ABA

"AI is an instrument just like anything else. You can do harm and you can do wonderful things. ESG is the embodiment of all the good things you can do with AI. Squeeze all the juice out of AI but at the same time we need to understand the consequences so we can do things responsibly!" The wise words from Aiko Yamashita, Senior Data Scientist at the Advanced Analytics Centre of Excellence in DNB Bank, during our conversation on Altair's'Future Says'.

Recently, the use of sound measures and metrics in Artificial Intelligence has become the subject of interest of academia, government, and industry. Efforts towards measuring different phenomena have gained traction in the AI community, as illustrated by the publication of several influential field reports and policy documents. These metrics are designed to help decision takers to inform themselves about the fast-moving and impacting influences of key advances in Artificial Intelligence in general and Machine Learning in particular. In this paper we propose to use such newfound capabilities of AI technologies to augment our AI measuring capabilities. We do so by training a model to classify publications related to ethical issues and concerns. In our methodology we use an expert, manually curated dataset as the training set and then evaluate a large set of research papers. Finally, we highlight the implications of AI metrics, in particular their contribution towards developing trustful and fair AI-based tools and technologies. Keywords: AI Ethics; AI Fairness; AI Measurement. Ethics in Computer Science.

To design and engineer ethical and legal reasoners and responsible systems, Benzm\"{u}ller, Parent and van der Torre introduce LogiKEy methodology based on the semantical embedding of deontic logics into classic higher-order logic. In this paper, we considerably extend the LogiKEy deontic logics and dataset using an algebraic approach. We develop theory of input/output operations for normative reasoning on top of Boolean algebras.

Fox News congressional correspondent Jacqui Heinrich has the latest from Capitol Hill on'America Reports' The FBI was tipped off to a Texas man arrested Friday for allegedly assaulting police officers during the Capitol riot after messaging with a woman he met on the dating app Bumble in January, the Justice Department announced. Andrew Quentin Taake, 32, was charged with assaulting an officer, obstructing an official proceeding, and other offenses for his actions during the riot, which allegedly included pepper-spraying several officers and assaulting others with a whip-like weapon. The FBI received a tip from a woman he met on the online dating app, Bumble, on Jan. 9. Screenshots of their messages show that Taake sent the woman a selfie that was taken "about 30 minutes after being sprayed," allegedly telling the potential suitor that he was at the riot "from the very beginning." A woman who Andrew Quentin Taake matched with on Bumble tipped off the FBI about his alleged Capitol riot involvement. Taake allegedly flew to Washington, D.C., from Houston the day before the riot and returned home a few days later.