By combining robust regression and prior information, we develop an effective robust regression method that can resist adaptive adversarial attacks. Due to the widespread existence of noise and data corruption, it is necessary to recover the true regression parameters when a certain proportion of the response variables have been corrupted. Methods to overcome this problem often involve robust least-squares regression. However, few methods achieve good performance when dealing with severe adaptive adversarial attacks. Based on the combination of prior information and robust regression via hard thresholding from [ 1 ], this paper proposes an algorithm that improves the breakdown point when facing adaptive adversarial attacks. Furthermore, to improve the robustness and reduce the estimation error caused by the inclusion of a prior, the idea of Bayesian reweighting is used to construct a more robust algorithm. We prove the theoretical convergence of proposed algorithms under mild conditions. Extensive experiments show that, under different dataset attacks, our algorithms achieve state-of-the-art results compared with other benchmark algorithms, demonstrating the robustness of the proposed approach.

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users' satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes.

In early 19th-century England, the Luddites rebelled against the introduction of machinery in the textile industry. The Luddites' name originates from the mythical tale of a weaver's apprentice called Ned Ludd who, in an act of anger against increasingly dangerous and poor working conditions, supposedly destroyed two knitting machines. Contrary to popular belief, the Luddites were not against technology because they were ignorant or inept at using it (1). In fact, the Luddites were perceptive artisans who cared about their craft, and some even operated machinery. Moreover, they understood the consequences of introducing machinery to their craft and working conditions.

Artificial intelligence is pervasive; every major category of technology now incorporates AI techniques and the trend is growing. Although AI offers many benefits, risks and ethical issues abound. Despite having an enormous potential impact on society, jobs, and the economy, policymaking and educational planning have not kept pace with changes in technology, nor are we close to adopting updated legal frameworks. Also: 13 AI trends that will reshape the economy in 2018 TechRepublic Dr. Shirley Malcom is a respected and prominent educator who handles education policy at the American Association for the Advancement of Science (AAAS), which is the world's largest general scientific association and is best known for publishing Science magazine. Among her many honors, Shirley is a Regent of Morgan State University and on the Board of Trustees at Caltech. Education reform and worker re-training in the era of AI are crucial priorities for her.

When members of the scientific community gathered at the AAAS Annual Meeting in February, they did so in front of laptops and tablets from their home offices and dining tables. They presented over Zoom, submitted questions via chat, and caught up with colleagues over social media. The 2021 AAAS Annual Meeting was unlike any other in the meeting's 187-year history, but the fully virtual setting did not dampen enthusiasm for sharing science in keeping with the “Understanding Diverse Ecosystems” meeting theme. Dozens of scientific sessions shared new research in areas ranging from microbiomes to space travel. More than 40 workshops offered attendees the opportunity to discuss strategies for working in the ecosystems of academia and science policy. Plenary and topical lecturers covered timely topics, including Ruha Benjamin on how technology can deepen inequities, Anthony Fauci on the next steps for COVID-19 response, Mary Gray on research ethics, and Yalidy Matos on immigration policies. “The quality of the speakers was absolutely undeniable, and the diversity of the speakers—across gender, race, region—was just extraordinary,” said Sudip Parikh, chief executive officer of AAAS and executive publisher of the Science family of journals. “That is what our vision of the world looks like in a place where science is done with creativity and innovation and excellence.” Selecting a diverse meeting program is grounded in AAAS's values, but it is not without concerted effort, according to Claire Fraser. Fraser, who served as AAAS president through February and now serves as chair of the AAAS Board of Directors, selected the meeting theme and led the AAAS Meeting Scientific Program Committee, which oversees selection of the meeting's speakers. “The diversity doesn't happen by accident. I think it reflects the very strong commitment on the part of the Scientific Program Committee to make sure that not only is the science presented timely and excellent, but the diversity of speakers and participants is as broad as it possibly can be,” said Fraser, director of the Institute for Genome Sciences at the University of Maryland School of Medicine. Diversity isn't an afterthought—it's a deliberate part of the very first review of potential scientific sessions, according to Andrew Black, chief of staff and chief public affairs officer. When hundreds of volunteer reviewers evaluate the quality of the submissions before sending the best for consideration by the Scientific Program Committee, they are also looking for diversity across many dimensions, Black said. Among those dimensions are diversity of scientific discipline—befitting AAAS's multidisciplinary membership—but also gender, race and ethnicity, geographic diversity, career stage, and type of institution, including all types and sizes of universities, industry, and government. “Who do you see, who do you hear, and what kind of voices are in dialogue with each other? That's part of our assessment process,” said Agustín Fuentes, professor of anthropology at Princeton University and a member of the Scientific Program Committee. The review process offers opportunities for applicants to diversify their sessions. Applicants are often encouraged to look beyond their own networks to add a range of voices to their presentation to best communicate their ideas to the broader scientific community, Fuentes said. “We need to think very carefully in this moment in time about how do we not only redress past biases and discriminatory practices but how do we create a space, a voice, and a suite of presenters that is very inviting to a diverse audience,” Fuentes said. Added Fraser, “What you end up with is even better because you have such broad perspectives represented.” The committee also emphasized the importance of ensuring that a diverse group of decision-makers have a seat at the table. Members of the Scientific Program Committee, who are nominated from across AAAS and its 26 disciplinary sections and approved by the AAAS Board, represent a broad range of groups and perspectives, Fraser said. “What I firmly believe is that you can't come up with a diverse program like we had this year and like we've had in previous years without that diversity in the program committee,” Fraser said. Commitment to diversity across many axes is part of AAAS Annual Meeting history. In the 1950s, AAAS refused to hold meetings in the segregated South. In 1976, under one of AAAS's first female presidents, Margaret Mead, the Annual Meeting was fully accessible to people with disabilities for the first time. According to the AAAS Project on Science, Technology, and Disability, wheelchair ramps were added to the conference hall, programs were made accessible for hearing-impaired and visually impaired attendees, and Mead's presidential address was simultaneously interpreted in sign language. In 1978, AAAS's Board of Directors voted to move the following year's Annual Meeting out of Chicago because Illinois had not ratified the Equal Rights Amendment. In 1993, AAAS moved its 1999 meeting from Denver after Colorado voters adopted a constitutional amendment to deny residents protection from discrimination based on sexual orientation. Leaders at AAAS note that there is always more work to be done in the present and future—both at the Annual Meeting and year-round. AAAS continues to focus on its own systemic transformation in areas of diversity, equity, and inclusion and on the breadth of initiatives in its new Inclusive STEM Ecosystems for Equity & Diversity program, all to ensure that the scientific enterprise reflects the full range of talent. That goal resonated with many 2021 AAAS Annual Meeting speakers, too. A more diverse group of scientists creating artificial intelligence systems can improve those systems, said Ayanna Howard, a roboticist who leads The Ohio State University's College of Engineering, during her topical lecture, “Demystifying AI Through the Lens of Fairness and Bias.” Said Howard, “We as people are diverse and we're different and it makes us unique and beautiful, and our AI systems should be designed in such a way.” Nalini Nadkarni, a University of Utah biologist who delivered a topical lecture on “Forests, the Earth, and Ourselves: Understanding Dynamic Systems Through an Interdisciplinary Lens,” shared how she reaches young girls to let them know that science—and her own scientific specialty—is a space where they can thrive. She and her students created and distributed “Treetop Barbie,” dressing a doll in fieldwork clothes and creating a doll-sized booklet about canopy plants. The Annual Meeting offers a chance to show that science is best when it is for everyone, regardless of background or perspective, whether they're a kid or just a kid at heart. Said Parikh, “The AAAS Annual Meeting is where the pages of Science literally come alive. It's a place where scientists, no matter what discipline or industry they decided to pursue, can pull back and just fall in love with the idea of science again—like we did when we were kids.”

Rice University statistician Genevera Allen knew she was raising an important issue when she spoke earlier this month at the American Association for the Advancement of Science (AAAS) annual meeting in Washington, but she was surprised by the magnitude of the response. Allen, associate professor of statistics and founding director of Rice's Center for Transforming Data to Knowledge (D2K Lab), used the forum to raise awareness about the potential lack of reproducibility of data-driven discoveries produced by machine learning (ML). She cautioned her audience not to assume that today's scientific discoveries made via ML are accurate or reproducible. She said that many commonly used ML techniques are designed to always make a prediction and are not designed to report on the uncertainty of the finding. Her comments garnered worldwide media attention, with some commentators questioning the value of ML in data science.

Dr Genevera Allen from Rice University in Houston said that the increased use of such systems was contributing to a "crisis in science". She warned scientists that if they didn't improve their techniques they would be wasting both time and money. Her research was presented at the American Association for the Advancement of Science in Washington.

Next week in Washington, DC, the Annual Meeting of the American Association for the Advancement of Science (AAAS, the publisher of Science) will celebrate science and explore many daunting global challenges. The meeting's theme--Science Transcending Boundaries--considers how science can bring together people, ideas, and solutions from across real and artificial borders, disciplines, sectors, ideologies, and traditions. The scientific community must evolve to meet new realities if it is to continue its path of growth and progress and address the world's most pressing problems. The benefits of science and technology cannot be dismissed. They are embedded in our daily lives and undergird the solutions to everything from poverty to disease; sustainable food, water, and energy; climate change; and national and international security.

AAAS analyst assists a human rights organization in gathering data during an exhumation. Against a backdrop of summer heat and a constant roar of distant howler monkeys, a scientific analyst piloted a drone to collect data from a hillside in northern Guatemala. At his side, anthropologists affiliated with a regional human rights group painstakingly cleared soil and roots from human remains in a mass grave. "Remains contorted, overlapping, interlaced, a cruel, tragic mashup of Hieronymus Bosch and H.R. Giger," noted Jonathan Drake, senior program associate of the American Association for the Advancement of Science's Geospatial Technologies Project, summoning images from 15th- and 20th-century artists to describe the nightmarish remnants of an atrocity estimated to have occurred sometime after 1980, during Guatemala's lengthy civil war. Clothing with burnt edges stuck to the bones of some.

Research Scientist Suzanne Pierce leads a panel on water management and AI... view more Artificial intelligence - or AI - is helping people make better decisions about how to manage water resources. That's because scientists are taking the best tools of advanced computing to help make science-based decisions about complex and pressing problems in how to manage Earth's resources, including water. Some of those tools include benchmarks that make data accessible on open repositories and help ease testing on machine learning algorithms and other methodologies from intelligent systems. Other tools include new kinds of interfaces and visualizations that help decision makers see meaning in data. Computational tools, such as directed networks to visualize connections and patterns in a dataset, are helping bridge advanced computing with the geosciences. A science panel on AI and water management meets in Austin, Texas on February 17th at the 2018 meeting of the American Association for the Advancement of Science.