A 2019 survey found that 73 of 84 prominent AI strategy documents referenced transparency or explainability [81]. Influential intergovernmental bodies such as United Nations agencies and the Organization for Economic Cooperation and Development (OECD) have put forth transparency and explainability as key mechanisms for ensuring that algorithmic systems produce beneficial outcomes and uphold "democratic values" [121, 143]. Algorithmic transparency and explainability can serve many purposes, but some of the most important are legal in nature: allowing lawmakers to understand and craft effective rules for algorithmic systems, enabling a broader set of stakeholders to be aware of (and obtain redress from) algorithmic harms, and assisting regulators in exercising meaningful oversight over the use of algorithms [81, 109]. To serve these objectives, transparency measures and explanation techniques must be developed with an understanding of the specific goals, constraints, and incentives of policymakers. This paper aims to help bridge the gap between policymakers and the explanation research community, helping researchers to better understand and respond to the needs of policymakers. To this end, it provides case studies illustrating five uses for algorithmic transparency and explanation in policy settings. These case studies (Table 1) were selected to span four axes: the spectrum from explanation to transparency (including both requirements for specific explanation techniques, like those developed by the machine learning research community, and broader forms of transparency requirements); different jurisdictions (including U.S. federal regulators, U.S. states, and the EU); policy actors with differing technical and financial capacities; and a diverse array of policy approaches (including prescriptive technical rules, process-oriented rules, nonbinding guidelines, and modifications to legal procedures). Building on these case studies, this paper argues that explanation techniques developed by the research community can be too complex, too uncertain, or too restricted to satisfy the constraints that policymakers and the law operate under in practice. As a result, explanation is often limited in its ability to enable meaningful public policy solutions to algorithmic harms.

A delegation of top tech leaders including Sundar Pichai, Elon Musk, Mark Zuckerberg and Sam Altman convened in Washington on Wednesday for the first of nine meetings with US senators to discuss the rise of artificial intelligence and how it should be regulated. Billed as an "AI safety forum," the closed door meeting was organized by the Democratic senator Chuck Schumer who called it "one of the most important conversations of the year". The forum comes as the federal government explores new and existing avenues to regulate AI. "It will be a meeting unlike any other that we have seen in the Senate in a very long time, perhaps ever: a coming together of top voices in business, civil rights, defense, research, labor, the arts, all together, in one room, having a much-needed conversation about how Congress can tackle AI," Schumer said when announcing the forum. Several AI experts and other industry leaders are also in attendance, at the listening sessions, including Bill Gates; the Motion Picture Association CEO, Charles Rivkin; the former Google CEO Eric Schmidt; the Center for Humane Technology co-founder Tristan Harris; and Deborah Raji, a researcher at University of California, Berkeley. Some labor and civil liberties groups are also represented among the 22 attendees including Elizabeth Shuler, the president of the labor union AFL-CIO; Randi Weingarten, the president of the American Federation of Teachers; Janet Murguía, the president of UnidosUS; and Maya Wiley, the president and CEO of the Leadership Conference on Civil & Human Rights.

Sen. Elizabeth Warren said AI should be regulated to protect privacy and safety following a closed door hearing with tech leaders. Following a closed Senate AI forum with tech giants, union leaders and artificial intelligence experts, Sen. Elizabeth Warren, D-Mass., told reporters Wednesday AI should be regulated to protect privacy. She also criticized the decision to keep media and the public from viewing the hearing. "I do not understand why the press has been barred from this meeting," Warren said. "What most of the people have said is we want innovation, but we have got to protect safety."

Senate Majority Leader Charles E. Schumer (D-N.Y.) will host the AI Insight Forum -- which is intended to serve as the bedrock for his "all hands on deck" plan to respond to recent AI advances -- in the grand Kennedy Caucus Room, the historic stage of Senate probes into the sinking of the Titanic, as well as Watergate. The more than 20 attendees include Tesla CEO and X owner Elon Musk, Meta CEO Mark Zuckerberg, Google CEO Sundar Pichai and ChatGPT-maker OpenAI CEO Sam Altman, among other top tech executives, civil rights leaders, labor chiefs and researchers.

Haywood Talcove, CEO of LexisNexis Risk Solutions Government Group, tells Fox News Digital that criminal groups, mostly in other countries, are advertising on social media to market their AI capabilities for fraud and other crimes. Google is set to require political advertising that uses artificial intelligence to generate images or sounds come with a visible disclosure for users. "AI-generated content should absolutely be disclosed in political advertisements. Not doing so leaves the American people open to misleading and predatory campaign ads," Ziven Havens, the Policy Director at the Bull Moose Project, told Fox News Digital. "In the absence of government action, we support the creation of new rulemaking to handle the new frontier of technology before it becomes a major problem" Havens' comments come after Google revealed last week that it will start requiring the disclosure of the use of AI to alter images in political ads starting in November, a little more than a year before the 2024 election, according to a PBS report.

Ball bearings find widespread use in various manufacturing and mechanical domains, and methods based on machine learning have been widely adopted in the field to monitor wear and spot defects before they lead to failures. Few studies, however, have addressed the problem of censored data, in which failure is not observed. In this paper, we propose a novel approach to predict the time to failure in ball bearings using survival analysis. First, we analyze bearing data in the frequency domain and annotate when a bearing fails by comparing the Kullback-Leibler divergence and the standard deviation between its break-in frequency bins and its break-out frequency bins. Second, we train several survival models to estimate the time to failure based on the annotated data and covariates extracted from the time domain, such as skewness, kurtosis and entropy. The models give a probabilistic prediction of risk over time and allow us to compare the survival function between groups of bearings. We demonstrate our approach on the XJTU and PRONOSTIA datasets. On XJTU, the best result is a 0.70 concordance-index and 0.21 integrated Brier score. On PRONOSTIA, the best is a 0.76 concordance-index and 0.19 integrated Brier score. Our work motivates further work on incorporating censored data in models for predictive maintenance.

In this work, we propose data augmentation via pairwise mixup across subgroups to improve group fairness. Many real-world applications of machine learning systems exhibit biases across certain groups due to under-representation or training data that reflects societal biases. Inspired by the successes of mixup for improving classification performance, we develop a pairwise mixup scheme to augment training data and encourage fair and accurate decision boundaries for all subgroups. Data augmentation for group fairness allows us to add new samples of underrepresented groups to balance subpopulations. Furthermore, our method allows us to use the generalization ability of mixup to improve both fairness and accuracy. We compare our proposed mixup to existing data augmentation and bias mitigation approaches on both synthetic simulations and real-world benchmark fair classification data, demonstrating that we are able to achieve fair outcomes with robust if not improved accuracy.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Arkansas Gov. Sarah Huckabee Sanders' proposal to restrict the public's access to records about her administration, travel and security stumbled at the outset of a special legislative session that convened Monday, with lawmakers trying to rework the legislation in the face of growing criticism that it erodes the state's open records law. The House and Senate ended the day without any action on the legislation, one of several items Sanders placed on the agenda for the special session she announced Friday. The Senate scuttled plans to hold a committee hearing Monday night on the bill, as lawmakers worked on revising the proposed changes to the state's Freedom of Information Act.

Microsoft and chipmaker Nvidia are the latest companies to take the hot seat in a series of Senate judiciary hearings on artificial intelligence as the federal government continues to grapple with how to regulate the technology. Microsoft's president, Brad Smith, and Nvidia's chief scientist, William Dally, are expected to testify on Tuesday alongside Woodrow Hartzog, a professor of law at Boston University School of Law. Both companies have been at the forefront of the AI boom, ramping up their investment in developing and utilizing aspects of the AI supply chain. Microsoft invested in a series of partnerships as well as its own in-house AI technology, Copilot. In addition to its $10bn investment in the ChatGPT owner, OpenAI, Microsoft partnered with Meta on the release and support of the social media platform's open-source large language model Llama 2. Nvidia, for its part, has benefited from its early investment and focus on building computer chips for AI systems, raking in more than $13bn in revenue in the second quarter.

On Tuesday, September 12, at 12 p.m. US Eastern time, we will be hosting a subscriber-only roundtable conversation about how to regulate artificial intelligence. I'll help you decipher what is going on in AI regulation and what to pay attention to this fall. On Thursday, September 14, at 12 p.m. US Eastern time, I am interviewing Gareth Edwards, the director behind Rogue One: A Star Wars Story, about his new film, The Creator. The film is about the current state of AI and the pitfalls and possibilities ahead as this technology marches toward sentience. Lawmakers are back from summer vacation and ready for action.