More than two years after it initially began trials, Google's AI-powered reservation service Duplex is now available in 49 US states. This looks like it'll be the limit of Duplex's coverage in the US for the time being, as Google tells The Verge it has no timeline to launch the service in the last hold-out state -- Louisiana -- due to unspecified local laws. Adapting to local legislation is one of the reasons Duplex has taken so long to roll out across the US. Google tells The Verge it's had to add certain features to the service (like offering a call-back number for businesses contacted by Duplex) to make it legal in some states. In others, it's simply waited for legislation to change.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Young Americans for Liberty, the nation's leading youth libertarian organization, announced a free speech lawsuit against the University of Alabama in Huntsville Thursday aiming to strike down a policy that requires students to obtain speaking permits three days in advance of campus events. The Alliance Defending Freedom, which is representing the school's YAL chapter in the suit, is alleging that the policy violates Alabama's Campus Free Speech Act. "Alabama law is clear: Students don't need a permit from college officials to speak on campus, but that's exactly what the University of Alabama in Huntsville is doing -- violating the law and shutting down speech on campus," ADF counsel Michael Ross, who specializes in academic freedom, said in a statement.

Development of the intelligent autonomous robot technology presupposes its anticipated beneficial effect on the individuals and societies. In the case of such disruptive emergent technology, not only questions of how to build, but also why to build and with what consequences are important. The field of ethics of intelligent autonomous robotic cars is a good example of research with actionable practical value, where a variety of stakeholders, including the legal system and other societal and governmental actors, as well as companies and businesses, collaborate bringing about shared view of ethics and societal aspects of technology. It could be used as a starting platform for the approaches to the development of intelligent autonomous robots in general, considering human-machine interfaces in different phases of the life cycle of technology - the development, implementation, testing, use and disposal. Drawing from our work on ethics of autonomous intelligent robocars, and the existing literature on ethics of robotics, our contribution consists of a set of values and ethical principles with identified challenges and proposed approaches for meeting them. This may help stakeholders in the field of intelligent autonomous robotics to connect ethical principles with their applications. Our recommendations of ethical requirements for autonomous cars can be used for other types of intelligent autonomous robots, with the caveat for social robots that require more research regarding interactions with the users. We emphasize that existing ethical frameworks need to be applied in a context-sensitive way, by assessments in interdisciplinary, multi-competent teams through multi-criteria analysis. Furthermore, we argue for the need of a continuous development of ethical principles, guidelines, and regulations, informed by the progress of technologies and involving relevant stakeholders.

Such lawsuits have risen steadily, to about 3,500 in 2020 from roughly 2,900 in 2019 and about 2,300 in 2018, UsableNet said. The company predicts more than 4,000 such lawsuits for all of 2021 if trends hold. E-commerce companies are sued most often, accounting for 74% of federal cases between Jan. 1 and June 21, the report said. Rounding out the top five categories were digital media and agencies, finance, food service and healthcare, each accounting for less than 5% of the total. Get weekly insights into the ways companies optimize data, technology and design to drive success with their customers and employees. Companies with revenue below $50 million were the targets of two-thirds of lawsuits between Jan. 1 and June 21, a shift from the year-earlier period, when the share was less than half, UsableNet said.

VANCOUVER, Wash.--(BUSINESS WIRE)--ZoomInfo (NASDAQ: ZI), a global leader in modern go-to-market software, data, and intelligence, today announced it has agreed to acquire Chorus.ai, More than 20,000 global revenue teams trust ZoomInfo to power their go-to-market motions and drive efficient results. The planned acquisition of Chorus will add a new category of actionable insights to ZoomInfo's world-class intelligence layer, unlocking workflows and driving engagement informed by conversations. The acquisition expands ZoomInfo's total addressable market to $70 billion, and is expected to be accretive to growth immediately, generate positive adjusted operating income within 12 months, and be accretive to cash flow in the second half of FY 2022. Chorus uses machine learning and artificial intelligence to capture and analyze prospect and customer calls, meetings, and emails.

"All men by nature desire to know." - Aristotle "He who does not know what the world is does not know where he is." - Marcus Aurelius "If I have seen further, it is by standing on the shoulders of giants." "The universe is a giant causal machine. The world is "at the bottom" governed by causal algorithms. Our bodies are causal machines. Our brains and minds are causal AI computers". The 3 biggest unknown unknowns are described and analyzed in terms of human intelligence and machine intelligence. A deep understanding of reality and its causality is to revolutionize the world, its science and technology, AI machines including. The content is the intro of Real AI Project Confidential Report: How to Engineer Man-Machine Superintelligence 2025: AI for Everything and Everyone (AI4EE). It is all a power set of {known, unknown; known unknown}, known knowns, known unknowns, unknown knowns, and unknown unknowns, like as the material universe's material parts: about 4.6% of baryonic matter, about 26.8% of dark matter, and about 68.3% of dark energy. There are a big number of sciences, all sorts and kinds, hard sciences and soft sciences. But what we are still missing is the science of all sciences, the Science of the World as a Whole, thus making it the biggest unknown unknowns. It is what man/AI does not know what it does not know, neither understand, nor aware of its scope and scale, sense and extent. "the universe consists of objects having various qualities and standing in various relationships" (Whitehead, Russell), "the world is the totality of states of affairs" (D. "World of physical objects and events, including, in particular, biological beings; World of mental objects and events; World of objective contents of thought" (K. How the world is still an unknown unknown one could see from the most popular lexical ontology, WordNet,see supplement. The construct of the world is typically missing its essential meaning, "the world as a whole", the world of reality, the ultimate totality of all worlds, universes, and realities, beings, things, and entities, the unified totalities. The world or reality or being or existence is "all that is, has been and will be". Of which the physical universe and cosmos is a key part, as "the totality of space and times and matter and energy, with all causative fundamental interactions".

In the years after it was founded in 1999, the Swedish video game company Paradox Interactive quietly built a reputation for developing some of the best, and most hardcore, strategy games on the market. "Deep, endless, complex, unyielding games," is how Shams Jorjani, the company's chief business development officer, describes Paradox's offerings. Most of its biggest hits, such as the middle ages-themed Crusader Kings, or Sengoku, in which you play as a 16th-century Japanese noble, were loosely based on history. But in 2016, Paradox decided to try something a little different. Its new game, Stellaris, was a work of sprawling science fiction, set 200 years in the future. In this virtual universe, players could explore richly detailed galaxies, command their own fusion-powered starship fleets and fight with extraterrestrials to expand their space empires. Gamers could choose to play as the human race, or one of many alien species. Another type of alien is a sentient crystal that eats rocks.) The game was an instant hit, selling more than 200,000 copies in its first 24 hours. Later that year, Paradox decided to take Stellaris to China. This would mean navigating the country's notoriously tricky censorship rules, but given that China was, at the time, home to an estimated 560 million gamers, the commercial appeal was irresistible. Paradox had been burned in China before.

The World Health Organization (WHO) recently released a report presenting guidance around the ethical use of artificial intelligence (AI) in the health sector. The lack of a general consensus for ethical use of AI has sparked debate among those in the industry, with some raising concerns about the implications of this technology. This has led to organizations seeking to offer their own solutions, such as the National Institute of Standards and Technology's recent proposal to reduce bias in the use of AI. The WHO's report, titled Ethics and Governance of Artificial Intelligence for Health, seeks to address similar concerns -- as well as potential benefits -- of AI's potential roles in the health sector. It offers six primary principles for the use of AI: promote human well being, human safety and the public interest ensure transparency, explainability and intelligibility foster responsibility and accountability ensure inclusiveness and equity promote AI that is responsive and sustainable The organization's hope, the report states, is that these principles will be used as a foundation for AI stakeholders, including governments, developers and society.

The pervasiveness of abusive content on the internet can lead to severe psychological and physical harm. Significant effort in Natural Language Processing (NLP) research has been devoted to addressing this problem through abusive content detection and related sub-areas, such as the detection of hate speech, toxicity, cyberbullying, etc. Although current technologies achieve high classification performance in research studies, it has been observed that the real-life application of this technology can cause unintended harms, such as the silencing of under-represented groups. We review a large body of NLP research on automatic abuse detection with a new focus on ethical challenges, organized around eight established ethical principles: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values. In many cases, these principles relate not only to situational ethical codes, which may be context-dependent, but are in fact connected to universal human rights, such as the right to privacy, freedom from discrimination, and freedom of expression. We highlight the need to examine the broad social impacts of this technology, and to bring ethical and human rights considerations to every stage of the application life-cycle, from task formulation and dataset design, to model training and evaluation, to application deployment. Guided by these principles, we identify several opportunities for rights-respecting, socio-technical solutions to detect and confront online abuse, including ‘nudging’, ‘quarantining’, value sensitive design, counter-narratives, style transfer, and AI-driven public education applications.evaluation, to application deployment. Guided by these principles, we identify several opportunities for rights-respecting, socio-technical solutions to detect and confront online abuse, including 'nudging', 'quarantining', value sensitive design, counter-narratives, style transfer, and AI-driven public education applications.

Learning multimodal representations involves integrating information from multiple heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world applications in multimedia, affective computing, robotics, finance, human-computer interaction, and healthcare. Unfortunately, multimodal research has seen limited resources to study (1) generalization across domains and modalities, (2) complexity during training and inference, and (3) robustness to noisy and missing modalities. In order to accelerate progress towards understudied modalities and tasks while ensuring real-world robustness, we release MultiBench, a systematic and unified large-scale benchmark spanning 15 datasets, 10 modalities, 20 prediction tasks, and 6 research areas. MultiBench provides an automated end-to-end machine learning pipeline that simplifies and standardizes data loading, experimental setup, and model evaluation. To enable holistic evaluation, MultiBench offers a comprehensive methodology to assess (1) generalization, (2) time and space complexity, and (3) modality robustness. MultiBench introduces impactful challenges for future research, including scalability to large-scale multimodal datasets and robustness to realistic imperfections. To accompany this benchmark, we also provide a standardized implementation of 20 core approaches in multimodal learning. Simply applying methods proposed in different research areas can improve the state-of-the-art performance on 9/15 datasets. Therefore, MultiBench presents a milestone in unifying disjoint efforts in multimodal research and paves the way towards a better understanding of the capabilities and limitations of multimodal models, all the while ensuring ease of use, accessibility, and reproducibility. MultiBench, our standardized code, and leaderboards are publicly available, will be regularly updated, and welcomes inputs from the community.