The European Union is likely to introduce among the first, most stringent, and most comprehensive AI regulatory regimes of the world's major jurisdictions. In this report, we ask whether the EU's upcoming regulation for AI will diffuse globally, producing a so-called "Brussels Effect". Building on and extending Anu Bradford's work, we outline the mechanisms by which such regulatory diffusion may occur. We consider both the possibility that the EU's AI regulation will incentivise changes in products offered in non-EU countries (a de facto Brussels Effect) and the possibility it will influence regulation adopted by other jurisdictions (a de jure Brussels Effect). Focusing on the proposed EU AI Act, we tentatively conclude that both de facto and de jure Brussels effects are likely for parts of the EU regulatory regime. A de facto effect is particularly likely to arise in large US tech companies with AI systems that the AI Act terms "high-risk". We argue that the upcoming regulation might be particularly important in offering the first and most influential operationalisation of what it means to develop and deploy trustworthy or human-centred AI. If the EU regime is likely to see significant diffusion, ensuring it is well-designed becomes a matter of global importance.

A bill is headed to the governor's desk that would create a path for suing people who send unsolicited sexual pictures, but the legislation stops short of making "cyberflashing" a crime in California. If signed by Gov. Gavin Newsom, SB 53 by Sen. Connie Leyva (D-Chino) will allow Californians to take someone to civil court over unwanted lewd photos sent to them electronically; plaintiffs who win a suit could get up to $30,000 in damages. The legislation, approved Monday on the Senate floor in a 37-0 vote, comes after reports of men using the AirDrop iPhone feature to send lewd pictures to nearby strangers or on online dating apps without consent from the recipients. The bill applies to senders over 18 and defines obscene images as anything that depicts a person engaging in sexual acts, including masturbation, or photos of genitals "in a patently offensive way, and that, taken as a whole, lacks serious literary, artistic, political, or scientific value." The bill is sponsored by the women-centered dating app Bumble.

Can an artificial intelligence (AI) system be an inventor? Stephen Thaler recently submitted two patent applications for which an artificial intelligence system named "DABUS" was listed as the sole inventor. Specifically, the first application was directed to a food or beverage container that facilitates stacking.1 The second application was directed to a light device including a neural flame that serves as a signal beacon for human detection.2 The USPTO denied the patent applications for failing to list any human as an inventor.

The rapid pace of AI adoption in business could be heading for some major speed bumps. According to Gartner experts presenting at the Gartner CFO & Finance Executive Conference in June 2022, half of all AI deployments are expected to be postponed between now and 2024, as companies face barriers to upscaling AI in-house. AI governance and how enterprises are going to monitor and control the use of data in their AI platforms are emerging as significant snags. AI governance is a relatively new concept, as AI itself is still only in the early stages of development, but there are already complications emerging. For some companies, the governance of AI applications is included in data or model governance structures.

As per Section 6 of The Patents Act, an application for a patent can be made by any person claiming to be the true and first inventor of the invention. Further Section 2(1)(s) shows how a natural person is set out from others such as the Government under the meaning of'person'. Thus, only a natural person who is true and first to invent, who contributes his originality, technical knowledge or skill to the invention would qualify to be recognized as an inventor in India. However, this was put to test in the case of the Device for Autonomous Bootstrapping of Unified Sentience ("DABUS"), an Artificial Intelligence ("AI") system created by Dr Stephen Thaler. DABUS is trained to substitute aspects of human brain function.

All that automation yields data that can be used to analyze workers' performance. Those analyses, whether done by humans or software programs, may affect who is hired, fired, promoted, and given raises. Some artificial intelligence programs can mine and manipulate the data to predict future actions, such as who is likely to quit their job, or to diagnose medical conditions. If your job doesn't currently involve these types of technologies, it likely will in the very near future. This worries me me--a labor and employment law scholar who researches the role of technology in the workplace--because unless significant changes are made to American workplace laws, these sorts of surveillance and privacy invasions will be perfectly legal.

Every weekday, The Detail makes sense of the big news stories. This week, we talked about the burgeoning concerns over artificial intelligence, talked to two former political party presidents about their hidden role, visited a food bank operating in the wealthy North Shore, looked at the fight to keep foot-and-mouth disease out of our farms, and finished the week with a new Supreme Court case trying to hold big corporations liable for contributing to climate change. Whakarongo mai to any episodes you might have missed. Artificial intelligence systems running rogue might seem like the stuff of science-fiction, but these systems are increasingly common in many high-tech elements of society, from self-driving cars to digital assistants, facial identification, Netflix recommendations, and much, much more. The capabilities of artificial intelligence are growing at pace; a pace that's outstripping regulatory frameworks.

As I write this, Amazon is announcing its purchase of iRobot, adding its room-mapping robotic vacuum technology to the company's existing home surveillance suite, the Ring doorbell and prototype aerial drone. This is in addition to Amazon already knowing what you order online, what websites you visit, what foods you eat and, soon, every last scrap of personal medical data you possess. The trend of our gadgets and infrastructure constantly, often invasively, monitoring their users shows little sign of slowing -- not when there's so much money to be made. Of course it hasn't been all bad for humanity, what with AI's help in advancing medical, communications and logistics tech in recent years. In his new book, Machines Behaving Badly: The Morality of AI, Scientia Professor of Artificial Intelligence at the University of New South Wales, Dr. Toby Walsh, explores the duality of potential that artificial intelligence/machine learning systems offer and, in the excerpt below, how to claw back a bit of your privacy from an industry built for omniscience. Published by La Trobe University Press. The Second Law of Thermodynamics states that the total entropy of a system – the amount of disorder – only ever increases.

Atmospheric pollution remains one of the major public health threat worldwide with an estimated 7 millions deaths annually. In Africa, rapid urbanization and poor transport infrastructure are worsening the problem. In this paper, we have analysed spatio-temporal variations of PM2.5 across different geographical regions in Africa. The West African region remains the most affected by the high levels of pollution with a daily average of 40.856 $\mu g/m^3$ in some cities like Lagos, Abuja and Bamako. In East Africa, Uganda is reporting the highest pollution level with a daily average concentration of 56.14 $\mu g/m^3$ and 38.65 $\mu g/m^3$ for Kigali. In countries located in the central region of Africa, the highest daily average concentration of PM2.5 of 90.075 $\mu g/m^3$ was recorded in N'Djamena. We compare three data driven models in predicting future trends of pollution levels. Neural network is outperforming Gaussian processes and ARIMA models.

The value alignment problem is concerned with the design of systems that provably abide by our human values. One approach to this challenge is through the leverage of prescriptive norms that, if carefully designed, are able to steer a multiagent system away from harmful outcomes and towards more beneficial ones. In this work, we first present a general methodology for the automated synthesis of value aligned normative systems, based on a consequentialist view of values. In the second part, we provide analytical tools to examine such value aligned normative systems, namely the Shapley value of individual norms and the compatibility of several values under a fixed set of norms. We illustrate all of our contributions with a running example of a society of agents where taxes are collected and redistributed according to a set of parametrised norms.