As millions of people are playing with AI-powered image-generation tools like DALL-E and Midjourney, new works of art are generated by the billions. Many of them are curiosities, some of them are legitimately incredible works of art that I wouldn't hesitate to stick on my wall. In fact, I did; I have a Meural digital art display, and it's currently playing a rotation of some of the most interesting works of art Midjourney has generated for me. The picture above made me think, though; the prompt for it is "Lovers, in the style of Banksy," which is remarkably close, stylistically, as a lot of other Banksy works -- it even put the frame on it for me, unprompted. With a small amount of manual retouching (or with a lot more experimentation), I am confident I could get Midjourney to generate a work that anybody would recognize as "a Banksy." It's paintbrushes at dawn as artists feel the pressure of AI-generated art The challenge becomes complex, and I'm going to be keeping a very close eye on the legal universe to see how this is going to evolve over time.

The nonpartisan think tank Brookings this week published a piece decrying the bloc's regulation of open source AI, arguing it would create legal liability for general-purpose AI systems while simultaneously undermining their development. Under the EU's draft AI Act, open source developers would have to adhere to guidelines for risk management, data governance, technical documentation and transparency, as well as standards of accuracy and cybersecurity. If a company were to deploy an open source AI system that led to some disastrous outcome, the author asserts, it's not inconceivable the company could attempt to deflect responsibility by suing the open source developers on which they built their product. "This could further concentrate power over the future of AI in large technology companies and prevent research that is critical to the public's understanding of AI," Alex Engler, the analyst at Brookings who published the piece, wrote. "In the end, the [E.U.'s] attempt to regulate open-source could create a convoluted set of requirements that endangers open-source AI contributors, likely without improving use of general-purpose AI."

The Port of Montevideo is located in the capital city of Montevideo, on the banks of the "Río de la Plata" river. Due to its strategic location between the Atlantic Ocean and the "Uruguay" river, it is considered one of the main routes of cargo mobilization for Uruguay and MERCOSUR . Over the past decades, it has established itself as a multipurpose port handling: containers, bulk, fishing boats, cruises, passenger transport, cars, and general cargo. MERCOSUR or officially the Southern Common Market is a commercial and political bloc established in 1991 by several South American countries. Moreover, only two companies concentrate all-cargo operations in this port: the company of Belgian origin Katoen Natie and the Chilean and Canadian capital company Montecon.

A recently published Panel for the Future of Science and Technology (STOA) study examines the impact of biases on datasets used to support decision-making systems based on artificial intelligence. It explores the ethical implications of the deployment of digital technologies in the context of proposed European Union legislation, such as the AI act, the data act and the data governance act; as well as the recently approved Digital Services Act and Digital Markets Act. It ends by setting out a range of policy options to mitigate the pernicious effects of biases in decision-making systems that rely on machine learning. Machine learning (ML) is a form of artificial intelligence (AI) in which computers develop their own decision-making processes for situations that cannot be directly and satisfactorily addressed by available algorithms. The process is adjusted through the exploration of existing data on previous similar situations that include the solutions found at the time. The broader and more balanced the dataset is, the better the chances will be of obtaining a valid result; but there is no a priori way of knowing whether the data available will suffice to collect all aspects of the problem at hand.

The UK's highest court is set to decide whether artificial intelligence (AI) robots should be allowed to patent their own inventions. Britain's Supreme Court has agreed to hear a computer scientist's bid to list his AI machine as the sole inventor of two separate products, in an application to the UK's patent office. The Supreme Court will hear Dr Stephen Thaler's bid to overturn an earlier ruling from a lower court, banning him from filing a patent application on behalf of his DABUS robot. The case comes after the UK's intellectual property office refused two patent applications, filed by Thaler on behalf of his DABUS system, over his failure to identify a "person" as the inventor of the products. Thaler had sought to file one patent for a "Food Container" and another for a flashing light, under the title "Devices and Methods for Attracting Enhanced Attention," in 2018.

DAPA, the Digital Asset Policy Alliance, is launching as a collaborative initiative focused on the public policy implications of web3 with initial participants from Fabric Ventures, the web3 venture contributor, Coadec, The Coalition for a Digital Economy, Project Vellir, NEAR Protocol and Unstoppable Finance. DAPA welcomes other volunteers and will progressively decentralise with'community-driven' at its heart with the upcoming DAPA DAO. DAPA's mission is to improve understanding of web3 and crypto technology and ensure that new industry regulation protects consumers and businesses, while also promoting innovation and adoption of the transformative benefits of this new technology. Decentralisation technology has the potential to transform our society for the better. There has been rapid growth in blockchain technology and consumer demand for web3 applications, which has attracted the attention of policy makers and regulators, including in the UK, EU and US.

With the increasing attention non-binary people receive in Western societies, strategies of gender-fair language have started to move away from binary (only female/male) concepts of gender. Nevertheless, hardly any approaches to take these identities into account into machine translation models exist so far. A lack of understanding of the socio-technical implications of such technologies risks further reproducing linguistic mechanisms of oppression and mislabelling. In this paper, we describe the methods and results of a workshop on gender-fair language and language technologies, which was led and organised by ten researchers from TU Wien, St. P\"olten UAS, FH Campus Wien and the University of Vienna and took place in Vienna in autumn 2021. A wide range of interest groups and their representatives were invited to ensure that the topic could be dealt with holistically. Accordingly, we aimed to include translators, machine translation experts and non-binary individuals (as "community experts") on an equal footing. Our analysis shows that gender in machine translation requires a high degree of context sensitivity, that developers of such technologies need to position themselves cautiously in a process still under social negotiation, and that flexible approaches seem most adequate at present. We then illustrate steps that follow from our results for the field of gender-fair language technologies so that technological developments can adequately line up with social advancements. ---- Mit zunehmender gesamtgesellschaftlicher Wahrnehmung nicht-bin\"arer Personen haben sich in den letzten Jahren auch Konzepte von genderfairer Sprache von der bisher verwendeten Binarit\"at (weiblich/m\"annlich) entfernt. Trotzdem gibt es bislang nur wenige Ans\"atze dazu, diese Identit\"aten in maschineller \"Ubersetzung abzubilden. Ein fehlendes Verst\"andnis unterschiedlicher sozio-technischer Implikationen derartiger Technologien birgt in sich die Gefahr, fehlerhafte Ansprachen und Bezeichnungen sowie sprachliche Unterdr\"uckungsmechanismen zu reproduzieren. In diesem Beitrag beschreiben wir die Methoden und Ergebnisse eines Workshops zu genderfairer Sprache in technologischen Zusammenh\"angen, der im Herbst 2021 in Wien stattgefunden hat. Zehn Forscher*innen der TU Wien, FH St. P\"olten, FH Campus Wien und Universit\"at Wien organisierten und leiteten den Workshop. Dabei wurden unterschiedlichste Interessensgruppen und deren Vertreter*innen breit gestreut eingeladen, um sicherzustellen, dass das Thema holistisch behandelt werden kann. Dementsprechend setzten wir uns zum Ziel, Machine-Translation-Entwickler*innen, \"Ubersetzer*innen, und nicht-bin\"are Privatpersonen (als "Lebenswelt-Expert*innen") gleichberechtigt einzubinden. Unsere Analyse zeigt, dass Geschlecht in maschineller \"Ubersetzung eine ma\ss{}geblich kontextsensible Herangehensweise erfordert, die Entwicklung von Sprachtechnologien sich vorsichtig in einem sich noch in Aushandlung befindlichen gesellschaftlichen Prozess positionieren muss, und flexible Ans\"atze derzeit am ad\"aquatesten erscheinen. Wir zeigen auf, welche n\"achsten Schritte im Bereich genderfairer Technologien notwendig sind, damit technische mit sozialen Entwicklungen mithalten k\"onnen.

This paper considers the multi-party classification problem that arises in document review for discovery in legal proceedings. The plaintiff (henceforth: Bob) issues a request for production to the defendant (henceforth: Alice). The legal team of Alice is then accountable for reviewing all documents and provides the responsive ones. Grossman and Cormack (2010) show this manual process can be significantly improved by automation. A potential issue with the adoption of this technology, however, is that automation could reduce transparency and accountability, and the accuracy and completeness of this process relies critically on the accountability of Alice's legal team and its obligations under the rules of professional responsibility.

Cyber Threat Intelligence (CTI) sharing is an important activity to reduce information asymmetries between attackers and defenders. However, this activity presents challenges due to the tension between data sharing and confidentiality, that result in information retention often leading to a free-rider problem. Therefore, the information that is shared represents only the tip of the iceberg. Current literature assumes access to centralized databases containing all the information, but this is not always feasible, due to the aforementioned tension. This results in unbalanced or incomplete datasets, requiring the use of techniques to expand them; we show how these techniques lead to biased results and misleading performance expectations. We propose a novel framework for extracting CTI from distributed data on incidents, vulnerabilities and indicators of compromise, and demonstrate its use in several practical scenarios, in conjunction with the Malware Information Sharing Platforms (MISP). Policy implications for CTI sharing are presented and discussed. The proposed system relies on an efficient combination of privacy enhancing technologies and federated processing. This lets organizations stay in control of their CTI and minimize the risks of exposure or leakage, while enabling the benefits of sharing, more accurate and representative results, and more effective predictive and preventive defenses.

Piper Companies is seeking a Data Scientist, in a hybrid environment to join a cutting-edge Technology and AI oriented company located in Boston, MA. The Data Scientist will support machine learning research and development to further develop the production inference pipeline. Keywords: data scientist, data science, machine learning, ml, ml frameworks, machine learning frameworks, data querying, data, sensor data, data collection, ai, data mining, data analysis, imu, python, tensorflow, pytorch, cloud computing, emg, eeg, ecg, cv, algorithms, hybrid work, hybrid, boston ma, boston Massachusetts, boston. We are driven by the belief that Artificial Intelligence is mankind's greatest invention. It is the key to building a safer, more vibrant, transparent, and empowered society. We are determined to be an active contributor to shaping our future for the better.