Yes, be concerned about what they took. Be more concerned about what they left behind.
Chinese Military Hackers Launch Tripple Cyberattack on Major Telecom Carriers
Emissary Panda (APT27), Naikon, and Soft Cell are the organizations that carried out various hacking activities on the same telecom carriers in Southeast Asia at the same time, according to Cybereason.
… Once compromised, the hackers gained access to the sensitive information contained in key network resources such as Domain Controllers (DC), high-level corporate resources such as billing servers that contain call detail record data (CDR), as well as key network components such as telecom carriers' billing servers.
A very good overview!
https://fpf.org/blog/now-on-the-internet-everyone-knows-youre-a-dog/
NOW, ON THE INTERNET, EVERYONE KNOWS YOU’RE A DOG
An Introduction to Digital Identity
(Related) On a slippery slope toward “Papers, citizen!”
Microsoft will require proof of COVID-19 vaccination to enter buildings in the US
Microsoft has informed employees that it will require proof of vaccination for anyone entering a Microsoft building in the US starting in September.
Perhaps Amazon’s next technological breakthrough will be a cure for constipation, available in suppository form. An interesting way to ‘opt in.’
Does Amazon’s Sleep Tracking Technology Invade Bedroom Privacy? Concerns Raised About Data Sharing, Opacity of Intentions for Collected Information
Amazon’s new sleep tracking technology proposes to cast an “electromagnetic bubble” over customers, monitoring their movements throughout the night in an attempt to improve quality of rest. Critics have already raised multiple concerns, from exactly what Amazon intends to do with the data it collects about sleep habits to the amount of radiation it would need to emit to function.
The apparent market demand for Amazon’s new sleep tracking tech stems from reports of common sleep disturbance during the Covid-19 pandemic; studies find that as many as half of all respondents are saying that they have been having trouble getting a full night of rest since early last year.
Explaining AI.
https://fpf.org/blog/the-spectrum-of-ai-companion-to-the-fpf-ai-infographic/
THE SPECTRUM OF AI: COMPANION TO THE FPF AI INFOGRAPHIC
In December of 2020, FPF published the Spectrum of Artificial Intelligence – An Infographic Tool. designed to visually display the variety and complexity of Artificial Intelligence (AI) systems, the fields this science is based on, and a small sample of the use cases these technologies support for consumers. Today, we are releasing the white paper: The Spectrum of Artificial Intelligence – Companion to the FPF AI Infographic to expand on the information included in this educational resource, and describe in more detail how the graphic can be used as an aide in education or in developing legislation or other regulatory guidance around AI-based systems. We identify additional, specific use cases for various AI technologies and explain how the differing algorithmic architecture and data demands present varying risks and benefits. We discuss the spectrum of algorithmic technology and demonstrate how design factors, data use, and model training processes should be considered for specific regulatory approaches.
Until we make lawyers obsolete, I suppose we have to train them.
https://www.bespacific.com/explainable-artificial-intelligence-lawyers-perspective/
Explainable artificial intelligence, lawyer’s perspective
Explainable artificial intelligence, lawyer’s perspective. Authors: Łukasz Górski, Shashishekar Ramakrishna ICAIL ’21: Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law June 2021 Pages 60–68 https://doi.org/10.1145/3462757.3466145 Published:21 June 2021
“Explainable artificial intelligence (XAI) is a research direction that was already put under scrutiny, in particular in the AI&Law community. Whilst there were notable developments in the area of (general, not necessarily legal) XAI, user experience studies regarding such methods, as well as more general studies pertaining to the concept of explainability among the users are still lagging behind. This paper firstly, assesses the performance of different explainability methods (Grad-CAM, LIME, SHAP), in explaining the predictions for a legal text classification problem; those explanations were then judged by legal professionals according to their accuracy. Secondly, the same respondents were asked to give their opinion on the desired qualities of (explainable) artificial intelligence (AI) legal decision system and to present their general understanding of the term XAI. This part was treated as a pilot study for a more pronounced one regarding the lawyer’s position on AI, and XAI in particular.”
(Related)
A dataset for evaluating legal question answering on private international law
A dataset for evaluating legal question answering on private international law. Francesco Sovrano, Monica Palmirani, Biagio Distefano,Salvatore Sapienza, Fabio Vitali. ICAIL ’21: Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law June 2021 Pages 230–234 https://doi.org/10.1145/3462757.3466094 Published: 21 June 2021.
“International Private Law (PIL) is a complex legal domain that presents frequent conflicting norms between the hierarchy of legal sources, legal domains, and the adopted procedures. Scientific research on PIL reveals the need to create a bridge between European and national laws. In this context, legal experts have to access heterogeneous sources, being able to recall all the norms and to combine them using case-laws and following the principles of interpretation theory. This clearly poses a daunting challenge to humans, whenever Regulations change frequently or are big-enough in size. Automated reasoning over legal texts is not a trivial task, because legal language is very specific and in many ways different from a commonly used natural language. When applying state-of-the-art language models to legalese understanding, one of the challenges is always to figure how to optimally use the available amount of data. This makes hard to apply state-of-the-art sub-symbolic question answering algorithms on legislative texts, especially the PIL ones, because of data scarcity. In this paper we try to expand previous works on legal question answering, publishing a larger and more curated dataset for the evaluation of automated question answering on PIL.”
Something to consider when it comes to Colorado.
https://www.zdnet.com/article/intel-dell-bring-ai-for-workforce-program-to-18-community-colleges/
Intel, Dell bring "AI for Workforce" program to 18 community colleges
Intel on Tuesday announced that it's partnering with Dell Technologies to expand its AI for Workforce Program, which helps community colleges develop AI certificates, augment existing courses or launch full AI associate degree programs. With Dell providing technical and infrastructure expertise, the program will expand to 18 schools across 11 states.
… So far, more than 80 community college professors have received professional development from Intel and have been certified as Intel AI trainers. Dell is helping the schools configure AI labs for teaching in-person, hybrid and online students.
… Intel has plans to expand to 50 more community and vocational colleges in 2022.
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