Thursday, October 27, 2022

I don’t remember if I was caught in this one or not. I’ll have to look back in my blog. I wonder how they can stall so long? (I hear the answer: “Good lawyers!”)

https://www.govexec.com/pay-benefits/2022/10/judge-finalized-63m-opm-hack-settlement-feds-two-months-damages/378950/

A Judge Has Finalized the $63M OPM Hack Settlement. Feds Now Have Two Months to Sign Up for Damages.

A federal judge on Wednesday formally finalized a $63 million settlement that will soon allow thousands of current and former federal employees to receive payouts as part of the agreement stemming from a 2015 breach of data maintained by the Office of Personnel Management.

OPM disclosed two data breaches in 2015: one that exposed the personnel files of all current and former federal employees and another that released the personally identifiable information of all applicants for security clearances, as well as their families. Those individuals are set to receive a minimum of $700 and up to $10,000 from the agreement if they can prove they were victims of the hack and incurred out-of-pocket expenses or lost compensable time. More than 22.1 million people were impacted by the breaches.

They now have until Dec. 23 to file a claim for damages.





How else could “explainable AI” work? (...and then a miracle happens!)

https://www.newscientist.com/article/2344251-ais-become-smarter-if-you-tell-them-to-think-step-by-step/

AIs become smarter if you tell them to think step by step

Artificial intelligence models can outperform humans at tasks AIs normally struggle with if they are told to think a certain way, but it doesn’t help them grasp sarcasm





Bias creeps into AI by training it on biased data, so it is great to have the government say, “Here is a completely bias free data set, trust us!”

https://federalnewsnetwork.com/artificial-intelligence/2022/10/coming-to-an-algorithm-near-you-a-big-federally-focused-training-data-set/

Coming to an algorithm near you: A big, federally-focused training data set

Contractors trying to develop artificial intelligence applications for the government face a challenge, namely a good data set for training the algorithms. Now a big new federally-oriented data set is coming from an unlikely source.





Curious that an app that requires you to have physical access to a device is so widespread. Claiming they are ‘baby monitor’ apps may explain a bit, but babies rarely text… (Listen or read)

https://techcrunch.com/2022/10/26/inside-thetruthspy-stalkerware/

Inside TheTruthSpy, the stalkerware network spying on thousands

A massive cache of leaked data reveals the inner workings of a stalkerware operation that is spying on hundreds of thousands of people around the world, including Americans.

The leaked data includes call logs, text messages, granular location data and other personal device data of unsuspecting victims whose Android phones and tablets were compromised by a fleet of near-identical stalkerware apps, including TheTruthSpy, Copy9, MxSpy and others.

These Android apps are planted by someone with physical access to a person’s device and are designed to stay hidden on their home screens but will continuously and silently upload the phone’s contents without the owner’s knowledge.





It’s a start.

https://www.bespacific.com/protecting-childrens-data-privacy-policy-paper-i-international-issues-and-compliance-challenges/

Protecting Children’s Data Privacy Policy Paper I: International Issues and Compliance Challenges

Complying with the growing number of laws on children’s privacy in the global marketplace is an increasingly complex undertaking. It involves reconciling measures to protect children from online harm and intrusions into their privacy with the equally important necessity for children to participate and engage online and to access beneficial or even essential online resources. Earlier this year, CIPL launched a project to explore the difficult policy issues as well as regulatory and compliance challenges that these competing mandates and interests present. As a first milestone in this project, CIPL has produced a white paper entitled “Protecting Children’s Data Privacy, Policy Paper I, International Issues and Compliance Challenges. ” This paper

  • identifies key issues and compliance challenges in the context of globally divergent legal standards and policy approaches relating to children’s data and online engagement

  • creates a foundation for further discussions among stakeholders and experts about how these issues  and challenges can be addressed in a way that enables effective compliance with privacy requirements and serves the best interest of the child

  • sets the stage for CIPL’s forthcoming second paper on the topic: Protecting Children’s Data Privacy, Policy Paper II: Practical Solutions to Protect Children and Enhance Compliance (working title), which will examine existing and potential solutions for these challenges.

Policy Paper I includes discussions of the following issues: best interest of the child; consent and legitimate interest; parental consent; age assurance; profiling for targeting to children; transparency; and the risk-based approach to children’s online protection. Four appendixes to the paper contain brief summaries of key laws, regulations, codes of conduct and regulatory guidance relating to children’s online privacy.”





Perspective. I’d like to see more like this…

https://technical.ly/software-development/machine-learning-work-ethics-use-value-spotify/

How does machine learning affect our work? Technologists talk ethics and use value

… “We’re all being trained by the ML that are helping us out,” he said. “We are being trained how to use these systems rather than having the systems learn how we work.”

… a Chicago-based technologist, said that he used to work for a payroll company that used machine learning to help clients predict which of their employees may leave based on pay. He and his colleagues had to work with the employers’ ethics team to determine which variables, especially demographic ones like race or gender, could be used.

“We were intentionally not allowed by our internal ethics committee to use these kinds of variables,” he noted.





Resource?

https://netl.doe.gov/key-lab-initiatives/sami

Science-based AI/ML Institute (SAMI)



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