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Can you trust a hacker to do what you pay for?

https://www.zdnet.com/article/cloud-provider-stopped-ransomware-attack-but-had-to-pay-ransom-demand-anyway/

Cloud provider stopped ransomware attack but had to pay ransom demand anyway

BlackBaud said it had to pay a ransom demand to ensure hackers would delete data they stole from its network.

Another SciFi term shows up in the AI literature.

https://thenextweb.com/neural/2020/07/17/a-beginners-guide-to-the-ai-apocalypse-artificial-stupidity/

A beginner’s guide to the AI apocalypse: Artificial stupidity

Welcome to the latest article in TNW’s guide to the AI apocalypse. In this series we’ll examine some of the most popular doomsday scenarios prognosticated by modern AI experts.

… You won’t find any comprehensive data on the subject outside of the testimonials at the Darwin Awards, but stupidity is surely the biggest threat to humans throughout all of history.

… Based on the fact that we can’t know exactly what’s going to happen once a superintelligent artificial being emerges, we should probably just start hard-coding “artificial stupidity” into the mix.

… So, rather than attempting to program advanced AI with a philosophical view on the sanctity of human life and what constitutes the greater good, we should just hamstring them with artificial stupidity from the start.

When do hackers cross the line?

https://venturebeat.com/2020/07/17/researchers-warn-court-ruling-could-have-a-chilling-effect-on-adversarial-machine-learning/

Researchers warn court ruling could have a chilling effect on adversarial machine learning

A cross-disciplinary team of machine learning, security, policy, and law experts say inconsistent court interpretations of an anti-hacking law have a chilling effect on adversarial machine learning security research and cybersecurity. At question is a portion of the Computer Fraud and Abuse Act (CFAA). A ruling to decide how part of the law is interpreted could shape the future of cybersecurity and adversarial machine learning.

… “If we are correct and the Supreme Court follows the Ninth Circuit’s narrow construction, this will have important implications for adversarial ML research. In fact, we believe that this will lead to better security outcomes in the long term,” the researchers’ report reads. “With a more narrow construction of the CFAA, ML security researchers will be less likely chilled from conducting tests and other exploratory work on ML systems, again leading to better security in the long term.”

Roughly half of circuit courts have ruled on the CFAA provisions around the country and have reached a 4-3 split. Some courts adopted a broader interpretation, which finds that “exceed authorized access” can deem improper access to information as including a breach of some terms of service or agreement. A narrow view finds that accessing information alone constitutes a CFAA violation.

… The paper, titled “Legal Risks of Adversarial Machine Learning Research,” was accepted for publication and presented today at the Law and Machine Learning workshop at the International Conference on Machine Learning (ICML).