Is a programming language a hacking tool? How about software to detect security weaknesses?

https://gizmodo.com/the-u-s-wants-to-crack-down-on-sales-of-commercial-hac-1847904305

The U.S. Wants to Crack Down on Sales of Commercial Hacking Tools for Obvious Reasons

After a slew of hacking scandals involving private surveillance companies, the U.S. is looking to impose new restrictions on the sale of commercial hacking tools—in the hopes of clamping down on abuse perpetuated by the industry.

On Wednesday, the Commerce Department announced a rule change that will put new limitations on the resale or export of “certain items that can be used for malicious cyber activities.” This applies to tools used to infiltrate digital systems and conduct surveillance—such as the notorious commercial spyware, Pegasus —as well as other hacking and “intrusion” software, the Washington Post first reported. The rule, which has reportedly been in development for years, will be put into effect in 90 days.

While the intricacies of the new 65-page rule are somewhat thorny, the biggest result is a new license requirement for American companies that want to sell hacking tools to countries “of national security or weapons of mass destruction concern,” as well as to “countries subject to a U.S. arms embargo,” the Commerce Department’s announcement says.

The new world order. Familiar technology vs. those incomprehensible idiots in Washington? Who do you trust? Who had responses ready and the will to use them?

https://www.foreignaffairs.com/articles/world/2021-10-19/ian-bremmer-big-tech-global-order

The Technopolar Moment

How Digital Powers Will Reshape the Global Order

After rioters stormed the U.S. Capitol on January 6, some of the United States’ most powerful institutions sprang into action to punish the leaders of the failed insurrection. But they weren’t the ones you might expect. Facebook and Twitter suspended the accounts of President Donald Trump for posts praising the rioters. Amazon, Apple, and Google effectively banished Parler, an alternative to Twitter that Trump’s supporters had used to encourage and coordinate the attack, by blocking its access to Web-hosting services and app stores. Major financial service apps, such as PayPal and Stripe, stopped processing payments for the Trump campaign and for accounts that had funded travel expenses to Washington, D.C., for Trump’s supporters.

The speed of these technology companies’ reactions stands in stark contrast to the feeble response from the United States’ governing institutions. Congress still has not censured Trump for his role in the storming of the Capitol. Its efforts to establish a bipartisan, 9/11-style commission failed amid Republican opposition. Law enforcement agencies have been able to arrest some individual rioters—but in many cases only by tracking clues they left on social media about their participation in the fiasco.

States have been the primary actors in global affairs for nearly 400 years. That is starting to change, as a handful of large technology companies rival them for geopolitical influence. The aftermath of the January 6 riot serves as the latest proof that Amazon, Apple, Facebook, Google, and Twitter are no longer merely large companies; they have taken control of aspects of society, the economy, and national security that were long the exclusive preserve of the state. The same goes for Chinese technology companies, such as Alibaba, ByteDance, and Tencent. Nonstate actors are increasingly shaping geopolitics, with technology companies in the lead. And although Europe wants to play, its companies do not have the size or geopolitical influence to compete with their American and Chinese counterparts.

Maturity models provide a good outline for thinking about improvement…

https://www.zdnet.com/article/ai-ethics-maturity-model/

AI ethics maturity model: A company guide

How to develop a maturity model for building an ethical and responsible AI practice.

All you have to get right is the hardest part.

https://techxplore.com/news/2021-10-machine-fair-accurate.html

How machine learning can be fair and accurate

Carnegie Mellon University researchers are challenging a long-held assumption that there is a trade-off between accuracy and fairness when using machine learning to make public policy decisions.

As the use of machine learning has increased in areas such as criminal justice, hiring, health care delivery and social service interventions, concerns have grown over whether such applications introduce new or amplify existing inequities, especially among racial minorities and people with economic disadvantages. To guard against this bias, adjustments are made to the data, labels, model training, scoring systems and other aspects of the machine learning system. The underlying theoretical assumption is that these adjustments make the system less accurate.

… "You actually can get both. You don't have to sacrifice accuracy to build systems that are fair and equitable," Ghani said. "But it does require you to deliberately design systems to be fair and equitable. Off-the-shelf systems won't work."

Kit T. Rodolfa et al, Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy, Nature Machine Intelligence (2021). DOI: 10.1038/s42256-021-00396-x

Journal information: Nature Machine Intelligence

How would you redesign a university to take advantage of these new technologies?

https://theconversation.com/future-of-college-will-involve-fewer-professors-166394

Future of college will involve fewer professors

Can’t hurt…

https://www.makeuseof.com/useful-web-tools-student-should-use/

5 Useful Web Tools Every Student Should Use