Sunday, March 28, 2021

Your papers, Comrade! We keep trying to implement a national identification card.

https://www.usatoday.com/story/news/health/2021/03/26/covid-vaccine-passports-new-york-first-vaccination-proof-system/6976009002/?scrolla=5eb6d68b7fedc32c19ef33b4

New York launches nation's first 'vaccine passports.' Others are working on similar ideas, but many details must be worked out.

Starting Friday, New Yorkers will be able to pull up a code on their cell phone or a printout to prove they've been vaccinated against COVID-19 or recently tested negative for the virus that causes it.

The first-in-the-nation certification, called the Excelsior Pass, will be useful first at large-scale venues like Madison Square Garden, but next week will be accepted at dozens of event, arts and entertainment venues statewide. It already enables people to increase the size of a wedding party, or other catered event.





If compliance is following a series of steps, software can handle compliance.

https://insidebigdata.com/2021/03/27/financial-chief-data-officers-making-advances-in-data-management-and-compliance-but-over-half-of-manual-processes-remain/

Financial Chief Data Officers Making Advances in Data Management and Compliance but Over Half of Manual Processes Remain

Risk data aggregation is the top compliance concern for chief data officers (CDOs) within financial services firms, with 88% of these organizations devoting 40% or more of their total data practice budget to compliance functions, according to new research launched ahead of the leading data management event for financial services, FIMA.

The survey, conducted by WBR Insights among data and information technology executives within the financial services sector and sponsored by InterSystems, highlights that financial organizations are allocating significant portions of their budget to compliance initiatives, and that 54% of those surveyed further revealed that at least half of these functions are still performed manually within their organization.

Review the full research at HERE.



(Related)

https://venturebeat.com/2021/03/27/what%E2%80%8C-%E2%80%8Cis%E2%80%8C-%E2%80%8Cdataops%E2%80%8C-%E2%80%8Cand%E2%80%8C-%E2%80%8Cwhy%E2%80%8C-%E2%80%8Cits%E2%80%8C-%E2%80%8Ca%E2%80%8C-%E2%80%8Ctop%E2%80%8C-%E2%80%8Ctrend/

What‌ ‌is‌ ‌DataOps,‌ ‌and‌ ‌why‌ ‌it’s‌ ‌a‌ ‌top‌ ‌trend‌

The‌ ‌term‌ ‌DataOps‌ ‌emerged‌ seven‌ ‌years‌ ‌ago‌ to refer to ‌best‌ ‌practices‌ for ‌getting‌ ‌proper‌ ‌analytics,‌ ‌and research firm Gartner calls it a major trend encompassing several steps in the data lifecycle.

Just‌ as‌ ‌the‌ ‌DevOps‌ ‌trend‌ ‌led‌ ‌to‌ ‌a‌ ‌better‌ ‌process‌ ‌for‌ ‌collaboration‌ ‌between‌ ‌‌developers‌ ‌and‌ ‌operations‌ ‌teams,‌ ‌DataOps‌ ‌refers‌ ‌to closer collaboration between various teams handling data and operations teams deploying data into applications.





Not sure I agree, unless it is impossible for a second firm to access the same/similar data.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3810366

Machine Learning as Natural Monopoly

Machine learning is transforming the economy, reshaping operations in communications, law enforcement, and medicine, among other sectors. But all is not well: It is now well-established that many machine-learning-based applications harvest vast amounts of personal information and yield results that are systematically biased. In response, policymakers have begun to offer a range of inchoate and often insufficient solutions, overlooking the possibility—suggested intuitively by scholars across disciplines—that these systems are natural monopolies, and thus neglecting the long legal tradition of natural monopoly regulation.

Drawing on the computer science, economics, and legal literatures, I find that machine-learning-based applications can be natural monopolies. Several features of machine learning suggest that this is so, including the fixed costs of developing these applications and the computational methods of optimizing these systems. This conclusion yields concrete policy implications: Where natural monopolies exist, public oversight and regulation is typically superior to market discipline through competition. Hence, where machine-learning-based applications are natural monopolies, this regulatory tradition offers one framework for confronting a range of issues—from privacy to accuracy and bias—that attend to such systems. Just as prior natural monopolies—the railways, electric grids, and telephone networks—faced rate and service regulation to protect against extractive, anticompetitive, and undemocratic behaviors, so too might machine-learning-based applications face similar public regulation to limit intrusive data collection and protect against algorithmic redlining, among other harms.





A syllabus with open source material.

https://digitalcommons.njit.edu/cgi/viewcontent.cgi?article=1336&context=hum-syllabi

PHIL 334-006: Engineering Ethics

What roles can engineers play in confronting the unprecedented challenges brought on by our increasingly technological world? This course examines various forms of engineering through the lens of applied ethics and the philosophy of technology. We will discuss topics such as whistleblowing, the ethics of drones, the politics of clean energy, sustainable design, and the extent to which automation poses a threat to democracy. This course also has a heavy focus on ethical issues pertaining to artificial intelligence, e.g., could robots ever be considered legal persons? We will spend a considerable amount of time discussing engineering approaches to the climate crisis and our responsibilities to future generations.





Helping my students leave…

https://www.makeuseof.com/resume-builder-apps-android/

The 7 Best Resume Builder Apps for Android





Wally’s PowerPoint tips?

https://dilbert.com/strip/2021-03-28



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