Be careful what you ask for. Then blame it on Twitter.
https://www.makeuseof.com/indian-politicians-tweets-manipulated-media/
Indian Politicians Object to Tweets Being Labelled as Manipulated Media
Twitter's fairly new manipulated media policy is already it's being put to the test. Once again, the Indian government is asking the company to reverse some of the actions it's taken to ensure that only accurate info is found on the platform.
Indian news outlet The News Minute reports that the Government of India is not happy with Twitter's decision to label some tweets made by Indian politicians as "manipulated media."
Two days after Twitter first applied the label to a tweet by spokesperson Sambit Patra of the BJP political party, the Indian government sent a notice to the company. It asked for the labels to be removed out of "fairness and equity," saying that keeping them on sullies the platform’s image of being "neutral and unbiased."
(Related)
India asks social media firms to remove reference to 'Indian variant' of coronavirus
India's information technology (IT) ministry has written to all social media companies asking them to take down any content that refers to an "Indian variant" of the coronavirus, according to a letter issued on Friday which was seen by Reuters.
I like it! A great summary.
Reimagining data responsibility: 10 new approaches toward a culture of trust in re-using data to address critical public needs
Data and data science offer tremendous potential to address some of our most intractable public problems (including the Covid-19 pandemic). At the same time, recent years have shown some of the risks of existing and emerging technologies. An updated framework is required to balance potential and risk, and to ensure that data is used responsibly. Data responsibility is not itself a new concept. However, amid a rapidly changing technology landscape, it has become increasingly clear that the concept may need updating, in order to keep up with new trends such as big data, open data, the Internet of things, and artificial intelligence, and machine learning. This paper seeks to outline 10 approaches and innovations for data responsibility in the 21st century. The 10 emerging concepts we have identified include:
End-to-end data responsibility
Decision provenance
Professionalizing data stewardship
From data science to question science
Contextual consent
Responsibility by design
Data asymmetries and data collaboratives
Personally identifiable inference
Group privacy
Data assemblies
Each of these is described at greater length in the paper, and illustrated with examples from around the world. Put together, they add up to a framework or outline for policy makers, scholars, and activists who seek to harness the potential of data to solve complex social problems and advance the public good. Needless to say, the 10 approaches outlined here represent just a start. We envision this paper more as an exercise in agenda-setting than a comprehensive survey.
Prejudged and convicted? Is there no way AI can work with police?
https://calhoun.nps.edu/handle/10945/67100
I’VE GOT MY AI ON YOU: ARTIFICIAL INTELLIGENCE IN THE LAW ENFORCEMENT DOMAIN
Artificial Intelligence (AI) systems provide a unique problem for users in the law enforcement domain. On one hand, AI systems provide an opportunity for optimizations and faster workflows, especially in the environment of growing data. On the other hand, if left unchecked AI systems have the potential to negatively affect the community served by law enforcement. This research focuses on three types of AI systems currently used by law enforcement: facial recognition, predictive risk assessments, and predictive policing. By looking at these three types of AI systems, this research attempts to evaluate the effectiveness of the technology while maintaining the privacy, fairness, transparency, and accountability expected by the public. These three case studies show how AI systems can have a negative impact on individuals identified via AI systems and the need for further research into effective measures to regulate the technology. Additionally, the European Union is currently working on potential frameworks for responsible implementation of AI systems, which provide a template for future efforts in the United States.
(Related)
https://digital.sandiego.edu/sdlr/vol58/iss1/4/
Face IT: Only Congress Can Preserve Privacy from the Pervasive Use of Facial Recognition Technology by Police
This Comment implores Congress to limit the development of law enforcement FRT databases. In Part II, the Comment describes facial recognition technology, examining its development and uses. This section describes how law enforcement compiles databases of faces. It concludes by exploring potential future applications of the technology. Part III discusses the privacy rights angle, answering why the American population should be concerned about—and why legislators should act to prevent—unchecked FRT-equipped law enforcement.
Part IV addresses the current statutory framework that governs law enforcement’s use of FRT. In this section, the Comment points out the general lack of enacted legislation regarding the use of biometric information by law enforcement. The analysis shows that current statutory law is blind to the potential abuses of FRT-equipped law enforcement agencies, making the technology ripe for exploitation.
In Part V, the Comment reviews Fourth Amendment jurisprudence and its applicability to FRT. Further, this section examines Supreme Court Fourth Amendment jurisprudence and concludes that recent decisions indicate that the Court would be unlikely to hold law enforcement’s uninhibited use of FRT unconstitutional. The section concludes that relying on the courts to protect citizens from technology’s encroachment on Fourth Amendment rights will result in millions of Americans losing privacy rights, even if the Court eventually changes its conception of what the Fourth Amendment protects.
Part VI proffers a legislative solution to directly address FRT’s use by law enforcement. The solution requires congressional action that addresses privacy concerns while still allowing law enforcement to use the cutting-edge technology. The proposed solution has two primary prongs: first, amending the U.S. Code to limit the authorization of the FBI’s collection and compilation of facial images to those obtained by law enforcement and correctional entities; second, proposing a new law that vests responsibility for the collection of non-criminal identification information in the Department of Health and Human Services, or another non-law enforcement agency.
Data has interests?
http://classic.austlii.edu.au/au/journals/LawTechHum/2021/8.html
Beyond Privacy: Protecting Data Interests in the Age of Artificial Intelligence
The fact that it is now a cliché to refer to our digital era as the ‘Fourth Industrial Revolution’ reinforces how important the internet and artificial intelligence (AI) have become. Algorithms increasingly influence the way we perceive ourselves, interact with others and understand the world around us. These are seismic impacts on the scale of the upheaval caused by the original Industrial Revolution. However, transformational change is usually a complicated mix of good and bad. For instance, while the Industrial Revolution may have created the foundations for the wealth and quality of life we enjoy today, it is also responsible for the explosion in carbon emissions that now drive catastrophic climate change. Similarly, while today’s technology industry is well known for building brilliant applications and devices, it also displays a dangerous proclivity to accumulate and manipulate personal data. To ameliorate the worst effects of this data-driven revolution, we must think more broadly about our data interests and how to best protect them. Protecting these interests requires re-thinking the law on information privacy and questioning whether the existing regimes are sufficient.
Part I of this article discusses the nature and origins of the interests we have in data.
Part II discusses how information privacy law has responded to the challenges born out of the data economy.
Part III discusses how the evolution of the data economy has created novel interests in data.
Start thinking. Most organizations do not know what processes they have, let alone how they work. Processes have evolved over time and a rarely well documented.
https://venturebeat.com/2021/05/22/a-first-step-to-automating-your-business-processes/
A first step to automating your business processes
… In speaking with Brent Harder, who is currently Head of Enterprise Automation at Fiserv, I learned of an interesting case that may provide organizations with an understanding on the importance of transparency in digital automation. Prior to joining Fiserv, Brent worked at a major, international bank based in New York City. This bank, like many other large financial institutions, struggled with how and where to start its enterprise automation program. After much thought and discussion, the client onboarding process was carefully chosen as the place to start. If client onboarding could be done faster, then not only would customer satisfaction improve, but the bank would also benefit by being able to recognize revenue sooner. That would be a big win-win.
However, when the team began looking at the end-to-end client onboarding process, they encountered several significant obstacles. A siloed organization, difficult-to-access data that was compartmentalized by department, and a fragmented technology landscape were just a few of the challenges. As Brent said, “we stood in our way.” [AKA: We have met the enemy and he is us,” Bob]
My AI says it won’t hire people any more.
An age of ‘robo sapiens’? Hiring troubles prompt some employers to eye more automation
The United States today is producing about the same amount of goods and services as before the coronavirus pandemic — but with 8.2 million fewer workers, equal to the combined payrolls of every employer in Virginia, Arizona and Iowa.
Greater productivity is the rare silver lining to emerge from the crucible of COVID-19. The health crisis forced executives to innovate, often by accelerating the introduction of industrial robots, advanced software and artificial intelligence that reduced their dependence upon workers who might get sick.
… Pilgrim’s Pride, a chicken processor based in Greeley, Colo., is implementing a “long-term strategy” of greater automation. The company cut its workforce over the past year by 1,200 people and expects to trim an additional 5,600 jobs this year, chief executive Fabio Sandri said last month.
Probably not “everything you need to know’ but it’s a start.
https://www.analyticsinsight.net/cryptocurrency-simplified-the-ultimate-guide-to-crypto-world/
CRYPTOCURRENCY SIMPLIFIED: THE ULTIMATE GUIDE TO CRYPTO WORLD
Perspective.
https://www.nytimes.com/2021/05/20/technology/tech-antitrust-paul-romer.html
Once Tech’s Favorite Economist, Now a Thorn in Its Side
… “Economists taught, ‘It’s the market. There’s nothing we can do,’” Mr. Romer said. “That’s really just so wrong.”
My brother still lives in New Jersey. Perhaps he could ‘shop vacuum’ up a few pounds if anyone has a good recipe? What wine goes with bugs?
https://www.cbsnews.com/news/cicadas-brood-x-eating-foodies/
The cicadas are coming — and foodies are getting ready to feast
Billions of Brood X cicadas are emerging after being underground for 17 years. As many in the eastern U.S. anxiously await their arrival, others are preparing for their plates for what they say is a delicacy.
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