German Constitutional Court Strikes Down Predictive Algorithms for Policing

Noting specially algorithms.  Meat to control a that level of specification?   Specifications of prediction? 

German Constitutional Court Strikes Down Predictive Algorithms for Policing

By Euractiv, February 17, 2023

Surveillance cameras at a German police station. 

In its ruling, the German Federal Constitutional Court struck down acts providing a statutory basis for police to process stored personal data through automated data analysis, in the case of Hesse, or automated data interpretation, in Hamburg.

The German Federal Constitutional Court declared the use of Palantir surveillance software by police in Hesse and Hamburg unconstitutional in a landmark ruling.

The ruling concludes a case brought by the German Society for Civil Rights (GFF) last year, hearings for which began in December. The plaintiffs argued that the software could be used for predictive policing, raising the risk of mistakes and discrimination by law enforcement. 

The German state of Hesse has been using the software since 2017, though it is not yet in place in Hamburg. The technology is provided by Palantir, a US data analytics firm which received early backing from intelligence agencies, including the CIA, FBI and NSA. 

The case was brought on behalf of 11 plaintiffs and rested on the argument that the software programme – named 'Hessendata' – facilitates predictive policing by using data to create profiles of suspects before any crime has been committed.

From Euractiv

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Will AI Discover new Laws of Physics?

 A possibility.

Will AI Discover new Laws of Physics?  in NewScientist

Algorithms can pore over astrophysical data to identify underlying equations. Now, physicists are trying to figure out how to imbue these “machine theorists” with the ability to find deeper laws of nature

This article has been viewed 3468 times in the last 24 hours.

PHYSICS 21 November 2022 By Thomas Lewton

SPEAKING at the University of Cambridge in 1980, Stephen Hawking considered the possibility of a theory of everything that would unite general relativity and quantum mechanics – our two leading descriptions of reality – into one neat, all-encompassing equation. We would need some help, he reckoned, from computers. Then he made a provocative prediction about these machines’ growing abilities. “The end might not be in sight for theoretical physics,” said Hawking. “But it might be in sight for theoretical physicists.”

Artificial intelligence has achieved much since then, yet physicists have been slow to use it to search for new and deeper laws of nature. It isn’t that they fear for their jobs. Indeed, Hawking may have had his tongue firmly in his cheek. Rather, it is that the deep-learning algorithms behind AIs spit out answers that amount to a “what” rather than a “why”, which makes them about as useful for a theorist as saying the answer to the question of life, the universe and everything is 42.

Except that now we have found a way to make deep-learning algorithms speak physicists’ language. We can leverage AI’s ability to scour vast data sets in search of hidden patterns and extract meaningful results – namely, equations. “We’re moving into the discovery phase,” says Steve Brunton at the University of Washington in Seattle.  ... ' 

UK fines Clearview AI £7.5M for Scraping Citizens’ Data

 Recently talked to a company about collecting 'public data' to build an infrastructure of facial images for non individual recognition purposes. . The governing laws about using such data is complex and getting more so, so beware.

UK fines Clearview AI £7.5M for scraping citizens’ data By Ryan Daws | May 23, 2022 | TechForge Media  in AINews

 Clearview AI has been fined £7.5 million by the UK’s privacy watchdog for scraping the online data of citizens without their explicit consent.

 The controversial facial recognition provider has scraped billions of images of people across the web for its system. Understandably, it caught the attention of regulators and rights groups from around the world.

 In November 2021, the UK’s Information Commissioner’s Office (ICO) imposed a potential fine of just over £17 million on Clearview AI. Today’s announcement suggests Clearview AI got off relatively lightly.

John Edwards, UK Information Commissioner, said:

“Clearview AI Inc has collected multiple images of people all over the world, including in the UK, from a variety of websites and social media platforms, creating a database with more than 20 billion images.

The company not only enables identification of those people, but effectively monitors their behaviour and offers it as a commercial service. That is unacceptable.

That is why we have acted to protect people in the UK by both fining the company and issuing an enforcement notice.”  The enforcement notice requires Clearview AI to delete all facial recognition data.  ...

A joint investigation by the UK’s ICO and the Office of the Australian Information Commissioner (OAIC) was first launched in July 2020.

Angelene Falk, Australian Information Commissioner and Privacy Commissioner, commented:  “The joint investigation with the ICO has been highly valuable and demonstrates the benefits of data protection regulators collaborating to support effective and proactive regulation.   

The issues raised by Clearview AI’s business practices presented novel concerns in a number of jurisdictions. By partnering together, the OAIC and ICO have been able to contribute to an international position, and shape our global regulatory environment.” Falk concluded that uploading an image to a social media site “does not unambiguously indicate agreement to collection of that image by an unknown third party for commercial purposes”.   ... ' 

And further on EuroNews. 

On Forthcoming Draft EU Rules About AI

Excerpt of EU regulation being considered, now in draft. 

The EU’s AI rules will likely take over a year to be agreed  By Ryan Daws | February 17, 2022  in AI News

Rules governing the use of artificial intelligence across the EU will likely take over a year to be agreed upon.

Last year, the European Commission drafted AI laws. While the US and China are set to dominate AI development with their vast resources, economic might, and light-touch regulation, European rivals – including the UK and EU members – believe they can lead in ethical standards.

In the draft of the EU regulations, companies that are found guilty of AI misuse face a fine of €30 million or six percent of their global turnover (whichever is greater). The risk of such fines has been criticised as driving investments away from Europe.

The EU’s draft AI regulation classifies systems into three risk categories:

Limited risk – includes systems like chatbots, inventory management, spam filters, and video games.

High risk – includes systems that make vital decisions like evaluating creditworthiness, recruitment, justice administration, and biometric identification in non-public spaces.

Unacceptable risk – includes systems that are manipulative or exploitative, create social scoring, or conduct real-time biometric authentication in public spaces for law enforcement.

Unacceptable risk systems will face a blanket ban from deployment in the EU while limited risk will require minimal oversight.

Organisations deploying high-risk AI systems would be required to have things like:

Human oversight.

A risk-management system.

Record keeping and logging.

Transparency to users.

Data governance and management.

Conformity assessment.

Government registration.

However, the cumbersome nature of the EU – requiring agreement from all member states, each with their own priorities – means that new regulations are often subject to more debate and delay than national lawmaking.  .... '

More Laws of Computing

 Not so much laws, but rather general indications of past trends that may usefully hold in the future. or not.  Here some proposals for mew laws.Good for tracking against new data.  

Moore’s Not Enough: ​4 New laws of Computing Moore’s and Metcalfe’s conjectures are taught in classrooms every day—these four deserve consideration, too  by ADENEKAN DEDEKE in IEEE Spectrum.  Below an intro, much more at the link.

MOORE'S LAW METCALFE'S LAW COMPUTING

I teach technology and information-systems courses at Northeastern University, in Boston. The two most popular laws that we teach there—and, one presumes, in most other academic departments that offer these subjects—are Moore’s Law and Metcalfe’s Law. Moore’s Law, as everyone by now knows, predicts that the number of transistors on a chip will double every two years. One of the practical values of Intel cofounder Gordon Moore’s legendary law is that it enables managers and professionals to determine how long they should keep their computers. It also helps software developers to anticipate, broadly speaking, how much bigger their software releases should be.

Metcalfe’s Law is similar to Moore’s Law in that it also enables one to predict the direction of growth for a phenomenon. Based on the observations and analysis of Robert Metcalfe, co-inventor of the Ethernet and pioneering innovator in the early days of the Internet, he postulated that the value of a network would grow proportionately to the number of its users squared. A limitation of this law is that a network’s value is difficult to quantify. Furthermore, it is unclear that the growth rate of every network value changes quadratically at the power of two. Nevertheless, this law as well as Moore’s Law remain a centerpiece in both the IT industry and academic computer-science research. Both provide tremendous power to explain and predict behaviors of some seemingly incomprehensible systems and phenomena in the sometimes inscrutable information-technology world.

King Camp Gillette reduced the price of the razors, and the demand for razor blades increased. The history of IT contains numerous examples of this phenomenon, too.

I contend, moreover, that there are still other regularities in the field of computing that could also be formulated in a fashion similar to that of Moore’s and Metcalfe’s relationships. I would like to propose four such laws.

Law 1. Yule’s Law of Complementarity

I named this law after George Udny Yule (1912), who was the statistician who proposed the seminal equation for explaining the relationship between two attributes. I formulate this law as follows:   .... '