Netherlands Regulating Tech

Another instructive regulation example.

How the Netherlands Is Taming Big Tech  By The New York Times, January 20, 2023

Microsoft chief privacy officer Julie Brill, at left, during in a 2018 White House discussion on childrens use of the Internet.

Microsoft chief privacy officer Julie Brill, at left, worked with the Dutch government on privacy issues.

In the Netherlands, government and educational institutions have pushed big tech companies to make significant privacy changes using a carrot-and-stick approach that involves negotiating their compliance with European data privacy standards.

After the Dutch Data Protection Authority said schools would have to discontinue use of Google's education apps if privacy risks were not addressed, Google responded with new privacy measures and transparency tools that will be rolled out in the Netherlands and elsewhere later this year.

Zoom also announced substantial changes to its data protection practices and policies after talks with a Dutch cooperative, SURF, that negotiates tech vendor contracts on behalf of the nation's universities and research institutions.

Now other nations are looking to the Dutch approach as they seek to regulate big tech.

From The New York Times       View Full Article - May Require Paid Subscription

Robotic Falcons to Deter Bird Strikes

 Novel Application.  might also deter birds eating key crops. 

Robotic Falcon Designed to Help Prevent Bird Strikes, By CNN, October 28, 2022

Collisions between birds and aircraft, known as bird strikes, can result in aircraft damage, as well as delays and cancellation of flights, costing the International Civil Aviation Organization a reported $1.4 billion each year.

Researchers at the University of Groningen (UG) in the Netherlands have developed a robotic peregrine falcon in a bid to prevent birds from colliding with aircraft.

The ground-controlled RobotFalcon imitates a falcon's movements to ward off birds, using propellers on its wings and a camera on its head to facilitate a "first-person view while steering."  ... 

UG's Rolf Storms said tests near the Dutch city of Workum showed the robot cleared flocks from fields within five minutes of taking off, with half the sites cleared within 70 seconds; a drone only managed to clear 80% of the birds from fields in the same time.  ... 

From CNN

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Government Authority Falls Due to Algorithm

Regulation 0f algorithms causes Dutch Tax Authority to fail.  An unusual event.  Fairness and impacts. 

The Dutch Tax Authority Was Felled by AI—What Comes Next? European regulation hopes to rein in ill-behaving algorithms by RAHUL RAO     in Spectrum IEEE

Until recently, it wasn’t possible to say that AI had a hand in forcing a government to resign. But that’s precisely what happened in the Netherlands in January 2021, when the incumbent cabinet resigned over the so-called kinderopvangtoeslagaffaire: the childcare benefits affair.

When a family in the Netherlands sought to claim their government childcare allowance, they needed to file a claim with the Dutch tax authority. Those claims passed through the gauntlet of a self-learning algorithm, initially deployed in 2013. In the tax authority’s workflow, the algorithm would first vet claims for signs of fraud, and humans would scrutinize those claims it flagged as high risk.

In reality, the algorithm developed a pattern of falsely labeling claims as fraudulent, and harried civil servants rubber-stamped the fraud labels. So, for years, the tax authority baselessly ordered thousands of families to pay back their claims, pushing many into onerous debt and destroying lives in the process.

“When there is disparate impact, there needs to be societal discussion around this, whether this is fair. We need to define what ‘fair’ is,” says Yong Suk Lee, a professor of technology, economy, and global affairs at the University of Notre Dame, in the United States. “But that process did not exist.”

Postmortems of the affair showed evidence of bias. Many of the victims had lower incomes, and a disproportionate number had ethnic minority or immigrant backgrounds. The model saw not being a Dutch citizen as a risk factor.

“The performance of the model, of the algorithm, needs to be transparent or published by different groups,” says Lee. That includes things like what the model’s accuracy rate is like, he adds.  .... '