The European Union has long been a trendsetter in privacy regulation. Its General Data Protection Regulation (GDPR) and stringent antitrust laws have inspired new legislation around the world. For decades, the EU has codified protections on personal data and fought against what it viewed as commercial exploitation of private information, proudly positioning its regulations in contrast to the light-touch privacy policies in the United States.

The new European data governance strategy (pdf) takes a fundamentally different approach. With it, the EU will become an active player in facilitating the use and monetization of its citizens’ personal data. Unveiled by the European Commission in February 2020, the strategy outlines policy measures and investments to be rolled out in the next five years.

This new strategy represents a radical shift in the EU’s focus, from protecting individual privacy to promoting data sharing as a civic duty. Specifically, it will create a pan-European market for personal data through a mechanism called a data trust. A data trust is a steward that manages people’s data on their behalf and has fiduciary duties toward its clients.

The EU’s new plan considers personal data to be a key asset for Europe. However, this approach raises some questions. First, the EU’s intent to profit from the personal data it collects puts European governments in a weak position to regulate the industry. Second, the improper use of data trusts can actually deprive citizens of their rights to their own data.

The Trusts Project, the first initiative put forth by the new EU policies, will be implemented by 2022. With a €7 million budget, it will set up a pan-European pool of personal and nonpersonal information that should become a one-stop shop for businesses and governments looking to access citizens’ information.

Global technology companies will not be allowed to store or move Europeans’ data. Instead, they will be required to access it via the trusts. Citizens will collect “data dividends,” which haven’t been clearly defined but could include monetary or nonmonetary payments from companies that use their personal data. With the EU’s roughly 500 million citizens poised to become data sources, the trusts will create the world’s largest data market.

For citizens, this means the data created by them and about them will be held in public servers and managed by data trusts. The European Commission envisions the trusts as a way to help European businesses and governments reuse and extract value from the massive amounts of data produced across the region, and to help European citizens benefit from their information. The project documentation, however, does not specify how individuals will be compensated.

Data trusts were first proposed by internet pioneer Sir Tim Berners Lee in 2018, and the concept has drawn considerable interest since then. Just like the trusts used to manage one’s property, data trusts may serve different purposes: they can be for-profit enterprises, or they can be set up for data storage and protection, or to work for a charitable cause.

IBM and Mastercard have built a data trust to manage the financial information of their European clients in Ireland; the UK and Canada have employed data trusts to stimulate the growth of the AI industries there; and recently, India announced plans to establish its own public data trust to spur the growth of technology companies.

The new EU project is modeled on Austria’s digital system, which keeps track of information produced by and about its citizens by assigning them unique identifiers and storing the data in public repositories.

Unfortunately, data trusts do not guarantee more transparency. The trust is governed by a charter created by the trust’s settlor, and its rules can be made to prioritize someone’s interests. The trust is run by a board of directors, which means a party that has more seats gains significant control.

The Trusts Project is bound to face some governance issues of its own. Public and private actors often do not see eye to eye when it comes to running critical infrastructure or managing valuable assets. Technology companies tend to favor policies that create opportunity for their own products and services. Caught in a conflict of interest, Europe may overlook the question of privacy.

And in some cases, data trusts have been used to strip individuals of their rights to control data collected about them. In October 2019, the government of Canada rejected a proposal by Alphabet/Sidewalk Labs to create a data trust for Toronto’s smart city project. Sidewalk Labs had designed the trust in a way that secured the company’s control over citizens’ data. And India’s data trust faced criticism for giving the government unrestricted access to personal information by defining authorities as “information fiduciaries.”

One possible solution could be to set up an ecosystem of data stewards, both public and private, that each serve different needs. Sylvie Delacroix and Neil Lawrence, the originators of this bottom-up approach, liken data trusts to pension funds, saying they should be tightly regulated and able to provide different services to designated groups.

When put into practice, the EU’s Trusts Project will likely change the privacy landscape on a global scale. Unfortunately, however, this new approach won’t necessarily give European citizens more privacy or control over their information. It is not yet clear what model of trusts the project will pursue, but the policies do not currently provide any way for citizens to opt out.

At a recent congressional antitrust hearing in the United States, four major platform companies publicly recognized the use of surveillance technologies, market manipulation, and forceful acquisitions to dominate the data economy. The single most important lesson from these revelations is that companies that trade in personal data cannot be trusted to store and manage it. Decoupling personal information from the platforms’ infrastructure would be a decisive step toward curbing their monopoly power. This can be done through data stewardship.

Ideally, the Trusts Project would show the world a more equitable way to capture and distribute the true value of personal data. There’s still time to deliver on that promise.

Anna Artyushina is a public policy scholar specializing in data governance and smart cities. She is a PhD candidate in science and technology studies at York University in Toronto.

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In the fast food industry, speed is everything. The concept has never just been about cooking quickly. Players in this competitive space spend huge fortunes every year on optimizing every aspect of the experience, from ordering, to queueing, to cleaning up afterwards. And while fast food restaurants are major employers worldwide, there’s always been a firm eye cast over the gains that automation has to offer.

Flipping Burgers

In the West, fast food most commonly brings burgers to mind. Preparing a quality burger requires attention to the grade of meat, fat content, as well as the preparation steps before it hits the grill. Then it’s all about temperature and time, and getting just the right sear to bring out the natural flavors of the beef. While a boutique burger joint will employ a skilled worker to get things just right, that doesn’t fly for fast food. Every order needs to be preparable by whichever minimum-wage worker got the shift, and be as repeatable as possible across entire countries, or even the world, to meet customer expectations.

In their efforts to improve efficiency, White Castle have taken the bold step of installing a robotic burger flipper, imaginitively named Flippy. Built by Miso Robotics, the robot hangs from a ceiling rail to minimise the space taken up in the kitchen area. Based on a Fanuc robot arm, the system uses artificial intelligence to manage kitchen resources, Flippy is capable of managing both the grill and fryers together to ensure fries don’t get cold while the burgers are still cooking, for example. Currently undergoing a trial run in Chicago, White Castle has ambitions to roll the technology out to further stores if successful.

We’ve seen other robotic burger systems before, too. In late 2018, our own [Brian Benchoff] went down to check out Creator, which cooks and assembles its burgers entirely by machine. Despite suspicions about the business model, Creator have persisted until the present day with their unique blend of technology and culinary arts. Particularly impressive were their restaurant modifications in the face of COVID-19. The restaurant received an overhaul, with meals being robotically prepared directly in a take-out box with no human contact. Take-out meals are double-bagged and passed to customers through an airlock, with a positive-pressure system in the restaurant to protect staff from the outside world.

Pizzabots

Pizza is a staple food for many, with high demand and a stronger dependence on delivery than other fast food options. This has led to the industry exploring many avenues for automation, from preparation to order fulfillment.

In terms of outright throughput, Zume were a startup that led the charge. Their system involves multiple robots to knead dough, apply sauce and place the pie in the oven. Due to the variable nature sizes and shapes of various toppings, these are still applied by humans in the loop. Capable of turning out 120 pizzas per hour, a single facility could compete with many traditional human-staffed pizza shops. They also experimented with kitchens-on-wheels that use predictive algorithms to stock out trucks that cook pizzas on the way to the customer’s door. Unfortunately, despite a one-time $4 billion USD valuation, the startup hit a rocky patch and is now focusing on packaging instead.

Picnic have gone further, claiming an output rate of up to 300 twelve-inch pies an hour. The startup aims to work with a variety of existing pizza restaurants, rather than striking out as their own brand. One hurdle to overcome is the delivery of a prepared pizza into the oven. There are many varieties and kinds of pizza oven used in commercial settings, and different loading techniques are required for each. This remains an active area of development for the company. The company has a strong focus on the emerging ghost kitchen model, where restaurants are built solely to fulfill online delivery orders, with no dining area.

Domino’s is one of the largest pizza companies in the world, and thus far have focused their efforts on autonomous delivery. The DRU, or Domino’s Robotic Unit, was launched to much fanfare, promising to deliver pizzas by a small wheeled robotic unit. Equipped with sensors to avoid obstacles and GPS navigation, the project has not entered mainstream service just yet. However, between this and the multitude of companies exploring drone delivery, expect to see this become more of a thing in coming years.

A more immediate innovation from Domino’s has been the DOM Pizza Checker. With customer complaints about pizza quality plaguing the chain, the pizza checker is an AI-powered visual system. It’s responsible for determining if the correct pizza has been made, with the right toppings and good distribution. An impressive practical use of AI imaging technology, it sounds an alarm if the pizza isn’t up to scratch, prompting it to be remade. However, it has come under scrutiny as a potential method to harass franchisees and workers. Additionally, the limitations of the system mean that Domino’s are still perfectly capable of turning out a bad pizza on occasion.

Other Efforts

One of the most visible examples of fast food automation is the widespread adoption of order kiosks by McDonalds, which kicked off in earnest in 2015. The majority of stores in the US now rely on these to speed up the ordering process, while also enabling more customization for customers with less fuss. Over-the-counter ordering is still possible at most locations, but there’s a heavy emphasis on using the new system.

In general, online ordering and delivery has become the norm, where ten years ago, the idea of getting McDonalds delivered was considered magical and arcane. This writer made seven attempts to take advantage of an early version of the service in China in 2015, succeeding only once, largely due to a lack of understanding of addresses written in non-Latin characters. However, due to the now-ubiquitous nature of services like Ubereats, Postmates, and Menulog, it’s simple for any restaurant to largely automate their ordering and fulfillment process, and reach customers at a distance from their brick-and-mortar locations.

Other efforts are smaller in scope, but contribute to great efficiency gains back-of-house. McDonalds and other chains have widely adopted automated beverage systems. Capable of automatically dispensing cups and the requisite fluids, they take instructions directly from the digital ordering system and take the manual labor out of drink preparation. They’re also great at slightly underfilling the cups, in a way that any human would consider incredibly rude.

Conclusion

Robots in the fast-food kitchen stand to reduce or eliminate tedious, repetitive work. Robots don’t get sick, and less human labour means fewer rostering hassles. It seems to be a foregone conclusion that more automation is on the way, and while some startups may falter, others will surely succeed. Your next meal may just yet be entirely prepared by a robot, even if it’s still delivered by a tired grad student on a moped. Come what may!

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GNU Emacs is one of the most powerful free/libre and open-source text editors, available for several operating systems regardless of the machine type such as GNU/Linux, BSD, macOS, Windows, and Solaris.

Now, after a year of development, Nicolas Petton has released a new version 27.1 of the Emacs text editor. Obviously, it comes with a wide variety of new changes, ranging from installation, startup, and editing to changes in specialized modes and packages.

GNU Emacs 27.1: What’s New

With Emacs 27.1, Cairo drawing functionality ( --with-cairo configure option) is no longer experimental. Now, if you configure Cairo drawing using Cairo >=1.16.0 with Emacs 27.1, you can even display multicolor fonts like Noto Color Emoji.

Subsequently, it also brings support for built-in printing when you build Emacs with GTK+. However, if you want to build Emacs with GTK 2 and GTK 3, you now require GTK 2.24 and GTK 3.10 respectively.

Another major change that Emacs 27.1 includes is the dropping default configuration of ImageMagick. This means Emacs no longer uses ImageMagick to display, resize, and rotate images owing to security and stability concerns with it.

However, if you still want ImageMagick, you can override the default using configure --with-imagemagick.

Speaking of the new mode, v27.1 has added a new command tab-bar-mode, which enables the tab bar at the top of each frame. Not only that, you can also use a new global-tab-line-mode command to enable the tab line above each window.

In image mode, it has added a new Exif library that can parse JPEG files and output data. Even ‘image-mode’ uses this library to automatically rotate images according to the orientation in the Exif data.

The list of new enhancements does not end here. Hence, for full details, I would suggest you read the summary of Emacs 27.1. However, here I’m listing other key new features included in GNU Emacs 27.1:

• Using HarfBuzz as a text shaping engine
• Built-in support for arbitrary-size integers
• Using ‘portable dumper’ in place of unexec
• Support for XDG conventions for init files
• Additional early-init initialization file
• Using Lexical-binding by default
• Default dynamic module support
• New ‘jsonrpc’ library to write JSONRPC applications
• Support for Unicode Standard version 13.0
• New package to parse ISO 8601 time, date, duration, and intervals
• Battery Status support in all Cygwin builds

Get GNU Emacs 27.1

Now, if you want to download Emacs 27.1, head over to the official page. If you’re already using Emacs, just update the package using the default package manager in your system.

The post GNU Emacs 27.1 Released: A Free/Libre And Open Source Text Editor appeared first on Fossbytes.

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