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Our Year in Review: How we’ve kept Firefox working for you in 2020

di, 15/12/2020 - 14:59

This year began like any other year, with our best intentions and resolutions to carry out. Then by March, the world changed and everyone’s lives — personally and professionally — turned upside down. Despite that, we kept to our schedule to release a new Firefox every month and we were determined to keep Firefox working for you during challenging times.

We shifted our focus to work on features aimed at helping people adjust to the new way of life, and we made Firefox faster so that you could get more things done. It’s all part of fulfilling our promise to build a better internet for people. So, as we eagerly look to the end of 2020, we look back at this unprecedented year and present you with our list of top features that made 2020 a little easier.

Keeping Calm and Carrying on

How do you cope with this new way of life spent online? Here were the Firefox features we added this year, aimed at bringing some zen in your life.

  • Picture-in-Picture: An employee favorite, we rolled out Picture-in-Picture to Mac and Linux, making it available on all platforms, where previously it was only available on Windows. We continued to improve Picture-in-Picture throughout the year — adding features like keyboard controls for fast forward and rewind — so that you could multitask like never before. We, too, were seeking calming videos; eyeing election results; and entertaining the little ones while trying to juggle home and work demands.
  • No more annoying notifications: We all started browsing more as the web became our window into the outside world, so we replaced annoying notification request pop-ups to stop interrupting your browsing, and added a speech bubble in the address bar when you interacted with the site.
  • Pocket article recommendations: We brought our delightful Pocket article recommendations to Firefox users beyond the US, to Austria, Belgium, Germany, India, Ireland, Switzerland, and the United Kingdom. For anyone wanting to take a pause on doom scrolling, simply open up a new tab in Firefox and check out the positivity in the Pocket article recommendations.
  • Ease eye strain with larger screen view: We all have been staring at the screen for longer than we ever thought we should. So, we’ve improved the global level zoom setting so you can set it and forget it. Then, every website can appear larger, should you wish, to ease eye strain. We also made improvements to our high contrast mode which made text more readable for users with low vision.


Get Firefox


Getting you faster to the places you want to visit

We also looked under the hood of Firefox to improve the speed and search experiences so you could get things done no matter what 2020 handed you.

  • Speed: We made Firefox faster than ever with improved performance on both page loads and start up time. For those the technical details:
      • Websites that use flexbox-based layouts load 20% faster than before;
      • Restoring a session is 17% quicker, meaning you can more quickly pick up where you left off;
      • For Windows users, opening new windows got quicker by 10%;
      • Our JavaScript engine got a revamp improving page load performance by up to 15%, page responsiveness by up to 12%, and reduced memory usage by up to 8%, all the while making it more secure.
  • Search made faster: We were searching constantly this year — what is coronavirus; do masks work; and what is the electoral college? The team spent countless hours improving the search experience in Firefox so that you could search smarter, faster — You could type less and find more with the revamped address bar, where our search suggestions got a redesign. An updated shortcut suggests search engines, tabs, and bookmarks, getting you where you want to go right from the address bar.
  • Additional under-the-hood improvements: We made noticeable improvements to Firefox’s printing experience, which included a fillable PDF form. We also improved your shopping experience with updates to our password management and credit card autofill.
Our promise to build a better internet

This has been an unprecedented year for the world, and as you became more connected online, we stayed focused on pushing for more privacy. It’s just one less thing for you to worry about.

  • HTTPS-Only mode: If you visit a website that asks for your email address or payment info, look for that lock in the address bar, which indicates your connection to it is secure. A site that doesn’t have the lock signals its insecure. It could be as simple as an expired Secure Socket Layer (SSL) certificate. No matter, Firefox’s new HTTPS-Only mode will attempt to establish fully secure connections to every website you visit and will also ask for your permission before connecting to a website if it doesn’t support secure connections.
  • Added privacy protections: We kicked off the year by expanding our Enhanced Tracking Protection, preventing known fingerprinters from profiling our users based on their hardware, and introduced a protection against redirect tracking — always on while you are browsing more than ever.
  • Facebook Container updates: Given the circumstances of 2020, it makes sense that people turned to Facebook to stay connected to friends and family when we couldn’t visit in person. Facebook Container — which helps prevent Facebook from tracking you around the web — added improvements that allowed you to create exceptions to how and when it blocks Facebook logins, likes, and comments, giving you more control over your relationship with Facebook.

Even if you didn’t have Firefox to help with some of life’s challenges online over the past year, don’t start 2021 without it. Download the latest version of Firefox and try these privacy-protecting, easy-to-use features for yourself.

The post Our Year in Review: How we’ve kept Firefox working for you in 2020 appeared first on The Mozilla Blog.

Categorieën: Mozilla-nl planet

Mozilla’s Vision for Trustworthy AI

di, 15/12/2020 - 12:25
Mozilla is publishing its white paper, “Creating Trustworthy AI.”

A little over two years ago, Mozilla started an ambitious project: deciding where we should focus our efforts to grow the movement of people committed to building a healthier digital world. We landed on the idea of trustworthy AI.

When Mozilla started in 1998, the growth of the web was defining where computing was going. So Mozilla focused on web standards and building a browser. Today, computing — and the digital society that we all live in — is defined by vast troves of data, sophisticated algorithms and omnipresent sensors and devices. This is the era of AI. Asking questions today such as ‘Does the way this technology works promote human agency?’ or ‘Am I in control of what happens with my data?’ is like asking ‘How do we keep the web open and free?’ 20 years ago.

This current era of computing — and the way it shapes the consumer internet technology that more than 4 billion of us use everyday — has high stakes. AI increasingly powers smartphones, social networks, online stores, cars, home assistants and almost every other type of electronic device. Given the power and pervasiveness of these technologies, the question of whether AI helps and empowers or exploits and excludes will have a huge impact on the direction that our societies head over the coming decades.

It would be very easy for us to head in the wrong direction. As we have rushed to build data collection and automation into nearly everything, we have already seen the potential of AI to reinforce long-standing biases or to point us toward dangerous content. And there’s little transparency or accountability when an AI system spreads misinformation or misidentifies a face. Also, as people, we rarely have agency over what happens with our data or the automated decisions that it drives. If these trends continue, we’re likely to end up in a dystopian AI-driven world that deepens the gap between those with vast power and those without.

On the other hand, a significant number of people are calling attention to these dangerous trends — and saying ‘there is another way to do this!’ Much like the early days of open source, a growing movement of technologists, researchers, policy makers, lawyers and activists are working on ways to bend the future of computing towards agency and empowerment. They are developing software to detect AI bias. They are writing new data protection laws. They are inventing legal tools to put people in control of their own data. They are starting orgs that advocate for ethical and just AI. If these people — and Mozilla counts itself amongst them — are successful, we have the potential to create a world where AI broadly helps rather than harms humanity.

It was inspiring conversations with people like these that led Mozilla to focus the $20M+ that it spends each year on movement building on the topic of trustworthy AI. Over the course of 2020, we’ve been writing a paper titled “Creating Trustworthy AI” to document the challenges and ideas for action that have come up in these conversations. Today, we release the final version of this paper.

This ‘paper’ isn’t a traditional piece of research. It’s more like an action plan, laying out steps that Mozilla and other like-minded people could take to make trustworthy AI a reality. It is possible to make this kind of shift, just as we have been able to make the shift to clean water and safer automobiles in response to risks to people and society. The paper suggests the code we need to write, the projects we need to fund, the issues we need to champion, and the laws we need to pass. It’s a toolkit for technologists, for philanthropists, for activists, for lawmakers.

At the heart of the paper are eight big challenges the world is facing when it comes to the use of AI in the consumer internet technologies we all use everyday. These are things like: bias; privacy; transparency; security; and the centralization of AI power in the hands of a few big tech companies. The paper also outlines four opportunities to meet these challenges. These opportunities centre around the idea that there are developers, investors, policy makers and a broad public that want to make sure AI works differently — and to our benefit. Together, we have a chance to write code, process data, create laws and choose technologies that send us in a good direction.

Like any major Mozilla project, this paper was built using an open source approach. The draft we published in May came from 18 months of conversations, research and experimentation. We invited people to comment on that draft, and they did. People and organizations from around the world weighed in: from digital rights groups in Poland to civil rights activists in the U.S, from machine learning experts in North America to policy makers at the highest levels in Europe, from activists, writers and creators to ivy league professors. We have revised the paper based on this input to make it that much stronger. The feedback helped us hone our definitions of “AI” and “consumer technology.” It pushed us to make racial justice a more prominent lens throughout this work. And it led us to incorporate more geographic, racial, and gender diversity viewpoints in the paper.

In the months and years ahead, this document will serve as a blueprint for Mozilla Foundation’s movement building work, with a focus on research, advocacy and grantmaking. We’re already starting to manifest this work: Mozilla’s advocacy around YouTube recommendations has illuminated how problematic AI curation can be. The Data Futures Lab and European AI Fund that we are developing with partner foundations support projects and initiatives that reimagine how trustworthy AI is designed and built across multiple continents. And Mozilla Fellows and Awardees like Sylvie Delacroix, Deborah Raj, and Neema Iyer are studying how AI intersects with data governance, equality, and systemic bias. Past and present work like this also fed back into the white paper, helping us learn by doing.

We also hope that this work will open up new opportunities for the people who build the technology we use everyday. For so long, building technology that valued people was synonymous with collecting no or little data about them. While privacy remains a core focus of Mozilla and others, we need to find ways to protect and empower users that also include the collection and use of data to give people experiences they want. As the paper outlines, there are more and more developers — including many of our colleagues in the Mozilla Corporation — who are carving new paths that head in this direction.

Thank you for reading — and I look forward to putting this into action together.

The post Mozilla’s Vision for Trustworthy AI appeared first on The Mozilla Blog.

Categorieën: Mozilla-nl planet

Why getting voting right is hard, Part II: Hand-Counted Paper Ballots

ma, 14/12/2020 - 18:42

In Part I we looked at desirable properties for voting system. In this post, I want to look at the details of a specific system: hand-counted paper ballots.

Sample Ballot

Hand-counted paper ballots are probably the simplest voting system in common use (though mostly outside the US). In practice, the process usually looks something like the following:

  1. Election officials pre-print paper ballots and distribute them to polling places. Each paper ballot has a list of contests and the choices for each contest, and a box or some other location where the voter can indicate their choice, as shown above.
  2. Voters arrive at the polling place, identify themselves to election workers, and are issued a ballot. They mark the section of the ballot corresponding to their choice. They cast their ballots by putting them into a ballot box, which can be as simple as a cardboard box with a hole in the top for the ballots.
  3. Once the polls close, the election workers collect all the ballots. If they are to be locally counted, then the process is as below; if they are to be centrally counted, they are transported back to election headquarters for counting.

The counting process varies between jurisdictions, but at a high level the process is simple. The vote counters go through each ballot one at a time and determine which choice it is for. Joseph Lorenzo Hall provides a good description of the procedure for California’s statutory 1% tally here:

In practice, the hand-counting method used by counties in California seems very similar. The typical tally team uses four people consisting of two talliers, one caller and one witness:

  • The caller speaks aloud the choice on the ballot for the race being tallied (e.g., “Yes…Yes…Yes…” or “Lincoln…Lincoln…Lincoln…”).
  • The witness observes each ballot to ensure that the spoken vote corresponded to what was on the ballot and also collates ballots in cross-stacks of ten ballots.
  • Each tallier records the tally by crossing out numbers on a tally sheet to keep track of the vote tally.

Talliers announce the tally at each multiple of ten (“10”, “20”, etc.) so that they can roll-back the tally if the two talliers get out of sync.

Obviously other techniques are possible, but as long as people are able to observe, differences in technique are mostly about efficiency rather than accuracy or transparency. The key requirement here is that any observer can look at the ballots and see that they are being recorded as they are cast. Jurisdictions will usually have some mechanism for challenging the tally of a specific ballot.

Security and Verifiability

The major virtue of hand-counted paper ballots is that they are simple, with security and privacy properties that are easy for voters to understand and reason about, and for observers to verify for themselves

It’s easiest to break the election in two phases:

  • Voting and collecting the ballots
  • Counting the collected ballots

If each of these is done correctly, then we can have high confidence that the election was correctly decided.


The security properties of the voting process mostly come down to ballot handling, namely that:

  • Only authorized voters get ballots and only one ballot. Note that it’s necessary to ensure this because otherwise it’s very hard to prevent multiple voting, where an authorized voter puts in two ballots.
  • Only the ballots of authorized voters make it into the ballot box.
  • All the ballots in the ballot box and only the ballots from the ballot box make it to election headquarters.

The first two of these properties are readily observed by observers — whether independent or partisan. The last property typically relies on technical controls. For instance, in Santa Clara county ballots are taken from the ballot box and put into clear tamper-evident bags for transport to election central, which limits the ability for poll workers to replace the ballots. When put together all three properties provide a high degree of confidence that the right ballots are available to be counted. This isn’t to say that there’s no opportunity for fraud via sleight-of-hand or voter impersonation (more on this later) but it’s largely one-at-a-time fraud, affecting a few ballots at a time, and is hard to perpetrate at scale.


The counting process is even easier to verify: it’s conducted in the open and so observers have their own chance to see each ballot and be confident that it has been counted correctly. Obviously, you need a lot of observers because you need at least one for each counting team, but given that the number of voters far exceeds the number of counting teams, it’s not that impractical for a campaign to come up with enough observers.

Probably the biggest source of problems with hand-counted paper ballots is disputes about the meaning of ambiguous ballots. Ideally voters would mark their ballots according to the instructions, but it’s quite common for voters to make stray marks, mark more than one box, fill in the boxes with dots instead of Xs, or even some more exotic variations, as shown in the examples below. In each case, it needs to be determined how to handle the ballot. It’s common to apply an “Intent of the voter” standard, but this still requires judgement. One extra difficulty here is that at the point where you are interpreting each ballot, you already know what it looks like, so naturally this can lead to a fair amount of partisan bickering about whether to accept each individual ballot, as each side tries to accept ballots that seem like they are for their preferred candidate and disqualify ballots that seem like they are for their opponent.

double marklizard people

A related issue is whether a given ballot is valid. This isn’t so much an issue with ballots cast at a polling place, but for vote-by-mail ballots there can be questions about signatures on the envelopes, the number of envelopes, etc. I’ll get to this later when I cover vote by mail in a later post.

Privacy/Secrecy of the Ballot

The level of privacy provided by paper ballots depends a fair bit on the precise details of how they are used and handled. In typical elections, voters will be given some level of privacy to fill out their ballot, so they don’t have to worry too much about that stage (though presumably in theory someone could set up cameras in the polling place). Aside from that, we primarily need to worry about two classes of attack:

  1. Tracking a given voter’s ballot from checkin to counting.
  2. Determining how a voter voted from the ballot itself.

Ideally — at least from the perspective of privacy — the ballots are all identical and the ballot box is big enough that you get some level of shuffling (how much is an open question), then it’s quite hard to correlate the ballot a voter was given to when it’s counted, though you might be able to narrow it down some by looking at which polling place/box the ballot came in and where it was in the box. In some jurisdictions, ballots have serial numbers, which might make this kind of tracking easier, though only if records of which voter gets which ballot are kept and available. Apparently the UK has this kind of system but tightly controls the records.

It’s generally not possible to tell from a ballot itself which voter it belongs to unless the voter cooperates by making the ballot distinctive in some way. This might happen because the voter is being paid (or threatened) to cast their vote a certain way. While some election jurisdictions prohibit distinguishing marks, as a practical matter it’s not really possible to prevent voters from making such marks if they really want to. This is especially true when the ballots need not be machine readable and so the voter has the ability to fill in the box somewhat distinctively (there are a lot of ways to write an X!). In elections with a lot of contests, as with many places on the US, it is also possible to use what’s called a “pattern voting” attack in which you vote one contest the way you are told and then vote the downballot contests in a way that uniquely identifies you. This sort of attack is very hard to prevent, but actually checking that people voted they way they were told is of course a lot of work. There are also more exotic attacks such as fingerprinting paper stock, but none of these are easy to mount in bulk.


One big drawback of hand-marked ballots is that they are not very accessible, either to people with disabilities or to non-native speakers. For obvious reasons, if you’re blind or have limited dexterity it can be hard to fill in the boxes (this is even harder with optical scan type ballots). Many jurisdictions that use paper ballots will also have some accommodation for people with disabilities. Paper ballots work fine in most languages, but each language must be separately translated and then printed, and then you need to have extras of each ballot type in case more people come than you expect, so at the end of the day the logistics can get quite complicated. By contrast, electronic voting machines (which I’ll get to later) scale much better to multiple languages.


Although hand-counting does a good job of producing accurate and verifiable counts, it does not scale very well1. Estimates of how expensive it is to count ballots vary quite a bit, but a 2010 Pew study of hand recounts in Washington and Minnesota (the 2004 Washington gubernatorial and 2008 Minnesota US Senate races) put the cost of recounting a single contest at between $0.15 and $0.60 per ballot. Of course, as noted above some of the cost here is that of disputing ambiguous ballots. If the races is not particularly competitive then these ballots can be set aside and only need to be carefully adjudicated if they have a chance of changing the result.

Importantly, the cost of hand-counting goes up with the number of ballots times the number of contests on the ballot. In the United States it’s not uncommon to have 20 or more contests per election. For example, here is a sample ballot from the 2020 general election in Santa Clara County, CA. This ballot has the following contests

Type Count President 1 US House of Representatives 1 State Assembly 1 Superior Court Judge 1 County Board of Education 1 County Board of Supervisors 1 Community College District 1 City Mayor 1 City Council (vote for two) 1 State Propositions 12 Local ballot measures 6 Total 32

In an election like this, the cost to count could be several dollars per ballot. Of course, California has an exceptionally large number of contests, but in general hand-counting represents a significant cost.

Aside from the financial impact of hand counting ballots, it just takes a long time. Pew notes that both the Washington and Minnesota recounts took around seven months to resolve, though again this is partly due to the small margin of victory. As another example, California law requires a “1% post-election manual tally” in which 1% of precincts are randomly selected for hand-counting. Even with such a restricted count, the tally can take weeks in a large county such as Los Angeles, suggesting that hand counting all the ballots would be prohibitive in this setting. This isn’t to say that hand counting can never work, obviously, merely that it’s not a good match for the US electoral system, which tends to have a lot more contests than in other countries.

Up Next: Optical Scanning

The bottom line here is that while hand counting works well in many jurisdictions it’s not a great fit for a lot of elections in the United States. So if we can’t count ballots by hand, then what can we do? The good news is that there are ballot counting mechanisms which can provide similar assurance and privacy properties to hand counting but do so much more efficiently, namely optical scan ballots. I’ll be covering that in my next post.

  1. By contrast, the marking process is very scalable: if you have a long line, you can put out more tables, pens, privacy screens, etc. 

The post Why getting voting right is hard, Part II: Hand-Counted Paper Ballots appeared first on The Mozilla Blog.

Categorieën: Mozilla-nl planet