Eamonn O'Brien-Strain

Today marks exactly one hundred years of Irish democracy. Formed from democratically elected members, the first Dáil (parliament) met on January 21, 1919, in Dublin. It was a promising start, with a woman cabinet member and a Socialist-leaning “Democratic Programme”. But that act of defiance against the British Empire sparked off a war of independence, then fifty years as a conservative confessional state, then thirty years of low-grade guerrilla war to the north.

But the people remained solidly committed to democracy despite the poverty and political strife, and finally, in the last twenty years, Ireland has emerged as a wealthy liberal European nation.

Throughout one hundred years, one thing has been constant in Ireland: democracy.

Ireland took the democratic traditions of its ex-colonial power and made something even better. From the beginning, it had instant-runoff, multi-member electoral districts which resulted in proportional representation in the Dáil and a necessity to compromise and form coalitions. Regular referendums are the norm, and minority populist sentiments from the left and right are represented in the Dáil, giving a safety valve for political frustration, a safety valve that doesn't exist in the antiquated first-past-the-post electoral systems of Britain and the United States.

As Britain and the United States struggle with political breakdown, they might do better than look to Ireland as a model of democracy.

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Consider a typical (sadly) tech workplace where there are four men for every woman.$^1$ Assume that women and men both exhibit bias to members of other genders at the same rate. Then women will experience gender bias at a rate of sixteen times more than men.

Yes, a simple mathematical model shows minority experience of bias relative to the majority experience goes up with the square of how underrepresented they are.

To take another example from the tech world, underrepresented minorities (Black, Latinx, Native American) are outnumbered typically at a ratio of twenty to one,$^1$ Again assuming racial bias happens both ways at the same rate, the model shows that the underrepresented minorities will experience racially biased behavior four hundred times more often than members of other groups.

This model could be part of the explanation for why so many members of the majority do not see bias in the workplace$^2$. A white man might not realize that some particular type of bias that he only experiences once a year might be experienced much more frequently by minorities: perhaps more than once a month by his women colleagues and more than once a day by his colleagues from underrepresented minorities.

The model applies to all kinds of biased acts ranging from small acts of exclusion and unconscious bias to full-on racial prejudice and sexual harassment. At every level of severity, it predicts marked increases in the expected frequency of the experienced bias with lower minority representation.

Of course, this model grossly simplifies the real world. Gender and race are not binaries. There are intersectionalities that make things more complex. Biased actions are not uniformly distributed and directed. One implication is that in practice, the ratio of experienced bias might grow a bit slower than the square, but I still think it grows faster than linear.

This squaring relationship is known as the Petrie Multiplier after its discoverer Karen Petrie. It is explained in detail in an article by Ian Gent$^3$.

(Note, I hesitated to publish this article as it reduces painful lived experience to cold impersonal mathematics, and I believe our first reactions to issues of representation and bias in tech should be outrage and a commitment to fix the system. But even as these issues divide us, there is one thing that unites us: we are all engineers, and at least in mathematics we can find a common understanding.)

Appendix

(You can stop reading now if you don't care about the mathematics.)

Assume a population of two disjoint groups of people (majorities and minorities) where there are $k$ majorities for every $1$ minority. Let the total population be $n$, so there are $\frac{n}{k+1}$ minorities and $\frac{n k}{k+1}$ majorities.

Assume that people in each group act in a biased way to individual members of the other group at the same rate $r$ per time period.

Thus in total, majorities perpetrate $\frac{r n k}{k+1}$ acts of bias directed at $\frac{n}{k+l}$ minorities, so each minority is a victim of $r k$ acts of bias.

Conversely, in total, minorities perpetrate $\frac{r n}{k+1}$ acts of bias directed at $\frac{n k}{k+l}$ majority members, so each majority is a victim of $\frac{r}{k}$ acts of bias.

Comparing the rate that minorities experience bias ($r k$) and the rate that majorities experience bias ($\frac{r}{k}$) we see that minorities experience bias at a rate of $k^2$ higher than majorities.

References

$^1$Google diversity annual report

$^2$Why Male Tech Workers Don't See the Gender Gap

$^3$The Petrie Multiplier: Why an Attack on Sexism in Tech is NOT an Attack on Men

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[See old version of this post to see what is being described.]

As an experiment, I'm seeing if I can use a navigational metaphor in which the articles in this blog are arranged left to right. To reinforce the metaphor I added some CSS animation that slides the page sideways when you click between articles. I also changed the index page to list the articles in the blog in a horizontal carousel. It's still pretty crude visually.

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[See old version of this post to see what is being described.]

So, I started off trying to have this blog using simple plain hand-written HTML. However, I soon start getting annoyed how much repeated boilerplate I had to write, such as in the <head and in linking together the articles from the main index page. So in an effort to make things more DRY I considered what simple templating systems I could used.

A long time ago, back before the web existed I used the M4 macro language. It has the advantage of being installed on my home Linux machine by default, so no extra dependencies are required. Let's see if we can use it as an HTML templating language.

You can see an example of a template using M4 in the source code of this blog. Note that there is just one simple line of boilerplate at the top and some closing parenthesis at the bottom, but otherwise the template is straightforward HTML.

    ARTI{}CLE( 2, {

    ...HTML goes here...

    })

The templates uses two M4 files:

1. lib.html which contains the HTML header and footers for all the pages.

2. data.m4 which contains the metadata for the pages, including the information needed to create the home page and to provide “previous” and “next” links on the article pages.

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One of the purposes of this blog is to experiment with simple ways put up a blog on the web without depending on any blogging platform. For this I wanted a free way to deploy static web pages on my own domain name. For this I chose Firebase Hosting, partly because I am very familiar with it, having worked on the Firebase team and personally knowing many of the Hosting development team, but also because it is actually the best solution I know of for what I want, and it is free for sites that have the traffic of typical personal sites.

People who are comfortable using the command line might be interested in following along the steps I took.

1. Go to http://firebase.com, login, and create a project.

2. Install Node. If you don’t already have it installed already, I suggest first installing nvm then doing:

   nvm install stable
   nvm use stable</pre>
   

3. Follow the instructions in the Hosting quickstart.

4. Replace index.html with the HTML you want as your home page.

5. Do firebase deploy

6. I’d recommend storing everything in Git, and you might as well make it a public repo, as the web site is public anyway. (Mine is on GitHub)

7. You also might want to register a domain name, and use Firebase Hosting to use that domain name (complete with a free SSL certificate so you the https: security for free.). I did this for eamonn.org

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I'm moving to the engineering team responsible for the main Google Search user interface!

Sad to be leaving my amazing colleagues in Cloud and Firebase, but so excited to be learning new tech and working on a product that has transformed the world and touches billions of people.

— Eamonn O'Brien-Strain 👨‍💻🔍🌁🇮🇪🇪🇺🇺🇲🇺🇳⚛️ (@eob) August 19, 2018

On Twitter yesterday I made a big announcement that I’m moving to a new team within Google.

For most of my five years at the company I have been working on products for external developers, first for App Engine where I lead the memcache team, then for Firebase and Cloud where I worked on privacy, security rules, and serverless events.

But now I am about to move to the team responsible for the main Google Search user interface. This is a huge change. I’m moving from infrastructure engineering to front-end engineering. And instead of building products for millions of developers, I’m building products for billions of end-users.

And this seems like a good time to make yet another attempt to start writing a regular blog. I’m going to start by eschewing the complexities of modern web development, using simple, plain handwritten HTML files. Now that I’m a front-end developer again, I can practice my skills here.

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“History does not repeat itself, but it rhymes” Around the turn of the 19th Century: the French Revolution and the American Revolution, together with the Industrial Revolutions killed off the ancien régimes with their aristocrats and divine right of kings.

The land-owning aristocrats lost their power and sometimes their heads.

Just after the turn of the 20th Century: World War I, together with the Bolshevik Revolution and the Scientific Revolution killed off a century of stable interest rates that had allowed the wealthy to live a life of leisure.

The capital-owning wealthy had most of their wealth wiped out.

Just after the turn of the 21st Century: resurgent religious fundamentalism and right-wing nationalism, together with the Internet revolution may be about to kill off a world in which multinational corporations and a technocratic elite thrived among increasing inequality.

What will happen to the technocratic elite?

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What is wrong with HP that would spur its announced fission into two daughter companies? My view from the technology trenches is different from what I am reading in the business press.

HP is not really a technology company any more. It is a logistics and marketing company. Much of its engineering is outsourced. I am not surprised that it is splitting itself according to its go-to-market and channel criteria, not technology criteria.

HP does not know how to innovate. Instead of letting a thousand flowers bloom and leaving itself open to positive black swans, it doubles down on big bets. When I was at HP Labs, we were encouraged to only propose projects that promised a billion dollars or more in revenue. There was no room for the small speculative project.

Software is eating the world, but HP cannot write software. It is even confused at the word “software”, using it as the name of a division that is just 10% of the company, even though software is actually crucial in every one of is divisions. HP’s software development is incredibly fragmented, with no returns to scale. Each of its many software development groups scattered throughout the company have their own idiosyncratic software engineering practices, some good some bad. The code of each development group is walled off from other groups, so code sharing across the company is rare. Managers regard access to their organization’s code as a weapon to use in internal battles and negotiations.

HP cannot attract and keep good software engineers. For example, I personally know 24 other engineers who, like me, have made the migration from HP Labs to Google over the years, and there are probably many more. In contrast I don’t know a single person who has moved in the reverse direction from Google to HP. Some of this is no doubt driven by superior remuneration and perks, but I think what really clinches the deal is that in a real technology company what the engineers do really matters. For that they are willing to tolerate the packed elbow-to-elbow work areas and the straitjacket of a company-wide unified software development process.

Maybe HP does need to split, so that at least one part of it has some chance of turning itself back into a real tech company. I wish my friends still there all the best as they navigate the transition.

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The political map of the world is a familiar image, and we have become used to the shapes and relative sizes of the countries. However the map gives undue weight to some countries with large uninhabited areas, even when you choose a map projection that does not distort areas too much.

So a few weeks ago I tried playing with a world map to give a clearer idea of where people actually live. I chopped out the parts of the countries that have very low population density, less than a threshold of about 5 people per square km (13 per square mile), To an extent this gives makes countries of equal population have more similar areas than a standard map, while stopping countries being distorted and sliding about as they do in a cartogram.

And looking at the countries through this lens is an interesting exercise. Let’s take a tour …

Australia

Australia is one of the most noticeably diminished countries. You can see that it has a relatively small population for its size and most of those people live along the East and and South-East. There is a little outpost of Perth far to the West, and if you look carefully you will see the tiny dot of Darwin in the North.

India

India has more than 50 times the population of Australia in less than half the area. Not surprisingly it is packed. It seems nowhere is uninhabited except maybe a little patch in the North in India-controlled Kashmir along the Himalayas.

Kazakhstan

In this view, Kazakhstan is also much diminished and looks like Australia, with large uninhabited areas in the center and with most people living around the boundaries of the country, either in the Steppes along the Northern border with Russia or along the South-Eastern border with the other ‘stans and China.

Ireland

The Republic of Ireland is almost all above the density threshold with just a little erosion along the West coast in Kerry, Galway, and Donegal.

United Kingdom

England and Wales seem mostly intact, but Scotland has lost much of its Highlands.

Canada

Canada is another country that is greatly diminished in this view. Despite its vast Northern expanses almost all its populations are huddled in the South along the US border, a lot of them down near Toronto and Montreal.

United States

The USA has a very noticeable vertical line down the center of the Great Plains splitting drier (emptier) areas like the Dakotas and West Texas from wetter (fuller) areas like Iowa and Eastern Texas. Large parts of the interior West are blank. Alaska has almost disappeared, the largest remaining area being a small blob around Anchorage where most Alaskans live. Other than Maine, the Eastern states are largely intact except for some patches in the Appalachians and some large parks.

Mexico

Mexico is pretty sparsely populated towards the North along the US border.

South Africa

South Africa has large sparsely inhabited areas, especially in the West, so that Cape Town in the South West is quite isolated.

Russia

Russia is spread out horizontally along the Steppes getting less and less populated the farther you go West. There are just a few tiny outposts along the Pacific. There is also a southward extension into the Caucasus region. Like Canada, its vast Northern expanses are largely unpopulated,

Egypt

Egypt, like many other North African countries has much of its population concentrated along the Mediterranean coastal plain. However Egypt also has a dense population concentrated along the Nile river, and also some people living along the Red Sea.

China

Although China has a huge population, you can see from this map that almost everyone lives in the Eastern half. The Tibetan areas are very lightly populated, and there is a Western outpost in the Turkic areas bordering the ‘stans.

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Today the New York Times marked the death of Seamus Heaney with an above-the-fold front page photo, and a long article illustrated with quotes from his work. As I read his beautifully crafted and emotionally powerful lines I mourned our loss, while also feeling some pride that the world was giving such recognition to someone who is my compatriot.

Including Heaney, there are four Irish Nobel Laureates in Literature, which is not a bad record for a country with the population of Louisiana. In science we have not done so well though. The Nobel committee awarded only one Nobel science prize to an Irish citizen, to Ernest Walton for splitting the atom in the 1930s. When I was growing up in Ireland I never heard about Walton, but like many Irish people I knew our literature laureates well: Yeats, Shaw, Becket, and Heaney.

The Irish education system does a great job of exposing children to literature. We learn about the deep tradition of poetry in the Irish language, with its special rhyming patterns, its storytelling, and its unique imagery. Our English literature classes teach us the great Irish writers alongside the best from the rest of the English-speaking world. Even in history the recounting of our cycles of repression, rebellion, and defeat are interspersed with uplifting stories of our bards, our poets, and our writers, and the hedge-school masters who defied the Sasanaigh to teach Latin and Greek in secret.

Perhaps the association of the humanities with Irishness was most strongly forged in the early part of the twentieth century. Around that time literature flowered in the Irish Renaissance. Meanwhile political nationalism spread and strengthened, and waged an ultimately successful rebellion that resulted in an independent Ireland. Strength in literature and strength in politics seemed to go together.

Now almost a century has passed. Look at the graph above that shows a measure of how high tech the workforce of each country in Europe is, and note that the third bar from the left is Ireland. In a generation the country has gone straight from a sleepy economy dominated by agriculture to a post-industrial economy dominated by science and technology. Of course, there has been a setback recently where some shortsighted use of financial technology combined with poor economic policy lead to an Irish banking bubble that burst disastrously when the worldwide crisis spewed its contagion across the globe. Still, I think Ireland will come back strongly in the long term, because graphs like this show that its workforce is well matched to the needs of the twenty-first century.

So despite being steeped in a national mythos so tied to writing and storytelling, the reality of Ireland is closer to that of Silicon Valley. Perhaps with this new reality, more Irish people will come to know about Walton, as well as all the Irish scientists, such as Bell, Boyle, Boole, Stokes, Beaufort, Fitzgerald, Hamilton, and Lord Kelvin, whose names live on in science. And hopefully we will add to that list, and maybe even a few more Irish scientists will make that trip to Stockholm.

So, the nation of Ireland as a whole has navigated the two cultures, of the humanities and the sciences. In my own small way I was part of that, for I distinctly remember in my mid teens confronting the decision of what academic direction I should take. I loved writing and remember the pleasure I got from turning ideas into sentences that sounded good. But I also loved Science and remember doing calculus just for fun to work out physics problems.

In the end the larger national level priorities were the decisive factor in how I chose. The government was investing in technology education, and the papers were full of the benefits of getting an engineering degree. Coming out of a working class background on the Northside of Dublin, I did not feel I had the luxury of making anything but the most pragmatic choice, so I choose electronic engineering. It had neither the romance of writing nor the excitement of scientific research, but I would likely get a job when I graduated.

And I do not regret the choice. It has given me a secure and comfortable career, a large part of it working in research labs just like I fantasized as a teenager. And I discovered pretty quickly that I really love programming, that I am one of those lucky people for whom work is never a chore, but something I look forward to every day.

Still, I sometimes wonder about the path not taken. Perhaps I could have been crafting beautiful prose not crafting elegant code, plotting stories not writing specs, observing people who could become characters in my novels not observing them to find usability bugs in my software.

And living here in San Francisco, I see the dance of the two cultures playing out here too. This city, sitting up at the end of a peninsula, has a long tradition steeped in the arts and humanities, while down at the base of the peninsula is Silicon Valley, the ultimate in technology. However in the last decade the valley has extended a pseudopod of yang into the yin of the city, and fertilized a booming high tech industry on the combined talents of designers and coders, of people who understand people and people who understand algorithms.

And this weekend half the city seems to be away in Nevada celebrating that amazing synthesis of art and technology that is Burning Man.

It feels good that the two cultures are coming together in the two places I love, the place where I live and the place where I am from.

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