Elizabeth Dubois has a great episode of Wonks and War Rooms where she interviews Etienne Rainville of The Boys in Short Pants podcast, former Hill staffer, and government relations expert. They unpack how government staffers collect information, process it, and identify experts.
Broadly, the episode focuses on how the absence of significant policy expertise in government and political parties means that social media—and Twitter in particular—can play an outsized role in influencing government, and why that’s the case.
While the discussion isn’t necessarily revelatory to anyone who has dealt with some elements of government of Canada, and especially MPs and their younger staffers, it’s a good and tight conversation that could be useful for students of Canadian politics, and also helpfully distinguishes of of the differences between Canadian and American political cultures. I found the forthrightness of the conversation and the honesty of how government operates was particularly useful in clarifying why Twitter is, indeed, a place for experts in Canada to spend time if they want to be policy relevant.
Jason Healey and Robert Jervis have a thought provoking piece over at the Modern War Institute at West Point. The crux of the argument is that, as a result of overclassification, it’s challenging if not impossible for policymakers or members of the public (to say nothing of individual analysts in the intelligence community or legislators) to truly understand the nature of contemporary cyberconflict. While there’s a great deal written about how Western organizations have been targeted by foreign operators, and how Western governments have been detrimentally affected by foreign operations, there is considerably less written about the effects of Western governments’ own operations towards foreign states because those operations are classified.
To put it another way, there’s no real way of understanding the cause and effect of operations, insofar as it’s not apparent why foreign operators are behaving as they are in what may be reaction to Western cyber operations or perceptions of Western cyber operations. The kinds of communiques provided by American intelligence officials, while somewhat helpful, also tend to obscure as much as they reveal (on good days). Healey and Jervis write:
General Nakasone and others are on solid ground when highlighting the many activities the United States does not conduct, like “stealing intellectual property” for commercial profit or disrupting the Olympic opening ceremonies. There is no moral equivalent between the most aggressive US cyber operations like Stuxnet and shutting down civilian electrical power in wintertime Ukraine or hacking a French television station and trying to pin the blame on Islamic State terrorists. But it clouds any case that the United States is the victim here to include such valid complaints alongside actions the United States does engage in, like geopolitical espionage. The concern of course is a growing positive feedback loop, with each side pursuing a more aggressive posture to impose costs after each fresh new insult by others, a posture that tempts adversaries to respond with their own, even more aggressive posture.
Making things worse, the researchers and academics who are ostensibly charged with better understanding and unpacking what Western intelligence agencies are up to sometimes decline to fulfill their mandate. The reasons are not surprising: engaging in such revelations threaten possible career prospects, endanger the very publication of the research in question, or risk cutting off access to interview subjects in the future. Healey and Jervis focus on the bizarre logics of working and researching the intelligence community in the United States, saying (with emphasis added):
Think-tank staff and academic researchers in the United States often shy away from such material (with exceptions like Ben Buchanan) so as not to hamper their chances of a future security clearance. Even as senior researchers, we were careful not to directly quote NSA’s classified assessment of Iran, but rather paraphrased a derivative article.
A student, working in the Department of Defense, was not so lucky, telling us that to get through the department’s pre-publication review, their thesis would skip US offensive operations and instead focus on defense.
Such examples highlight the distorting effects of censorship or overclassification: authors are incentivized to avoid what patrons want ignored and emphasize what patrons want highlighted or what already exists in the public domain. In paper after paper over the decades, new historical truths are cumulatively established in line with patrons’ preferences because they control the flow and release of information.
What are the implications as written by Healey and Jervis? In intelligence communities the size of the United States’, information gets lost or not passed to whomever it ideally should be presented to. Overclassification also means that policy makers and legislators who aren’t deeply ‘in the know’ will likely engage in decisions based on half-founded facts, at best. In countries such as Canada, where parliamentary committees cannot access classified information, they will almost certainly be confined to working off of rumour, academic reports, government reports that are unclassified, media accounts that divulge secrets or gossip, and the words spoken by the heads of security and intelligence agencies. None of this is ideal for controlling these powerful organizations, and the selective presentation of what Western agencies are up to actually risks compounding broader social ills.
Legislative Ignorance and Law
One of the results of overclassification is that legislators, in particular, become ill-suited to actually understanding national security legislation that is presented before them. It means that members of the intelligence and national security communities can call for powers and members of parliament are largely prevented from asking particularly insightful questions, or truly appreciate the implications of the powers that are being asked for.
Indeed, in the Canadian context it’s not uncommon for parliamentarians to have debated a national security bill in committee for months and, when asked later about elements of the bill, they admit that they never really understood it in the first place. The same is true for Ministers who have, subsequently, signed off on broad classes of operations that have been authorized by said legislation.
Part of that lack of understanding is the absence of examples of how powers have been used in the past, and how they might be used in the future; when engaging with this material entirely in the abstract, it can be tough to grasp the likely or possible implications of any legislation or authorization that is at hand. This is doubly true in situations where new legislation or Ministerial authorization will permit secretive behaviour, often using secretive technologies, to accomplish equally secretive objectives.
Beyond potentially bad legislative debates leading to poorly understood legislation being passed into law and Ministers consenting to operations they don’t understand, what else may follow from overclassification?
Nationalism, Miscalculated Responses, and Racism
To begin with, it creates a situation where ‘we’ in the West are being attacked by ‘them’ in Russia, Iran, China, North Korea, or other distant lands. I think this is problematic because it casts Western nations, and especially those in the Five Eyes, as innocent victims in the broader world of cyber conflict. Of course, individuals with expertise in this space will scoff at the idea–we all know that ‘our side’ is up to tricks and operations as well!–but for the general public or legislators, that doesn’t get communicated using similarly robust or illustrative examples. The result is that the operations of competitor nations can be cast as acts of ‘cyberwar’ without any appreciation that those actions may, in fact, be commensurate with the operations that Five Eyes nations have themselves launched. In creating an Us versus Them, and casting the Five Eyes and West more broadly as victims, a kind of nationalism can be incited where ‘They’ are threats whereas ‘We’ are innocents. In a highly complex and integrated world, these kinds of sharp and inaccurate concepts can fuel hate and socially divisive attitudes, activities, and policies.
At the same time, nations may perceive themselves to be targeted by Five Eyes nations, and deduce effects to Five Eyes operations even when that isn’t the case. When a set of perimeter logs show something strange, or when computers are affected by ransomware or wiperware, or another kind of security event takes place, these less resourced nations may simply assume that they’re being targeted by a Five Eyes operation. The result is that foreign government may both drum up nationalist concerns about ‘the West’ or ‘the Five Eyes’ while simultaneously queuing up their own operations to respond to what may, in fact, have been an activity that was totally divorced from the Five Eyes.
I also worry that the overclassification problem can lead to statements in Western media that demonizes broad swathes of the world as dangerous or bad, or threatening for reasons that are entirely unapparent because Western activities are suppressed from public commentary. Such statements arise with regular frequency, where China is attributed to this or to that, or when Russia or Middle Eastern countries are blamed for the most recent ill on the Internet.
The effect of such statements can be to incite differential degrees of racism. When mainstream newspapers, as an example, constantly beat the drum that the Chinese government (and, by extension, Chinese people) are threats to the stability and development of national economies or world stability, over time this has the effect of teaching people that China’s government and citizens alike are dangerous. Moreover, without information about Western activities, the operations conducted by foreign agencies can be read out of context with the effect that people of certain ethnicities are regarded as inherently suspicious or sneaky as compared to those (principally white) persons who occupy the West. While I would never claim that the overclassification of Western intelligence operations are the root cause of racism in societies I do believe that overclassification can fuel misinformation about the scope of geopolitics and Western intelligence gathering operations, with the consequence of facilitating certain subsequent racist attitudes.
A colleague of mine has, in the past, given presentations and taught small courses in some of Canada’s intelligence community. This colleague lacks any access to classified materials and his classes focus on how much high quality information is publicly available when you know how and where to look for it, and how to analyze it. Students are apparently regularly shocked: they have access to the classified materials, but their understandings of the given issues are routinely more myopic and less robust. However, because they have access to classified material they tend to focus as much, or more, on it because the secretive nature of the material makes it ‘special’.
This is not a unique issue and, in fact, has been raised in the academic literature. When someone has access to special or secret knowledge they are often inclined to focus in on that material, on the assumption that it will provide insights in excess of what are available in open source. Sometimes that’s true, but oftentimes less so. And this ‘less so’ becomes especially problematic when operating in an era where governments tend to classify a great deal of material simply because the default is to assume that anything could potentially be revelatory to an agency’s operations. In this kind of era, overvaluing classified materials can lead to less insightful understandings of the issues of the day while simultaneously not appreciating that much of what is classified, and thus cast as ‘special’, really doesn’t provide much of an edge when engaging in analysis.
The solution is not to declassify all materials but, instead, to adopt far more aggressive declassification processes. This could, as just an example, entail tying declassification in some way to organizations’ budgets, such that if they fail to declassify materials their budgets are forced to be realigned in subsequent quarters or years until they make up from the prior year(s)’ shortfalls. Extending the powers of Information Commissioners, which are tasked with forcing government institutions to publish documents when they are requested by members of the public or parliamentarians (preferably subject to a more limited set of exemptions than exist today) might help. And having review agencies which can unpack higher-level workings of intelligence community organizations can also help.
Ultimately, we need to appreciate that national security and intelligence organizations do not exist in a bubble, but that their mandates mean that the externalized problems linked with overclassification are typically not seen as issues that these organizations, themselves, need to solve. Nor, in many cases, will they want to solve them: it can be very handy to keep legislators in the dark and then ask for more powers, all while raising the spectre of the Other and concealing the organizations’ own activities.
We do need security and intelligence organizations, but as they stand today their tendency towards overclassification runs the risk of compounding a range of deleterious conditions. At least one way of ameliorating those conditions almost certainly includes reducing the amount of material that these agencies currently classify as secret and thus kept from public eye. On this point, I firmly agree with Healey and Jervis.
But testing algorithms for fairness is still largely optional at Facebook. None of the teams that work directly on Facebook’s news feed, ad service, or other products are required to do it. Pay incentives are still tied to engagement and growth metrics. And while there are guidelines about which fairness definition to use in any given situation, they aren’t enforced.
The Fairness Flow documentation, which the Responsible AI team wrote later, includes a case study on how to use the tool in such a situation. When deciding whether a misinformation model is fair with respect to political ideology, the team wrote, “fairness” does not mean the model should affect conservative and liberal users equally. If conservatives are posting a greater fraction of misinformation, as judged by public consensus, then the model should flag a greater fraction of conservative content. If liberals are posting more misinformation, it should flag their content more often too.
But members of Kaplan’s team followed exactly the opposite approach: they took “fairness” to mean that these models should not affect conservatives more than liberals. When a model did so, they would stop its deployment and demand a change. Once, they blocked a medical-misinformation detector that had noticeably reduced the reach of anti-vaccine campaigns, the former researcher told me. They told the researchers that the model could not be deployed until the team fixed this discrepancy. But that effectively made the model meaningless. “There’s no point, then,” the researcher says. A model modified in that way “would have literally no impact on the actual problem” of misinformation.
[Kaplan’s] claims about political bias also weakened a proposal to edit the ranking models for the news feed that Facebook’s data scientists believed would strengthen the platform against the manipulation tactics Russia had used during the 2016 US election.
The whole thing with ethics is that they have to be integrated such that they underlie everything that an organization does; they cannot function as public relations add ons. Sadly at Facebook the only ethic is growth at all costs, the social implications be damned.
When someone or some organization is responsible for causing significant civil unrest, deaths, or genocide then we expect that those who are even partly responsible to be called to account, not just in the public domain but in courts of law and international justice. And when those someones happen to be leading executives for one of the biggest companies in the world the solution isn’t to berate them in Congressional hearings and hear their weak apologies, but to take real action against them and their companies.
When science research interferes with politics, economics, or culture, science is most often the loser. Thus, governments and businesses control healthcare for their personal gains or concepts and disregard or avoid factual knowledge and events.
Michael B. A. Oldstone, Viruses, Plagues, & History: Past, Present, and Future
Even before the pandemic, many researchers in academia were struggling with poor mental health. Desiree Dickerson, an academic mental-health consultant in Valencia, Spain, says that burnout is a problem inherent in the academic system: because of how narrowly it defines excellence, and how it categorizes and rewards success. “We need to reward and value the right things,” she says.
Yet evidence of empathetic leadership at the institutional level is in short supply, says Richard Watermeyer, a higher-education researcher at the University of Bristol, UK, who has been conducting surveys to monitor impacts of the pandemic on academia. Performative advice from employers to look after oneself or to leave one day a week free of meetings to catch up on work is pretty superficial, he says. Such counsel does not reduce work allocation, he points out.
Academia has a rampant problem in how it is professionally configured. To get even a short term contract, now, requires a CV that would have been worthy of tenure twenty or thirty years ago. Which means that, when someone is hired as an assistant professor (with a 3-6 year probation period) they are already usually more qualified than their peers of the past and have to be prolific in the work that they contribute to and output, and do so with minimal or no complaints so as to avoid any problems in their transition from assistant to associate professor (i.e., full-time and sometimes protected employee).
Once someone has gone through the gauntlet, they come to expect that others should go through it as well: if the current generation can cut it, then surely the next generation of hires should be able to as well if they’re as ‘good’ as the current generation. Which means that those who were forced into an unsustainable work environment that routinely eats into personal time, vacation time (i.e., time when you use vacation days to catch up on other work that otherwise is hard to get done), child rearing time, and so forth, expect that those following them do the same.
Add into this the fact that most academic units are semi-self governing, and those in governorship positions (e.g., department chairs, deans) tend to lack any actual qualifications in managing a largely autonomous workforce and cannot rebalance work loads in a systemically positive way so as to create more sustainable working environments. As a result of a lack of formal management skills, these same folks tend to be unable to identify the issues that might come up in a workforce/network of colleagues, and they are also not resourced to know how to actually treat the given problem. And all of this presumes they are motivated to find and resolve problems in the first place. This very premise is often found faulty, given that those who are governing are routinely most concerned with the smooth running of their units and, of course, may keep in mind any junior colleagues who happen to cause ‘problems’ by expecting assistance or consideration given the systemic overwork that is the normal work-life imbalance.
What’s required is a full-scale revolt in the very structure of university departments if work-life balance is to be truly valued, and if academics are to be able to satisfy their teaching, service, and research requirements in the designated number of working hours. While the job is often perceived as very generous–and it is, in a whole lot of ways!–because you (ideally) have parts of it that you love, expecting people to regularly have 50-75 hour work weeks, little real downtime, little time with family and friends, and being placed on a constant treadmill of outputs is a recipe for creating jaded, cynical, and burned out professionals. Sadly, that’s how an awful lot of contemporary departments are configured.
The Cambridge Security Research Computer Laboratory has a really lovely blog series called ‘Three Paper Tuesday’ that I wish other organizations would adopt.
They have a guest (and usually a graduate student) provide concise summaries of three papers and then have a short 2-3 paragraph ‘Lessons Learned’ section to conclude the post. Not only do readers get annotated bibliographies for each entry but, perhaps more importantly, the lessons learned means that non-experts can appreciate the literature in a broader or more general context. The post aboutsubverting neural networks, as an example, concludes with:
On the balance of the findings from these papers, adversarial reprogramming can be characterised as a relatively simple and cost-effective method for attackers seeking to subvert machine learning models across multiple domains. The potential for adversarial programs to successfully avoid detection and be deployed in black-box settings further highlights the risk implications for stakeholders.
Elsayed et al. identify theft of computational resources and violation of the ethical principles of service providers as future challenges presented by adversarial reprogramming, using the hypothetical example of repurposing a virtual assistant as spyware or a spambot. Identified directions for future research include establishing the formal properties and limitations of adversarial reprogramming, and studying potential methods to defend against it.
If more labs and research groups did this, I’d imagine it would help to spread awareness of some research and its actual utility or importance in advancing the state of knowledge to the benefit of other academics. It would also have the benefit of showcasing to policymakers what key issues actually are and where research lines are trending, and thus empower them (and, perhaps, even journalists) to better take up the issues that they happen to be focused on. That would certainly be a win for everybody: it’d be easier to identify articles of interest for researchers, relevance of research for practitioners, and showcase the knowledge and communication skills of graduate students.
This long form photoessay showcases the absences that have been wrought by the pandemic in my city of Toronto, Ontario. The essay provides a meditation on a world of social isolation and distancing, and how the spaces that have historically united and bound Toronto’s residents have been left empty or made safe in response to being associated with risk and disease. Throughout, people are represented as separate from one another in their efforts to socially and physically distance, with individuals, pairs, or very small groups standing in juxtaposition to the much larger built world they inhabit.
All of the images were created using a combination of a Fuji X100f, Sony rx100ii, iPhone 11 Pro, and iPhone 12 Pro. Images were edited to taste using Apple Photos (for cropping) and Darkroom; two images had some healing applied using Snapseed.
For the past year, the Toronto Star has repeatedlyrunarticles that take mobility data from mobile device advertisers, to then assess the extent to which Torontonians are moving too much. Reporting has routinely shown how people are moving more or less frequently, with articles often suggesting that people are moving too much when they’re supposed to be staying put.
The problem? The ways in which ‘too much’ is assessed runs contrary to public health advice and lacks sufficient nuance to inform the public. In the most recent reporting, we find that:
Between Jan. 18 and Feb. 28, average mobility across Ontario increased from 58 per cent to 65 per cent, according to the marketing firm Environics Analytics. Environics defines mobility as a percentage of residents 15 or older who travelled 500 metres or more beyond their home postal code.
To be clear: in Ontario the provincial and local public health leaders have strongly stated that people should get outside and exercise. That can involve walking or other outdoor activities. Those activities are not supposed to be restricted to 500 metres from your home, which was advice that was largely provided in more restrictive lockdowns in European countries. And we know that mobility data is often higher in areas with higher percentages of BIPOC residents because they tend to have lower-paying jobs and must travel further to reach their places of employment.
As has become the norm, the fact that people have moved around more frequently as (admittedly ineffective) restrictions have been raised, and that people are ‘region hopping’ by going from more restricted zones to less restricted ones, is being tightly associated with personal or individual failures. From a quoted expert, we find that:
“It shows that once things start to open, people just seem to do whatever, and that’s a recipe for disaster.”
I would suggest that what we are seeing is a pent up, pretty normal, human response: the provincial government has behaved erratically and you have some people racing around to get stuff done before returning to another (ineffective) set of restrictions, and a related set of people who believe that if the government is letting them move around then things must be comparatively safer. To put it another way, in the former case you have people behaving rationally (if, in some eyes, selfishly) whereas in the latter you have a failure by government to solve a collective action problem by downloading responsibility to individuals. In both cases you are seeing an uptick in behaviour which is suggestive that they believe it’s safer to do things, now, than weren’t before when the government assumed some responsibility and signalled that moving was less safe and actively discouraged it by keeping businesses and other ‘fun’ things shut down.
Throughout the pandemic response in Ontario, what has been evident is that the provincial government simply cannot develop and implement effective policies to mitigate the spread of the pandemic. The result of muddling through things has been that the public, and especially small business, has suffered extraordinarily whilst the gains have been meagre. The lack of paid sick leave, as an example, has seriously stymied the ability of lower-income workers to actually keep themselves apart from others while they wait for diagnoses and, if positive, recover from their infections.
To be fair, the Toronto Star and other outlets have covered paid sick leave issues, along with lots of other failures by the provincial government in its handling of the pandemic. And there is certainly some obligation on individuals to best adhere to public health advice. But we’ve long known these are collective action problems: there is a need to move beyond downloading responsibility to individuals and for governments to behave effectively, coherently, and accountably throughout major crises. The provincial government has failed, and continues to fail, on every one of these measures to the effect that individuals are responding to the past, present, and expected future actions of the government: more unpredictability and more restrictions on their daily lives as a result of government ineptitude.
Whereas the journalists could have cast what Ontarians are doing as a semi-natural response to the aforementioned government failings, instead those individuals are being castigated. We shouldn’t be blaming the victims of the pandemic, but I guess that’s what happens when assessing mobility data.
Over the course of the pandemic I’ve finally built up a good workflow for annotating papers and filing them in a reference manager. Unfortunately, the reference manager that I’ve been using announced this week that they were terminating all support for their mobile and desktop apps and pushing everything into the cloud, which entirely doesn’t work with my workflow.
This means that I’m giving Zotero another shot (I tried them back when I was doing my PhD and the service wasn’t exactly ready for popular use at the time). On the plus side, Zotero has a good set of instructions for how to import my references from Mendeley. On the negative side, Mendeley has made this about as painful as possible: they encrypt the local database so you need to move back to an older version of the application and they then force you to manually download all of the documents which are attached to entries before the full bibliographic entries can be exported to another reference manager like Zotero. They have also entirely falsely asserted that the local encryption is required to comply with the GDPR which is pretty frustrating.
On the plus side, the manual labour involved in importing the references is done, though it cost me around two hours of time that could have been used for something that was actually productive. And Zotero has an app for iOS coming, and there is another app called PaperShip which interoperates with Zotero, which should cut down on the hopefully-pretty-temporary pain of adopting a new workflow. However, I’m going to need to do a lot of corrections in the database (just to clean up references) and most likely have start paying another yearly subscription service given that the free tier for Zotero doesn’t clearly meet my needs. Two steps backwards, one step forwards, I guess.
One of the best pandemic purchases I’ve made has been a HomePod Mini. One of the many reasons that I’ve liked it is I can use a Home automation to set a playlist or album to wake up to. This corrects an annoyance with the iPhone’s Alarms app, where you need to download a song to your device to reliably use it as an alarm.
However, I recently got a new iPhone which broke my alarm automation. I couldn’t figure out what was going on: I deleted and re-created the automation a few times and totally restarted the HomePod Mini. Neither of these actions helped. Not only did the automation not work at the designated times but the automation wouldn’t even work while using the test feature.
The settings for the automation were:
Enable This Automation (Only when I am home): On
When: Weekdays at a given time (Only when I am home)
Scenes: Weekday morning
Accessories: HomePod Mini
Media: Play Audio (Designated playlist, Shuffle, Set Custom Volume)
No matter what I did, the automation never fired. However, I figured out that as soon as I disabled the location-specific triggers the automation worked. This helped me to start narrowing down the problem and how to correct it.
You see, when I moved all of my data to my new iPhone it failed to transfer a setting that told the Home app to use my iPhone as the location to from which to trigger events. As a result, setting an automation to only fire when I was home couldn’t work because the device which had been triggering the Home automation (i.e., my old iPhone) wasn’t never geolocated to my network. You can fix this, however, by opening: Settings >> Privacy >> Location Services (On) >> Share My Location >> My Location (Set to “This Device).
Now that the Home app knows to use my iPhone’s location as the way of determining whether I’m at home, the trigger fires reliably.