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Can University Faculty Hold Platforms To Account?

Heidi Tworek has a good piece with the Centre for International Governance Innovation, where she questions whether there will be a sufficient number of faculty in Canada (and elsewhere) to make use of information that digital-first companies might be compelled to make available to researchers. The general argument goes that if companies must make information available to academics then these academics can study the information and, subsequently, hold companies to account and guide evidence-based policymaking.

Tworek’s argument focuses on two key things.

  1. First, there has been a decline in the tenured professoriate in Canada, with the effect that the adjunct faculty who are ‘filling in’ are busy teaching and really don’t have a chance to lead research.
  2. While a vanishingly small number of PhD holders obtain a tenure track role, a reasonable number may be going into the very digital-first companies that researchers needs data from to hold them accountable.

On this latter point, she writes:

If the companies have far more researchers than universities have, transparency regulations may not do as much to address the imbalance of knowledge as many expect.

I don’t think that hiring people with PhDs necessarily means that companies are addressing knowledge imbalances. Whatever is learned by these researchers tends to be sheltered within corporate walls and protected by NDAs. So those researchers going into companies may learn what’s going on but be unable (or unmotivated) to leverage what they know in order to inform policy discussions meant to hold companies to account.

To be clear, I really do agree with a lot in this article. However, I think it does have a few areas for further consideration.

First, more needs to be said about what, specifically, ’transparency’ encompasses and its relationships with data type, availability, etc. Transparency is a deeply contested concept and there are a lot of ways that the revelation of data basically creates a funhouse of mirrors effect, insofar as what researchers ‘see’ can be very distorted from the reality of what truly is.

Second, making data available isn’t just about whether universities have the professors to do the work but, really, whether the government and its regulators have the staff time as well. Professors are doing a lot of things whereas regulators can assign staff to just work the data, day in and day out. Focus matters.

Third, and related, I have to admit that I have pretty severe doubts about the ability of professors to seriously take up and make use of information from platforms, at scale and with policy impact, because it’s never going to be their full time jobs to do so. Professors are also going to be required to publish in books or journals, which means their outputs will be delayed and inaccessible to companies, government bureaucrats and regulators, and NGO staff. I’m sure academics will have lovely and insightful discussions…but they won’t happen fast enough, or in accessible places or in plain language, to generally affect policy debates.

So, what might need to be added to start fleshing out how universities are organised to make use of data released by companies and have policy impacts in research outputs?

First, universities in Canada would need to get truly serious about creating a ’researcher class’ to analyse corporate reporting. This would involve prioritising the hiring of research associates and senior research associates who have few or no teaching responsibilities.1

Second, universities would need to work to create centres such as the Citizen Lab, or related groups.2 These don’t need to be organisations which try and cover the waterfront of all digital issues. They could, instead, be more focused to reduce the number of staff or fellows that are needed to fulfil the organisation’s mandate. Any and all centres of this type would see a small handful of people with PhDs (who largely lack teaching responsibilities) guide multidisciplinary teams of staff. Those same staff members would not typically need a a PhD. They would need to be nimble enough to move quickly while using a peer-review lite process to validate findings, but not see journal or book outputs as their primacy currency for promotion or hiring.

Third, the centres would need a core group of long-term staffers. This core body of long-term researchers is needed to develop policy expertise that graduate students just don’t possess or develop in their short tenure in the university. Moreover, these same long-term researchers can then train graduate student fellows of the centres in question, with the effect of slowly building a cadre of researchers who are equipped to critically assess digital-first companies.

Fourth, the staff at research centres needs to be paid well and properly. They cannot be regarded as ‘graduate student plus’ employees but as specialists who will be of interest to government and corporations. This means that the university will need to pay competitive wages in order to secure the staff needed to fulfil centre mandates.

Basically if universities are to be successful in holding big data companies to account they’ll need to incubate quasi-NGOs and let them loose under the university’s auspice. It is, however, worth asking whether this should be the goal of the university in the first place: should society be outsourcing a large amount of the ‘transparency research’ that is designed to have policy impact or guide evidence-based policy making to academics, or should we instead bolster the capacities of government departments and regulatory agencies to undertake these activities

Put differently, and in context with Tworek’s argument: I think that assuming that PhDs holders working as faculty in universities are the solution to analysing data released by corporations can only hold if you happen to (a) hold or aspire to hold a PhD; (b) possesses or aspire to possess a research-focused tenure track job.

I don’t think that either (a) or (b) should guide the majority of the way forward in developing policy proposals as they pertain to holding corporations to account.

Do faculty have a role in holding companies such as Google, Facebook, Amazon, Apple, or Netflix to account? You bet. But if the university, and university researchers, are going to seriously get involved in using data released by companies to hold them to account and have policy impact, then I think we need dedicated and focused researchers. Faculty who are torn between teaching, writing and publishing in inaccessible locations using baroque theoretical lenses, pursuing funding opportunities and undertaking large amounts of department service and performing graduate student supervision are just not going to be sufficient to address the task at hand.


  1. In the interests of disclosure, I currently hold one of these roles. ↩︎
  2. Again in the interests of disclosure, this is the kind of place I currently work at. ↩︎
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Facebook Prioritizes Growth Over Social Responsibility

Karen Hao writing at MIT Technology Review:

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.

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Trump staffers worried about, and strategizing for, their next job

Per Politco, Trump staffers are worrying about their next job. I cannot believe that people working in the current administration continue to be given anonymity by the press: employees of the White House have knowingly supported a morally and ethically bankrupt president and administration, and what they’re most concerned about following the horror show of yesterday is their job prospects?

Expose them. Make them accountable for their culpability in what they have helped to nurture into existence. These people do not deserve anonymity.

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Privacy and Contemporary Motor Vehicles

Writing for NBC News, Olivia Solon provides a useful overview of just how much data is collected by motor vehicles—using sensors embedded in the vehicles as well as collected by infotainment systems when linked with a smartphone—and how law enforcement agencies are using that information.

Law enforcement agencies have been focusing their investigative efforts on two main information sources: the telematics system — which is like the “black box” — and the infotainment system. The telematics system stores a vehicle’s turn-by-turn navigation, speed, acceleration and deceleration information, as well as more granular clues, such as when and where the lights were switched on, the doors were opened, seat belts were put on and airbags were deployed.

The infotainment system records recent destinations, call logs, contact lists, text messages, emails, pictures, videos, web histories, voice commands and social media feeds. It can also keep track of the phones that have been connected to the vehicle via USB cable or Bluetooth, as well as all the apps installed on the device.

Together, the data allows investigators to reconstruct a vehicle’s journey and paint a picture of driver and passenger behavior. In a criminal case, the sequence of doors opening and seat belts being inserted could help show that a suspect had an accomplice.

Of note, rental cars as well as second hand vehicles also retain all of this information and it can then be accessed by third-parties. It’s pretty easy to envision a situation where rental companies are obligated to assess retained data to determine if a certain class or classes of offences have been committed, and then overshare information collected by rental vehicles to avoid their own liability that could follow from failing to fully meet whatever obligations are placed upon them.

Of course, outright nefarious actors can also take advantage of the digital connectivity built into contemporary vehicles.

Just as the trove of data can be helpful for solving crimes, it can also be used to commit them, Amico said. He pointed to a case in Australia, where a man stalked his ex-girlfriend using an app that connected to her high-tech Land Rover and sent him live information about her movements. The app also allowed him to remotely start and stop her vehicle and open and close the windows.

As in so many different areas, connectivity is being included into vehicles without real or sufficient assessment of how to secure new technologies and defray harmful or undesirable secondary uses of data. Engineers rarely worry about these outcomes, corporate lawyers aren’t attentive to these classes of issues, and the security of contemporary vehicles is generally garbage. Combined, this means that government bodies are almost certainly going to expand the ranges of data they can access without having to first go through a public debate about the appropriateness of doing so or creation of specialized warrants that would limit data mining. Moreover, in countries with weak policing accountability structures, it will be impossible to even assess the regularity at which government officials obtain access to information from cars, how such data lets them overcome other issues they state they are encountering (e.g., encryption), or the utility of this data in investigating crimes and introducing it as evidence in court cases.

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CSIS’s New Powers Demand New Accountability Mechanisms

CSIS’s New Powers Demand New Accountability Mechanisms:

It is imperative that the Canadian public trust that CSIS is not acting in a lawless manner. And while improving how SIRC functions, or adding Parliamentary review, could regain or maintain that trust, a more cost-sensitive approach could involve statutory reporting. Regardless, something must be done to ensure that CSIS’ actions remain fully accountable to the public, especially given the new powers the Service may soon enjoy. Doing anything less would irresponsibly expand the state’s surveillance capabilities and threaten to dilute the public’s trust in its intelligence and security service.