“Excellence R Us”: university research and the fetishisation of excellence

Is “excellence” really the most efficient metric for distributing the resources available to the world’s scientists, teachers, and scholars? Does “excellence” live up to the expectations that academic communities place upon it? Is “excellence” excellent? And are we being excellent to each other in using it?

During the panel today on Journals in the digital age: penser de nouveaux modèles de publication en sciences humaines at CSDH-SCHN 2020 someone linked to an essay on  “Excellence R Us”: university research and the fetishisation of excellence in Palgrave Communications (2017). The essay does what should have been done some time ago, it questions the excellence of “excellence” as a value for everything in universities. The very overuse of “excellence” has devalued the concept. Surely much of what we do these days is “good enough” especially as our budgets are cut and cut.

The article has three major parts:

  • Rhetoric of excellence – it looks at how there is little consensus around what excellence between disciplines. Within disciplines it is negotiated and can become conservative.
  • Is “excellence” good for research – the second section argues that there is little correlation between forms of excellence review and long term metrics. They go on to outline some of the unfortunate side-effects of the push for excellence; how it can distort research and funding by promoting competition rather than collaboration. They also talk about how excellence disincentivizes replication – who wants to bother with replication if
  • Alternative narratives – the third section looks at alternative ways of distributing funding. They discuss looking at “soundness” and “capacity” as an alternatives to the winner-takes-all of excellence.

So much more could and should be addressed on this subject. I have often wondered about the effect of the success rates in grant programmes (percentage of applicants funded). When the success rate gets really low, as it is with many NEH programmes, it almost becomes a waste of time to apply and superstitions about success abound. SSHRC has healthier success rates that generally ensure that most researchers gets funded if they persist and rework their proposals.

Hypercompetition in turn leads to greater (we might even say more shameless …) attempts to perform this “excellence”, driving a circular conservatism and reification of existing power structures while harming rather than improving the qualities of the underlying activity.

Ultimately the “adjunctification” of the university, where few faculty get tenure, also leads to hypercompetition and an impoverished research environment. Getting tenure could end up being the most prestigious (and fundamental) of grants – the grant of a research career.

 

Google Developers Blog: Text Embedding Models Contain Bias. Here’s Why That Matters.

Human data encodes human biases by default. Being aware of this is a good start, and the conversation around how to handle it is ongoing. At Google, we are actively researching unintended bias analysis and mitigation strategies because we are committed to making products that work well for everyone. In this post, we’ll examine a few text embedding models, suggest some tools for evaluating certain forms of bias, and discuss how these issues matter when building applications.

On the Google Developvers Blog there is an interesting post on Text Embedding Models Contain Bias. Here’s Why That Matters. The post talks about a technique for using Word Embedding Association Tests (WEAT) to see compare different text embedding algorithms. The idea is to see whether groups of words like gendered words associate with positive or negative words. In the image above you can see the sentiment bias for female and male names for different techniques.

While Google is working on WEAT to try to detect and deal with bias, in our case this technique could be used to identify forms of bias in corpora.

The Viral Virus

Graph of word "test*" over time
Relative Frequency of word “test*” over time

Analyzing the Twitter Conversation Surrounding COVID-19

From Twitter I found out about this excellent visual essay on The Viral Virus by Kate Appel from May 6, 2020. Appel used Voyant to study highly retweeted tweets from January 20th to April 23rd. She divided the tweets into weeks and then used the distinctive words (tf-idf) tool to tell a story about the changing discussion about Covid-19. As you scroll down you see lists of distinctive words and supporting images. At the end she shows some of the topics gained from topic modelling. It is a remarkably simple, but effective use of Voyant.

COVID-19 contact tracing reveals ethical tradeoffs between public health and privacy

Michael Brown has written a nice article in the U of Alberta folio on COVID-19 contact tracing reveals ethical tradeoffs between public health and privacyThe article quotes me extensively on the subject of the ethics of these new bluetooth contact tracing tools. In the interview I tried the emphasize the importance of knowledge and consent.

  • Users of these apps should know that they are being traced through them, and
  • Users should consent to their use.

There are a variety of these apps from the system pioneered by Singapore called TraceTogether to its Alberta cousin ABTraceTogether. There are also a variety of approaches to tracing people from using credit card records to apps like TraceTogether. The EFF has a good essay on Protecting Civil Rights During a Public Health Crisis that I adapt here to provide guidelines for when one might gather data without knowledge or consent:

  • Medically necessary: There should be a clear and compelling explanation as to how this will save lives.
  • Personal information proportionate to need: The information gathered should fit the need and go no further.
  • Information handled by health informatics specialists: The gathering and processing should be handled by health informatics units, not signals intelligence or security services.
  • Deleted: It should be deleted once it is no longer needed.
  • Not be organized due to vulnerable demographics: The information should not be binned according to stereotypical or vulnerable demographics unless there is a compelling need. We should be very careful that we don’t use the data to further disadvantage groups.
  • Use reviewed afterwards: The should be a review after the crisis is over.
  • Transparency: Government should transparent about what they are gathering and why.
  • Due process: There should be open processes for people to challenge the gathering of their information or to challenge decisions taken as a result of such information.

Is this crisis a turning point?

The era of peak globalisation is over. For those of us not on the front line, clearing the mind and thinking how to live in an altered world is the task at hand.

John Gray has written an essay in the New Statesman on Why this crisis is a turning point in history. He argues that the era of hyperglobalism is at an end and many systems may not survive the shift to something different. Many may think we will, after a bit of isolated pain, return to the good old expanding wealth, but the economic crisis that is now emerging may break that dream. Governments and nations may be broken by collapsing systems.

The tech ‘solutions’ for coronavirus take the surveillance state to the next level

Neoliberalism shrinks public budgets; solutionism shrinks public imagination.

Evgeny Morozov has crisp essay in The Guardina on how The tech ‘solutions’ for coronavirus take the surveillance state to the next level. He argues that neoliberalist austerity cut our public services back in ways that now we see are endangering lives, but it is solutionism that constraining our ideas about what we can do to deal with situations. If we look for a technical solution we give up on questioning the underlying defunding of the commons.

There is nice interview between Natasha Dow Shüll Morozov on The Folly of Technological Solutionism: An Interview with Evgeny Morozov in which they talk about his book To Save Everything, Click Here: The Folly of Technological Solutionism and gamification.

Back in The Guardian, he ends his essay warning that we should focus on picking between apps – between solutions. We should get beyond solutions like apps to thinking politically.

The feast of solutionism unleashed by Covid-19 reveals the extreme dependence of the actually existing democracies on the undemocratic exercise of private power by technology platforms. Our first order of business should be to chart a post-solutionist path – one that gives the public sovereignty over digital platforms.

Digitization in an Emergency: Fair Use/Fair Dealing and How Libraries Are Adapting to the Pandemic

In response to unprecedented exigencies, more systemic solutions may be necessary and fully justifiable under fair use and fair dealing. This includes variants of controlled digital lending (CDL), in which books are scanned and lent in digital form, preserving the same one-to-one scarcity and time limits that would apply to lending their physical copies. Even before the new coronavirus, a growing number of libraries have implemented CDL for select physical collections.

The Association of Research Libraries has a blog entry on Digitization in an Emergency: Fair Use/Fair Dealing and How Libraries Are Adapting to the Pandemic by Ryan Clough (April 1, 2020) with good links. The closing of the physical libraries has accelerated a process of moving from a hybrid of physical and digital resources to an entirely digital library. Controlled digital lending (where only a limited number of patrons can read an digital asset at a time) seems a sensible way to go.

To be honest, I am so tired of sitting on my butt that I plan to spend much more time walking to and browsing around the library at the University of Alberta. As much as digital access is a convenience, I’m missing the occasions for getting outside and walking that a library affords. Perhaps we should think of the library as a labyrinth – something deliberately difficult to navigate in order to give you an excuse to walk around.

Perhaps I need a book scanner on a standing desk at home to keep me on my feet.

How useful is AI in a pandemic?

DER SPIEGEL: What are the lessons to be learned from this crisis

Dräger: It shows that common sense is more important than we all thought. This situation is so new and complicated that the problems can only be solved by people who carefully weigh their decisions. Artificial intelligence, which everyone has been talking so much about recently, isn’t much help at the moment.

Absolutely Mission Impossible: Interview with German Ventilator Manufacturer, Speigel International, Interviewed by Lukas Eberle und Martin U. Müller, March 27th, 2020.

There are so many lessons to be learned from the Coronavirus, but one lesson is that artificial intelligence isn’t always the solution. In a health crisis that has to do with viruses in the air, not information, AI is only indirectly useful. As the head of production of the German Drägerwerk ventilator manufacturer company puts it, the challenge of choosing who to sell ventilators to in this time is not one to handed over to an AI. Humans carefully weighing decisions (and taking responsibility for them) is what is needed in a crisis.

The Machine Stops

Imagine, if you can, a small room, hexagonal in shape, like the cell of a bee. It is lighted neither by window nor by lamp, yet it is filled with a soft radiance. There are no apertures for ventilation, yet the air is fresh. There are no musical instruments, and yet, at the moment that my meditation opens, this room is throbbing with melodious sounds. An armchair is in the centre, by its side a reading-desk — that is all the furniture. And in the armchair there sits a swaddled lump of flesh — a woman, about five feet high, with a face as white as a fungus. It is to her that the little room belongs.

Like many, I reread E.M. Forester’s The Machine Stops this week while in isolation. This short story was published in 1909 and written as a reaction to The Time Machine by H.G. Wells. (See the full text here (PDF).) In Forester it is the machine that keeps working the utopia of isolated pods; in Wells it is a caste of workers, the Morlochs, who also turn out to eat the leisure class.  Forester felt that technology was likely to be the problem, or part of the problem, not class.

In this pandemic we see a bit of both. Following Wells we see a class of gig-economy deliverers who facilitate the isolated life of those of us who do intellectual work. Intellectual work has gone virtual, but we still need a physical layer maintained. (Even the language of a stack of layers comes metaphorically from computing.) But we also see in our virtualized work a dependence on an information machine that lets our bodies sit on the couch in isolation while we listen to throbbing melodies. My body certainly feels like it is settling into a swaddled lump of fungus.

An intriguing aspect of “The Machine Stops” is how Vashti, the mother who loves the life of the machine, measures everything in terms of ideas. She complains that flying to see her son and seeing the earth below gives her no ideas. Ideas don’t come from original experiences but from layers of interpretation. Ideas are the currency of an intellectual life of leisure which loses touch with the “real world.”

At the end, as the machine stops and Kuno, Vashti’s son, comes to his mother in the disaster, they reflect on how a few homeless refugees living on the surface might survive and learn not to trust the machine.

“I have seen them, spoken to them, loved them. They are hiding in the mist and the ferns until our civilization stops. To-day they are the Homeless — to-morrow—”

“Oh, to-morrow — some fool will start the Machine again, to-morrow.”

“Never,” said Kuno, “never. Humanity has learnt its lesson.”

 

2020 Brings the Death of IT | I, Cringely

It’s the end of IT because your device will no longer contain anything so it can be simply replaced via Amazon if it is damaged or lost, with the IT kid in the white shirt becoming an Uber driver.

How many of us have laughed at The IT Crowd? I remember when I was in support at the University of Toronto and would advise people to turn their computer off and back on. Suprisingly that actually helped in some cases, as did wiggling the cable to the printer (back when there were lots of pins.) Robert X. Cringely, who is apparently not the only Cringely, has a prediction that 2020 Brings the Death of IT in his I, Cringely site. He predicts that all of us working at home in isolation is going to accelerate a computing paradigm called SASE (Secure Access Service Edge – pronounced “sassy”) where individual devices are connected to cloud-based services. IT will disappear because to fix something you will just order another from Amazon. There will be no fixing the local, just replacing it. The rest is all up in the cloud and maintained by someone like Google. Locally we just have appliances.