Frequently Asked Questions

See more FAQs at the UW site

Who are you?

I am Thore Husfeldt, a Ph.D. in Computer Science, an associate professor at IT University of Copenhagen, and a full professor at Lund University. My research is in algorithms, so I have professional expertise in at least one tiny sliver of the vast field of concepts that this overly ambitious course claims to cover. Outside of my narrow research agenda, I am professionally involved in various aspects of the role of Computer Science in society and education. Moreover, one of the life-long private obsessions of my life is bullshit (or, if you want, epistemology, pseudoscience, bias) – I’ve been a card-carrying member of the Sceptics movement, and am widely read in the history of the Enlightenment, philosophy of science, sociology and psychology of bias, data communication, etc.

The current course is mainly designed by two college professors at the University of Washington in Seattle: Carl Bergstrom is a member of the Department of Biology, and Jevin West is a member of the Information School.

So you’re just copying Carl’s and Jevin’s course?

The short answer is yes. I’d started thinking about what such a course should involve because I may have to design one in two or three years for a Data Science programme. (Nothing about that is settled yet.) Still, I had some half-baked ideas about contents and tone,  but nothing coherent.

Along comes Carl’s and Jevin’s course, and it’s as if they read my mind, down to the selection of the readings. I’d be hard pressed to come up with something better. Since Carl and Jevin invite the world to copy their course, this format seems to be a perfect way to spread the word. (Yes, I’ve talked to them. They couldn’t be happier.)

It would be very strange if the course got everything right in the first iteration. But what better way to learn about that than run with it and talk about it? After all, all progress is made in environments of institutionalised disconfirmation.

Note that the ITU course is aimed at a much smaller and very different audience (Ph.D. Students at ITU) than the UW course, so the course format is different and invites input from the participants. I very much expect the ITU course to diverge from UW. I also have the ambition to add a few home-made modules at the end, with a stronger focus on algorithms, big data, and the internet.

Why are you doing this?

As Carl and Jevin explain on thir home page, we feel that the world has become over-saturated with bullshit and we’re sick of it. However modest, this course is our attempt to fight back.

We have a civic motivation as well. It’s not a matter of left- or right-wing ideology; both sides of the aisle have proven themselves facile at creating and spreading bullshit. Rather (and at the risk of grandiose language) adequate bullshit detection strikes us as essential to the survival of liberal democracy. Democracy has always relied on a critically-thinking electorate, but never has this been more important than in the current age of false news and international interference in the electoral process via propaganda disseminated over social media. Mark Galeotti’s December 2016 editorial in The New York Timessummarized America best defense against Russian “information warfare”:

“Instead of trying to combat each leak directly, the United States government should teach the public to tell when they are being manipulated. Via schools and nongovernmental organizations and public service campaigns, Americans should be taught the basic skills necessary to be savvy media consumers, from how to fact-check news articles to how pictures can lie.”

We could not agree more.

So is this some sort of swipe at the Trump administration?

No. We began developing this course in 2015 in response to our frustrations with the credulity of the scientific and popular presses in reporting research results. While the course may seem particularly timely today, we are not out to comment on the current political situation in the United States and around the world. Rather, we feel that in a democracy everyone will all be better off if people can see through the bullshit coming from all sides. You may not agree with us about the optimal size of government or the appropriate degree of US involvement in global affairs, and we’re good with that. We simply want to help people of all political perspectives resist bullshit, because we are confident that together all of us can make better collective decisions if we know how to evaluate the information that comes our way.

So is this some sort of swipe at Postmodernism?

No. Even though my own epistemological biases are somewhat ossified, the motivation of postmodernism as a reasoned critique and analysis of the methods and rhetorical devices sometimes ridiculed as “scientism” is completely consistent with this course and a highly welcome perspective.

What exactly is bullshit anyway?

Surprising as it may seem, there has been considerable scholarly discussion about this exact question. Unsurprisingly given that scholars like to discuss it, opinions differ.

As a first approximation, we subscribe to the following definition:

Bullshit is language, statistical figures, data graphics, and other forms of presentation intended to persuade by impressing and overwhelming a reader or listener, with a blatant disregard for truth and logical coherence.

It’s an open question whether the term bullshit also refers to false claims that arise from innocent mistakes. Whether or not that usage is appropriate, we feel that the verb phrase calling bullshit definitely applies to falsehoods irrespective of the intentions of the author or speaker. Some of the examples treated in our case studies fall into this domain. Even if not bullshit sensu stricto, we can nonetheless call bullshit on them.

In this course, we focus on bullshit as it often appears in the natural and social sciences: in the form of misleading models and data that drive erroneous conclusions.

What about bias?

The ITU course adds the phrase “overcoming bias” to the course title. I feel that calling bullshit is something you do to others, while overcoming bias is something you can do to yourself. Though these skills are related, they are not the same. Moreover, one of the imminent threats of automated decision making is exactly the algorithmic confirmation of bias. There is a large body of recent work in social psychology (Kahneman–Tversky, Haidt) as well as very active internet-based communities that I feel belongs into such a course.

I may be wrong.

When do we start and how can I register?

At ITU, register before 14 March to register, see the ITU page for this course. I expect to start on 28 March. (All of which is subject to change.)

At University of Washington, registration is closed. For the latest information about that course, follow them on twitter, on  facebook, or by joining our mailing list.

I’m not an ITU or UW student. Will the course be offered online?

Informally, yes. The full UW syllabus is already online. You can find almost all of the readings on the internet and the few that are not online should be at your local library. We will be adding course materials, including new case studies and tools-and-tricks articles, as they become available. We aim to livestream the the Spring 2017 lectures and make video clips from lectures freely available on youtube or similar. For the latest updates on new material, follow the UW course on twitter, on facebook, or by joining their mailing list.

In the longer-term we may develop an open online course (a MOOC). When and if we do so, we will endeavor to keep enrollment costs to an absolute minimum.

Can they actually use the word “bullshit” in the title of a US college course?

Apparently yes. I’m impressed.

What’s with the old art?

Bullshit is by no means a modern invention and has many aspects. Danish culture is blessed with one of the best narrative antidotes agains the social mechanisms underlying the spread of bullshit, Hans Christian Andersen’s Kejserens Nye Klæder (The Emperor’s New Clothes). The illustration is one of Vilhelm Petersen’s drawings. It’ll probably go on the syllabus.

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