Mar 6, 2022

Confidence in Science

Feb 19, 2022

AI Dermatology: Part 2

​In the last post, I discussed the possible broader implications of Google’s recent foray into making an AI dermatology tool. In this follow up post, I want to focus on the research behind the product announcement, bringing a slightly critical eye.

Feb 5, 2022

AI Dermatology: Part 1

Dec 19, 2020

Vaccine Allocation at Stanford Hospital

In a video that was widely shared last Friday, a representative from Stanford Medical Center spoke to residents protesting how the hospital chose to allocate its first shipment of COVID-19 vaccines. The hospital had around 5,000 initial doses to distribute (and expects to have tens of thousands more within the next few weeks), and came up with an allocation scheme in which only 7 of the approximately 1,300 residents were on the list. Many of these residents deal directly with patients who have COVID-19, whereas other more senior physicians, as well as other front line workers, such as nurses and food service employees, were given priority. In the video, the spokesperson explains that the algorithm they used to come up with an allocation scheme “clearly didn’t work”, to which protestors respond by shouting “Algorithms suck!” and “Fuck the algorithm!” …

Oct 3, 2020

The case for professional critics in science

In many areas of science, there is an increasingly urgent unmet need, a role that could be simultaneously fascinating, rewarding, and potential remunerative. It is a role that already exists in various forms, but which could be made into something much more potent, especially if forces converged to make it more prominent. I am talking, of course, about the professional science critic.

In the popular imagination, science operates something like a priesthood: scientists enter elite institutions as novices and emerge years later as full-fledged representatives of The Truth. Along the way, they are trained to be experts and professionals in their subject, to excel in action as well as in thought, and to sacrifice their worldly interests for the sake of their calling. The scholarly journals and peer review process are imagined to operate like an ecumenical council, guiding and filtering the thoughts of the broader community of the devout, and only allowing to pass what is deemed to be true and useful and good.

Jul 20, 2019

Representational Power

Dec 17, 2018

On the Perils of Automated Face Recognition

May 25, 2018

What everyone needs to know about interpretability in machine learning

For anyone who’s been paying attention, it should be apparent that statistical machine learning systems are being widely deployed for automated decision making in all kinds of areas these days, including criminal justice, medicine, education, employment, policing, and so on. Particularly with the recently enacted GDPR—the new European regulation about data and privacy—there is growing interest in having systems that are interpretable, that is, we can make some sense of why they are making the prediction that they are making. To borrow an example from Been Kim, if a computer tells you that you need surgery, you’re probably going to ask for some sort of explanation.

May 14, 2018

Privacy in Context

Although it was not the largest of its kind, or the most invasive, or even particularly surprising, the recent Cambridge Analytica scandal produced a surprisingly large amount of outrage and commentary. If nothing else, it was yet another reminder that we have gradually slipped into a regime where certain aspects of our privacy that could once be taken for granted are now long gone. Are people concerned? Is this something we should be worried about? What exactly are the harms that come from this sort of loss of privacy.

Nov 27, 2017

Emergent Archives

It’s fascinating to think about how much we give to the internet, and sometimes, how much it gives back. In my mind, there is a fairly direct historical connection between self-archiving practices from a couple of decades ago (keeping a diary, making photo albums, writing letters, etc.), to all the more recent variations on this idea (status updates, tweets, photo feeds, etc.). The difference is arguably in how much of the background work is taken care of for us, and the fact that we now make so much of this information public or semi-public. While many have explored the implications of this for privacy, security, and surveillance, there is another aspect that gets less attention: the automatic creation of our own archives.