- Scientists Have Been Underestimating the Pace of Climate Change by Naomi Oreskes, Michael Oppenheimer, and Dale Jamieson for Scientific American. Errors in temperature measuring have led to an underestimation of global climate change.
- Explainable AI Won’t Deliver. Here’s Why by Cassie Kozyrkov for Hackernoon. “Imagine choosing between two spaceships. Spaceship 1 comes with exact equations explaining how it works, but has never been flown. How Spaceship 2 flies is a mystery, but it has undergone extensive testing, with years of successful flights like the one you’re going on.” Kozyrkov favours option two – but isn’t she in danger of the turkey problem, trusting the farmer?
- How Does a Computer ‘See’ Gender? by Stefan Wojcik, Emma Remy, and Chris Baronavski. Interactive piece how machines differentiate between males and females.
- The Why of the World by Tim Maudlin for Boston Review. Book Review of Pearl and Mackenzie’s The Book of Why. If data depicts correlations, how can we identify causation? The book advocates “causal graphs” to answer these questions or to determine when such questions cannot be answered from the data at all.
- Refik Anadol Induces a ‘Machine Hallucination’ at Artechouse in New York’s Chelsea Market. Artist Refik Anadol created “Machine Hallucination” with NVIDIA’s StyleGAN and PgGAN algorithms.
- What Lies Deep by Matthew Buckley for Boston Review. In 2012 the discovery of the Higgs boson, an elementary particle in the Standard Model of particle physics, made waves beyond the world of physicists. What are the next topics for the Large Hadron Collider?
- What Statistics Can and Can’t Tell Us About Ourselves by Hannah Fry for The New Yorker. At a time where data is seen as the ultimate truth we need to double down on eradicating unknown influences as much as blind faith in the authority of the results – and be aware that we’ll inevitably fall short.
- Kahneman and Tversky’s “Debatable” Loss Aversion Assumption by Jason Collins. Loss aversion ties neatly into the explanation of many observed behaviours. However, studies are not as supportive of that effect as general assumed, with the early research into the topic particularly misrepresented.
- Simjacker – Next Generation Spying Over Mobile by Cathal McDaid for AdaptiveMobile Security. Simjacker is a spyware-like SMS code accessing the users’ SIM and retrieving sensitive information. It’s believed to have been around for more than two years.
- Face Recognition, Bad People and Bad Data by Ben Evans. From his piece on facial recognition: “We worried that these databases would contain bad data or bad assumptions, and in particular that they might inadvertently and unconsciously encode the existing prejudices and biases of our societies and fix them into machinery. We worried people would screw up. And, we worried about people deliberately building and using these systems to do bad things. That is, we worried what would happen if these systems didn’t work and we worried what would happen if they did work.”
September Reading List
September 22, 2019