The mythology of technology is powerful, but also kind of superficial. It usually doesn’t take much to move past the marketing and vapour ware to understand whether a tool is useful or not. With AI this has been a bit more challenging, as the opaqueness of the tech often makes it difficult for us to scrutinize or understand what is taking place behind the scenes. Similarly the language and hype around AI deliberately hides or downplays the role of humans in making these automated systems work.

Ever since the pandemic hit early last year, supply chains have been stressed, and consumer demand has exhibited herd characteristics. In response to the crisis, and perhaps as a result of our increased time at home and on social media, demand is often exceeding supply when it comes to items that a lot of people all of a sudden really need.

I recently found out that I will be eligible to get a vaccine in the next phase, here in Ontario, meaning it’s possible I could get my first shot in April. Sometimes there are benefits to having a chronic illness and compromised immune system.

There is a general perception that with sufficient data, and smart enough machine learning, the future can be predicted.
An ongoing and arguably controversial example of this are weather forecasts. As a farmer I’ve become one of those people who pay close attention to weather forecasts, and it is remarkable how often they can be wrong.

Watching the big tech executives face off against a range of Congressional officials was an exercise in (mediocre) surrealist theatre, and a reflection of two regimes, one in decline, and the other on the rise.

Yesterday’s issue, that explored efforts to dissect the recent attempted insurrection, was partly a result of open source intelligence efforts. Whether New York Times or volunteers on the Internet, there has been an open, widespread, and participatory effort to identify people involved in the events of January 6th.