The Rich in Canada have Steadily been Paying Lower Tax Rates since 1949

A report has been making the rounds this week by UC Berkeley economists Emmanuel Saez and Gabriel Zucman whose deep dive found that the richest 400 families in the country in 2018 were taxed 23% on average. That’s less than the bottom half of American households, who paid 24.2% when factoring in the totality of taxes Americans pay.

The idea of “progressive” taxes is that people making more money should have to pay more when they make over a certain thresholds or “tax brackets”. While Saez and Zucman dig into various tax exemptions rather than the explicitly stated and public tax brackets, the stated taxes have been regularly becoming less progressive not only in the US, but also in Canada.

I made the following graph shows to how tax brackets have changed since 1949.

Combined Federal and Provincial Marginal Income Tax Rates for Selected Years and Selected Nominal Income Levels, 1949 to 1994

Source: The National Finances, 1985-86 (Toronto: Canadian Tax Foundation, 1986), 101, and The National Finances, 1994 (Toronto: Canadian Tax Foundation, 1994), 7:7. a The provincial rates are assumed to be 30.5 of the basic federal tax in 1972, 47 percent in 1986 and 1987, and 52 percent in 1994. Note: Owing to the refundable goods and service tax credits and child tax benefits, the 1994 rates for the lower income levels are not comparable to those of earlier years.

(More info:

Finn Brunton on How Our Fear of AI Relates to Our Fears of Our Own Nature

AI, especially in popular culture, is often a jumping-off point for dialogue with ourselves about what the future means, sometimes at the expense of understanding the present. Norbert Wiener, the cyberneticist, who actually played chess against a replica of [chess-playing automaton] El Ajedrecista in the 1950s, often compared the threat of AI (in terms of automation and Cold War military strategy) to the golem, and the sorcerer’s apprentice, and the monkey’s paw—magical objects whose execution of poorly specified desires using unlimited power leads to disaster.

I would suggest that one way to think about the mythic properties of current AI might be the doppelgänger: the sinister reflection embodying our fears about ourselves, in which we can see our own anxieties, desires, and unspoken biases. The truly human part of artificial intelligence is that we can’t resist making it all about us.

Finn Brunton, Assistant Professor, New York University Department of Media, Culture, and Communication
Source: AI: Machines or Magic?


Before we showcased our perfect lives on Facebook, we poured our souls onto Blogspot and LiveJournal. This is the legacy of blogging.

Starting a new blog in 2018 feels like a retread – but in the spirit of I do want to share half-baked thoughts and rough ideas.

Here we go!