Brahmin Left vs. Merchant Right: Rising Inequality and the Changing Structure of Political Conflict

Conclusions

Globalisation/migration (domestic vs external inequality) and educational expansion (education vs property inequality) have created new multi-dimensional conflicts about inequality, leading to the collapse of the postwar left-vs-right party system.

Why didn’t democracy reduce inequality?

Because multi-dimensional coalitions are complicated.

Without a strong egalitarian-internationalist platform, it’s difficult to have the low-education, low-income voters from all origins vote for the same party.

Racism/nativism & higher education = powerful forces dividing the poor if there’s no strong uniting platform.

-Thomas Piketty, “Brahmin Left vs. Merchant Right: Rising Inequality and the Changing Structure of Political Conflict.” EHESS & Paris School of Economics Sciences Po, January 24 2019

h/t Boing Boing, which provides a nice overview. Open Question: Am I a member of the Brahmin Left?

Liberatory Education | The Hedgehog Review

“In a psychic context, racial reparations may be less obviously needed, but needed nonetheless, for those of us from white families and communities that practice racial thoughtlessness. We, too, need to study race and racism in order to understand ourselves, because the implicit attitudes about race that we have consciously and unconsciously created and accepted are poisoning us and have imprisoned our minds. We are literally dying from our inability to break free of our prejudice, our unexamined opinions. There are direct correlations to be made between white attitudes about race, lack and fear of education, hopelessness and despair, and addiction. It is just not possible to think freely when you are also desperate to cling to your biases.”

—Leslie W. Lewis, “Liberatory Education.” Hedgehog Review. 21.2 (Summer 2019).

Read this essay. It is absolute fire, and equally applicable to gender, class, sexual orientation, disability and other prejudices.

Open Syllabus Project, Visualized

“A new interactive visualization from Open Syllabus turns this trove of data into a color-coded stippling of different-sized dots, each one representing a particular text. Float over each dot and a box appears in the corner of the screen, showing the number of syllabi that have assigned the text, and a link to a profile page with more detailed analysis. Called the “Co-Assignment Galaxy,” the infographic does what a list cannot: draws connections between all these works and their respective fields of study.

-Josh Jones, “A New Interactive Visualization of the 165,000 Most-Frequently Assigned Texts in College Courses.” openculture.com. July 22, 2019.

A list of the top 50 works is available from the Open Syllabus Project website.

Goodhart’s Law & The Ivy League

“Two years ago I was at an event in Boston and I happened to sit at a dinner table across from a guy widely recognized to be one of the most brilliant people in the world.  We talked mostly about AI but at one point the conversation turned to hiring, and he told me that for 2 decades he has tracked the performance of everyone who worked for him. Based on that performance tracking, he had stopped hiring from Harvard and Stanford. He said that historically, his best employees came from Harvard, Stanford, and MIT, but that starting 5 or 6 years prior, the people coming out of Harvard and Stanford started to really slip in their performance. I asked why, and he said that he didn’t know, but had a hypothesis. He said “I believe that ivy league college admissions has become so competitive that it rewards people who are good at the admissions process, not people who are good.”

This is a form of Goodhart’s Law, which says “when a measure becomes a target, it ceases to be a good measure.” You can see where this is going, and that there may be a similar law for machine learning.  We are in a phase of AI where we are using data sets that were created for other purposes, not with AI in mind. What happens when you know all your data is going to be fed into an AI?  Does it change the data you create?

-Rob May, “Goodhart’s Law and AI Data Sets.” Inside AI. June 3, 2019.

AI For Everyone

“AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone–especially your non-technical colleagues–to take. In this course, you will learn: – The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science – What AI realistically can–and cannot–do – How to spot opportunities to apply AI to problems in your own organization – What it feels like to build machine learning and data science projects – How to work with an AI team and build an AI strategy in your company – How to navigate ethical and societal discussions surrounding AI Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI.”

A.I. for Everyone.

Audit the course for free. Takes 6-8 hours to complete.

h/t, Open Culture.

How to Teach Yourself Hard Things

  1. Identify what you don’t understand (maybe the most important one)
  2. Have confidence in your knowledge
  3. Ask questions
  4. Do research

…Taking a bit of extra time to take a piece of knowledge that you’re pretty sure of (“there are 65535 ports, Wikipedia said so”) and make it totally ironclad (“that’s because the port field in the TCP header is only 16 bits”) is super useful because there is a big difference between “I’m 97% sure this is true” and “I am 100% sure about this and I never need to question it again”. Things I know are 100% true are way easier to rely on.”

—Julia Evans, “How to teach yourself hard things.” jvans.ca. September 1, 2018.

I would add that the an important pitfall is those things that we are sure is 100% true that aren’t true. Being a philosophical skeptic, this is probably everything.

Bad Gyms

When some one enters a gym for the first time, what are they looking for? If they are young, the driving force is often performance. Athletes want to be better at their chosen sport, and the gym provides a training ground in which to improve.

For the non-athlete entering the gym later in life, the focus may be on a particular goal – such as losing weight, cardiovascular fitness, or strength, but these too are performance goals. A desire for improvement is the motivation.

But, there is an interesting disconnect between the user of the gym and the gym owner. The concern of the gym owner, particularly if the gym owner is a corporation, is to reduce their risk of liability and reduce costs.

Enter any “fitness center” offered as an amenity by a corporation and you will find a wide variety machines that are designed, primarily, to prevent people from injuring themselves. These machines encourage repetitive, defined movements that limit the range of motion and the potential for injury. Free weights, if they are available at all, are confined to low weight dumbbells.

The simple fact is exercise machines are less effective forms of exercise than exercising with free weights. Yet, machines are the only options on offer because they are safer, and machines are cheaper than paying for staff to help people learn to exercise with free weights safely.

As a result of this typical safe gym environment, we almost never hear the simple truth. The overall best exercise for improving fitness is lifting heavy weights over a complete range of motion. If you wish to improve your health and fitness, deadlifts and squats are the single best way to do it. People using the gym need to learn how to do these exercises safely. A good gym trains people to do effective exercises safely. A bad gym provides machines to do less effective exercises that are safe and cost effective. Almost all the gyms we have are bad.

The Case Against Education | RadioWest

“Bryan Caplan says our higher education system is a waste of time and money. Caplan is a Princeton-educated, tenured professor of economics at George Mason University. He argues though that while a degree has become indispensable for competing in the job market, college isn’t actually teaching applicable skills or even teaching people how to learn. And worse yet? Many graduates are deep in debt and still not getting a great job.”

Listen to the Interview.