1. Pizza Hut Gorbachev TV Spot Commercial

Millienial: It is Obama!

Boomer: Because of him, we have death panels!

Millenial: Because of him, we have health care!

Greatest Generation: Because of him, we have many things… like Taco Bell’s Doritos Cheesy Gordita Crunch.

2. Vicious Cycles: Theses on a philosophy of news

This is my favorite piece of writing on the news.

3. Successes in Biological Control

Originally brought to the US to breed with the native silkworms, the gypsy moth, Lymantria dispar L., escaped through a broken window in Medford, MA in 1868-9 and began defoliating deciduous forests and shade trees in many regions of North America. […] In the late 1980s and early 1990s, scientists noticed gypsy moth cadavers hanging from trees in the northeastern forests and identified the cause as a fungal infection. This discovery renewed interest in using fungi for control.

4. What explains voter aversion to carbon taxes and what can be done?

Pairs well with an earlier post. See also State and trends of carbon pricing in 2019.

5. Principles for the Application of Human Intelligence

However, the replacement of algorithms with a powerful technology in the form of the human brain is not without risks. Before humans become the standard way in which we make decisions, we need to consider the risks and ensure implementation of human decision-making systems does not cause widespread harm. To this end, we need to develop principles for the application for the human intelligence to decision making.

Full post

• ## Progress and preservation in IDA

This post arose out of my attempts to understand IDA and ways it could fail. It might help you do the same and could provide useful vocabulary for discussing desiderata for IDA.

We want IDA to satisfy progress—decomposition should make answering questions easier—and preservation—semantics should be retained across transformations. We need progress in each decomposition and, furthermore, repeated decompositions must be able to eventually simplify each question such that it can be answered directly by a human. Also, each decomposition and aggregation of questions and answers must introduce no more than a bounded amount of semantic drift and, furthermore, repeated decompositions and aggregations should also introduce no more than a bounded amount of semantic drift.

$\def\sc#1{\dosc#1\csod} \def\dosc#1#2\csod{{\rm #1{\small #2}}}$

Iterated distillation and amplification (henceforth IDA) is a proposal for improving the capability of human-machine systems to suprahuman levels in complex domains where even evaluation of system outputs may be beyond unaugmented human capabilities. For a detailed explanation of the mechanics, I’ll refer you to the original paper just linked, section 0 of Machine Learning Projects for Iterated Distillation and Amplification, or one of the many other explanations floating around the Web.

We can view IDA as dynamic programming with function approximation1 instead of a tabular cache. Just like the cache in dynamic programming, the machine learning component of IDA is a performance optimization. We can excise it and look at just the divide-and-conquer aspect of IDA in our analysis. Then this simplified IDA roughly consists of: (1) repeatedly decomposing tasks into simpler subtasks; (2) eventually completing sufficiently simple subtasks; and (3) aggregating outputs from subtasks into an output which completes the original, undecomposed task. We’ll examine this simplified model2 in the rest of the post. (If you’d like a more concrete description of the divide-and-conquer component of IDA, there’s a runnable Haskell demo here.)

### Safety is progress plus preservation

For type systems, the slogan is “safety is progress plus preservation”. Because we’re using this only as a cute analogy and organizing framework, we’ll not get into the details. But for type systems:

Progress
“A well-typed term is […] either […] a value or it can take a step according to the evaluation rules.”
Preservation
“If a well-typed term takes a step of evaluation, then the resulting term is also well typed.”

(Both from (Pierce and Benjamin 2002).)

We also need progress and preservation in IDA. Roughly:

Progress
A question is easy enough to be answered directly or can be decomposed into easier subquestions.
Preservation

Let’s try to make this more precise.

Full post

• ## A corrected model suggests climate change interventions may be within a factor of two of direct cash transfers

In an earlier EA forum post, data from a new paper on country-level social cost of carbon is used to estimate the comparative cost-effectiveness of climate change interventions and global development interventions (cost-effectiveness of the latter as determined by GiveWell’s models). A central component of the earlier post (henceforth GDvCC1) is supposed to be income2-weighting—$10 dollars of lost income means a great deal more in terms of utility for someone that makes$200 per year than for someone that makes \$20,000 per year. More granular, country-level data on the social cost of carbon gets us closer to accounting for this distributional consideration3 and allows us to express the social cost of carbon in a way that’s directly comparable with the outputs of GiveWell’s models. GDvCC’s model finds that, in its “realistic” scenario, climate change interventions are 3% as cost-effective as GiveDirectly and 0.4% as cost-effective as GiveWell’s median top charity. However, I think there’s an error in the way the country-level social cost of carbon (CSCC) is interpreted in GDvCC which leads to incorrect income-weighting. Correcting for this error suggests that climate change interventions (again, under “realistic” assumptions) are 57% as cost-effective as GiveDirectly.

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