Thank you for clarifying the voting system for me. So my comment most likely irritated some folks with lots of karma. 

I certainly don't want to say things that irritate folks in the EA community . I was giving voice to what I might hear from some of my women friends, something like: "Yes Helen Toner was an EA, but she was a woman who was questioning what Altman was doing too."  According to this article, Altman tried to push out Helen Toner "because he thought a research paper she had co-written was critical of the company." But she was on a board whose responsibility to make sure that AI serves humanity. So here job was in some sense to be critical of the company when it might be diverging from the mission of serving humanity. So when she tries to do her job, some founder-guy tries to her because the public discussion about the issue might be critical of something he implemented?

I think this information indicates that there is not only an EA/non-EA dimension to that precursor event, but I think most women would recognize that there is also a gender/power/authority dimension to that precursor event. 

In spite of such considerations, I also agree with the idea that we should not focus on differences, conflict and divisions. And now I will more fully understand the karma cost of irritating someone who has much more karma than me on the forum. 

Thank you for the feedback on my comment. It has been informative. 

I am amazed that the EA community has such a negative reaction to someone pointing out the possibilities of institutional/AI-leadership sexism.

Within minutes my comment got -14 karma points. Interesting!

It is also the two women board members are also now off the board. So I would also like to hear what happened from a woman's perspective. Was it another case of powerful men not wanting to cede authority to women who are occupying positions of authority?

There could be many layers to what happened.

Thanks Emily:

I see some resonance between the behavioral science "Mistakes" that you think EAs might be making and differences that I find in my approach to EA work compared to what seems to be documented in the EA literature. 

Specifically, I was recently reading more thoroughly the works of Peter Singer, (specifically The Life You Can Save and The Most Good That You Can Do), and while I appreciated the arguments that were being made, I did not feel as though they reflected or properly respect the real beliefs and motivations of the friends and family that donate to support my EA activities. 

In this sense I also see a set of behavior science mistakes that the EA movement seems to be making from my particular individual perspective. 

So in my 30 years of doing Africa-focused, quantitatively-oriented development projects, I have developed a different "Theory of Change" for how my personal EA activities can have impact. 

This personal EA-like Theory of Change has three key elements: (1) Attracting non-EA donors for non-EA reasons to support EA Global Health and Welfare (GHW) causes, (2) Focusing on innovation to increase EA GHW impact leverage to 100:1, and (3) Cooperating with other EAs with the assumption that each member of the EA community has a different set of beliefs and an individual agenda. Cooperation serves aligned and community interests. 

I would appreciate it if you might comment on whether some of my divergences from general EA practice might address some of the "behavioral science" issues that you have identified.  

The first element of my Theory of Change is that for my EA causes to be successful, my projects have to be able to attract mostly non-EA donors. I recognize that my EA-type views are the views of a relatively tiny minority in our larger society. Therefore, I do not personally try to change people's moral philosophy which seems to be Peter Singer's approach. When I do make arguments for people to modify their moral philosophy, I find that people usually find this to be either threatening or offensive. 

Element #1: While the vast majority donors do not donate based on "maximum quantitative cost-effectiveness," they do respond to respectful arguments that a particular cause or charity that you are working on is more important and impactful than other causes and charities.  When "maximum quantitative cost-effectiveness" is a reason for someone that they know and respect to dedicate their life effort and money to a cause, many people will be willing to join and support that person's commitment. So while only a few people may be motivated by EA philosophical arguments, many more people can support the movement if people that they like, know and respect show a strong commitment to the movement. 

This convinces people to support EA causes because they see that EAs are honest, dedicated, and committed people that they can trust. You do not have to convince people of EA philosophy to have people donate to EA cause/efforts.  Most people who donate to EA causes could potentially have strong philosophical disagreements with the EA movement. 

The second element of my Theory of Change is that EA projects need to have very large amounts of impact leverage. So it is important to constantly improve the impact leverage of EA projects. Statistics on charitable donations indicates, that most people donate only a few percent of their income to charity, and may donate less than 1% of income to international charitable causes. 

Element #2: If people are going to donate less than 1% of income to international charitable causes, then in order to try to address the consequences of international economic inequality, EA Global Health and Welfare charities should strive to have 100:1 leverage or impact.  That is, $1 of charitable donation should produce $100 of benefit for people in need. In that way, it may be possible to create an egalitarian world over the long term in spite of the fact that people may be willing to give only 1% of their income on average to international charitable causes. 

In my little efforts, I think I have gotten to 20:1 impact leverage.  I hope I can demonstrate something closer to 50:1 impact leverage in a year or two. 

The third element of my EA theory of change is that I assume that every EA has a different personal agenda that is set by their personal history and circumstances.  It is my role to modify that agenda, only if someone is open to change. 

Element #3: Everyone in the EA movement has a different personal agenda and different needs and goals.  Therefore my goal in interacting with other EAs is to help them realize their full potential as an EA community participant on their terms.  Now since, I have my own personal views and agenda, generally I will help the agenda of others when it is low cost to my work or when it also make a contribution to my personal EA agenda (i.e. encouraging EA GHW projects to have 100:1 impact leverage). But if I can keep my EA agenda general enough, then there should be lots of alignment between my EA agenda and the agenda/interests of other EAs and I can be part of a substantial circle of associates that are mutually supportive. 

Now this Theory of Change or Theory of Impact is to some extent assuming fairly minimal behavior change. It assumes that most people support EA causes for their own reasons.  And it also assumes that people will not change their charitable donation behavior very much. It puts most of the onus of change on a fairly small EA community that achieves the technical accomplishment of attaining 100:1 impact leverage. 

Does this approach avoid the mistakes that you mention, while at the same time making a minimal impact on changing  behavior???

Just curious.  I hope this response to your presentation of EA behavior science "Mistakes" is useful to you. 

Thanks Jamie: our method is most useful when one has a relatively small sample of field data. In that case it is easy to calculate the averages of the bottom third, middle third, and top third of values and this is good enough because the data sample is not sufficient to specify the distribution with any greater precision.

Our method can also be calculated in any spreadsheet extremely easily and quickly without using any plug-ins or tools.

But agreed, if someone has the time, data and capacity, your method is better.

I don't know if this is useful to you, but we have a somewhat easier way of solving the same problem using what we call a simplified Monte Carlo estimation technique. This is described in the following post:

https://forum.effectivealtruism.org/posts/icxnuEHTXrPapHBQg/a-simplified-cost-effectiveness-estimation-methodology-for

It is not quite as accurate as your method because it approximates the probability distributions as a three-value distribution, but it addresses the issue of CEA inputs being uncorrelated and can be done in any spreadsheet without a need of using any extra tools or web services.  You just calculate for all combinations of inputs, and then use standard spreadsheet tools like cumulative probability plots or histogram calculators to get the probability distribution of results:

"In our CE estimation with uncertain inputs, we implement a highly simplified Monte Carlo method that we call a simplified Monte Carlo or "poor man's" Monte Carlo calculation.

In our simplified Monte Carlo calculation, we initially estimate ranges for all or most of the input parameters, and represent these ranges by low, median, and high values. Given a probability distribution of what values a parameter may take, the low value represents the average value of the lowest 1/3 of possibilities, the median value represents the average of the middle 1/3 of probable values and the high value represents the average of the largest 1/3 of probably values. This approximates a probability distribution of possible input parameter values by three discrete values of equal probability. 

Once all of the input parameters are represented by three values of equal probability, then the CE result is calculated for all combinations of input parameters. If each of the input parameters are independent and uncorrelated, then the set of CE values that result from all combinations of inputs all have equal probability. A histogram of the full set of CE results is then constructed to illustrate the full range of possible CE values and their respective approximate probabilities. "

I completely agree that GiveDirectly could explain this a hell of a lot better. I suspect that their team has a diversity of points of view and this prevents them from committing to a more concrete explanation like what I presented.  I explained the capital accumulation in terms of what I see when I visit actual households: someone starts with mud walls and a thatch roof, then they take their surplus and build a bigger house with concrete floors, brick walls and metal roof, move into that and then they can buy nicer furniture because dirt isn't falling down from the thatch roof all of the time.  They have obviously invested in higher productivity housing services which increases their consumption income.  But this evidence is anecdotal. 

I think GiveDirectly tried to anecdotally explain how cash transfers get invested with their shop example in the video. But again, I totally agree that their explanation has holes that make it hard for people who don't already agree with them to have the explanation that they need to understand why cash transfer requirements are likely to decrease substantially over time. 

You claim that investments that improve the quality of services consumed (such as cement floors, brick walls and metal roofs) are not "productive investments" and do not produce a long-term improvement in income. 

This is our key point of disagreement. I disagree with your claim.  We can agree to disagree. 

I think we are disagreeing on how income/poverty is properly measured. 

In my work in low-income developing country conditions the most relevant measurement of income is "consumption income" the value of the goods and services that people consume. 

Where I work, it is common for 1/3 to 1/2 of household consumption to be self-produced: i.e. generated with no cash income, and no cash expenditure. 

In these conditions, an investment in improved housing does produce a long-term increase in consumption income because it increases the value of the housing services that the family is consuming over many years with no further cash expenditure. It is a one-time cash expenditure and a long-term consumption income increase. 

Increasing consumption income is what households in rural Africa see as real, tangible poverty reduction. 

I agree that GiveDirectly did not support its claims in ways that certain people can find convincing. Because many people in richer countries live in places where most consumption has an associated financial transaction, and many folks do not have familiarity with living in a subsistence economy that can enable an intuitive understanding of un-monetized production and consumption economics. 

But for those who do spend time working in the practice of improving rural African household economic conditions, GiveDirectly's claims seem well-supported because in rural Africa it is very common for people to make cash expenditures to increase consumption income over the long term. People like me consider such improvements in housing and infrastructure as productive investments even if they produce benefits that are not monetized. 

GiveDirectly has shown that the impact of cash transfers are multi-year, and if the benefit lasts more than one year, then the cash transfer in an subsequent year can be less than the cash transfer in the previous year to maintain a household above the extreme poverty threshold.  Thus, IMHO, GiveDirectly has shown what it needs to show to make the claim that cash transfers likely can decrease year-over-year to maintain incomes above the extreme poverty threshold in a larger scale program. 

I have worked in the field in rural Africa on projects for almost 30 years, and from my experience you seem to be missing a pretty huge factor in your argument that there is insufficient evidence that the annual cost of extreme poverty reduction through cash transfers would decline over time. 

I don't quite understand how your argument can ignore household capital accumulation?

A portion of the $100 billion per year that the poor recipients would receive would be spent on durable goods and productive assets that raise the standard of living to some degree for several years for the beneficiary households.  Say each year 25% of money is spent on durable goods and assets that have a lasting effect of three years.  Then the first year, you need $100 billion, but the next year, you need only $75 billion, and then year after that you need only 0.75 x 75 =  $56 billion ...  One could of course build a much better conceptual model and estimation of this, but any durable goods and productive asset investments by beneficiaries should decrease the need for future cash transfers.

And there are many investments that people make in rural Africa that have very long, durable effects: sending kids to school, cement floors, durable metal roofs, buying a motorcycle to replace your bicycle, a mechanical irrigation pump so you can grow crops in the dry season and increase agricultural income. 

In order NOT to have a fairly rapid decrease in the amount of annual cash transfers (i.e. the hypothesis of your post), you would have to have only a very small amount of the cash transfers spent on productive or durable assets that last two to several years. 

I think the studies have satisfied a very high burden of proof with respect to showing that a substantial portion of the cash transfers are spent on durable and productive assets and that there exists a multi-year positive impact. 

I think that now the burden of proof is on you to show or demonstrate how spending on productive and durable assets would not lead to capital accumulation that would decrease the cost of maintaining a certain minimum standard of living in subsequent years.  I don't think you have shown that yet in your post. 

If a portion of income is spent on something that has a positive return, then that positive return needs to be subtracted from the income subsidy for the following year that is needed to maintain the minimum income level. But maybe I am I missing something in this logic?

In the course of my work over the past 30 years, I have talked to hundreds of rural African households about their finances and economics. When they get more money, they spend some on consumption, but they also invest. Very low-income households in rural Africa also have many very small investment opportunities that have payback times of months, not years. The investments they make can give them a return which increases income over the next year of which they take a portion of the surplus and invest again.  This becomes household equity that is used to sustain a long-term increase in household income. When you visit villages in Africa over many years, you see the dynamic of increased durable infrastructure and household financial equity over time: Dirt floors change to cement floors, mud walls become brick walls, thatch roofs become metal roofs, kids playing in the dirt become kids going to school, people who used to have to walk everywhere are able to ride motorcycle or minivan. 

Perhaps this comment is useful to you. Or maybe I am missing something and you can enlighten me as to why household asset accumulation would not necessarily decrease the cost of a global cash transfer program that is meant to eliminate extreme poverty at large scale.