This is my first-ever AMA and I'm excited about it -- thanks to Aaron for the push! I will be answering questions here the afternoon of Monday, March 8 between 1-3pm East Coast time.
Here's some information about me and my work:
- Currently, I'm an independent consultant offering specialized strategy and research services to foundations, government agencies, large NGOs, and other institutions. Some of my clients have included the Walton Family Foundation, Omidyar Network, ACLU, International Rescue Committee, and the State of Victoria in Australia.
- I believe high-quality decision-making is critically neglected relative to its importance in most professional settings, which is one reason I'm helping to develop improving institutional decision-making as an EA cause area.
- I write a lot about social sector decision-making, including this feature in the spring 2020 issue of Stanford Social Innovation Review, my articles on Medium, and a quarterly-ish newsletter I publish on this topic.
- I also ran or co-ran two giving circles last year, one focused on rapid global coronavirus response and the other on electoral politics in the US. I really enjoyed both of these projects!
- I'm about two decades into my career. I started out as a composer and arts administrator and, needless to say, things have changed a lot.
I am happy to answer questions about any of the above, or anything else that's on your mind! I may not get to everything, especially if there are a lot of questions, but I'll try my best.
(Update: I've now come to the end of the time I budgeted, but will continue monitoring this discussion and will try for one or two follow-ups this week if I can!)
Are there theory-of-change-level misconceptions that you commonly find yourself correcting for your clients? What are some of the strategic mistakes you frequently see made by institutions on the scale you advise?
I love the way you phrased this question -- in fact, one of the reasons why I'm such a big believer in theories of change (so much so that I wrote an introductory explainer about them) is that they are excellent for revealing strategic mistakes in a client's thinking.
A frequent pitfall I come across is that the originators of an organization or program often fall in love with the solution rather than the problem. By that I mean they see a problem, think immediately of a very detailed solution for that problem -- whether it's a software platform, some other kind of technology or innovation, an adaptation of an existing idea to a new audience or environment, etc. -- and get so invested in executing on that solution that it doesn't even occur to them to think about modifications or alternatives that might have higher potential. Alternatively, the solution can become so embedded in the organization's identity that people who join or lead it later on see the specific manifestation of the solution as the organization's reason to exist rather than the problem it was trying to solve or opportunity it was trying to take advantage of.
This often shows up when doing a theory of change for a program or organization years down the line after reality has caught up to the original vision -- day-to-day activities, carried out by employees or successors and shaped through repeated concessions to convenience or other stakeholders, often imply a very different set of goals than are stated in the mission or vision statement! For that reason, when doing a theory of change, I try to encourage clients to map backwards from their goals or the impact they want to create and forget for a moment about the programs that currently exist, to encourage them to see a whole universe of potential solutions and think critically about why they are anchored on one in particular.
Hello Ian. Could you say a bit what providing strategy and research looks like? I don't have an intuitive grasp on what sort of things that involves and I'd appreciate an example or two!
Hi Michael, there are some sample project descriptions over at my website, but I'll paste a couple here for convenience:
Those should give you a high-level sense of what I do, but I'm happy to answer more specific questions as bandwidth allows.
What would be your top 3-5 tips for making good decisions in an organisation?
(I'm perhaps most interested in your independent impression, before updating on others' views.)
Great questions!
Thanks for these answers. I think I find your answer to Q2 particularly interesting. (FWIW, I also think I probably have a different perspective to your re your answer to Q1, but I imagine any quick response from me would probably just rehash old debates.)
Would you include even cases that rely on things like believing there's a non-trivial chance of at least ~10 billion humans per generation for some specified number of generations, with a similar or greater average wellbeing than the current average wellbeing? Or cases that rely on a bunch of more specific features of the future, like what kind of political systems, technologies, and economic systems they'll have?
How do you feel about longtermist work that specifically aims at one of the following?
My general intuition is that if there's a strong case that some action today is going to make a huge difference for humanity dozens or hundreds of generations into the future, that case is still going to be pretty strong if we limit our horizon to the next 100 years or so. Aside from technologies to prevent an asteroid from hitting the earth and similarly super-rare cataclysmic natural events, I'm hard pressed to think of examples of things that are obviously worth working on that don't meet that test. But I'm happy to be further educated on this subject.
Yeah, that sort of "anti-fragile" approach to longtermism strikes me as completely reasonable, and obviously it has clear connections to the IIDM cause area as well.
I might be misunderstanding you here, so apologies if the rest of this comment is talking past you. But I think the really key point for me is simply that, the "larger" and "better" the future would be if we get things right,[1] the more important it is to get things right. (This also requires a few moral assumptions, e.g. that wellbeing matters equally whenever it happens.)
To take it to the extreme, if we knew with certainty that extinction was absolutely guaranteed in 100 years, then that massively reduces the value of reducing extinction risk before that time. On the other extreme, if we knew with certainty that if we reduce AI risk in the next 100 years, the future will last 1 trillion years, contain 1 trillion sentient creatures per year, and they will all be very happy, free, aesthetically stimulated, having interesting experiences, etc., then that makes reducing AI risk extremely important.
A similar point can also apply with negative futures. If there's a non-trivial chance that some risk would result in a net negative future, then knowing how long that will last, how many beings would be in it, and how negative it is for those beings is relevant to how bad that outcome would be.
Most of the benefits of avoiding extinction or other negative lock-ins accrue more than 100 years from now, whereas (I'd argue) most of the predictable benefits of things like bednet distribution accrue within the next 100 years. So the relative priority of the two broad intervention categories could depend on how "large" and "good" the future would be if we avoid negative lock-ins. And that depends on having at least some guesses about the world more than 100 years from now (though they could be low-confidence and big-picture, rather than anything very confident or precise).[1]
So I guess I'm wondering whether you're uncomfortable with, or inclined to dismiss, even those sorts of low-confidence, big-picture guesses, or just the more confident and precise guesses?
(Btw, I think the paper The Case for Strong Longtermism is very good, and it makes the sort of argument I'm making much more rigorously than I'm making it here, so that could be worth checking out.)
[1] If we're total utilitarians, we could perhaps interpret "larger" and "better" as a matter of how long civilization or whatever lasts, how many beings there are per unit of time during that period, and how high their average wellbeing is. But I think the same basic point stands given other precise views and operationalisations.
[2] Put another way, I think I do expect that most things that are top priorities for their impact >100 years from now will also be much better in terms of their impact in the next 100 years than random selfish uses of resources would be. (And this will tend to be because the risks might occur in the next 100 years, or because things that help us deal with the risks also help us deal with other things.) But I don't necessarily expect them to be better than things like bednet distribution, which have been selected specifically for their high near-term impact.
How do you decide what sorts of clients to seek out, agree to consult for, or position yourself to consult for in future?
E.g., would you ideally want to mostly work with clients who are fairly focused on typical EA cause areas and who seem fundamentally receptive towards prioritising well within those areas (even if they don't currently prioritise well)? Or would you aim to focus on a different type of client? Or do you not have strong preferences on that front?
One of the realities of consulting is that, unless you get very lucky, you generally do have to be at least somewhat opportunistic in taking projects early on. I'm now in the fourth year of running my business and I'm able to be a lot pickier than I was when I first started, but if I limited my work to clients that were only focused on typical EA cause areas, I'd run out of clients pretty quickly. So I've cast my net quite a bit more broadly, which not only expands the opportunity set but also hedges against me getting typecast and positions me to be competitive/relevant in a wider range of professional networks, which I think is valuable for all sorts of reasons.
Another thing to keep in mind is that I've found that having clients that look great on paper doesn't always mean that you are able to achieve a lot of impact with them. Some of my most successful projects have been with clients that did smaller-scale work or were less sophisticated in their approach, because they knew they needed guidance from an outside expert and were willing to cede a lot of authority and creative input to me as part of the process. When you're really trying to innovate and move the field forward, it helps a lot to have clients like these because they aren't anchored on the usual ways of doing things, which makes them more open to trying out ideas. A lot of the sales process for consulting comes down to reassurance that someone else has done this thing and it worked out great for them, so getting those first few case studies locked down can be really important.
Thanks for the answer :)
So it sounds like part of your theory of change for your work is getting opportunities to test out innovations related to better decision-making practices and generating examples of these working, in order to inform other efforts to improve decision-making which are perhaps higher stakes in a direct sense?
A part of it, definitely. At the same time, there are other projects that may not offer much opportunity for innovation but where I still feel I can make a difference because I happen to be good at the thing they want me to do. So a more complete answer to your original question is that I choose and seek out projects based on a matrix of factors including the scale/scope of impact, how likely I am to get the gig, how much of an advantage I think working with me would offer them over whatever the replacement or alternative would be, how much it would pay, the level of intrinsic interest I have in the work, how much I would learn from doing it, and how well it positions me for future opportunities I care about.
What are the frameworks you find most helpful in your work supporting clients with their decision-making?
Besides theory of change, which tessa mentioned, I've found myself increasingly focusing on the "front end" of decision-making rather than very detailed tools to choose from among defined alternatives, because in my experience leaders and teams generally need help putting more structure around their decision-making process before they can engage productively with such methods.
One innovation I've been working on is a tool called the decision inventory, which is a way for clients to get a sense of the landscape of decisions facing them and prioritize among those decisions. It's a much more intuitive exercise and can be done much more quickly than a formal decision analysis or cost-benefit model, so it lends itself well to introducing the concepts and building buy-in among a team to do this kind of work. It can be especially helpful for teams because different team members have a different view of the decision landscape, and will have different ideas about what decisions are important for which reasons, so activating that collective intelligence can be educational for leaders.
I previously asked a batch of questions which I'd be interested to hear your take on:
(My own tentative answers, and those of a bunch of other people, can be seen at the linked post.)
What are the main careers paths/options you considered (or are considering) as alternatives to your current path? What led you to choose your current path rather than those alternatives?
If you were advising someone five years behind you, but on a somewhat similar track (a MBA type leaving a senior role at a mission-driven organization to become an independent consultant), what would your top pieces of advice be re:
Thank you!
What are the major risks or downsides that may occur, accidentally or otherwise, from efforts to improve institutional decision-making?
How concerned are you about these (how likely you think they are, and how bad would they be if it happened)?
As part of the working group's activities this year, we're currently in the process of developing a prioritization framework for selecting institutions to engage with. In the course of setting up that framework, we realized that the traditional Importance/Tractability/Neglectedness schematic doesn't really have an explicit consideration for downside risk. So we've added that in the context of what it would look like to engage with an institution. With the caveat that this is still in development, here are some mechanisms we've come up with by which an intervention to improve decision-making could cause more harm than good:
I think all of these risks are very real but also ultimately manageable. The most important way to mitigate them is to approach engagement opportunities carefully and, where possible, in collaboration with people who have a strong understanding of the institutions and/or individual decision-makers within them.
In your opinion, how much of a factor in making good decisions is the actual process vs a healthy team culture and psychological safety amongst team members to challenge others/take risks?
On what timescales do you see most of the impact from improving institutional decision-making starting to kick in, and what does the growth function look like to you?