EA - Why EA needs OR by wesg

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Why EA needs OR, published by wesg on July 21, 2022 on The Effective Altruism Forum. Summary Operations Research (OR) is the field of applying advanced analytics to make better decisions. That is, making the best possible decision under constraints and uncertainty – exactly the problem that EAs try to solve every day. Given the relevance and apparent lack of engagement with OR, I think this is a neglected skill set within EA. In particular, OR offers tools and research for making large-scale projects more effective [more], a talent pool already skilled with these tools able to contribute to and propose relevant projects [more], rigorous conceptual frames for thinking about large-scale decision-making problems [more]. The key takeaways of this post are: EA Orgs should consider whether there are opportunities to apply off-the-shelf OR tools within your programs [more] or if focused OR research would be useful [more]. Community Builders should allocate resources towards recruiting OR PhD students as they are both already skilled and generally receptive to EA ideas [more]. Students should consider whether any existing or potential OR projects excite them, and whether it is worth it to learn more about OR on their own or by taking classes. Author Note: I am a current OR PhD student at MIT, so I have a good understanding of OR academia but have less visibility into the EA landscape and the existing operational sophistication of EA orgs. I’d like to thank Daniel Wang, Juan Gil, James Aung, Emma Abele, and Sudhanshu Kasewa for feedback on this post and more generally for their support in bringing me into the EA community. What is OR? Operations research (OR; sometimes also called management science, decision science, operations management, systems engineering, industrial engineering) is a combination of applied math, computer science, and economics focused on developing the mathematical theory and techniques necessary to solve large scale decision-making problems and applying such tools in practice. Solving a decision-making problem usually implies finding the “best” decision out of a large decision space defined by a series of constraints (eg, maximizing the impact of bednet distribution subject to cost and logistical constraints). Mathematically, this is a constrained optimization problem. As such, the main technical pillar of OR is modeling and solving these types of optimization problems. OR is used widely across industry for optimizing decisions about resource allocation, logistics, supply chain management, scheduling, manufacturing, and much more (see Appendix 1: OR Tools and Applications, and Appendix 2: Why haven’t I heard of OR?). Why EA needs OR There are several ways I can see OR being useful within EA: tools and research for making large-scale projects more effective, a talent pool already skilled with these tools able to take on relevant projects, and more rigorous conceptual frames for thinking about large-scale decision-making problems. Relevant Research The following is a nonexhaustive list of existing OR research that could be of interest to the EA community. I believe this list demonstrates that There exists research which is already useful There exists significant altruistic energy within the OR community There exists substantial opportunity for more focused OR research on core cause areas that could be made more effective with the right partnerships (see next section) Biosecurity “Where to Locate COVID-19 Mass Vaccination Facilities?” Bertsimas, Dimitris, et al. Naval Research Logistics (NRL).. “Designing Response Supply Chain Against Bioattacks.” Simchi-Levi, David, et al. Operations Research.. “Forecasting COVID-19 and Analyzing the Effect of Government Interventions.” Li, Michael Lingzhi, et al. Operations Research.. “OR’s Next Top Model: Decision Mode...