TL;DR: Witness is a small app that lets you log donations you’ve made elsewhere and see them as a growing portfolio of estimated impact. I built the prototype from the behavioural research on giving, and I would value your feedback before going further.
I’m a researcher based in Belgium, with a PhD in economics and management mainly focused on human-computer interaction. My background is in mixed-methods research on how people respond to technology.
Witness lets you log a donation made elsewhere, to a GiveWell top charity or any other organisation, and translates it into estimated impact. You see specific units per programme, such as children receiving vitamin A supplementation or bednets distributed, along with cumulative lives saved and healthy life-years. The app also offers an annual giving goal (including the 10% Pledge), recurring gifts, milestones and a lifetime projection. Your data stays in your browser, and anonymous usage data is only collected if you opt in. You can try the first prototype made using AI here: https://witness-impact-portfolio.lovable.app
The problem I’m focusing on is retention. In Giving What We Can’s 2023-2024 impact evaluation, only about 30% of 10% Pledgers were still recording donations on the platform five years after pledging. My hypothesis is that existing tools record donations well but rarely help people see, year after year, what those donations are achieving.
Witness handles no money and isn’t affiliated with GiveWell or any listed charity. It is a personal project. I built it using Lovable and Claude. Comments are welcome here, or you can message me directly. Thank you for reading.
Quentin
Aknin, L. B., Dunn, E. W., Whillans, A. V., Grant, A. M., & Norton, M. I. (2013). Making a difference matters: Impact unlocks the emotional benefits of prosocial spending. Journal of Economic Behavior & Organization, 88, 90–95. https://doi.org/10.1016/j.jebo.2013.01.008
Cryder, C. E., Loewenstein, G., & Scheines, R. (2013). The donor is in the details. Organizational Behavior and Human Decision Processes, 120(1), 15–23. https://doi.org/10.1016/j.obhdp.2012.08.002
Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125(6), 627–668. https://doi.org/10.1037/0033-2909.125.6.627
GiveWell. (2024, April). How much does it cost to save a life? https://www.givewell.org/how-much-does-it-cost-to-save-a-life
Giving What We Can. (2025, June 3). GWWC’s 2023–2024 impact evaluation (executive summary). Effective Altruism Forum. https://forum.effectivealtruism.org/posts/AywMrGRvtA7Rq5b6r/gwwc-s-2023-2024-impact-evaluation-executive-summary
Karlan, D., & Wood, D. H. (2017). The effect of effectiveness: Donor response to aid effectiveness in a direct mail fundraising experiment. Journal of Behavioral and Experimental Economics, 66, 1–8. https://doi.org/10.1016/j.socec.2016.05.005
Sailer, M., & Homner, L. (2020). The gamification of learning: A meta-analysis. Educational Psychology Review, 32(1), 77–112. https://doi.org/10.1007/s10648-019-09498-w
Silverman, J., & Barasch, A. (2023). On or off track: How (broken) streaks affect consumer decisions. Journal of Consumer Research, 49(6), 1095–1117. https://doi.org/10.1093/jcr/ucac029
van der Bles, A. M., van der Linden, S., Freeman, A. L. J., & Spiegelhalter, D. J. (2020). The effects of communicating uncertainty on public trust in facts and numbers. Proceedings of the National Academy of Sciences, 117(14), 7672–7683. https://doi.org/10.1073/pnas.1913678117
Hi - I love the idea behind this app.
I've logged in and started logging all my donations. At the moment, I feel like the app provides value by essentially mutiplying the amount donated by a relevant multiplier (e.g. divide donations by $5,000 to get lives saved, or multiplying donations by 10x to see the number of animals helped).
I think this is good- but I can imagine an app which uses simulations/case-studies like https://anyhumanever.com/ or https://spawn-again.vercel.app/ to provide people with a way of visualising who they are helping and by how much (E.g. if you donated £5,000 to AMF you could draw a random life and see who it is you most likely helped save). Or if you donated £5,000 to THL you could get some more data on how many hours of hurtful/disabling pain you removed (drawing from their own evaluations which are numerous). Basically the app could become a place which centralises cost-benefit-evaluation data and then multiplies it by user's donation portfolio. This sounds like a heavy lift to me, but with coding agents all sorts of things are possible.
Best of luck with the project!
Thank you so much, it made my day to read that you’ve started logging your donations! You’re right about how it works for now. Witness takes GiveWell’s cost per outcome and turns each gift into a range, which is useful but maybe a bit dry.
I love the idea of drawing a life, and it could also give people a reason to come back between donations. I’d frame it as a portrait of the kind of person a gift typically helps (a child in a region where AMF distributes nets, for example), since GiveWell’s numbers can’t tell us who exactly.
Animal welfare is a gap I need to fill, because a gift to THL currently shows no impact at all. Hours of pain averted, based on the Welfare Footprint Project’s estimates, look like a good place to start. Thanks again for taking the time to try the app and write this!