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CODE@MIT

@codemit.bsky.social

Conference on Digital Experimentation (CODE@MIT) hosted by the MIT Initiative on the Digital Economy

CODE@MIT @codemit.bsky.social · 28/08/2026

Submissions for CODE@MIT are open until Sept 13th. As @dholtz.bsky.social noted www.linkedin.com/feed/update/... we're particularly interested in these topics this year:

- New metrics and outcomes for changing products and user experiences (e.g., designing outcome measures for conversational, generative, and other complex products; measuring productivity and the quality of product-development and experimentation processes; distinguishing meaningful outcomes from engagement and other intermediate signals; constructing metrics from text and high-dimensional behavioral data; validating AI-generated labels, evaluations, and measures)

- Using experiments to uncover causal mechanisms (e.g., moving beyond average treatment effects and ship/no-ship decisions to understand why interventions work; using process data (including AI-mediated conversations) to reconstruct heterogeneous user experiences; causal mediation and mechanism discovery; identifying which components of complex or AI-based treatments generate observed effects; using AI tools to analyze previously intractable qualitative and behavioral data)

- Experimental design under rapid iteration and treatment abundance (e.g., designing experiments when AI and other technologies make treatments inexpensive and continuously generated; exploring large, continuous, or combinatorial treatment spaces; allocating scarce traffic across many candidate interventions; integrating offline and synthetic evaluation, factorial designs, bandits, and sequential experiments; determining the diminishing value of additional treatments and iterations)

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Reposted by CODE@MIT

Dean Eckles @eckles.bsky.social · 23/07/2026

We're excited to be hosting CODE@MIT again this fall! We invite a mix of work involving experimentation — methods, cool experiments, industry reports, etc. Look for more info later on this year's invited speakers.

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Reposted by CODE@MIT

Rafael M Batista @rafmbatista.bsky.social · 23/07/2026

This is an excellent conference. I attended a few years ago to present a digital experiment I ran and have been itching for an excuse to return. Call for abstracts now open!

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CODE@MIT @codemit.bsky.social · 23/07/2026

📢 Call for abstracts for the Conference on Digital Experimentation (CODE@MIT), which takes place Nov 13-14. 📨 Submit your best work by *Sept 13th*! ide.mit.edu/events/2026-...

ide.mit.edu

2026 CODE@MIT: The Conference on Digital Experimentation at MIT

Join us for CODE@MIT 2026, the conference that's reshaping how researchers and practitioners think about digital experimentation.

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Reposted by CODE@MIT

Ben Waber @bwaber.bsky.social · 03/12/2025

Next was an intriguing talk by Iavor Bojinov on the design and analysis of switchback and panel experiments at @codemit.bsky.social youtu.be/Uz1b0IYs_NU?... (5/11)

youtu.be

CODE@MIT 2025: Plenary Session 1

YouTube video by MIT Initiative on the Digital Economy

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Reposted by CODE@MIT

Ben Waber @bwaber.bsky.social · 03/12/2025

Next was a great talk by Ramesh Johari on network congestion experiments and interference at @codemit.bsky.social www.youtube.com/watch?v=W5vW... (3/11)

youtube.com

CODE@MIT 2025: Plenary Session 2

YouTube video by MIT Initiative on the Digital Economy

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CODE@MIT @codemit.bsky.social · 08/12/2025

Videos from this year's plenary talks on digital experimentation are now available: www.youtube.com/@mitide/videos

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CODE@MIT @codemit.bsky.social · 05/09/2025

📢 Call for abstracts for the Conference on Digital Experimentation (CODE@MIT), which takes place Nov 14-15. 📨 Submit your best work by *Sept 12th*! ide.mit.edu/events/2025-... Here are three topics we're particularly interested in getting more submissions on this year:

With just ten days left until the final abstract deadline, I wanted to highlight some exciting research directions we're hoping to see at CODE 2025 (Nov 14-15 at MIT). This year, we are particularly interested in attracting submissions on the following topics:

1. Meta-experimental methodology and organizational learning from experimentation (e.g., how do systematic experimentation practices influence organizational decision-making? What factors drive institutional adoption of experimental methods? How can we develop frameworks for measuring the aggregate scientific and practical value of experimentation portfolios?)

2. Experimental evidence as foundational input for causal inference and predictive modeling (e.g., integrating randomized controlled trials with observational methods in econometric modeling, data-driven optimization, and synthetic control approaches; RCTs as inputs to media mix models; validation frameworks for surrogate endpoints and proxy measures)

3. AI and experimentation (e.g., AI-assisted experimental design and analysis; RCT-based evaluation frameworks for AI systems; using experiments to improve AI system performance; AI systems as experimental subjects or tools)

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