Positech is back #CSCW2026 !
Join the wonderful group of organizers for a day of collaborative discussions on how social technologies can help people build the capacity to care about global challenges in ways that are both effective and sustainable :)
People today are drowning in awareness of suffering with nowhere productive to put it. This is a problem that social technology research can and should tackle!
At our #CSCW2026 workshop, we’ll spend the day exploring how to design toward sustainable care.
Apply by Aug 3: positech.github.io/cscw2026
People today are drowning in awareness of suffering with nowhere productive to put it. This is a problem that social technology research can and should tackle!
At our #CSCW2026 workshop, we’ll spend the day exploring how to design toward sustainable care.
Apply by Aug 3: positech.github.io/cscw2026
[Qualitative Researchers]
We are researching how qualitative researchers are using and/or thinking about AI in their research pipeline.
If you are a qualitative researcher and can spare some minutes, please answer this survey: cornell.ca1.qualtrics.com/jfe/form/SV_...#AI#QualitativeResearch
Is the only way we can create algorithms that people understand to make them trivially simple? We argue, no.
People can predict the behavior of algorithms that are arbitrarily complex, if and only if they are available, compact and aligned.
arxiv.org/abs/2601.18966
Is the only way we can create algorithms that people understand to make them trivially simple? We argue, no.
People can predict the behavior of algorithms that are arbitrarily complex, if and only if they are available, compact and aligned.
arxiv.org/abs/2601.18966
Alignment is the factor with greatest flexibility, perhaps because people are used to errors in their algorithms.
Users are willing to tolerate relatively high error rates if a single obvious feature has more signal than noise, e.g., if the like count is highly correlated.
This work was done with an amazing team! Thanks to my collaborators and advisors: @helenasresearch.bsky.social, Ignacio Javier Fernandez, Chijioke Chinaza Mgbahurike, Ralf Herbrich, Jeff Hancock, @mbernst.bsky.social
It'll get presented this fall at #CSCW2026 but should be out sooner in PACM HCI
Is the only way we can create algorithms that people understand to make them trivially simple? We argue, no.
People can predict the behavior of algorithms that are arbitrarily complex, if and only if they are available, compact and aligned.
arxiv.org/abs/2601.18966
These properties also shape which mental models users deploy when reasoning about algorithm behavior.
Users default to incorporating highly available engagement signals into their mental models regardless of whether they are present in the underlying algorithm.
When users cannot explain an algorithm with one clear idea, they often juggle multiple (incorrect) mental models.
Compactness becomes a kind of crumple zone: by vaguely combining additional factors, users avoid being clearly proven wrong.
Is the only way we can create algorithms that people understand to make them trivially simple? We argue, no.
People can predict the behavior of algorithms that are arbitrarily complex, if and only if they are available, compact and aligned.
arxiv.org/abs/2601.18966
We test this theory in a large pre-registered study (N=1250) where participants predicted the behavior of 25 social media feed-ranking algorithms systematically varying the ACA properties, ranging from single-feature rankings to complex, LLM-based systems.
We find that users predict algorithm behavior accurately if and only if all three properties hold, regardless of algorithmic complexity.
For non compliant algorithms, prediction accuracy falls to around chance.
Is the only way we can create algorithms that people understand to make them trivially simple? We argue, no.
People can predict the behavior of algorithms that are arbitrarily complex, if and only if they are available, compact and aligned.
arxiv.org/abs/2601.18966
It is tempting to say that unpredictability is inevitable as algorithms grow more complex, in our social media feeds and beyond.
But that intuition fails. Predictability hinges instead on whether users can faithfully translate an algorithm’s behavior into a usable mental model.
Three factors matter here: (cognitive) availability means the algorithm is built on concepts users already reason with, (conceptual) compactness means those concepts cohere to a single construct, and alignment means people and the algorithm apply the concept in similar ways.
Our new article in @science.org enables social media reranking outside of platforms' walled gardens.
We add an LLM-powered reranking of highly polarizing political content into N=1256 participants' feeds. Downranking cools tensions with the opposite party—but upranking inflames them.
A novel new study finds you can reduce polarization on X simply with a simple change to the algorithm. I spoke with the researchers: www.platformer.news/stanford-pol...
We're doing a follow-up (in-person) workshop @ CSCW! Positech 2: Design for Hope will explore how design methodologies can help us envision and achieve positive social futures AND how these processes cultivate hope in the face of otherwise overwhelming challenges. More: positech-cscw-2025.github.io
Following up on last year’s Positech workshop, thrilled to announce our workshop @acm-cscw.bsky.social 2025 on how design might help us cultivate deliberate hope in the face of complex societal challenges, whether in our everyday or broader aspirations 🌱
cfp 👉 positech-cscw-2025.github.io
a couple of hours before my keynote, I went through an intense negotiation with the organisers (for over a hour) where we went through my slides and had to remove anything that mentions 'Palestine' 'Israel' and replace 'genocide' with 'war crimes'
1/
i think it is a sign of low character to post something controversial knowing it will get angry comments and then insult the people who responded to your ragebait
AI companions aren’t science fiction anymore 🤖💬❤️
Thousands are turning to AI chatbots for emotional connection – finding comfort, sharing secrets, and even falling in love. But as AI companionship grows, the line between real and artificial relationships blurs.
I'm so excited to join the CS department at Johns Hopkins University (@jhu.edu) as an Assistant Professor! I'm looking for students interested in social computing, HCI, and AI—especially around designing better online systems in the age of LLMs. Come work with me! piccardi.me
I'm so excited to join the CS department at Johns Hopkins University (@jhu.edu) as an Assistant Professor! I'm looking for students interested in social computing, HCI, and AI—especially around designing better online systems in the age of LLMs. Come work with me! piccardi.me
I'm excited to announce that I’ll be joining the Computer Science department at Johns Hopkins as an Assistant Professor this Fall! I’ll be working on large language models, computational social science, and AI & society—and will be recruiting PhD students. Apply to work with me!
BREAKING: We're sending an open letter to universities across the country, offering support and urging them to reject pressure to punish international students and faculty for exercising their First Amendment rights.
Schools must hold firm against the Trump administration's censorship attempts.
I just sent our university president and provost an urgent request to defend First Amendment freedoms at Stanford, given this administration’s willingness to punish those who disagree with it.
I urge you to do the same with your university leaders.
Zuck positioned these changes as a return to history practice but, for these policy changes, that is untrue. The specific examples I called out above have been prohibited on the site since I wrote the first set of hate speech standards in 2009. 🧵 8/11
Dismantling the fact-checking infrastructure is going to be super handy when things start going wrong in the new administration and they want to redirect blame onto the left.
My advisor warned me that academics trend towards bitterness. He encouraged me to intentionally resist this, remember where I came from, and never forget the privilege of getting to spend a life working with knowledge and ideas. He too said that bitterness and resentment is easy.
In high school, my social studies teacher took me aside and told me that "cynicism was the easy path" and that I needed to resist it. It's probably the most important thing I learned in school.
How do people *really* read Wikipedia? 📖 👀
We explored how readers navigate, fall into rabbit holes, and engage with information in a chapter for the ‘Handbook of Computational Social Science,’ edited by @tahayasseri.bsky.social. Stay tuned for the full book! 📚
Preprint: arxiv.org/abs/2501.00939
The future (imo) will be filled with a constant ache and continual search for — with increasingly diminished capacity for discovery / identification of — authenticity.
I am fascinated by the people at Meta who think this is a *good* idea in exactly the same way I'm fascinated by conspiracy theorists.
It just seems so patently awful to me. And in ways that every sensible person I know would immediately grasp.
New paper: Do social media algorithms shape affective polarization?
We ran a field experiment on X/Twitter (N=1,256) using LLMs to rerank content in real-time, adjusting exposure to polarizing posts. Result: Algorithmic ranking impacts feelings toward the political outgroup! 🧵⬇️
Academic job market post! 👀
I’m a CS Postdoc at Stanford in the Stanford HCI group.
I develop ways to improve the online information ecosystem by designing better social media feeds & improving Wikipedia. I work on AI, Social Computing, and HCI.
piccardi.me 🧵
This paper argues that online spaces become ghost towns because it's too easy to lurk without contributing, and that asking people to regularly re-commit—or the incoming messages start getting muted—reverses the trend. arxiv.org/abs/2410.23267
It works! #cscw2024 paper by @popowski.bsky.social
.