www.sciencedirect.com/science/arti... Behind this paper: a physician from Iran, a social scientist from Australia, a behavioral scientist from Norway, a history and philosophy enthusiast from the US, and a data scientist from the US.

To ensure AI delivers meaningful value, we need five fundamental tools: a mirror, a flashlight, a microscope, a paintbrush, and a podium. The mirror helps us examine our own motivations and values—ensuring we're building AI for the right reasons.

www.nature.com/articles/s41... We need AI that will keep humans on the rails, and humans that will keep AI on the rails. Bruno Latour would say AI systems aren't neutral tools but active participants in networks that reconfigure relationships between humans, institutions, and knowledge production.

datascienceandhealth.ubc.ca/events/ai-fu... Join us at the AI & Future of Medicine at the University of British Columbia in Vancouver, Canada on November 15-16, 2025 as we forge a path forward in the chaos that the AI hype has wrought.

Medical education does not exist in a vacuum, and attempts to reform it in isolation are fundamentally inadequate if the broader healthcare system remains broken. (The illustration is provided by Dancing with Markers.)

sites.google.com/view/ai-fait... Please join us at the Vatican on September 8th for dialogues around AI and faith. "Faith and Artificial Intelligence: Using language models to promote human connection“

arxiv.org/abs/2508.16519 How do we make AI worth its cost? Simple: We fix the world. First up: Publish or perish culture.

www.techrxiv.org/users/953594... We are at a critical juncture where AI could either extend scientific progress or flood the literature with confident mirages—scientific deepfakes that erode the trust science needs to correct itself.

open.spotify.com/show/7w2YAD1... For those who were not able to attend last Monday's event on the bias of language and how LLMs will shape the course of society, here is a link to the audio recordings of the talks and panel discussions.

arxiv.org/abs/2508.00952 Academic laboratories face mounting resource constraints: budgets are tightening, grant overheads are potentially being capped, and the market rate for data-science talent significantly outstrips university compensation.

forms.cloud.microsoft/pages/respon... Please join us at the National University of Singapore (NUS) Seminar for Responsible AI for Eldercare on August 27th from 14.00 - 16.30 at MD1, Tahir Foundation Building. The global population is aging while the healthcare workforce is shrinking.

sites.google.com/view/mithic-... A meeting of the hearts and souls at MIT. Please join us on August 18th (Monday) for a day of reflection in this age of AI. MIT Critical Data and MIT Global Languages partnered to explore the bias of language itself and how language models might shape human behavior.

elty.it/medico/hacka... Please join us at Google Italy office in Milan on September 3-4 as we explore foundational issues with AI in the health space through hands-on workshops on data interrogation and critical thinking.

www.biomedcentral.com/collections/... Artificial intelligence is not about coding or developing algorithms. It's about critical thinking and reimagining systems equipped with powerful tools that retrieve information, create and validate knowledge, call out biases, and challenge the statusquo

Bangkok datathon mentors July 2025. Only 3 mentors including myself were not local. This is the only sustainable and scalable strategy. AI by us for all of us. The students from different schools planned the entire event.

informatics.bmj.com/content/32/1... To everyone building AI models, please don't stop when you have a model that performs accurately on an unseen test set. You need to figure out whether the model uses "shortcut" features.

news.mit.edu/2025/changin... AI is our chance to rewrite the rules. If we fail, it’s because we failed to dream big enough about how a reimagined world could look.

www.sciencedirect.com/science/arti... AI technologies contribute to climate change and sociopolitical instability due to their high consumption of natural, energy and human resources that are typically "extracted" within power structures.

journals.lww.com/ccejournal/f... In this paper, we investigated the model performance of GOSSIS (Global Open Source Severity of Illness Score) under geographical, temporal and pandemic dataset shift. AI Models should be bound by space and time. In other words, AI models have expiration dates.

dl.acm.org/doi/10.1145/... Machine learning courses are not teaching students how to understand the data. Everyone is racing just to build the next model with the best accuracy based on very flawed data. AI is tempting us with shortcuts to traditional rewards such as papers and citations.

www.sciencedirect.com/science/arti... It is crucial that AI developers understand the "backstory" of the data. Who made it to the cohort, and who did not? Sampling selection bias leads to spurious associations and/or shortcut features that are easily learned by algorithms.

link.springer.com/article/10.1... It is alluring to think that AI will deliver care to the 4.5 billion without access to a health system. But "generating workflows that require building trust and relationships" cannot be conjured by AI.

www.sciencedirect.com/science/arti... If your business model is still selling algorithms, please stop. The accuracy of models is limited in time and space. The pursuit of generalizability is misguided. AI should be local, iterative, reflective and reflexive.

www.biomedcentral.com/collections/... We are still accepting submissions to a special collection around AI for the journal Critical Care.We are not interested in papers that are only developing algorithms with near-perfect accuracy.We are already drowning in models. We are particularly interested in

www.medrxiv.org/content/10.1... This paper is published today behind a paywall so I'm sharing the preprint here. It describes a causal inference framework to evaluate impact of life-sustaining therapies in the ICU across different demographic axes.

www.sciencedirect.com/science/arti... The collection of extensive demographic data raises important concerns that include the construction of intersectional social categories (ie, race and its shifting meaning in different sociopolitical contexts), the risks of biological reductionism, (cont.)

www.atsjournals.org/doi/10.1164/... Not only are the medical devices and biomarkers not optimized across patient demographics and other features, the intensity/frequency of measurement varies across patients.

www.jscai.org/article/S277... Knowledge, our understanding of truth, is purely based on experiences and observations, and that there is no such thing as “ground truth”. How we see things objectifies, or more aptly, “subjectifies” those things.

journals.plos.org/digitalhealt... The pursuit of diversity goes much deeper than simply a core tenet of some "liberal" ideology. For artificial intelligence, specifically reinforcement learning, successful adaptation to changing conditions requires a level of diversity among agents' actions.

jbiomedsci.biomedcentral.com/articles/10.... It is unrealistic to expect the machine learning community to be able to understand the social patterning of the data generation process.

www.medrxiv.org/content/10.1... How can we do fairness evaluation and health service research when we don't have accurate demographic labels that reflect social determinants of health in the majority of EHR datasets?

In order to advance AI in healthcare, it is crucial that developers understand (1) how the data came about, (2) the accuracy of the instruments and devices used to measure physiologic signals, bmjopen.bmj.com/content/15/1...