What building a research institute at 100% adoption actually looks like
70 years of AI hype
Quoting from Olivia Guest et al. (2025) "Against the Uncritical Adoption of AI Technologies in Academia."
AI Economy Institute - Microsoft Research
The AI Economy Institute (AIEI) is Microsoft’s flagship think tank dedicated to shaping an inclusive, trustworthy AI economy. We building a network of scholars and convening that network with our subject matter experts to explore how artificial intelligence is transforming work, education, and productivity – and making this knowledge base available to policy-makers, educators, and […]
As more Americans adopt AI tools, fewer say they can trust the results | TechCrunch
AI adoption is rising in the U.S., but trust remains low, with most Americans concerned about transparency, regulation, and the technology’s broader societal impact, according to a new Quinnipiac poll.
DAIR Institute
The Distributed AI Research Institute is a globally distributed organization of academics, activists, and engineers conducting community-rooted research.
The AI Roles Continuum: Blurring the Boundary Between Research and...
The rapid scaling of deep neural networks and large language models has collapsed the once-clear divide between "research" and "engineering" in AI organizations. Drawing on a qualitative synthesis...
Charting AI’s Role in Scientific Discovery — Renaissance Philanthropy – A brighter future for all through science, technology, and innovation
Renaissance Philanthropy, with support from Google.org , is conducting a landscape study of AI integration in scientific research — and we want your perspective.
Cosmik Updates: February 2026 - Cosmik Labs
@atproto.science @cosmik.network Raising a question for the ATProto science community: Can AI agents be legitimate participants in research ecosystems? What would make their outputs trustworthy?
Implementation Science for AI Integration in Digital Health Systems
We systematically reviewed studies of implementation science frameworks used for healthcare AI deployment (2020-2026). Following PRISMA 2020, we searched MEDLINE, Embase, Web of Science, and Scopus and included 87 empirical studies. CFIR was most common (42.5%), followed by RE-AIM (28.7%) and EPIS (18.4%). The most frequent barriers were data infrastructure limitations (67.8%), clinician trust deficits (58.6%), and regulatory uncertainty (52.9%). Implementation success was associated with organizational readiness (r=0.64, p
The State of Sovereign AI Adoption (Research) | Cohere
Understand the key drivers and barriers for adopting sovereign AI across critical industries, based on an IDC InfoBrief commissioned by Cohere.
Why the AI Policy Debate Should Focus More on the Harness and Protocol Layers
A conversation with Raffi Krikorian, CTO of Mozilla and author of the newsletter Owners Not Renters.
My AI Adoption Journey
My experience adopting any meaningful tool is that I've necessarily gone through three phases: (1) a period of inefficiency (2) a period of adequacy, then finally (3) a period of workflow and life-altering discovery.
AI Is Changing Who Wins Research Grants
A new study from the Northwestern Innovation Institute finds that proposals showing stronger signs of AI-assisted writing were more likely to receive support from the National Institutes of Health, while also tending to align more closely with ideas that had already been funded.
What we can’t measure about AI – yet | Aeon Essays
The costs of transformative innovations are immediately clear: it’s the longterm gains that are hardest to understand
Absolutely incredible figure from this journal article arguing that AI should be accepted into the publication and peer review process. #MedSky doi.org/10.1515/cclm-2025-1180
Absolutely incredible figure from this journal article arguing that AI should be accepted into the publication and peer review process. #MedSky doi.org/10.1515/cclm-2025-1180
