Remember that AI class I’ve been blogging about? It’s got me thinking. Here is a take on what is collaboration that I would not have noticed without the priming from our discussion a couple week’s ago: “In a formulation that was galling to both sociologists and scientists, [Latour] once argued that Louis Pasteur did not just, as is commonly accepted, discover microbes; rather, he collaborated with them.”
From same article as above https://onlinelibrary.wiley.com/doi/epdf/10.1002/sdr.1596
Social organizational network as an important factor as well— power mapping with Spectrum of Allies exercise useful?
“[H]aving a technically sound model is not enough to assure widespread and effective use …” — additional elements, such as a champion in a leadership role and clearly defined problem to model help.
A goal that I have not yet attained: finding a keeper-of-the-model in the client organization, who can run additional scenarios.
I missed it but the recording is high quality: https://www.youtube.com/watch?v=p8EtCUyLxIE
I missed the last Augmented Intelligence class, but two times ago we read and discussed Horvitz,E. (1999) Principles of Mixed-Initiative User Interfaces. CHI 99. http://erichorvitz.com/chi99horvitz.pdf
This is about 20 years old, but still makes sense to me. The presenter paired it with some
I’ve been way to busy helping different groups wring insights from GBD estimates with microsimulation. But in my copious spare time, I’ve been enjoying a paper that studies what factors allow different groups to use models.
The authors focus on a particular Systems Dynamics model of the health system, but I think their finding can be generalized to other models and other systems. For example, “the actual utility of the model is dependent upon a match between the scope of the community’s defined problem and the capabilities of the model.” That makes sense to me, but I’m not sure I thought of it explicitly before I saw it written out.
I have been a fan of this educational offering for a while now, and I have been mentioning that for a while now, too. But I am moved to say it again, because I’m planning a four-session Intro to Python training for aspiring Health Metrics Scientists, and the SWC curriculum is making that so easy. It could have been so hard. ❤ u SWC.
Some papers from this summer’s SummerSim (editor’s note: summer-before-last) are available online now:
- Untangling Uncertainty with Common Random Numbers: A Simulation Study
- Microsimulation Models for Cost-Effectiveness Analysis: A Review and Introduction To CEAM
I sat-in on a CSE seminar recently, where a big crowd is exploring the state of the art in human-and-computer-together intelligence. It was really fun. The topic was a discussion of a paper on human/computer collaboration from the 1990s:
Grosz, B. J. (1996). Collaborative systems (AAAI-94 presidential address). AI magazine, 17(2), 67.
But just as fun as the classic article and discussion it inspired, was an even older vision of what digital assistants might be, from Apple in the 1980s:
I left thinking that a knowledge navigator like the one Apple envisioned is not really collaboration, but when it makes the Brazil and Sahara simulations work together, that might be collaboration. But to be a true collaborator, both agents need to want something (or “desire” something?) for themselves.
I hope I have time to attend again soon.
I’m not sure this list is useful, but at least I’ll find it when I next search:
I read random papers once in a while from the AMS Math Reviews program, and I read one recently about an MCMC approach to X-ray imaging. It was a fun, detailed look at a few different ways to do sampling, and use effective sample size to figure out which worked better when.
It did also leave me wondering what the giant X-ray machines buried 1,000 feet underground are for, though.