Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biologically inspired design is the use of designs found in nature for analogy and inspiration in designing technological systems. Biological systems, processes, and strategies provide insights into sustainable and adaptable design that can inspire technological innovation. Thus, using nature for inspiration and emulating nature is a research field growing in scope, activity, and importance.We recently organized two workshops on “Charting a Course for Computer-Aided Bio-Inspired Design” sponsored by the United States National Science Foundation (NSF). These workshops brought together a few dozen leading researchers in computational methods and tools for biologically inspired design (http://designengineeringlab.org/BID-workshop/NSF_BID_Workshops.html). An edited volume based on the workshops and containing a dozen chapters describing the state of the art is forthcoming. Here, we briefly summarize some of the main findings from the two workshops.Biologically inspired design seeks to exploit biology for several different kinds of design such as sustainable design, creative design, and complex system design. Although these different kinds of design are mutually compatible and consistent—one can have complex systems that are sustainable, for example—the three design types have different emphases and foci. Some of the discussion at the first workshop focused on sustainable design and complex system design.The goal of biologically inspired sustainable design is to use biology as an inspiration for designing technological products that are ecologically sustainable. Although biological systems are not always optimal, they typically use only local and abundant resources, and often are very efficient in the use of resources such as energy and water. Of course, this does not guarantee that biologically inspired designs will be necessarily sustainable, but it promises that they may be more sustainable than equivalent products available in the market today. Consider the following specific cases:The goal of biologically inspired complex systems design is to use the characteristically complex interactions found in nature as a design guide to technological systems that are complex and integrated among their constituent components. Although biologists often welcome complexity, engineers typically attempt to avoid it. Approaching complex system design from a biologist’s perspective, such as using complexity to allow for mechanisms for coping with design failures appears a promising avenue with the following observations:Some of the discussion at the second workshop focused on the development of a potential research program at NSF. Here is one possible design for the program: NSF would invite proposals for research on biologically inspired design that has much potential to solve urgent and critical challenges faced by the United States and the world as a whole, including ecological sustainability, design innovation and complex system design. Proposals must be from suitable multidisciplinary teams (i.e., members might include biologists, cognitive scientists, computer scientists, designers, and engineers), addressing small to medium scale designs (such as household products or automotive systems), have demonstrated computational and educational components, and have a well-formed evaluation plan. Suitable research topics include but are not limited to the following:The proposed research should be extensible, and must be shared in order to promote community building.In summary, it is clear that recent research efforts across the disciplines of biology, computing, design, and engineering have attempted to address the various problems associated with not only developing biologically inspired designs, but also teaching students how to develop biologically inspired designs. It is also evident that there is a need for much additional work on refining the proposed methods and tools as well as developing new methods to address current limitations. We recommend that NSF establish a new crosscutting program in biologically inspired design that seeks to fund transformative research as briefly summarized above. Such a program can support high risk-high reward research that otherwise has no home in NSF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it