AI News, Artificial Intelligence for Computational Sustainability: A Lab Companion/Preface
- On Thursday, October 4, 2018
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Artificial Intelligence for Computational Sustainability: A Lab Companion/Preface
Long-term planet sustainability requires the intelligent use of intelligent computational systems, at least if we accept that planet-transforming technology and over-population are here to stay, taxing human abilities to plan intelligently and with the long-view.
This requires socially-engaged computational thinkers who can build and evaluate intelligent systems technology, informed by sustainability applications, and able to work across disciplinary lines.
To engage computing students on sustainability problems doesn’t simply require an AI education, leaving to hope that they will later see and act on its relevance to sustainability, but the connections are best made when they are made explicit, else the knowledge may be left inert in the student (Bransford, et al., 1990),
This text is motivated by a desire for increasing and sustaining the numbers and diversity of the computing community engaged in environmental and societal sustainability, and in particular is focused on introducing sustainability content into undergraduate courses on AI.
In addition to describing the AI and sustainability lab text generally, the chapter discusses the implications of the project for integration of research and education, and communicating science to the public;
Wikipedia’s popularity as a source for students and many others, faculty included (though typically not in their areas of expertise), make accurate and complete communication of scientific knowledge in the medium all the more critical.
for example, calls upon its members to contribute to Wikipedia, directly and through their students, to better insure completeness and accuracy, while also exercising these scientists and their associates on the critical skills of communicating science to the public.
Articles generally covering unsupervised learning, to take but one example, most notably clustering, are dominated by material from classic data clustering of statistics, with very limited coverage of uniquely machine learning and AI perspectives.
We can hope and expect that the sustainability text on Wikibooks will be a steppingstone for its contributors, largely self-selected to care substantially about educational and public outreach, to more broadly contribute to Wikipedia articles on AI.
Ideally, students who participate as Wikipedians will see their efforts as contributing to global pedagogy, both as it relates to sustainability and AI, and this will contribute to their self-image as people who can make a difference in society, in large part by working in community.
More broadly, universities are facing important questions of how to best use the World’s freely-available educational resources for a better onsite education – one that ideally fosters a commitment to place, a vital prerequisite to a commitment to sustainability.
In addition, a primary organization based on AI topics will help to highlight sustainability-related problems that share similar problem structure, but which may be in very different sustainability domains, thus encouraging abstraction and generalization on the part of students and guarding against inert knowledge.
The authors apply their methods to grizzly bear corridor design, finding paths between existing protected ecological reserves to allow for bear population mobility and increasing possibilities of genetic diversity.
Indeed, the intent of this effort is not to displace one bit of AI content from AI courses, but rather to facilitate the easy adoption by instructors of sustainability problems that can be used to motivate AI methods and concepts, while passing on sustainability knowledge in the process.
In addition, a hope is that the evolving lab text will be a resource for broader impact and education plans of research projects, such as NSF proposals and awards, in large part because this opportunity will be promoted, perhaps going so far as to provide templates for such activities on the lab book site, as well as virtual-meeting tutorial sessions on Wikibooks editing.
There are important broader impact motivations too, notably to foster integration of research and education, better communication of science to the public, and presenting opportunities to students and faculty for contributing, in community, on a global stage.
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