AI (Artificial Intelligence)

This is a growing collection of references and material about AI, concepts, tools and environments. To learn about (generative) AI, start with the self-paced workshop on Generative AI & Prompt Engineering (Tyson Swetnam).

Articles about AI

Interestingly, when I started populating this list, AI hallucinated several entries, which I had to go back and properly curate.

How might we think about AI?

As Ezra Klein noted recently, John Culkin (1967) provided a helpful summary of Marshall McLuhan’s ideas:

  • “We shape our tools and thereafter they shape us.”
  • “The environments set up by different media are not just containers for people; they are processes which shape people.”

Klein went on ‘to steal one more McLuhanism, “the numb stance of the technological idiot” [is] to treat A.I. as merely a tool waiting passively for our use. To use A.I. deeply is to engage in a process, not just to push a button. It will reshape us; it already is. We have to be attentive to how.’

Jaron Lanier has written and spoken extensively about AI. His provocative There is no AI reframed AI as a tool for human social collaboration, particularly when credit for sources encourages data dignity.

A couple articles point out that new startups have found early success in building new tools with AI agents while legacy companies (think Google) see only marginal replacement of human force by AI agents. AI’s disruption of the workforce is real, and it may be radically changing what we do. However, rather than eliminating the need for people, many (most?) realms of society and industry have an opportunity to rethink how we work and collaborate. As multiple authors writing in early 2026 point out, this is not a future event, but something we are now experincing.

What about ethics and environmental impact of AI?

AI companies are trying to improve their efficiency, and their image. The power and water demands for rapid growth of data centers, including those for commercial AI companies, is a serious challenge even as machines and algorithms are becoming more efficient in their use of those scarce resources. Also, there is an emerging effort to support the communities that are protecting and nourishing the water that weaves through their lands. Below is an eclectic collection of resources about AI and its implications.

AI and Scientific Community

These references were gleaned from the ESIIL Network Slack Channel.

Energy and Water Reports

Company Statements

Carbon-neutral and micro data center forecasts and best practices

Table of contents

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