AI_Hmwk7_HumanPrompt - TheEvergreenStateCollege/upper-division-cs-23-24 GitHub Wiki
here Read the following two articles about energy usage in computing
Generative AI’s environmental costs are soaring — and mostly secret, by
In the same dev diary entry as above, write a response of at least 500 words addressing the following questions:
How would you summarize the main point or thesis of each article?
Try to summarize them each in one sentence.
How would you divide and expand the thesis of each article above into two or three main parts? That is:
for the permacomputing article, how would you summarize its main sections?
for the AI energy article, how would you summarize its main sections?
What are two pieces of evidence or arguments that each article provides to support their thesis?
Provide two pieces of evidence or arguments for the permacomputing article.
Provide another two pieces of evidence or arguments for the AI energy article.
What is a related piece of evidence or arguments that you've found independently (e.g. through reading / watching the news, search engines)?
Find one piece of evidence or argument that supports or refutes the permacomputing article.
Find one piece of evidence or argument that supports or refutes the AI energy article.
How are the two readings similar or different?
How would you describe the overall attitude of each article?
How would you describe the approach each article takes?
To what extent do you agree or disagree with the thesis of each article, as you've stated it above?
Do you find the pieces of evidence or arguments that you provide convincing? Why or why not?
If you use an AI chat to help develop your response, include a link to your chat and attempt to make it a 50%-50% chat: write prompts, questions, or your own summaries that are at least as long (in number of words) as the responses the AI gives you, or ask the AI to deliberately shorten its answers.
A google search for "environmental crisis artificial intelligence" yields results claiming AI's positive impact on our looming future. "Existing AI systems include tools that predict weather, track icebergs and identify pollution," the results boast. Yet, even these claims don't boast to work toward the underlying problem. These issues are remarked upon in the readings this week. In the first of the two, "Generative AI’s environmental costs are soaring — and mostly secret", author Kate Crawford describes how the snowballing energy expenses of AI are beginning to be regarded as a serious threat, and congress is considering a bill to respond to these growing threats. The second "Thoughts on Permacomputing", more broadly reimagines the world of computing aligned with the values of permaculture. While Crawford is examining the issue in terms of its present legal state, Viznut considers it in terms of its cultural state. Both identify the necessity to change the way we optimize our AI to become more sustainable - a claim especially true if we societally select AI are our messiah. In Crawford’s article, she makes a frightening claim: "within years, large AI systems are likely to need as much energy as entire nations." Crawford shares a recent legal case made against the industry giant, OpenAI, for using 6% of an entire city’s water supply to train one of their models at their database. When communities are facing water scarcity and struggle to access potable water, this amounts to an enormous concern. This type of case is rare still - Crawford points out that defining the breadth of concern is difficult. Companies don’t monitor themselves and make this information public. This is one of the issues that will hopefully be addresses by the bill Crawford announced was introduced in February, the aptly named “Artificial Intelligence Environmental Sustainability Act”. Yet, after looking more closely at the bill I see that it states that industry is not going to be expected to share this information, instead a voluntary sharing system is going to be introduced. Further, the bill states that at the conclusion of the 4 years this act is in place, the EPA, Secretary of Energy, and director of the National Institute of Standards for Technology will assemble a conclusion outlining the results of these volunteered reports, the structure of the reports and finally: “Recommendations for legislative or administrative action to mitigate the negative and promote the positive environmental impacts of artificial Intelligence.” The legal system, it appears, will inevitably fail us. We turn then to finding a solution In Vikar’s exploration, “Thoughts on Permacomputing”, the author considers ideas intrinsic to permaculture which is described most simply as a “closed-loop system”, i.e. one that does not produce waste. As revealed by Crawford’s article, the artificial intelligence industry as it stands today produces an incomprehensible amount of waste in the form of energy and water use. It consumes, without end. Vikar considers many aspects of computing and how they might be better served by a permaculture-esque view. Hardware could be reused, energy conservation could be valued higher, we could use the energy grid as a determinant for our use, rather than having our energy use determine energy production. During a recent lecture I attended, the speaker discussed “Calm Technology”. The idea was introduced in the 1990s, and describes the concept of designing technology so that it becomes peripheral, instead of our focus. In one of the best examples provided, she explained that a window was a piece of technology: allowing us to witness the state of our environment, whilst protecting us from the elements. It’s already implemented, and doesn’t require the additional power of retrieving weather information from a server, and rendering it on some piece of technology. We rely on it - yet we expect that during hours of darkness or fog it might not be as useful. Without it, we could still step outside - we’re not beholden, though it aids us. Both authors make note