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Artificial Intelligence: Research, Writing, Teaching, & Ethics

Environmental Impact

Each ChatGPT search is estimated to consume 5x more energy than a Google search. Beyond individual use, the continual demand for newer iterations means companies are constantly training new models - training that requires huge amounts of energy. Specifically, the amount of electricity consumed results in both substantial CO2 emissions and water consumption. 1, 3

"Scientists have estimated that the power requirements of data centers in North America increased from 2,688 megawatts at the end of 2022 to 5,341 megawatts at the end of 2023, partly driven by the demands of generative AI. Globally, the electricity consumption of data centers rose to 460 terawatts in 2022. This would have made data centers the 11th largest electricity consumer in the world, between the nations of Saudi Arabia (371 terawatts) and France (463 terawatts), according to the Organization for Economic Co-operation and Development." 1 This trend is projected to continue, leading to data centers being 5th on the global list (between Japan and Russia) by the end of 2025. 1, 2

While the increased use of electricity is often highlighted, the amount of water consumed to cool data centers and computing equipment also has significant environmental impacts. It's estimated that 2L of water are required for each kilowatt of energy the data centers consume. To put this in direct perspective: ChatGPT needs a 500-ml bottle of water to answer 20-50 questions (efficiency is influenced by things like outside temperature, etc). 4,5

Data centers use purified water free of bacteria - meaning direct competition for water resources our communities rely on. Protests have begun in countries like Chile and Uruguay over planned data centers that would tap drinking water reservoirs. In Dalles, Oregon, the city government filed a lawsuit to keep water usage by Google's three data centers a secret, and when records were made public it became clear the data centers use more than a quarter of the city's water supply. 4

Read more: 

  1. Explained: Generative AI's Environmental Impact (January 2025)
  2. Electricity Grids Creak as AI Demands Soar (May 2024)
  3. The Climate and Sustainability Implications of Generative AI (March 2024)
  4. As Use of A.I. Soars, so Does the Energy and Water it Requires (February 2024) 
  5. How Much Water does AI Consume? (November 2023)

Copyright

Unlicensed Materials & Copyright

AI is notorious for being trained on information that it doesn't legally have access to. From book collections to unlicensed works to art, multiple lawsuits are underway to determine what is "fair use" and what is a copyright violation. 

What does this mean?

Data usage - using copyrighted data could violate copyright, and infringement - direct or unintentional - can be costly. A business using AI trained on unlicensed works could be on the hook for willful infringement, which includes damages of up to $150,000 for each instance. (Appel, Neelbauer, Schweidel, 2023)

Attribution - even if training data is used legally, properly citing your sources is always important! There are citation guidelines out for how to attribute information written or created by AI.

AI & Copyright

Copyright protects only original human-authored and created works, including those made with AI assistance, but does not extend to works generated by AI.

Part 1 of Artificial Intelligence Report released by the U.S. Copyright Office in July, 2024.

What Can I (and Should I) Share with AI?

Keep in mind that what you share with AI becomes a part of the training model. Anything you share in a question with ChatGPT becomes publically available.

What information should I avoid sharing with AI?

  1. Personal information - it's tempting to have ChatGPT help write a resume, or a letter of recommendation. But don't include personal details - passwords, names, addresses, dates of employment - in your query. This is true when talking with company chatbots as well. Risks include:
    • Identity theft
    • Losing control of your information - AI services often share gathered data with companies for marketing and targeted ads, so you can't be sure who has your information.
    • Protip: Ask the tool to give you suggestions for your resume or recommendation. Prompts might include, "Please come up with a bullet list of ways to describe the job responsibilities of a server at a local restaurant," or "Give me several suggestions of ways to describe a reliable student working in an undergraduate research lab."
  2. Research data that hasn't been published - if you've collected data for a project, that data is proprietary information. Don't share it until you're ready to publish it!
    • If the data set is publically available, others could use your data to publish before you get a chance
    • Journals might not choose to publish something that is already freely available.
    • Material might be shared without acknowledgement of your authorship
  3. Academic Article PDF/Full Text - academic research is copyrighted, proprietary information.
    • If it's open access, the AI should already have access (in fact, most research AI tools use SemanticScholar for this).
    • If it's behind a paywall and you're accessing through the Libraries, sharing with AI could violate copyright.
  4. Student's work, especially without permission or disclosure