AI and Academic Use

As the development and proliferation of AI has seen enormous growth, so have concerns related to ethics, safety, and governance (or lack thereof) of these tools. Within higher education contexts, there are many considerations for instructors, researchers, and students should evaluate before deciding to integrate tools in their teaching, scholarship, or course work. 

Below, we briefly summarize major debates about the ethics of using AI. This should serve as a starting point, and we encourage all our users to investigate the issues further as you evaluate various tools, their potential benefits, and the potential risks. 

Often called "algorithmic bias," bias in AI and machine learning generally comes down to the data used to train AI tools, the ways in which they may be flawed or over or under-represent certain groups, and then perpetuate harms that can disadvantage people. As the Algorithmic Justice league notes in their mission, "We now live in a world where AI governs access to information, opportunity and freedom. However, AI systems can perpetuate racism, sexism, ableism, and other harmful forms of discrimination, therefore, presenting significant threats to our society - from healthcare, to economic opportunity, to our criminal justice system." 

With AI tools being integrated into education, surveillance, finance, health, and even dating systems, there are many potential real-life outcomes that potential users should be concerned about. 

Further Reading

Privacy has emerged as a major concern related to AI tools, especially on the part of scholars and community advocates, and it can take a number of different forms, from the potential leakage of sensitive or personal information, to the vulnerability of the AI systems to hacking and attacks, to the possibility of abusive surveillance systems. 

As Mark Coeckelbergh explains, "AI, and in particular machine learning applications working with big data, often involves the collection and use of personal information. AI can also be used for surveillance, on the street but also in the workplace and—through smart-phones and social media—everywhere. Often people do no even know that data are being gathered, or that the data they provided in one context are then used by third parties in another context." (97-98)

As researchers are expected to be transparent and ethical in their collection, handling, and use of data for research, AI companies should be held to similar standards. However, these practices are often obscured and opaque, making the evaluation of those tools and your potential privacy and security risks difficult to assess. 

The use of copyrighted material, both writing and visual art, without licensing, permission, or attribution has become a major concern for scholars and creatives alike. The U.S. Copyright Office is in the process of publishing reports about the application of copyright lat and policy as it relates to the training and output of generative AI. As of now, numerous lawsuits are still making their way through the courts, so these topics are not yet settled law, but we recommend following these cases as developments emerge. Below, we share some resources to help you stay abreast of the information.

Like any new technology, the emergence of AI has also linked to changes in work and the exploitation of laborers.

As Kate Crawford argues in The Atlas of AI, "I focus on how the experience of work is shifting in relation to increased surveillance, algorithmic assessment, and the modulation of time. Put another way, instead of asking whether robots will replace humans, I'm' interested in how humans are increasingly treated like robots and what this means for the role of labor. Many forms of work are shrouded in the term 'artificial intelligence,' hiding the fact that people are often performing rote tasks to shore up the impression that machines can do the work. But large-scale computation is deeply rooted in and running on the exploitation of human bodies." (56)

Additionally, we're seeing AI change the nature of work every day, and the implications of this are not yet clear. 

The environmental impacts of AI have caused growing concern and alarm. These technologies require immense amounts of energy and natural resources to function, while their components also produce waste that disproportionately affects poor communities, communities of color, and those in the Global South.