AI

From hundreds of internal projects to tinkering with the AI technology, Arizona State’s chief information officer reveals new details.

One university grapples with how to teach using large-language models.

In our essay, we discuss equity implications surrounding the usage of generative artificial intelligence (AI) in higher education. Specifically, we explore how the use of such technologies by students in higher education such as, but not limited to, multi-language learners, students from marginalized linguistic communities, students with disabilities, and low-income students has the potential to facilitate transformative learning. We describe how such tools, when accessible to learners, can help address barriers that prevent students from fully engaging in their learning. Additionally, we explain how the usage of generative AI has the potential to alter the lens through which students view their learning, countering assumptions and broadening what can be considered an “appropriate” use of assistive technologies to support learning for diverse students. We also address various limitations of generative AI with regards to equity such as the requirement to pay to access some of the applications, as well as linguistic and other biases within the outputs produced, reflective of the data used to train the tools. Throughout this piece, we share insights from a study of undergraduate students’ perspectives and usage of generative AI and potential future directions for the technologies. This essay aims to increase awareness of the opportunities and challenges around who benefits and who is excluded when generative AI is used within colleges and universities.

Algorithms and humans both contribute to bias in AI, but AI may also hold the power to correct or reverse inequities among humans.

In this informative guide we discuss how a student can use AI in an ethical, fair, and lawful manner to assist with learning and studying.

Tim Fawns, Monash University

Updates for old friends, and for new followers some links back to where we've been

Kathryn Conrad[Critical AI 2.1 is a special issue, co-edited by Lauren M.E. Goodlad and Matthew Stone, collecting interdisciplinary essays and think pieces on a wide range of topics involvin

Voters are concerned about AI models using incomplete data to make discriminatory predictions.

A short history of labor.

Elon Musk is suing OpenAI; he probably won’t win, because there wasn’t a contract to be breached, but the lawsuit does highlight how far OpenAI is from the non-profit it started as.

GenAI & Ethics: Investigating ChatGPT, Gemini, & Copilot Torrey Trust Professor of Learning Technology University of Massachusetts Amherst torrey@umass.edu | www.torreytrust.com

It is worthwhile spending some time on social media to see the relentless bombardment faced by students from influencers peddling AI tools that straddle the line between aiding study and blatantly enabling cheating. These influencers flourish is contradictions and promise the moon: complete your homework in five minutes flat, forget about ever attending another lecture, let AI take up the pen for you. In each pitch, the essence of learning is overshadowed by a pervasive call to save time. Welcome to the dizzying world of AI influencer culture, where the pursuit of profit drives companies to use influencers as direct conduits to push their products onto students.

A conversation with UC Berkeley School of Public Health Professor Jodi Halpern about AI ethics, empathy, and mental health.

Following my keynote to the Association for Learning Technologies (ALT) winter summit on AI and ethics

Generative AI gained widespread attention earlier this year, but one group has had to reckon with it more quickly than most: educators. Teachers and school administrators have struggled with two big questions: should the use of generative AI be banned? And should a school implement new tools to detect when students have used generative AI? EFF believes the answer to both of these questions is no.

OpenAI's board and Altman had different visions for how the disruptive tech ought to be developed.

Blog site of Professor Laura Czerniewicz

AI won't kill us all — but that doesn't make it trustworthy. Instead of getting distracted by future existential risks, AI ethics researcher Sasha Luccioni t...

Yoshua Bengio’s pioneering research helped bring about ChatGPT and the current AI boom. Now he’s worried AI could harm civilization, and says the future needs a humanity defense organization.

Today the risks of artificial intelligence are clear — but the warning signs have been there all along

Academic Integrity and Artificial Intelligence through the lens of Equity, Diversity and Inclusion with Sarah Elaine Eaton#MyFest23 #equityUnboundLink to webpage link to this conference: https://myfest.equityunbound.org

As educators, we know the potential that artificial intelligence (AI) has for our profession. Generative AI, a subset of AI that can generate new and ...