Co-Intelligence: How AI and Humans Can Work Together by Ethan Mollick presents an optimistic view of the future in which Generative AI tools complement and enhance human creativity, productivity, and decision-making. Mollick skillfully explains how healthcare, education, and businesses of all types will benefit from incorporating AI tools. However, the book falls short in addressing the critical ethical issues surrounding Large Language Models (LLMs). While Mollick touches on these topics, he fails to engage deeply with topics such as intellectual property, energy usage, and exacerbating inequalities. This review offers a critical analysis of Co-Intelligence, emphasizing the need for a deeper exploration of ethical frameworks to guide AI development.
The following are the key recommendations made by the Computer Science Working Group. All ten recommendations are needed to set the foundation for a robust and sustainable approach to computer science education. The first five recommendations have been prioritized by the working group as important first steps in achieving this plan. An important component of every recommendation is building awareness in order to address the many misconceptions about computer science and who is able to acquire and harness these skills. Awareness of computer science needs to be introduced early and able to grow over time as access to computer science education increases.
It is no use burying our heads in the sand and banning AI-based tools. The horses are out of the barn and are running wild in all directions. These tools are becoming more and more powerful and are being used in new ways every day. We have a real chance to help students understand their own responsibility, take charge of their own learning, and use this amazing technology to improve their self-efficacy, their knowledge, their outcomes, and ultimately their lives. Let’s use it!
Chen, B., Bartucz, J. Scharber, C., Rao, V., & DeLiema, D. (2023, April). Toward a framework for justice-oriented data science education in K-12 Schools. Paper presented at the annual AERA conference, Chicago, IL.
I wanted to start my last blog post with the same quotation that I used in the first, because I believe that it feels like the missing link in educational technology: My contention is, first, that we should want more from our educational efforts than adequate academic achievement and, second, that we will not achieve even that meager success unless our children believe that they themselves are cared for and learn to care for others. Nel Noddings, Caring: A Feminine Approach to Ethics and Moral Education, 1984 This quote was written almost 40 years ago, yet how many technological tools…
“The most powerful experiences in peer-guided learning at scale tend to be deep, collaborative, sustained, and interest-driven. These characteristics, however, are at odds with the pedagogical approach of most schools, which usually require that learning experiences are experience individually, not collectively, along a set of mandated curriculum guidelines, not determined by students’ interests, and for uniform time-spans – the class period, the marking period, the semester – not sustained over time.” Justin Reich, Failure to Disrupt Throughout the book Failure to Disrupt, I was constantly struct by the recurring theme of community, connectedness, and lack thereof. The proponents of learning…
Reading through the history of learning technologies presents a woefully consistent approach. From the earliest mechanical computation machines, through television, the internet, and now virtual reality and artificial intelligence, the trend has always been for those in power to become enamored with the latest technology and try to shoe-horn it into the education space. Instead of asking “what is the cheapest way we can use this exciting new thing in education?”, we should be asking: “where are the weak points in education and what kind of technology would strengthen them?” Of course, it is not until recently that we would…