The AI Daily Brief: Artificial Intelligence News and Analysis - AI and the Necessary Transformation of Education

Episode Date: July 21, 2024

A reading and discussion inspired by https://hechingerreport.org/opinion-what-teachers-call-ai-cheating-leaders-in-the-workforce-might-call-progress/ Concerned about being spied on? Tired of censored responses? AI Daily Brief listeners receive a 20% discount on Venice Pro. Visit ⁠https://venice.ai/nlw⁠ and enter the discount code NLWDAILYBRIEF. Learn how to use AI with the world's biggest library of fun and useful tutorials: https://besuper.ai/ Use code 'podcast' for 50% off your first month. The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614 Subscribe to the newsletter: https://aidailybrief.beehiiv.com/ Join our Discord: https://bit.ly/aibreakdown

Today on the AI Daily Brief, a look at why certain AI strategies might be very bad for education, but very good for work. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. To join the conversation, follow the Discord link in our show notes. Hello, friends, happy weekend. And it, of course, being a weekend, we are doing one of our Longreeds episodes. I decided to try to move beyond politics or big think issues. We've had so much of that recently. and I found this really interesting opinion piece in the Hetchinger report called opinion.

What teachers called AI cheating, leaders in the workforce might call progress. As you'll see, it gets into just how complicated it's going to be to integrate AI into these various processes in societal institutions, and why in some ways what's good for one might not be good for others, or at least they might run at cross purposes. So let's read this piece, and then we'll come back and discuss it a little bit more. and this time this is not AI reading, this is just me. The piece is by C. Edward Watson and Jose Antonio Bowen, and they write, As the use of artificial intelligence grows, teachers are trying to protect the integrity of their educational practices and systems. When we see what AI can do in the hands of our students, it's hard to stay neutral about how and if to use it.

Of course, we worry about cheating. AI can be used to write essays and solve math problems. But we also have deeper concerns regarding learning. When our students use AI, they may not be engaging is deeply with our assignments in coursework. They have discovered ways AI can be used to create essay outlines and help with project organization and other such tasks that are key components of the learning process. Some of this could be good. AI is a fabulous tool for getting started or unstuck. AI puts together old ideas in new ways and can do this at scale. It will make creativity easier for everyone. But this very ease has teachers wondering how we can keep our students motivated to do the hard work when there are so many new shortcuts. Learning goals, curriculum, courses,

and the way we create assignments will all need to be re-evaluated. The new realities of work must also be considered. A shift in employers' job postings rewards those with AI skills. Many companies report already adopting generative AI tools or anticipate incorporating them into their workflow in the near future. A core tension has emerged. Many teachers want to keep AI out of our classrooms, but also know that future workplaces may demand AI literacy.

What we call cheating, businesses could see as efficiency and progress. The complexities, opportunities, and decisions, that lie between banning AI and teaching AI are significant. It is increasingly likely that using AI will emerge as an essential skill for students, regardless of their career ambitions, and that action is required of educational institutions as a result. Integrating AI into the curriculum will require change. The best starting point is a better understanding of what AI literacy looks like in our current landscape. In our new book, which editor's note is called Teaching with AI, a Practical Guide to a New Era of Human Learning, we make it clear that the specifics of AI literacy will vary some

somewhat from one subject to the next, but there are some AI capacities that everyone will now need. Before even writing a prompt, the AI users should develop an understanding of the following. The role of human and AI collaborations, how to navigate the ethical implications of using AI for a given purpose, which AI tool to use when and why, how to use their selected AI tool fully and successfully, the limitations of generative AI systems and how to work around them, prompt engineering and all of its nuances. This knowledge will help our students write successful prompts, but additional skills in AI literacy will be required once AI returns a response. These include the abilities to, review and evaluate AI-produced content, including how to

determine its accuracy and recognize bias, edit AI content for its intended audience and purpose, follow up with AI to refine the output, take responsibility for the quality of the final work. The development of AI literacy mirrors the development of other key skills, such as critical thinking. Teaching AI literacy begins by teaching the capacities above, as well as others specific to your own subject. While the inclination may be to start teaching AI literacy by opening a browser, faculty should begin by providing an ethical and environmental context regarding the use of AI and the responsibilities each of us has when working with AI. Amazon Web Services recently surveyed employers from all business sectors about what skills employees need to use AI well. In

ranked order, their answers included the following. Critical thinking and problem solving, creative thinking and design competence, technical proficiency, ethics and risk management, communication, math, teamwork, management, writing. Higher education is quite adept at teaching skills, and many of those noted are among the American Association of College and University's list of essential learning outcomes for higher education. Faculty will need to improve their own AI literacy and explore the most advanced generative AI tools. A good way to begin is to ask AI to perform assignments and projects that you typically ask your students to complete and then try to improve the AI's response. Understanding what AI can and cannot do well within the context of your course will be key as you contemplate revising

your assignments and teaching. Faculty should also find out if their college has an advisory board comprised of past students and or employers. Reach out to them for firsthand insight on how AI is shifting the landscape and keep that conversation going over time. That information will be essential as you think about AI literacy within your subjects and courses. These actions will ultimately position you to be able to navigate the complexities and decisions that lie between ban and teach. Today's episode is brought to you by Super Intelligent, the platform for fun, fast AI learning. Super has a ton of new things going on. We recently announced our partnership with Spotify, through which users of that app can now

access Super Intelligent content directly from their mobile apps. We've also just launched the AI learning feed. In addition to seeing the tutorials that we're dropping, there are polls, news items with related lessons, and a chance for people to show off the projects and use cases that are making AI come alive for them. We've also just kicked off the Super Summer Challenge. where each week will share a new challenge that you can use to discover new AI tools and use cases. Go to Bsuper.a.i and use code super fun for 50% off your first two months. That's Bsuper.com.

Today's episode is brought to you by Venice. Venice is a private, uncensored generative AI app. It accesses open source models to enable text, image, and code generation without the fear of being spied on or having your data exploited. Discuss anything with Venice without concerns about it being monitored, sold, or given to advertisers and governments. Venice is different because your conversations and creations are kept securely within your own browser, never stored or accessible by Venice. Unlike other AI apps, Venice won't tell you what's okay to say or not. Venice won't patronize you. It simply provides direct access to machine intelligence. No topics are off limits, no ideas are taboo. With Venice, you're in control of the AI, as you should be. Pro subscriptions are available for $49 a year or $8 per month. Try it for free without an account at venice.a.i.

All right. Back to NLW here. A couple of things that I I think are notable about this and interesting. First of all, the concern around cheating is really only given lip service here. It's quite clear that the point of this essay, and probably the broader book that it's connected to, is to try to move beyond this very layer zero kind of conversation around, is AI going to be used for cheating or not? I think that's good because this whole cheating thing is just an absolutely unwinnable battle. We really just have to rethink from the ground up exactly what we prioritize and what we emphasize. And on the one hand, this will be the most challenging part of this whole transition. But at the same time, having to go through

this fundamental or more fundamental reevaluation is, I think, a lot better than just sort of nibbling around the edges of an education system that has long hungered for a bigger change. The next part that I think is really fascinating, is there awareness that something that could be very bad in the context of learning could be very good or at least consider? good in the context of work. Basically, that shortcuts and doing things fast could be really valuable in a workplace situation. As they put it what we call cheating, businesses could see as efficiency in progress. Now, I think it's ultimately a lot more nuanced than that. I think that businesses are still going to want people to have understanding and competency and not just be parroting whatever

AI spits out. And so there perhaps is more overlap than it might initially seem. But I think it's smart and cognizant for people who are thinking about education updates, to understand, or at least to try to put themselves in the mindsets of employers who are excited about the shortcuts. This idea, then, the big concern that they have, is around the depth with which students engage with the material. This actually reminded me of a tweet from Andre Carpathy back in February. He gave it a title on Shortification of Learning. He said, there are lots of videos on YouTube, TikTok, etc., that gave the appearance of education, but if you look closely, they are really just entertainment. This is very convenient for everyone involved. The people watching enjoy thinking they are learning, but actually

they are just having fun. The people creating this content also enjoy it because fun has a much larger audience, fame and revenue. But as far as learning goes, this is a trap. This content is an epsilon away from watching The Bachelorette. It's like snacking on those garden veggie straws, which feel like you're eating healthy vegetables until you look at the ingredients. Learning is not supposed to be fun. It doesn't have to be actively not fun either, but the primary feeling should be that of effort. It should look a lot less like the 10-minute full-body workout from your local digital media creator, and a lot more like a serious session at the gym. You want the mental equivalent of sweating. It's not that the Quickey doesn't do anything, it's just that it's wildly

suboptimal if you actually care to learn. I find it helpful to explicitly declare your intent upfront as a sharp binary variable in your mind. If you are consuming content, are you trying to be entertained or are you trying to learn? And if you are creating content, are you trying to entertain or are you trying to learn? You'll go down a different path in each case. So for those who actually want to learn unless you are trying to learn something narrow and specific, close those tabs with quick blog posts. Close those tabs of Learn XYZ in 10 minutes. Consider the opportunity cost of snacking and seek the meal. The textbook, stocks, paper, manuals, long form. Allocate a four-hour window. Don't just read, take notes, reread, re-phrase, process, manipulate, and learn. Now, this took on a whole new meeting

when Andre announced that he was starting an AI plus education company called Eureka Labs. We don't know exactly how they're going to do things yet, but my guess is that it's going to go a lot more in depth. Anyways, the point being that I think that it's a valid question that they're bringing up in this essay. Now, they offer a bunch of specifics around how we can engage with AI-based curriculum more deeply, what specific skills around using AI and thinking about AI we should do, and all of that's great. But mostly what excites me is that it's the beginning of a conversation that moves past the first generation of, is AI going to be used to cheat or not, and into some real specifics. I'm excited to see this conversation evolve. I'm excited to see leadership from

educators in it. And I appreciate you hanging out today to think through it. Until next, time. Peace.