Sioux Falls School Board discusses AI use in classrooms
SIOUX FALLS, S.D. (KELO) — A lot of businesses are turning to artificial intelligence to save money and time, so it's important for students to learn about it. But how should AI be used in the classroom?
It's a topic the Sioux Falls School Board took up Monday afternoon.
'Every time I turn on the TV, every time I turn on my phone, it's just all about AI. It's growing all over, not only in the schools, I imagine, but banking, health care, all over the place. It's really accelerating,' SFSD assistant superintendent of academic achievement Kirk Zeeck said.
That's why the Sioux Falls School Board is looking into just how much guidance students should receive from AI on an assignment.
In October, Jefferson High School English teacher Michele Wheeler asked her students to write about a scary character. Then, she asked them to recreate the story using AI. Wheeler says the AI generated a similar story for multiple students.
'What happened is the students actually started to get angry because they had some autonomy about their stories when they were writing them handwritten. Then they're seeing, wait a minute, why is it creating the same story for all of us? Then we got to talk about that AI can create, but it is not creative,' Wheeler said.
Which helped students see one of the downsides of AI.
'They really began to understand that human element piece that needs to be a part of it, that interaction from the beginning to the end in order to keep their voice in it,' Wheeler said.
'If all we do is tell kids, 'You can't use AI,' then it becomes sneaky. If we can help them use it, use it responsibly and be able to think critically about it, I think we're going be worlds ahead then if we try to have this 'You can't use that, that's cheating mentality,'' Sioux Falls School Board president Carly Reiter said.
A few of the common AI tools used in classrooms include Chat GPT, Magic School and Diffit.
Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Axios
20 minutes ago
- Axios
Behind the Curtain: The scariest AI reality
The wildest, scariest, indisputable truth about AI's large language models is that the companies building them don't know exactly why or how they work. Sit with that for a moment. The most powerful companies, racing to build the most powerful superhuman intelligence capabilities — ones they readily admit occasionally go rogue to make things up, or even threaten their users — don't know why their machines do what they do. Why it matters: With the companies pouring hundreds of billions of dollars into willing superhuman intelligence into a quick existence, and Washington doing nothing to slow or police them, it seems worth dissecting this Great Unknown. None of the AI companies dispute this. They marvel at the mystery — and muse about it publicly. They're working feverishly to better understand it. They argue you don't need to fully understand a technology to tame or trust it. Two years ago, Axios managing editor for tech Scott Rosenberg wrote a story, "AI's scariest mystery," saying it's common knowledge among AI developers that they can't always explain or predict their systems' behavior. And that's more true than ever. Yet there's no sign that the government or companies or general public will demand any deeper understanding — or scrutiny — of building a technology with capabilities beyond human understanding. They're convinced the race to beat China to the most advanced LLMs warrants the risk of the Great Unknown. The House, despite knowing so little about AI, tucked language into President Trump's "Big, Beautiful Bill" that would prohibit states and localities from any AI regulations for 10 years. The Senate is considering limitations on the provision. Neither the AI companies nor Congress understands the power of AI a year from now, much less a decade from now. The big picture: Our purpose with this column isn't to be alarmist or " doomers." It's to clinically explain why the inner workings of superhuman intelligence models are a black box, even to the technology's creators. We'll also show, in their own words, how CEOs and founders of the largest AI companies all agree it's a black box. Let's start with a basic overview of how LLMs work, to better explain the Great Unknown: LLMs — including Open AI's ChatGPT, Anthropic's Claude and Google's Gemini — aren't traditional software systems following clear, human-written instructions, like Microsoft Word. In the case of Word, it does precisely what it's engineered to do. Instead, LLMs are massive neural networks — like a brain — that ingest massive amounts of information (much of the internet) to learn to generate answers. The engineers know what they're setting in motion, and what data sources they draw on. But the LLM's size — the sheer inhuman number of variables in each choice of "best next word" it makes — means even the experts can't explain exactly why it chooses to say anything in particular. We asked ChatGPT to explain this (and a human at OpenAI confirmed its accuracy): "We can observe what an LLM outputs, but the process by which it decides on a response is largely opaque. As OpenAI's researchers bluntly put it, 'we have not yet developed human-understandable explanations for why the model generates particular outputs.'" "In fact," ChatGPT continued, "OpenAI admitted that when they tweaked their model architecture in GPT-4, 'more research is needed' to understand why certain versions started hallucinating more than earlier versions — a surprising, unintended behavior even its creators couldn't fully diagnose." Anthropic — which just released Claude 4, the latest model of its LLM, with great fanfare — admitted it was unsure why Claude, when given access to fictional emails during safety testing, threatened to blackmail an engineer over a supposed extramarital affair. This was part of responsible safety testing — but Anthropic can't fully explain the irresponsible action. Again, sit with that: The company doesn't know why its machine went rogue and malicious. And, in truth, the creators don't really know how smart or independent the LLMs could grow. Anthropic even said Claude 4 is powerful enough to pose a greater risk of being used to develop nuclear or chemical weapons. OpenAI's Sam Altman and others toss around the tame word of " interpretability" to describe the challenge. "We certainly have not solved interpretability," Altman told a summit in Geneva last year. What Altman and others mean is they can't interpret the why: Why are LLMs doing what they're doing? Anthropic CEO Dario Amodei, in an essay in April called "The Urgency of Interpretability," warned: "People outside the field are often surprised and alarmed to learn that we do not understand how our own AI creations work. They are right to be concerned: this lack of understanding is essentially unprecedented in the history of technology." Amodei called this a serious risk to humanity — yet his company keeps boasting of more powerful models nearing superhuman capabilities. Anthropic has been studying the interpretability issue for years, and Amodei has been vocal about warning it's important to solve. In a statement for this story, Anthropic said: "Understanding how AI works is an urgent issue to solve. It's core to deploying safe AI models and unlocking [AI's] full potential in accelerating scientific discovery and technological development. We have a dedicated research team focused on solving this issue, and they've made significant strides in moving the industry's understanding of the inner workings of AI forward. It's crucial we understand how AI works before it radically transforms our global economy and everyday lives." (Read a paper Anthropic published last year, "Mapping the Mind of a Large Language Model.") Elon Musk has warned for years that AI presents a civilizational risk. In other words, he literally thinks it could destroy humanity, and has said as much. Yet Musk is pouring billions into his own LLM called Grok. "I think AI is a significant existential threat," Musk said in Riyadh, Saudi Arabia, last fall. There's a 10%-20% chance "that it goes bad." Reality check: Apple published a paper last week, "The Illusion of Thinking," concluding that even the most advanced AI reasoning models don't really "think," and can fail when stress-tested. The study found that state-of-the-art models (OpenAI's o3-min, DeepSeek R1 and Anthropic's Claude-3.7-Sonnet) still fail to develop generalizable problem-solving capabilities, with accuracy ultimately collapsing to zero "beyond certain complexities." But a new report by AI researchers, including former OpenAI employees, called " AI 2027," explains how the Great Unknown could, in theory, turn catastrophic in less than two years. The report is long and often too technical for casual readers to fully grasp. It's wholly speculative, though built on current data about how fast the models are improving. It's being widely read inside the AI companies. It captures the belief — or fear — that LLMs could one day think for themselves and start to act on their own. Our purpose isn't to alarm or sound doomy. Rather, you should know what the people building these models talk about incessantly. You can dismiss it as hype or hysteria. But researchers at all these companies worry LLMs, because we don't fully understand them, could outsmart their human creators and go rogue. In the AI 2027 report, the authors warn that competition with China will push LLMs potentially beyond human control, because no one will want to slow progress even if they see signs of acute danger. The safe-landing theory: Google's Sundar Pichai — and really all of the big AI company CEOs — argue that humans will learn to better understand how these machines work and find clever, if yet unknown ways, to control them and " improve lives." The companies all have big research and safety teams, and a huge incentive to tame the technologies if they want to ever realize their full value.
CNBC
30 minutes ago
- CNBC
The way you program an AI is like the way you program a person, says Nvidia's Huang
Nvidia CEO Jensen Huang says artificial intelligence is the "great equalizer" because it lets anyone program using everyday language. Speaking at London Tech Week on Monday, Huang said that, historically, computing was hard and not available to everyone. "We had to learn programming languages. We had to architect it. We had to design these computers that are very complicated," he said on stage alongside U.K. Prime Minister Kier Starmer. "Now, all of a sudden ... there's a new programming language. This new programming language is called 'human.'" Conversational AI models were thrown into the spotlight in 2022 when OpenAI's ChatGPT exploded onto the scene. In February, the San Francisco-based tech company said it had 400 million weekly active users. Users can ask chatbots, such as ChatGPT, Google's Gemini or Microsoft's Copilot, questions and they respond in a conversational way that feels more like talking to another human than an AI system. CEO Huang, whose company engineers some of the world's most advanced semiconductors and AI chips, highlighted that this technology can now be used in programming. He highlighted that very few people know how to use programming languages like C++ or Python, but "everybody ... knows 'human'." "The way you program a computer today, to ask the computer to do something for you, even write a program, generate images, write a poem — just ask it nicely," he said. "And the thing that's really, really quite amazing is the way you program an AI is like the way you program a person." He gave the example of simply asking a computer to write a poem to describe the keynote speech at the London Tech Week event. "You say: You are an incredible poet ... And I would like you to write a poem to describe today's keynote. And without very much effort, this AI would help you generate such a wonderful poem," he said. "And when it answers ... you could say: I feel like you could do even better. And it would go off and think about it, and it'll come back and say, in fact, I I can do better, and it does do a better job." Huang's comments come as a growing number of companies — such as Shopify, Duolingo and Fiverr — encourage their employees to incorporate AI into their work. Indeed, last week OpenAI announced that it has 3 million paying business users. Huang regularly touts AI's ability to help workers do their jobs more efficiently and has encouraged workers to embrace the technology as they look to make themselves valuable employees — especially given the horror stories around AI's potential to replace jobs. "This way of interacting with computers, I think, is something that almost anybody can do, and I would just encourage everybody to engage it," Huang added on Monday. "Children are already doing that themselves naturally, and this is going to be transformative.
Yahoo
36 minutes ago
- Yahoo
WWDC: Apple faces AI, regulatory challenges as it woos software developers
By Stephen Nellis CUPERTINO, California (Reuters) -Apple is facing an unprecedented set of technical and regulatory challenges as some of its key executives are set to take the stage on Monday at the company's annual software developer conference. On the technical side, many of the long-awaited artificial-intelligence features Apple promised at the same conference a year ago have been delayed until next year, even as its rivals such as Alphabet's Google and Microsoft woo developers with a bevvy of new AI features. Those unfulfilled promises included key improvements to Siri, its digital assistant. On the regulatory front, courts in the U.S. and Europe are poised to pull down the lucrative walls around Apple's App Store as even some of the company's former supporters question whether its fees are justified. Those challenges are coming to a head at the same time U.S. President Donald Trump has threatened 25% tariffs on Apple's best-selling iPhone. Apple's shares are down more than 40% since the start of the year, a sharper decline than Google and also lagging the AI-driven gains in Microsoft shares. Apple has launched some of the AI features it promised last year, including a set of writing tools and image-generation tools, but it still relies on partners such as ChatGPT creator OpenAI for some of those capabilities. Bloomberg has reported that Apple may open up in-house AI models to developers this year. But analysts do not believe Apple yet has what technologists call a "multi-modal" model - that is, one capable of understanding imagery, audio and language at the same time - that could power a pair of smart glasses, a category that has become a runaway hit for Meta Platforms. Google said last month it would jump back in to this category, with partners. Such glasses, which are far lighter and cheaper than Apple's Vision Pro headset, could become useful because they would understand what the user is looking at and could help answer questions about it. While Apple has focused on its $3,500 Vision Pro headset, Google and Meta have seized on the smart glasses as a cheaper way to deploy their AI software prowess against Apple in its stronghold of hardware. Meta Ray-Bans all sell for less than $400. Analysts say Apple needs to answer that challenge but that it is not likely to do so this week. "I'm not trying to replace my phone - this is a complementary thing that gives me more world context, because it's got a camera and it sees what I see, and I can talk to it in natural language," said Ben Bajarin, CEO of technology consultancy Creative Strategies. "Apple is not positioned to do that." To be sure, Apple's rivals are not decisively ahead in smart glasses. Anshel Sag, principal analyst with Moor Insights & Strategy, said Meta's Ray-Bans still lack some features and Google has not yet landed its "Gemini" model in a mass-market pair of glasses yet. "Meta has the undisputed lead, but Google is catching up fast and probably has the best-suited AI for the job," Sag said. "Vision Pro is great, but it's a showroom product that developers can use." But Bob O'Donnell, CEO of TECHnalysis Research, said it remains far from clear that smart glasses will gain wide acceptance. O'Donnell also said it is not certain that Apple is at any particular disadvantage if it partners with a company such as Google, OpenAI or even a smaller firm like Perplexity for core AI technology. So far, O'Donnell said, there is not yet strong evidence that consumers are basing major hardware-purchasing decisions on AI features. "There's an argument to be made that it's OK that (Apple) is behind because, except for the bleeding edge, most people don't care," O'Donnell said.
