AI expert: ‘We'll be toast' without changes in AI technology
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Forbes
11 minutes ago
- Forbes
4 Things Schools Need To Consider When Designing AI Policies
Artificial intelligence has moved from Silicon Valley boardrooms into homes and classrooms across America. A recent Pew Research Center study reveals that 26% of American teenagers now utilize AI tools for schoolwork—twice the number from two years prior. Many schools are rushing to establish AI policies. The result? Some are creating more confusion than clarity by focusing solely on preventing cheating while ignoring broader educational opportunities AI presents. The challenge shouldn't be about whether to allow AI in schools—it should be about how to design policies that strike a balance between academic integrity and practical preparation for an AI-driven future. Here are four essential considerations for effective school AI policies. 1. Address Teacher AI Use, Not Just Student Restrictions The most significant oversight in current AI policies? They focus almost exclusively on what students can't do while completely ignoring teacher usage. This creates confusion and sends mixed messages to students and families. Most policies spend paragraphs outlining student restrictions, but fail to answer basic questions about educator usage: Can teachers use AI to create lesson plans? Are educators allowed to use AI for generating quiz questions or providing initial feedback on essays? What disclosure requirements exist when teachers use AI-generated content? When schools prohibit students from using AI while allowing teachers unrestricted access, the message becomes hypocritical. Students notice when their teacher presents an AI-generated quiz while simultaneously forbidding them from using AI for research. Parents wonder why their children face strict restrictions while educators operate without clear guidelines. If students are required to disclose AI usage in assignments, teachers should identify when they've used AI for lesson materials. This consistency builds trust and models responsible AI integration. 2. Include Students in AI Policy Development Most AI policies are written by administrators who haven't used ChatGPT for homework or witnessed peer collaboration with AI tools. This top-down approach creates rules that students either ignore or circumvent entirely. When we built AI guidelines for WITY, our AI teen entrepreneurship platform at WIT - Whatever It Takes, we worked directly with students. The result? Policies that teens understand and respect because they helped create them. Students bring critical information about real-world AI use that administrators often miss. They are aware of which platforms their classmates use, how AI supports various subjects, and where current rules create confusion. When students participate in policy creation compliance increases significantly because the rules feel collaborative rather than punitive. 3. Balance AI Guardrails With Innovation Opportunities Many AI policies resemble legal warnings more than educational frameworks. Fear-based language teaches students to view AI as a threat rather than a powerful tool requiring responsible use. Effective policies reframe restrictions as learning opportunities. Instead of "AI cannot write your essays," try "AI can help you brainstorm and organize ideas, but your analysis and voice should drive the final work." Schools that blanket-ban AI usage miss opportunities to prepare students for careers where AI literacy will be essential. AI access can vary dramatically among students. While some students have premium ChatGPT subscriptions and access to the latest tools, others may rely solely on free versions or school-provided resources. Without addressing this gap, AI policies can inadvertently increase educational inequality. 4. Build AI Literacy Into Curriculum and Family Communication In an AI-driven economy, rules alone don't prepare students for a future where AI literacy is necessary. Schools must teach students to think critically about AI outputs, understand the bias in AI systems, and recognize the appropriate applications of AI across different contexts. Parents often feel excluded from AI conversations at school, creating confusion about expectations. This is why schools should explain their AI policies in plain language, provide examples of responsible use, and offer resources for parents who want to support responsible AI use at home. When families understand the educational rationale behind AI integration—including teacher usage and transparency requirements—they become partners in developing responsible use habits rather than obstacles to overcome. AI technology changes rapidly, making static policies obsolete within months. Schools should schedule annual policy reviews that include feedback from students, teachers, and parents about both student and teacher AI usage. AI Policy Assessment Checklist School leaders should evaluate their current policies against these seven criteria: Teacher Guidelines: Do policies clearly state when and how teachers can use AI? Are disclosure requirements consistent between students and educators? Student Input: Have students participated in creating these policies? Do rules reflect actual AI usage patterns among teens? Equity Access: Can all students access the same AI tools, or do policies create advantages for families with premium subscriptions? Family Communication: Can parents easily understand the policies? Are expectations clear for home use? Are there opportunities for workshops for parents? Innovation Balance: Do policies encourage responsible experimentation or only focus on restrictions? Is the school policy focusing on preparing students for the AI-driven workforce? Regular Updates: Is there a scheduled review process as AI technology evolves? Does the school welcome feedback from students, teachers and parents? Skills Development: Do policies include plans for teaching AI literacy alongside restrictions? Who is teaching this class or workshop? Moving Forward: AI Leadership The most effective approach treats students as partners, not adversaries. When teens help create the rules they'll follow, when teachers model responsible usage, and when families understand the educational reasoning behind policies, AI becomes a learning tool rather than a source of conflict. Schools that embrace this collaborative approach will produce graduates who understand how to use AI ethically and effectively—exactly the capabilities tomorrow's economy demands.
Yahoo
an hour ago
- Yahoo
Prediction: This Unstoppable Stock Will Be a Founding Member of the $6 Trillion Club by 2027
Key Points Nvidia is the flag bearer for generative AI, which is still in the early innings. The chipmaker furnishes the graphics processing units (GPUs) that supply the computational horsepower that underpins AI. While Nvidia has grown at a blistering pace over the past few years, it likely has further to run, and it's still attractively priced. 10 stocks we like better than Nvidia › Artificial intelligence (AI) has stolen the limelight over the past few years, and there's plenty of evidence to suggest this is just the beginning. Developers continue to create new applications for the technology, which is being leveraged to produce original content, streamline business processes, and enhance productivity. Despite making headlines for more than two years, it's still early days for the adoption of AI, and the evidence suggests spending continues to ramp up. In fact, the four horsemen of technology -- namely Microsoft, Alphabet, Amazon, and Meta Platforms -- are poised to collectively spend more than $400 billion for the capital expenditures required to support their AI ambitions this year, and these outlays show no signs of slowing. With data center spending at the top of the shopping list, Nvidia (NASDAQ: NVDA) is positioned to reap the rewards of much of that spending. The company pioneered the graphics processing units (GPUs) that perform the mathematical calculations required to enable AI, and I predict it will parlay the unrelenting demand for those chips into charter membership in the $6 trillion club. A GPU primer Nvidia pioneered the first GPU back in 1999 to render lifelike images in video games. The groundbreaking development that made that possible was parallel processing, which breaks up massive computing jobs into smaller, more manageable chunks. This enabled the simultaneous processing of a multitude of mathematical computations, making Nvidia's chips a game-changer. This was just the beginning of the journey for the humble GPU, which proved adept at enabling or accelerating other applications, including those in the cloud or data centers, where the majority of AI processing takes place. Nvidia has become the gold standard for data center GPUs, controlling an eye-watering 92% of the market, according to business intelligence firm IoT Analytics. The feverish demand for these specialty chips has driven Nvidia's financial results and its stock price into the stratosphere. Show me the money In its fiscal 2026 first quarter (ended April 27), Nvidia generated record revenue of $44 billion, which surged 69% year over year and 12% sequentially. This fueled adjusted earnings per share (EPS) that jumped 27% to $0.76. The headliner was the data center business, which includes processors used for cloud computing, data centers, and AI. Revenue for the segment surged 73% to $39 billion, driven by relentless demand for AI. This could be just the beginning. Big Four accounting firm PricewaterhouseCoopers (PwC) estimates the AI market could be worth $15.7 trillion by 2030, with Nvidia being a major beneficiary by supplying the cutting-edge chips that underpin the technology. The path to $6 trillion Nvidia currently boasts the world's highest market cap for a publicly traded company, at roughly $4.44 trillion (as of this writing). This means its stock price would need to rise 35% to drive its value to $6 trillion. According to Wall Street, Nvidia is poised to generate revenue of more than $201 billion in fiscal 2026 (which began in January), giving it a forward price-to-sales (P/S) ratio of roughly 22. Assuming its P/S remains constant, Nvidia would need to increase its revenue to roughly $272 billion annually to support a $6 trillion market cap. Wall Street forecasts estimate that Nvidia will grow its revenue by 53% this year and 25% next year. If the company can attain those benchmarks, it could reach a $6 trillion market cap as early as 2027. But don't take my word for it. Loop Capital analyst Ananda Baruah has just issued a Street-high price target of $250 on Nvidia stock, suggesting it could reach a market cap of $6.1 trillion over the next 12 to 18 months. The analyst cited supply chain checks and concluded that hyperscale adoption of generative AI and AI factories could generate spending of $2 trillion by 2028, with Nvidia as a major beneficiary. Given the widespread adoption of AI, I believe Baruah's call is prescient. It's important to remember that these gains won't come in a straight line. A review of Nvidia's charts reveals that the stock price has fallen 25% or more from its peak on at least five separate occasions, and in one case, it plunged 66%. On the other hand, it would be difficult to overstate the company's success. Despite the aforementioned volatility, over the past decade, Nvidia's revenue has grown by 3,735%, while its net income has surged 13,911%. Furthermore, the company's relentless innovation and improving financial performance have fueled a blistering increase in its stock price, which has soared 30,870%. Nvidia is currently selling for 31 times next year's earnings, which is certainly a premium. However, given its impressive track record, consistent execution, and the significant opportunity represented by AI, I'd argue it's a small price to pay for such a high-quality company. Do the experts think Nvidia is a buy right now? The Motley Fool's expert analyst team, drawing on years of investing experience and deep analysis of thousands of stocks, leverages our proprietary Moneyball AI investing database to uncover top opportunities. They've just revealed their to buy now — did Nvidia make the list? When our Stock Advisor analyst team has a stock recommendation, it can pay to listen. After all, Stock Advisor's total average return is up 1,070% vs. just 184% for the S&P — that is beating the market by 885.55%!* Imagine if you were a Stock Advisor member when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $668,155!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,106,071!* The 10 stocks that made the cut could produce monster returns in the coming years. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of August 13, 2025 Danny Vena has positions in Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has positions in and recommends Alphabet, Amazon, Meta Platforms, Microsoft, and Nvidia. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy. Prediction: This Unstoppable Stock Will Be a Founding Member of the $6 Trillion Club by 2027 was originally published by The Motley Fool
Yahoo
2 hours ago
- Yahoo
Amazon.com, Inc. (AMZN) Is The Largest Position In My Trust, Says Jim Cramer
We recently published . Inc. (NASDAQ:AMZN) is one of the stocks Jim Cramer recently discussed. Inc. (NASDAQ:AMZN)'s shares have lost 1% since the firm's latest earnings report, as investors worry about the firm's cloud computing business. After the earnings, Cramer asserted that one reason the firm is facing a growth slowdown with its AWS business is due to over-reliance on its custom Trainium AI chips. This time, he discussed Inc. (NASDAQ:AMZN) retail business as well: 'So I think that, there isn't anything in my mind that says that, you take warehouses being up, that employing people in warehousing. . .And then you take a look at what Amazon's doing. You read how their big warehouses have no people. And them I'm supposed to conclude that the problem is warehouse employment? You need to be a little more granular than the Labor Department. 'Hey by the way, let's not forget. We are going to have a number of drug stores in this country that is probably about one fifth of what we have now. And that was the Amazon factor. So you're going to get your food, you're going to get your drugs, it's going to come to your house. It's a whole new world. And Amazon's got it. Let's just walk away from the idea that web services is declining just for a few minutes please.' While we acknowledge the potential of AMZN as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an extremely cheap AI stock that is also a major beneficiary of Trump tariffs and onshoring, see our free report on the . READ NEXT: 30 Stocks That Should Double in 3 Years and 11 Hidden AI Stocks to Buy Right Now. Disclosure: None. This article is originally published at Insider Monkey. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
