Stem Talent Drain: A Looming Challenge
Stem Talent Drain: A Looming Challenge
The U.S. isn't running out of ideas — it's running out of people. Restrictive immigration policies are pushing top STEM talent to competitors abroad, and America's innovation edge is paying the price.
Everything Can't Be Urgent #workwellness
Everything feels urgent—but it can't all be. MIT SMR columnist Melissa Swift shares a simple 3-button mental trick to cut through the overwhelm.
Your team member is in crisis. Do this first.
When someone on your team is struggling, what you do in the first 24 hours matters most. MIT SMR columnist Melissa Swift shares how to keep a crisis from spreading.
Unlocking AI Factories for 2026 #innovation #aiinnovation
AI factories aren't data centers — they're internal capabilities that combine tools, data, and models to help companies build AI faster. Tom Davenport explains why more organizations are adopting this approach in 2026.
The AI Bubble Deflating the Hype for 2026 #aibubble #mitsloan
Tom Davenport and Randy Bean have seen this before — they lived through the dot-com bubble, and they see the same warning signs with AI today. Their advice? Take the long view and don't panic.
AI Trends in 2026: Key Insights for Leaders
AI experts Thomas H. Davenport and Randy Bean see five artificial intelligence and data science trends emerging in the year ahead. In this video, they share their predictions and offer their expert insights into why agentic AI isn’t yet ready for prime time, whether we’re in an AI bubble that will soon deflate, generative AI’s role as an enterprise resource, who should be responsible for managing AI, and how “AI factories” will accelerate value for the companies that invest in them.
Get a better sense of how to guide your organization’s AI efforts with expert advice from Davenport and Bean. For a deeper look at these trends, read their full article, “Five Trends in AI and Data Science for 2026,” here: https://sloanreview.mit.edu/article/five-trends-in-ai-and-data-science-for-2026/.
Timestamps:
00:00 - Introduction: 2026 AI Predictions
00:41 - Trend 1: Agentic AI Value Stays Elusive
03:07 - Trend 2: The AI Bubble Will Deflate
05:16 - Trend 3: GenAI Becomes an Enterprise Resource
07:13 - Trend 4: Who Manages AI? The Debate Continues
10:06 - Trend 5: AI Factories Will Accelerate Value
12:22 - AI Factories Versus Data Centers
12:47 - Recap and Conclusion
The Smart Leader's Secret Weapon Humility #ceo #ceomindset #inspiredleadership
Kevin Nolan (GE Appliances CEO) on why humility matters: The best leaders know their job isn't to have all the answers—it's to tap into the smarts already in their organization.
Connecting Language and (Artificial) Intelligence: Princeton’s Tom Griffiths
In this bonus episode, Princeton University professor and artificial intelligence researcher Tom Griffiths joins Sam to unpack The Laws of
Thought, his new book exploring how math has been used for
centuries to understand how minds — human and machine — actually work.
Tom walks through three main frameworks shaping intelligence today — rules and symbols, neural networks, and probability — and he explains why modern AI only makes sense when you see how those pieces fit together.
The conversation connects cognitive science, large language models, and the limits of human versus machine intelligence. Along the way, Tom and Sam dig into language, learning, and what humans still do better — like judgment, curation, and metacognition. Read the episode transcript here (https://bit.ly/3LipoSu) .
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Leaders at All Levels: 7 Strategies to Give Your Team Real Power
Your team has talent, but is a traditional hierarchy holding people back? Distributed leadership unlocks team members’ potential by giving individuals greater autonomy and decision-making power, and it’s simpler to start than many leaders imagine. In this short video, learn seven strategies from industry leaders that you can begin to implement right now.
Nurture, Don't Judge A Leadership Approach#innovation
GE Appliances CEO Kevin Nolan on why great leaders don't judge ideas—they encourage them.
#Leadership #Innovation #Management #GEAppliances #CEO #MITSloan
Why AI Code Costs More Than You Think#vibecoding #techdebt
Professors Geoffrey Parker, Edward Anderson, and Burcu Tan explain that AI-generated code creates technical debt at an unprecedented scale. This debt is particularly dangerous for "software developer" because it's harder to fix and detect than traditional problems, impacting overall "software engineering" and "development" efforts. The widespread use of "ai coding" and "artificial intelligence" tools, while efficient, introduces significant "tech debt" that can cost billions if not managed carefully in "programming" initiatives.
Why Building Walls Won't Win the AI Race
The US is only 6-8 months ahead of China in AI. You can't wall off knowledge anymore — the global innovation system is too interconnected. The only way to stay ahead? Invest in R&D capabilities, not restrictions. Especially while AI is still early-stage.
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