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Killer Innovations with Phil McKinney

Killer Innovations with Phil McKinney

著者： Phil McKinney
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 Step into the world of relentless creativity with the Killer Innovations Podcast, hosted by Phil McKinney. Since 2005, it has carved its niche in history as the longest-running podcast. Join the community of innovators, designers, creatives, entrepreneurs, and visionaries who are constantly pushing boundaries and challenging the status quo. Discover the power of thinking differently and taking risks to achieve success. The podcast covers a wide range of topics, including innovation, technology, business, leadership, creativity, design, and more. Every episode is not just talk; it's about taking action and implementing strategies that can help you become a successful innovator. Each episode provides practical tips, real-life examples, and thought-provoking insights that will challenge your thinking and inspire you to unleash your creativity. The podcast archive: KillerInnovations.com About Phil McKinney: Phil McKinney, CTO of HP (ret) and CEO of CableLabs, has been credited with forming and leading multiple teams that FastCompany and BusinessWeek list as one of the “50 Most Innovative”. His recognition includes Vanity Fair naming him “The Innovation Guru,” MSNBC and Fox Business calling him "The Gadget Guy," and the San Jose Mercury News dubbing him the "chief seer."See http://philmckinney.com 経済学
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  • The $1.2 Billion Innovation Disaster: 5 Decision Mistakes That Kill Breakthrough Technology (HP WebOS Case Study)

    The $1.2 Billion Innovation Disaster: 5 Decision Mistakes That Kill Breakthrough Technology (HP WebOS Case Study)
    2025/06/10
    In 2011, HP killed a $1.2 billion innovation in just 49 days. I was the Chief Technology Officer who recommended buying it. What happened next reveals why smart people consistently destroy breakthrough technology—and the systematic framework you need to avoid making the same mistake. HP had just spent $1.2 billion acquiring Palm to get WebOS—one of the most advanced mobile operating systems ever created. It had true multitasking when iOS and Android couldn't handle it, an elegant interface design, and breakthrough platform technology. I led the technical due diligence and recommended the acquisition because I believed we were buying the future of mobile computing.We launched it on the HP TouchPad tablet. Then, the CEO killed it just 49 days after launch. Here's a question that should keep every innovation leader awake at night: How do you destroy breakthrough technology worth over a billion dollars in less than two months? The answer isn't what you think. It's not about bad technology, poor market timing, or insufficient resources. It's about systematic thinking errors that intelligent people make when evaluating innovation under pressure. And these same patterns are happening in companies everywhere, right now. I'm going to show you exactly how this happens, why your company is vulnerable to the same mistakes, and give you a proven framework to prevent these disasters before they destroy your next breakthrough innovation. On my Studio Notes on Substack, I share the personal story of watching this unfold while recovering from surgery. In this episode, I want to focus on the systematic patterns that caused this disaster and the decision framework that can prevent it. Here's my promise: by the end of this episode, you'll understand the five thinking errors that consistently destroy innovation value, you'll have a complete decision framework to avoid these traps, and you'll know exactly how to apply this to your current innovation decisions. Because here's what this disaster taught me: intelligence doesn't predict decision quality. Systematic thinking frameworks do. The Pattern That Destroys Billion-Dollar Innovations Let me start with the fundamental problem that makes these disasters predictable. When the HP Board hired Leo Apotheker as CEO, they created what I call a "cognitive mismatch," and it reveals why smart people make terrible innovation decisions. Apotheker came from SAP, where he'd run a $15 billion software company. HP was a $125 billion technology company with breakthrough mobile platform technology. The board put someone whose largest organizational experience was half the size of HP's smallest division in charge of evaluating platform innovations he'd never encountered before. But here's the crucial insight: the problem wasn't his experience level. The problem was how his professional background created mental blind spots that made him literally unable to see WebOS as an opportunity. Here's what's dangerous: Apotheker couldn't see WebOS as valuable because his entire career taught him that software companies don't do hardware. His brain was wired to see hardware as a distraction, not an advantage. To him, WebOS represented exactly the kind of hardware business he wanted to eliminate. Your expertise becomes your blind spot. You literally can't see opportunities outside your professional comfort zone. And this is the first critical principle: Your job background creates mental filters that determine what opportunities you can even see. And this pattern is happening in your company right now. Your finance team evaluates platform investments using metrics designed for traditional products. Your marketing team rejects concepts they can't explain with existing frameworks. Your engineers dismiss breakthrough ideas that don't fit current technical roadmaps. The pattern is always identical: intelligent people using the wrong thinking frameworks to evaluate breakthrough technology. Let me show you exactly how this destroys innovation value. The Five Systematic Thinking Errors That Kill Innovation WebOS died because of five predictable cognitive errors that occur when smart people evaluate breakthrough technology under pressure. These aren't unique to HP—I've seen identical patterns destroy innovation value across multiple industries. Error #1: Solving the Wrong Problem The most dangerous mistake happens before you evaluate any options: framing the wrong decision question. Apotheker was asking "How do I transform HP into a software company?" when the strategic question was "How do we build competitive advantage in mobile computing platforms?" When you optimize solutions for the wrong problem, you get excellent answers that destroy strategic value. The Warning Sign: Your team jumps straight to evaluating options without questioning whether you're solving the right challenge. Error #2: Identity-Driven Decision Making Your professional background creates systematic blind spots about breakthrough ...
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    30 分
  • Your Child's Creative Brain on AI: The Emergency Parents Don't See

    Your Child's Creative Brain on AI: The Emergency Parents Don't See
    2025/06/03
    University of Washington researchers discovered something that should concern every parent: children who use AI to create can no longer create without it. And here's the concerning part: most parents have absolutely no idea it's happening. If you've been following our series on Creative Thinking in the AI Age, you know I've been tracking how artificial intelligence is rewiring human creativity. We've explored the 30% decline in creative thinking among adults, the science of neuroplasticity, and practical exercises to rebuild our creative capabilities. But today's episode is different. Today, we're talking about your child's developing brain. And I need to be direct with you—the next 30 minutes might be the most important parenting conversation you have this year. Because while we've been worried about AI taking our jobs, it's already changing our children's minds. Unlike us adults, who developed our creative thinking before AI existed, our kids are growing up with artificial intelligence as their creative co-pilot from the very beginning. Here's my promise to you: by the end of this episode, you'll know exactly how to tell if your child is developing AI dependency, you'll understand why their developing brain is more vulnerable than yours, and you'll have an assessment tool to evaluate your family's situation—plus immediate strategies you can start using today. But first, let me show you what's happening in homes just like yours—and why this is both preventable and completely reversible. The Crisis Hiding in Plain Sight A few weeks ago, a mother shared a story that stopped me in my tracks. Her 10-year-old daughter used to spend hours drawing elaborate fantasy worlds, completely absorbed in her creative process. Now, when her mother suggests drawing something, the daughter responds, 'Can I just use AI to make it look better?' At first, this seemed like smart efficiency—why not use available tools? However, when the mother asked her daughter to draw a simple picture with no digital help, something alarming occurred. The child just stared at the blank paper and started crying, unable to create anything on her own. This story isn't unique. It's happening everywhere, and parents are missing it because the signs look like success. Before we go further, let me be clear: this isn't your fault. AI dependency developed gradually, and most parents missed the early signs because they actually looked positive. Think about your own child for a moment. Has their homework gotten easier? Do they finish writing assignments faster than they used to? Are their projects suddenly more polished? If you answered yes, you might be looking at what I call the "homework mirage." Here's what the homework mirage looks like: Your child sits down to write a story for English class. Instead of staring at the blank page like kids have done for generations, they open ChatGPT. They type: "Write me a story about a brave knight." In thirty seconds, they have three paragraphs that would have taken them an hour to write. You see the finished assignment. It's well-written, grammatically correct, and creative. You think, "Great! They're learning to use technology efficiently." But here's what you don't see: your child's brain just missed a crucial workout. Remember in our first episode when we talked about brain pathways being like muscles? When we don't use them, they weaken. This is happening to children at a speed that concerns researchers worldwide. (Reference: Newman, M. et al., 2024, "I want it to talk like Darth Vader: Helping Children Construct Creative Self-Efficacy with Generative AI," University of Washington) Dr. Ying Xu from Harvard put it perfectly when she asked the critical question: "Are they actually engaging in the learning process, or are they bypassing it by getting an easy answer from the AI?" And here's the concerning part—kids who use AI to complete tasks do produce higher quality work in the short term. But when you take the AI away, their abilities are worse than before they started using it. But this goes way beyond homework. Children are experiencing what experts call the "Creative Confidence Crisis." Kids who used to love making art now say, "I'm not good enough" when they see AI-generated images. Children ask AI to help with simple creative tasks, such as making up games or telling stories. The scale of this problem is significant. Recent research shows that 31% of teenagers are already using AI to create pictures and images. Sixteen percent are using it to make music. And parents? Most have no idea how much their children are depending on these tools. As one researcher told me, "Parents and teachers are pretty much out of the loop, so young people are using AI platforms with virtually no guidance." This brings us to a crucial question: Why are children more vulnerable to this than adults? Why Your Child's Brain Is at Risk In our second episode, we explored neuroplasticity—your brain's ability to ...
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    29 分
  • Human-AI Creative Partnership: How to Harness AI While Preserving Your Innovative Edge

    Human-AI Creative Partnership: How to Harness AI While Preserving Your Innovative Edge
    2025/05/27
    The most innovative creators don't use AI as a replacement – they use it as a strategic partner in a carefully choreographed dance of human and machine intelligence. Welcome to Part 4 of our series, Creative Thinking in the AI Age – on strengthening your uniquely human creativity while using AI as a partner, not a replacement. In Part 1, we explored the alarming decline in creative thinking as we've grown dependent on AI. In Part 2, we discovered how neuroplasticity allows us to rebuild and enhance our creative capabilities. And in Part 3, I gave you a practical 10-minute daily workout to strengthen the neural pathways essential for innovative thinking. Today, we're bringing it all together with something immediately actionable: a framework for creating productive partnerships with AI that enhance rather than diminish your creative capabilities. This isn't about rejecting AI – it's about using it strategically to amplify your uniquely human abilities. When used properly, AI can handle routine cognitive tasks while freeing your mind for the breakthrough thinking that algorithms simply cannot replicate. Let me start by clarifying the fundamental difference between human and machine intelligence that drives this partnership: Convergent thinking is the process of analyzing existing data to find optimal solutions within defined parameters. This is what AI excels at – processing vast amounts of information to identify patterns and generate options based on probability distributions of what has worked before. Divergent thinking is the ability to generate novel ideas by making unexpected connections, breaking conventional patterns, and imagining what doesn't yet exist. This is where humans uniquely excel – our capacity for intuitive leaps, metaphorical thinking, and insight that transcends existing data. The most powerful creative partnerships leverage both: AI's computational strength and the human capacity for originality. Let me demonstrate with a simple example. If I asked an AI to design a chair, it would analyze thousands of existing chair designs and generate variations based on established patterns. The results would be functional but predictable. But what if I first engaged in divergent thinking by questioning the very concept of sitting? What if I reimagined a chair as something that supports the body in motion rather than at rest? This human insight – this conceptual leap – changes everything about how we might approach the design. Now when I engage AI, I'm not asking it to "design a chair" but to help explore a completely new approach to supporting the human body. The AI becomes a tool for expanding and refining my original insight rather than a replacement for it. This is the heart of creative partnership: human divergent thinking provides the spark of originality, while AI convergent thinking helps develop and refine that spark into something practical. The Art Of Creative Prompting Before we dive into our five-step framework, let's talk about what makes an effective AI prompt for creative work. The way you communicate with AI dramatically impacts the quality and originality of what you receive in return. Throughout this episode, I've included actual prompts formatted in code blocks that you can copy, edit, and paste directly into your favorite AI tool – whether that's ChatGPT, Claude, or others. These aren't theoretical; they're battle-tested approaches I've used with innovation teams. The most powerful creative prompts share three key characteristics: They express curiosity rather than certainty – Phrases like "I'm exploring," "I'm curious about," or "Help me understand" signal to the AI that you're in an exploratory mode rather than seeking definitive answers. This subtle shift encourages broader, more nuanced responses.They use specific framing devices – Notice how our example prompts use structures like "What aspects are overlooked?" or "What contradictions exist?" These frames direct the AI's analytical power toward particular angles of exploration. The formula prompts I've shared provide ready-to-use framing devices for different situations.They maintain creative tension – Effective prompts don't ask for immediate solutions but instead create a productive tension by examining contradictions, assumptions, or overlooked aspects. This tension generates the creative friction from which original insights emerge. When using the example prompts throughout this episode, customize them to your specific challenge, but maintain these structural elements that encourage exploration rather than premature convergence. The goal is to shape AI responses that serve as thought-provoking material for your own creative thinking, not as final answers. Here's a quick formula for effective prompts: "What aspects of [problem] are most overlooked?""What contradictions exist in how people approach [challenge]?""What assumptions might be limiting how we think about [issue]?""What ...
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    34 分

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