Paul asks, “What do you think is the biggest misconception about AI?” Something I say in all my keynotes: AI is math, not magic. There’s no magic here. AI is just the application of mathematics to data at a very large scale. In turn, that means AI can’t do things that fundamentally aren’t math at…
Summary In today's episode, I share insights from a conversation with Paul about the biggest misconceptions surrounding AI. Here's what this means for you. You gain a clearer mental model of AI that helps you set realistic expectations and identify where AI can and cannot add value in your work. You'll also learn these concepts:…
Summary In today's episode, I explain why marketers should commit to sharing only tracked links so they can finally see what's happening in dark social spaces. Here's what this means for you. You gain the ability to attribute conversations on Slack, WhatsApp, text messages, and private DMs to real channels by embedding UTM codes in…
Paul asks, “What excites you most about AI?” In the context of marketing and data science, AI allows us to scale our inquiries to our data. We have overwhelming amounts of data, and most of it goes unused. Think about all the data just in Google Analytics. How much of it do you actually use?…
Summary In today's episode, I share what excites me most about AI in marketing and data science, focusing on how machine learning unlocks value sitting inside underused data. Here's what this means for you. You gain a practical way to find patterns hiding in your marketing data and turn dormant analytics into actionable insights. You'll…
Paul asks, “If you were entering college, knowing what you know now, what would you study?” Mathematics, statistics, comp sci, anthropology fieldwork, and psychology. Definitely not what I studied, except for anthropology. If you think about what data science and AI encompasses, I’d want skills in each of the four major areas. Can’t see anything?…
Summary In today's episode, I answer Paul's question about what I would study if I were entering college today, knowing what I know now. Here's what this means for you. You gain a candid look at the four skill pillars that matter most for AI and data science, along with honest advice about learning styles…
Paul asks, “What can marketers do to ensure the ethical use of AI in their marketing?” Ethics isn’t something machines understand. They’re still fundamentally calculators at their core, no matter how sophisticated the AI, and a calculator is nonmoral, non-ethical. They’re tools, so the burden of ethics is on the users of the tools. If…
Summary In today's episode, I explore how marketers can ensure the ethical use of AI by grounding decisions in utilitarian principles and examining their company's moral foundation before adopting powerful tools. Here's what this means for you. You learn that AI amplifies existing behavior rather than creates new ethics, so your organization's character determines whether…
Shawn asks, “How can I develop data science skills without spending lots of money?” Learning marketing data science without spending a lot of money is very straightforward: download the free, open-source tools you need, and find one of the many, many courses available to teach you data science basics. I recommend IBM’s CognitiveClass.ai course site.…
