You’re busy. We get it. We’ve compiled some of the top-clicked and shared articles that you don’t want to miss. Here is a quick review of the top news in marketing analytics, data science, and leadership you should be reading. Application Migration and Modernization with IBM WebSphere Hybrid Edition via @IBMTraining We are pleased to […]
Read More… from Marketing Analytics, Data Science and Leadership – May 17, 2021 Week In Review
In this episode of In-Ear Insights, Katie and Chris tackled the thorny ethics of what you put in your AI models, based on leaked memos from Tiktok allegedly discriminating against protected classes. How do we know when an AI model is behaving badly by accident and by design? What are the steps we should take […]
Read More… from {PODCAST} In-Ear Insights: Ethics, Explainability, AI, and Tiktok
In this week’s In-Ear Insights, Katie and Chris discuss shiny object syndrome, blind spots in your marketing technology (especially around AI and machine learning) and how arrogance can lead to substantial technical problems in your tech stack and company culture. How can you avoid pitfalls and blind spots? How do you manage AI and machine […]
Read More… from {PODCAST} In-Ear Insights: Shiny Object Syndrome and Tech Arrogance
In this episode of In-Ear Insights, Chris and special guest John Wall discuss the state of consumer recommendation engines. Why are recommendations so narrow and ineffective many times? What could we do to improve them beyond what we get now? Listen in as we discuss limitations of computational power, algorithm choice, and more. [podcastsponsor] Watch […]
Read More… from {PODCAST} In-Ear Insights: Why Consumer Recommendation Engines Fail
In this week’s In-Ear Insights, Katie and Chris discuss what happens when algorithm choices go wrong. What happens when junior or naive AI engineers or data scientists make bad choices for algorithms. Using an example from a writing analysis website, we discuss what went wrong, what an appropriate choice should have been, and why it’s […]
Read More… from {PODCAST} In-Ear Insights: When Algorithm Choices Go Wrong
In this episode of In-Ear Insights, Katie and Chris tackle the sorry state of digital advertising, and advertising in general. Why is advertising so terrible? Are companies and marketers focused on the wrong metrics? What are we doing with the data we collect, and could we be doing something different and better with it? Find […]
Read More… from {PODCAST} In-Ear Insights: The Sorry State of Advertising
In this week’s In-Ear Insights, Katie and Chris discuss the current state of AI deployment. Companies are rushing ahead to put models and algorithms into action with little to no due diligence, and the consequences can be disastrous. Should AI adopt a practice similar to clinical trials, where a model must prove that it causes […]
Read More… from {PODCAST} In-Ear Insights: Should AI Adopt a Clinical Trials Process?
Based on a question from our analytics community, in this episode of In-Ear Insights, Katie and Chris tackle the challenges of new technology. When a new piece of technology makes a big splash, how do we evaluate it? How should we assess whether it’s right for us, whether it makes sense to pursue it? What […]
Read More… from {PODCAST} In-Ear Insights: Evaluating New Technologies
On June 18, 2020, I sat down with Jeff Coyle and the MarketMuse community to answer questions after our webinar together on Natural Language Processing and its application to content marketing. Let’s see what’s on the minds of the content marketing community. Tatiana asks, “I’ll kick things off with my question – do you have […]
Introduction The recurring perception that artificial intelligence, AI, is somehow magical and can create something from nothing leads many projects astray. That’s part of the reason that the 2019 Price Waterhouse CEO Survey shows fewer than half of US companies are embarking on strategic AI initiatives – the risk of failure is substantial. In this […]
Read More… from 5 Ways Your AI Projects Fail, After Action Reviews and Post-Mortems
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