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Maria Alice Maia
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Researcher-Practitioner's Toolkit
Making better decisions requires better tools. This category demystifies the powerful methods used in cutting-edge academic research and translates them into practical, actionable frameworks for business leaders and professionals. From causal inference and quasi-experimental designs to advanced preference measurement techniques like conjoint analysis, these articles provide the "how-to" for measuring true impact and moving beyond simple correlations
Is Your AI a Genius or a Savant? Using Adaptive Testing to Find Out
You want to drive adoption of a critical new AI tool. Your data team builds a model and tells you to target the obvious evangelists—the...
Maria Alice Maia
Sep 223 min read
Beyond the Hype: A Leader's Checklist for AI Trustworthiness
You just invested millions in a new country-wide sales program. The initial data says it's working… on average. But what if that...
Maria Alice Maia
Sep 173 min read
The New Science of Prompting: How to Speak the Language of AI
Your new loyalty program is a roaring success… or is it? You set a threshold: spend over €100/month and get a 10% discount. A quick...
Maria Alice Maia
Sep 153 min read
Research to ROI | Beyond A/B Tests: A Causal Method to Finally Measure the True ROI of Your Training Programs
You just spent $2 million on a new sales training program. The team that took the course showed a 15% lift in performance six months...
Maria Alice Maia
Sep 33 min read
From Research to ROI | The Real-Time Index: A Playbook for Turning Unstructured Text into a Strategic Asset
Your brand perception report is already a history lesson. Here’s a story I see play out constantly. A major consumer goods company tracks...
Maria Alice Maia
Sep 13 min read
Deconstructing Complexity: How Kernel Regression Reveals the Simple Truth in Over-Hyped Models
That 'sophisticated AI' your team built to predict employee turnover? It might be an illusion. A very expensive, beautifully back-tested...
Maria Alice Maia
Aug 273 min read
Your data science team is brilliant. So why are their models useless in the real world?
I’ve seen this movie a dozen times, from massive consumer goods companies to agile tech startups. A team of brilliant PhDs spends six...
Maria Alice Maia
Aug 242 min read
Creative Chaos vs. Corporate Control: The Coming Clash in Human-AI Collaboration
Your AI is secure, robust, and completely sterile. You’ve successfully engineered out the risk—and the possibility of a breakthrough....
Maria Alice Maia
Aug 204 min read
New Method: Calibrating Chaos: A New Playbook for Modeling Entire Digital Economies | Bayesian Calibration of large-scale ecosystem models
Your company is flying blind, and your big data model is the blindfold. A major music streaming service is facing a crisis. Their most...
Maria Alice Maia
Aug 184 min read
What is Re-Identifiable Data" and Why Tech Regulation Should Measure its Risk
Are regulators playing an unwinnable game of whack-a-mole with AI security? Every week, a new vulnerability. Every month, a new privacy...
Maria Alice Maia
Aug 133 min read
Beyond the Highest Bid: What's Behind the Conflict Between Auction Theory and AI-Led Ad Auctions
Your platform’s revenue is strong, but your users are slowly dying inside. Imagine a large marketplace platform. Quarter after quarter,...
Maria Alice Maia
Aug 113 min read
Beyond "Maybe": A Framework for Statistically Guaranteed LLM Outputs | Are you using probabilistic models as deterministic oracles?
Your LLM just cost you a seven-figure fine. It confidently misclassified a critical customer complaint as a simple inquiry, and you had...
Maria Alice Maia
Aug 73 min read
From Research to ROI | New Method: Text Analysis | Your data may be telling only half of the story
You look at the dashboard. Sales for your flagship product are flat, but stable. Customer surveys show a respectable 4.2 out of 5...
Maria Alice Maia
Aug 42 min read
New Method | Your Recommendation Engine is Lying to You: Machine Learning Matrix Completion & Recommender Systems
Let's be brutally honest. Most corporate recommendation engines are stuck in kindergarten. They operate on a laughably simple logic: "You...
Maria Alice Maia
Jul 282 min read
The Illusion of Understanding: Why 'Explainable AI' Can Be Dangerously Misleading
Your company just invested in a state-of-the-art AI system. You were promised transparency. You were promised "Explainable AI." When the...
Maria Alice Maia
Jul 212 min read
A Year of Data Insights: My Top 5 Learnings for Managers and Tech Pros
This past year, we’ve journeyed from the halls of EU regulators to the frontiers of AI research and the front lines of business. We’ve...
Maria Alice Maia
Jul 143 min read
Causal ML Unpacked: Your Questions on Bringing Rigor to AI
Your ML model is telling you a beautiful story. The problem? It's probably fiction. You have a model that predicts customer churn with...
Maria Alice Maia
Jul 72 min read
New Method: Causal Inference with Machine Learning (Advanced Topics)
Stop Asking "Did It Work?" Start Asking "WHO Did It Work For?" I see it constantly. Companies spend millions on a new training program, a...
Maria Alice Maia
Jun 303 min read
New Method: Using Multiple Outcomes (TMO) to Adjust Standard Errors for Spatial Correlation
Are You Confident in Your Data? Or Just Dangerously Wrong? Imagine you’re a leader at a major retail chain. You’ve just rolled out a new...
Maria Alice Maia
Jun 234 min read
From 'Lie to Me' to Public Trust: What Neuroscience Taught Me About AI Adoption
What do users say they want? And what does their subconscious actually crave? Early in my career, I ran a project playfully named "Lie...
Maria Alice Maia
Jun 163 min read
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