Maria Alice Maia
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The Human-AI Frontier
Technology is only as effective as our ability to trust and adopt it. This category decodes the complex drivers of human behavior in the age of AI. Here, we explore the psychology behind user trust, the cognitive biases that shape our interactions with intelligent systems, and the behavioral dynamics that determine whether a new technology thrives or fails. These posts bridge insights from neuroscience, economics, and real-world projects to build a more human-centric approach to technology.


Is Your AI a Genius or a Savant? Using Adaptive Testing to Find Out



Beyond the Hype: A Leader's Checklist for AI Trustworthiness



The New Science of Prompting: How to Speak the Language of AI



Beyond the Algorithm: AI as an Accelerant for Inequality and Autocracy



The AI Productivity Paradox: Why Your Multi-Million Dollar Investment Isn't Moving the Needle



Research to ROI | Beyond A/B Tests: A Causal Method to Finally Measure the True ROI of Your Training Programs



From Research to ROI | The Real-Time Index: A Playbook for Turning Unstructured Text into a Strategic Asset



Deconstructing Complexity: How Kernel Regression Reveals the Simple Truth in Over-Hyped Models



Your data science team is brilliant. So why are their models useless in the real world?



Creative Chaos vs. Corporate Control: The Coming Clash in Human-AI Collaboration



What is Re-Identifiable Data" and Why Tech Regulation Should Measure its Risk



Beyond the Highest Bid: What's Behind the Conflict Between Auction Theory and AI-Led Ad Auctions



Beyond "Maybe": A Framework for Statistically Guaranteed LLM Outputs | Are you using probabilistic models as deterministic oracles?



From Research to ROI | New Method: Text Analysis | Your data may be telling only half of the story



You asked to be forgotten. We deleted your data. But did our AI really forget you?



New Method | Your Recommendation Engine is Lying to You: Machine Learning Matrix Completion & Recommender Systems



The Illusion of Understanding: Why 'Explainable AI' Can Be Dangerously Misleading

![[PT] Um aviso importante sobre a privacidade e segurança de dados do Brasil - An important warning about data privacy and security in Brazil](https://static.wixstatic.com/media/ce8291_5617b63e9bb44e71bab28eeb435eebdc~mv2.png/v1/fill/w_333,h_250,fp_0.50_0.50,q_35,blur_30,enc_avif,quality_auto/ce8291_5617b63e9bb44e71bab28eeb435eebdc~mv2.webp)
![[PT] Um aviso importante sobre a privacidade e segurança de dados do Brasil - An important warning about data privacy and security in Brazil](https://static.wixstatic.com/media/ce8291_5617b63e9bb44e71bab28eeb435eebdc~mv2.png/v1/fill/w_454,h_341,fp_0.50_0.50,q_95,enc_avif,quality_auto/ce8291_5617b63e9bb44e71bab28eeb435eebdc~mv2.webp)
[PT] Um aviso importante sobre a privacidade e segurança de dados do Brasil - An important warning about data privacy and security in Brazil



A Year of Data Insights: My Top 5 Learnings for Managers and Tech Pros



Causal ML Unpacked: Your Questions on Bringing Rigor to AI

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