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The negative and positive sides of the jagged AI frontier
The person saying “AI is incredible” is not hallucinating.
Sep 11
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Adriana Beal
2
February 2026
Confidently Incorrect
When AI productivity gains come with statistically significant nonsense
Feb 18
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Adriana Beal
2
November 2025
Evidence-Based Recommendations for Everyone but Myself
Why Data Analysts Wing Their Own Professional Development Decisions
Nov 28, 2025
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Adriana Beal
2
September 2025
The "old school" secret to extracting value from generative AI and beyond
Frequent reports about how companies with AI-led processes are outperforming their peers is helping drive a huge interest in introducing Generative AI…
Sep 17, 2025
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Adriana Beal
2
February 2025
Specificity is the way
Key questions to create high-impact data visualizations in the age of AI
Feb 13, 2025
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Adriana Beal
3
April 2024
LLM mistakes to avoid (Part II)
The key for effective model evaluation is to start from a clear-cut use case
Apr 8, 2024
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Adriana Beal
Mistakes to avoid when using LLM-powered chatbots for business
Part I: Why tests designed for humans shouldn't be trusted to measure LLMs' capabilities
Apr 4, 2024
March 2024
Three mistakes causing your "data-driven" strategies to fail to create breakthrough performance
(And how to fix them)
Mar 14, 2024
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Adriana Beal
1
November 2023
Data needs people more than people need data
Back in 2018, alarmist headlines about Amazon’s Whole Foods stealing Trader Joe’s shoppers were everywhere.
Nov 7, 2023
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Adriana Beal
2
September 2023
AI rich, insight poor
The challenge plaguing corporate generative AI efforts in customer service
Sep 6, 2023
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Adriana Beal
1
August 2023
Why generative AI is just the latest technology getting in the way of smart data management
The problem persists, but don't blame large language models for it
Aug 27, 2023
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Adriana Beal
4
May 2023
How to increase your individual productivity with free generative AI
Even if, like me, you refuse to use ChatGPT for content creation
May 23, 2023
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Adriana Beal
1
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