Oct 2, 2024 · Here are a handful of high-profile AI blunders from the past decade to illustrate what can go wrong.
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Mar 29, 2018 · The recent revelation that data miner Cambridge Analytica Ltd. improperly accessed 50 million Facebook users' personal data has heightened public concern.
Explore the fascinating world of big data ethics with 10 real-world experiments. Learn how ethical challenges shape data use, privacy, and trust.
It is essential to not lack (proper) data, focus on training, rely on one technique, ask the wrong question, listen (only) to the data, accept leaks from the ...
Aug 7, 2022 · Working for data teams unavoidably creates horror stories that crystalize themselves in the brains of those who have experienced them.
Jan 31, 2024 · This article aims to categorize them and provide recommendations that help the reader identify misconceptions and avoid the resulting traps.
8 Reasons Why Big Data Science and Analytics Projects Fail · 1. Not having the Right Data · 2. Not having the Right Talent · 3. Solving the Wrong Problem · 4.
Jan 3, 2019 · Be careful about missing values. Often when multiple data sets are merged, missing values can be induced: one variable isn't present in ...
Fail to define an objective. 2. Start too big. 3. Lack support from the keepers of the data. 4. Wait for perfect data. 5. Believe you have perfect data. 6. Rely ...
Sep 27, 2023 · Bad data quality refers to moments when data is inaccurate, missing, or otherwise unreliable, leading to what is termed as data downtime ...