Ten Agile Axioms That Make Managers Anxious

https://www.forbes.com/sites/stevedenning/2018/06/17/ten-agile-axioms-that-make-managers-anxious/#1953dd114619

Bias detectives: the researchers striving to make algorithms fair

how to fight your own biases when writing ML algorithms?

https://www.nature.com/articles/d41586-018-05469-3

Culture is the Behavior You Reward and Punish

https://jocelyngoldfein.com/culture-is-the-behavior-you-reward-and-punish-7e8e75c6543e

The Intelligent Enterprise, by Analogy

https://timoelliott.com/blog/2018/06/the-intelligent-enterprise-by-analogy.html

The Intelligent Enterprise is a virtuous cycle: data is used to create proactive business actions that improve the customer journey, leading to more customers, more data, and even better products and services.

Replacing Humans: Robots Among Us

great documentary about robots in Japan

https://www.cbsnews.com/news/robots-replacing-humans-cbsn-originals/

The end of the Data Scientist Bubble

Stumbled in this post from 2014, very relevant:

“Any data scientist worth their salary will say you should start with a question, NOT the data.”

“Someone who is unable to provide added value on data is NOT a data scientist”

https://www.datasciencecentral.com/profiles/blogs/the-data-scientist-buble-has-started-to-explode

Notes from the AI frontier: Applications and value of deep learning

https://www.mckinsey.com/global-themes/artificial-intelligence/notes-from-the-ai-frontier-applications-and-value-of-deep-learning

3 Tips for Presenting in English When You’re Not a Native Speaker

https://hbr.org/2018/04/3-tips-for-presenting-in-english-when-youre-not-a-native-speaker

Why Data Scientists Must Focus on Developing Product Sense

Business is the differential between a data scientist and a great data scientist.

https://www.kdnuggets.com/2018/04/data-scientists-product-sense.html

How to run your first meeting as a new manager

https://m.signalvnoise.com/how-to-run-your-first-meeting-as-a-new-manager-84aaef872c1b

Great advices (for new and for the experienced as well)

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