
The YouTube algorithm that I helped build in 2011 still recommends the flat earth theory by the *hundreds of millions*. This investigation by @RawStory shows some of the real-life consequences of this badly designed AI.
Flat Earth conference attendees explain how they have been brainwashed by YouTube and Infowarshttps://t.co/gqZwGXPOoc
— Raw Story (@RawStory) November 18, 2018

https://t.co/EKed0B1XhD
8/
https://t.co/yZpqdiJgsR
https://t.co/cqYz3SbDO8
https://t.co/M2mVtZRut9
https://t.co/myxPsrhlKa
Flat-earthers are the canaries in the coalmine /18
I think they're missing the point. 19/
With AI in charge of our information, we're facing a brand new, existential problem that concerns all of us. We need to develop tools to understand it better. 20/
From the algorithm's point of view, flat earth is a gold mine.
Full article: https://t.co/LPjCKpbwXj
21/

https://t.co/LPjCKpbwXj 22/
More from Tech
A common misunderstanding about Agile and “Big Design Up Front”:
There’s nothing in the Agile Manifesto or Principles that states you should never have any idea what you’re trying to build.
You’re allowed to think about a desired outcome from the beginning.
It’s not Big Design Up Front if you do in-depth research to understand the user’s problem.
It’s not BDUF if you spend detailed time learning who needs this thing and why they need it.
It’s not BDUF if you help every team member know what success looks like.
Agile is about reducing risk.
It’s not Agile if you increase risk by starting your sprints with complete ignorance.
It’s not Agile if you don’t research.
Don’t make the mistake of shutting down critical understanding by labeling it Bg Design Up Front.
It would be a mistake to assume this research should only be done by designers and researchers.
Product management and developers also need to be out with the team, conducting the research.
Shared Understanding is the key objective
Big Design Up Front is a thing to avoid.
Defining all the functionality before coding is BDUF.
Drawing every screen and every pixel is BDUF.
Promising functionality (or delivery dates) to customers before development starts is BDUF.
These things shouldn’t happen in Agile.
There’s nothing in the Agile Manifesto or Principles that states you should never have any idea what you’re trying to build.
You’re allowed to think about a desired outcome from the beginning.
It’s not Big Design Up Front if you do in-depth research to understand the user’s problem.
It’s not BDUF if you spend detailed time learning who needs this thing and why they need it.
It’s not BDUF if you help every team member know what success looks like.
Agile is about reducing risk.
It’s not Agile if you increase risk by starting your sprints with complete ignorance.
It’s not Agile if you don’t research.
Don’t make the mistake of shutting down critical understanding by labeling it Bg Design Up Front.
It would be a mistake to assume this research should only be done by designers and researchers.
Product management and developers also need to be out with the team, conducting the research.
Shared Understanding is the key objective
I\u2019d recommend that the devs participate directly in the research.
— Jared Spool (@jmspool) November 18, 2018
If the devs go into the first sprint with a thorough understanding of the user\u2019s problems, they are far more likely to solve it well.
Big Design Up Front is a thing to avoid.
Defining all the functionality before coding is BDUF.
Drawing every screen and every pixel is BDUF.
Promising functionality (or delivery dates) to customers before development starts is BDUF.
These things shouldn’t happen in Agile.
You May Also Like
Nano Course On Python For Trading
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
