We hear a lot about Facebook as a platform for manipulation - using machine learning to bypass our critical faculties and trick us into believing things that are bad for us - but the real show is in Facebook's ability to target, not manipulate.

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People who hold disfavored views struggle to find one another and mobilize. To find other people that feel the same way as you and make common cause with them to effect political change, you have to reveal your views and suffer social sanction.

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Search allows people who hold these views to find one another. If you have a deep feeling about your gender being nonbinary but don't know the words for it, you can search for communities of people who have those words, join them, and discover who you've been all along.

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This is why, in this moment, so many ideas are migrating from the fringe to the center: ideas about racial justice, gender identity, alternatives to market systems, etc. People have harbored these views all along, but have held back on expressing them.

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Being able to express yourself in private, among people who share your views, is a prelude to going public and putting your case to the wider world in hopes of effecting change.

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This goes for ALL disfavored views: not just ones we laud, but also the ones we deplore. Many Americans have nursed secret white supremacism but only whispered about it, because saying it aloud would attract social sanction, with real consequences.

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Search let these people find each other. Having formed groups, they were able to brave social consequences and begin to shout about it. When they did, they converted people who were sort-of racist all along to their cause. "Radicalization" is closely related to "convincing."

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But search isn't the only way that groups with hard-to-find traits can be discovered: there's also targeting. Ad-tech companies spy on us, ascribe traits to us, then sell the right to target those traits to advertisers.

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"Show my ad to midwestern high school cheerleaders"

"To people shopping for a new fridge"

"To the owners of senior dogs"

"To people with diabetes"

"To readers of cyberpunk science fiction novels"

"To people skeptical of Big Tech"

"To Bernie Sanders supporters"

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"To violent, Trump-addled conspiracists plotting insurrection"

https://t.co/Q8lsg2yCXg

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To be fair, the Facebook ads "for body armor, gun holsters, and other military equipment next to content promoting election misinformation and news about the attempted coup at the US Capitol" were probably not necessarily targeted at "coup plotting" per se.

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More from Cory Doctorow #BLM

Today's Twitter threads (a Twitter thread).

Inside: Planet Money on HP's myriad ripoffs; Strength in numbers; and more!

Archived at: https://t.co/esjoT3u5Gr

#Pluralistic

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On Feb 22, I'm delivering a keynote address for the NISO Plus conference, "The day of the comet: what trustbusting means for digital manipulation."

https://t.co/Z84xicXhGg

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Planet Money on HP's myriad ripoffs: Ink-stained wretches of the world, unite!

https://t.co/k5ASdVUrC2

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Strength in numbers: The crisis in accounting.

https://t.co/DjfAfHWpNN

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#15yrsago Bad Samaritan family won’t return found expensive camera https://t.co/Rn9E5R1gtV

#10yrsago What does Libyan revolution mean for https://t.co/Jz28qHVhrV? https://t.co/dN1e4MxU4r

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More from Machine learning

10 PYTHON 🐍 libraries for machine learning.

Retweets are appreciated.
[ Thread ]


1. NumPy (Numerical Python)

- The most powerful feature of NumPy is the n-dimensional array.

- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.

Ref:
https://t.co/XY13ILXwSN


2. SciPy (Scientific Python)

- SciPy is built on NumPy.

- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.

Ref: https://t.co/ALTFqM2VUo


3. Matplotlib

- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

- You can also use Latex commands to add math to your plot.

- Matplotlib makes hard things possible.

Ref: https://t.co/zodOo2WzGx


4. Pandas

- Pandas is for structured data operations and manipulations.

- It is extensively used for data munging and preparation.

- Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage.

Ref: https://t.co/IFzikVHht4

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1/“What would need to be true for you to….X”

Why is this the most powerful question you can ask when attempting to reach an agreement with another human being or organization?

A thread, co-written by @deanmbrody:


2/ First, “X” could be lots of things. Examples: What would need to be true for you to

- “Feel it's in our best interest for me to be CMO"
- “Feel that we’re in a good place as a company”
- “Feel that we’re on the same page”
- “Feel that we both got what we wanted from this deal

3/ Normally, we aren’t that direct. Example from startup/VC land:

Founders leave VC meetings thinking that every VC will invest, but they rarely do.

Worse over, the founders don’t know what they need to do in order to be fundable.

4/ So why should you ask the magic Q?

To get clarity.

You want to know where you stand, and what it takes to get what you want in a way that also gets them what they want.

It also holds them (mentally) accountable once the thing they need becomes true.

5/ Staying in the context of soliciting investors, the question is “what would need to be true for you to want to invest (or partner with us on this journey, etc)?”

Multiple responses to this question are likely to deliver a positive result.