Foo camp aftermath

I had a great time at Foo Camp last weekend. It’s an awesome melting pot people and ideas. Extremely high innovation density.

Here are my notes (“things to dig into later”) from the weekend, with no attempt at explanation. These are a mix of nifty resources, topics discussed, and my own thoughts.

Data visualization
Pythonic perambulation 

From the “Cleverness with Slack” session:
FutureBot for Slack
Emoji : mechanism for "silence does not imply consent"
Async Standup plugin
Look up the point of contact for a customer
Trello integration

Process/culture things to have conversations about:
Scrollback culture: decide which rooms must be read in full.
When to use notifications
Adoption: Engineering teams vs sales teams
People who are uncomfortable broadcasting
Hiring: Slack means people need to communicate well in writing.
Onboarding process
Metadiscussion among teachers/power users as opposed to the main community

Feature requests
Ephemeral access to rooms
First class action links
Faster syncing
Valid DM pairs (for Chinese-wall compliance)

Examples of interesting Slack communities:
Home buying with girlfriend
YC founders
Sandwich network
Julia committers

Slack as antidote to “Trip to HQ phenonmenon"
Deep learning Bots on Slack
Culture transmission — slack brings this into the open.

Precision medicine
"21st century research platform"
Health data as a publicly provided commodity (kinda like census)
Right to access data: BS around HIPPA
Million veterans project

Wouldn’t it be nice if...
wider EMR adoption
NIH data stream
clarify patients’ rights
Accelerating access to data

Google baseline study
value-based payer models

WTF economy
“Tech is becoming the villain in our economic narrative"
But compared to what?
Shift work at McDonalds or Walmart is pretty lousy, too.

What’s working in the new economy?
Voluntary, augmentation, better service

Driving income inequality…?
The wealthy underspend as a percentage of income.
Need better metrics for CPI / GDP / etc.

What work feels like

End state for new economy companies?
(Evil) monopoly?
Regulated monopoly?

10 principles for new economy, taking domestic workers as an example.

How to keep open source communities healthy
Paid v fully paid
Dedicated v casual
Community grows iff casual participants can successfully commit code.
Culture, technology, process barriers

When to break up big modules?

Quantified place
What makes a space a place?
Interactive architecture
Chat rooms for furniture
Google interactive spaces project - pubs network for devices
Architectural Psychology
Experienceing Architectures
Christopher Alexander
Francis Duffy
Comfort in buildings
Sick building syndrome

wirecutter.com - really great gadget reviews
thesweethome.com - really great DIY reviews
Coral Platform @ Mozilla - new, collaborative tools for journalists

Data and design: What can they teach each other about creativity?
Data as window into experience and behavior
Shared mental models require interaction and experience
Numbers don’t move people, stories do.
3 questions for graphs:
What should viewers learn? do? feel?
Good data often elicits conversation, instead of “driving decisions."
Care = 1 / time.
Desire is the engine of story
Designers and data scientists often intimidate each other. This is bad. We need more collaborative teams and common language.
The best data products elicit behavior and data that improve themselves.
More than traditional software, data products bring (recorded, analyzable) data closer to human experience
Therefore, data from data products tends to be easier to interpret and work with?
Idiots are the best resource you have for user testing.
Outliers generate new questions
Bonus: probable things, not impossible things.
Outliers help define the edges of possibility.

How data hurts people
Undocumented migrants
Police “threat” lists of protestors
Uber’s policing of protests in China
SMS to protestors in Ukraine
Facebook stalkers - location gleaned from the posting of a friend of a friend
Random face identification of strangers in Facebook photos
Medical data
Misdiagnosis in medical data
Small testing -> massive testing
unnecessary risky surgery
direct costs, recovery time, cost to well-being, lost wages
Data distraction
Overreacting to news from 23 and me
Genetic coercion
Wanted: a term like “uncanny valley” for data products that are kind of creepy.
“The machine knows more about me than expected."
Expectancy violation theory
Family falls apart after discovering half-brother through 23 and me
Ashley Madison breach
CBO breach
WMDs in Iraq:
circumventing expert analysis
cherrypicking bits of data
process is opaque
Nathaniel …?
War crimes and mass graves
“What appears to be…” — essential linguistic cue
RadioShack auctioning user data
"Wiggle room in the evidence."

Data as radioactive waste
Atlantic article: Lies, Damn lies, and medical science

Projector mapping
Ultra-short throw projectors

TurboSquid - 3d models 

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