I've discovered you can dye things

I always struggle to find the exact right color for whatever material I’m using to make something. If I just used paint it would be easier. But I’m always trying to use physical materials that feel familiar to represent blocks of data or pieces of something that add up to a big dataset.

When I saw these gorgeous acrylic blocks online, I hunted to find a way to make them or buy them inexpensively - after much frustration I went deep into youtube and found a video for how to dye plastic and acrylic. The trick is boiling dye. Big pots of boiling idye poly - very exciting it worked!

Hand dyed polished acrylic

And when I bought a bunch of very expensive wool felt and hated some of the colors, I ‘fixed’ them by putting the wool into boiling pots of idye natural. I discovered that if you dyed them in one color, you could dry and dip into another color to create this triple layer color pattern when you cut into the felt. I was trying to approximate materials that looked and felt like bio-fabricated futurist cellular stuff that could grow on walls. Totally worked.

Hand dyed wool felt

My last foray into dying was a breakthrough to try dying paper… same problem, really nice cotton paper is hard to find in good colors at any price. Some of the best paper from Nepal and India are completely missing, heavy Lotka paper is impossible to find, and Khadi paper that came in interesting colors is nowhere to be found. Voila!

This works better than I expected, 100% Khadi paper from Talas and I’m off and running. It’s an unbelievable pain cause you mix the dyes to make better colors, pour boiling dye into flat roasting pans and each piece takes about 10 minutes and you need to keep turning it over with tongs to keep the color even. Totally worth it. Wait til you see what I can make.

Don’tcha love a time-lapse?

Why being tall as a kid made me curious about the future. TEDx 2018 clip.

Friend nutrition -- who to see, know, ignore

…who you hang out with will be like diet and exercise, in the future we'll manipulate body chemistry with friends.

I have a few people in my life who are a bit 'toxic'. What if I got a nudge to ignore them, or that lunch date we promised simply 'fell' off the calendar.

This is the future.

It's not about the data gathered on you, our next fixation will be the data gathered about the people around you. Human interaction feels complicated, but the intricacies of friends are ripe for machine learning. A great deal of human interaction can be patterned and captured in a very large AI system. It's coming.

I predict we will casually use the data we know about us and the people around us to manipulate our body chemistry. The surprise is that it will be easy. It will start with how people affect us. Are they toxic or a vitamin?

We already use social networks like a life-long rolodex, the obsessive of us 'curate' our feed by specifying who is a close friend, who we keep an eye on and who we unfollow. Soon, the proper dosage of friends will get served up to us in easy-to-consume social networks and digital messaging. Who we encounter may not be so random.

Why now? What has shifted in the adjacent possible to imagine this now? Growth of machine learning and neural networks, ubiquity of social media, plus the number of recent studies showing health impact of friends. Plus, it builds on what people intuitively do now.

A blast of studies using social media and real-live tracking show if you have a friend who becomes obese, you have 57% chance of tipping the BMI meter into obesity. Students with studious room-mates study more, diners sitting next to big eaters at the lunch counter eat more. Friends of friends have a surprising effect, even if you don’t personally know them, if you want to stop smoking, lose weight or survive illness WHO you know has a massive effect.

Friends, plus friends of friends. Think about the people who influence you?

Turns out the number of friends you have is actually governed by the size of your neocortex, the Dunbar number, named after the anthropologist who studied primates in the 1980’s. You basically have 150 friends. While you might have 500 acquaintances, 15 close friends and a handful of intimate friends, the 150 number is common across all cultures.

Steve Cole, a genomics researcher at UCLA found people chronically lonely have significantly more heart disease, are more vulnerable to metastatic cancer, have an increased risk of stroke, are more likely to develop Alzheimer’s, and die at twice the rate of those better connected to friends. Describing body chemistry underlying these results Cole explained “when people felt lonesome, they had significantly higher levels of norepinephrine, the hormone that shuts down viral defense but escalates production of certain white blood cells.” And he noted numerous sleep issues – so if the body chemistry doesn’t hurt you the sleep problems surely will.

Chatting about this to a writer friend, who pushed – how would this work in real life? I imagined a software application, a platform extension of a large social media network. I even went so far as to name it Friend Nutrition, with the tagline ‘who to see, know and ignore’. Offering the promise to seamlessly change our behavior – for cognitive, productivity AND health purposes.

Have you noticed how friends make you feel? Some kick you in the butt to exercise more, dress better, eat fish, think of a new project, believe a new job is possible, start a business... and others do just the opposite? Friends really are the new family, in big cities like Seattle and Denver 40% of adults live alone.   New research has measured stress, inflammation, and sleep in response to your friend connections... all the things that affect how your body fights disease. Experience how the underpinnings of your immune system could be bolstered by the people around you.

This imagined app gives users an invisible nudge – who to see, who to know and who to ignore. The algorithm ensures which friend’s posts have visibility in your feed, which text messages always get a response, which alerts take priority, it watches your calendar and makes sure to rearrange for people you need to make time for. Those lunch meetings with toxic people get rescheduled enough times to fall off the calendar for good. And network mathematics influence which people you need to meet and pushes you to get to that event. The feeling of random encounters for that perfect introduction at the right moment is not so random anymore. Amidst a day of too much to do and too few real friend encounters - Friend Nutrition is an invisible nudge that pays off. 

The potential pitch to venture investors is - software to disrupt the random way we make friends by using machine learning and voice sensors in your phone. People want to connect - 81% of US internet users are on facebook, 50% of 18-24 year old’s go to social media when they wake up everyday. Friends are the most powerful mechanism to influence how you feel – and it’s left to chance? Friend Nutrition will watch, learn and serve a nutritious mix. No FDA approval required.

If there is an inch to be found in anything that is random, disorganized or could be tweaked for advantage, the software world will find it.

The most ubiquitous sensor voluntarily carried around is the microphone in your phone. Voice pitch, timing and natural language analysis can indicate emotional response. Think I'm making this up, check out the Sociometer study from MIT, now called Humanzye, captures body mirroring and voice pitch to good result. The language analysis tool LIWC analyzes psychographics of the speaker and accurately models two person interactions. Another AI project at MIT Media Lab monitors emotional tone of unstructured conversations in real time with 83% accuracy, and a sentiment score on 5 second chunks of dialogue. While there are tons of sensors possible, voice and text alone could be enough to monitor emotional response of people interaction with high precision.

How can you measure an actual friendship, that’s nuts. The AI in this app doesn't actually understand HOW you make friends, the algorithm just watches your response to people. Assuming you’re limited to about 150 relationships, friends are often one dimensional - we don’t insist they be everything like a parent or a spouse. One friend invites you to fun parties, another challenges you to be a better person. Does a finite number of one-dimensional friends make it easier to model and adjust a mix?

The AI in this app doesn't actually understand HOW you make friends, it just watches your response to people.

The learning algorithm can observe steps that lead to a positive friendship and favor more of those.  The right mix is more like a ‘cocktail’ sweet, salty, acidic… Not all our encounters need to be super-pleasant, A perfect formula could be a mix of slightly acidic questioning people who make us nervous and others who act like a positive vitamin boost. And every now and then you need to meet an "I-learned-a-lesson" person, or you’re doomed to be one of those naïve unchallenged souls.

This whole system of an unsupervised machine learning for friends would be like AlphaGo from Google. It mastered the complex game of Go. The intricate system of moves, countermoves, and how a friendship forms, shifts and responds is something like a game. AlphaGo for friends. Watching latent variables, the analytics could find unnoticed or uncharacterized human responses to friends in the real world. The training dataset for billions of social interactions exists, WE have been training the social media dataset for a decade - it's huge, 510,000 comments a minute. 2.2 billion facebook users. Facebook is learning how we interact, better than we understand ourselves.

Analytics of friends - how could it benefit us in a way that’s helpful enough to overcome the slightly invasive manipulative creepiness of it. You can see it would work, a deep learning algorithm finding a way to payoff what sociologists have been touting, layering on vast social media use and reliance on digital tools for most all connections. It’s a drug-free boost using our own human chemistry.

Perhaps this scenario is not so far from reality, our friends will become like diet and exercise. I wrote this article because I imagine an academic team somewhere is working on this right now and could use some encouragement. Tell them to feel free to steal the name and tagline.

Friend Nutrition - like a balanced meal of who to see, know and ignore. 

Why is this not data visualization? Show me the data.

I really hate it when people describe my work as data visualization. 

These are experiments to anticipate a future when art is simply the way we will consume data about ourselves... and the people around us. Art holds emotion and nuance, we can read it as pattern that explains the experience. The data is just an ingredient.

I imagine we will live in spaces filled with 'bumpy walls' with color and texture that tells us an ever changing story about ourselves. And the mesmerizing part of this will be how it will anticipate and predict for us, a type of time-travel into our future to give us a glimpse of what will come. Maybe biofabricated and grown or lasercut with tiny robots... the idea is that these will be easy to recycle and update all by themselves. 

But rarely do I show where the actual data originated, and how the work happens. Here is a presentation I pulled together for a meeting last week, and thought it was helpful enough to share.

Friend Nutrition: who to see, know, ignore...

I have a few people in my life who are a little 'toxic' -- what if I got a nudge to ignore them, or that lunch date we promised simply 'fell' off the calendar.

This is the future.

It's not about the data gathered about you, our next fixation will be the data gathered about the people around you. I predict who you hang out with will be like diet and exercise, we'll manipulate body chemistry with friends.

I'm dipping into 'art science' it's a near-future version of art-science-fiction. Here's my pitch.

OK, I'm joking when I say -disrupt- it's become a way to make fun of silicon valley startups, but.... if there is an inch to be found in anything that is random, disorganized or could be tweaked for advantage, the software world will find it.

Have you noticed how friends make you feel? Some kick you in the butt and you exercise more, dress better, eat fish, think of a new project, feel a new job is possible, start a business... and others do just the opposite? Friends really are the new family, in cities like Seattle and Denver 40% of adults live alone. In the last couple years, sociology of friends has exploded with new studies, friends of friends influence if you smoke, lose weight, how you vote. New research has measured stress, inflammation... all the things that affect how your body fights disease, the underpinnings of your immune system could be manipulated with the people around you. No FDA approval required.

Friends are huge.... the most powerful mechanism to influence how you feel, and it's left to chance?

My imagined software 'Friend Nutrition' gives you a nudge... the comments and posts you see in your social media, the messages that get priority and you see first. A toxic meeting? Boom - canceled. Who you run into in the real world, those serendipitous introductions, friend-of-friend meetings at somethingorother. Not so accidental, the mathematics of networks can connect you to situations and people that are part of a nutritious mix. Amid a day of too much to do and too few real friend encounters - Friend Nutrition is an invisible nudge. 

Yeah, I made up the results...but I asked friends in the know and looked at tons of academic studies, the behavioral change is probably even higher, but I wanted it to look believable.

How would this software make money? At the same time it serves up visible connections, it reverse bills for product placement - there is a fancy bike in the image, a can of LaCroix water, the car in the background of the selfie ...those companies get microbilled for visible product placement.

How? It's machine learning for the complex interaction of friends. It doesn't actually understand HOW you make friends, it just watches your response to people. Your friend network is limited, with maybe 150 casual friends and about 15 intimate friends - so the actual numbers are pretty reasonable. 

The best sensors will be tracking your voice from the microphone on your phone - the pitch, timing, language analysis all very indicative of how you are responding. Think I'm making this up, check out the Sociometer study from MIT, company is now called Humanzye. 

This whole system of an unsupervised machine learning for friends would be like AlphaGo from the DeepMind team acquired by Google. It mastered the complex game of Go. The complex system of moves, countermoves, and how a friendship forms, shifts and responds is something like a game. The training dataset for billions of social interactions exists, WE are training the social media dataset - it's huge, 500,000 comments a minute. 2 billion users of facebook, 80% of US internet users. Yes, it's learning how we interact, better than we understand ourselves.

Friend Nutrition - like a balanced meal of who to see, know and ignore. 

Hell, I wrote this post, cause I imagine an academic team is working on this, and could use some encouragement :-).