Rabbit Hole – Four Book Recommendations and an Amazon Story

Painkillers not Vitamins

I recently made the misguided wager with an ex-Amazon Product Manager that I could give up reading Kindle and get all of my books from the library, which seemed like a reasonable bet as:

  • I generally, aesthetically, prefer paper books
  • I live next door to a very, very good library
  • I hate losing bets

Nonetheless, I lost the bet (and so a very good bottle of bourbon), from which I take away two lessons:

  1. Don’t bet with Amazon product guys on your usage of products they designed
  2. Sell painkillers not vitamins

There has been a sharp revival over the past couple of months in the Valley of the ‘Painkillers’ and ‘Vitamins’ analogy in in terms of categorizing technology Products and Features.

It’s not a new concept. Here is someone writing about it from 2014 in an article called Is Your Product a ‘Vitamin’ or ‘Painkiller?’  

TL;DR: Vitamins are “nice to have” but you feel like you can probably get away with skipping them, at least in the short term. Painkillers, well, y’know, reduce a real, currently felt pain.

So simple but such a strong heuristic. Especially on the consumer side when you have enormous numbers of smart people armed with a huge ongoing stream of data to test and develop into new, more addictive painkiller variants.

[Ed. note – Epsilon Theory is definitely a vitamin, not a painkiller, and we’ve built the business model around that concept, where you pay us money because you WANT to, not because you HAVE to. It’s a challenge, to put it nicely, and many is the day I hear the siren call of the painkiller alternative.]


Code: The Hidden Language of Computer Hardware and Software

Now that I’ve lost my library bet I’m free to go back to over-consuming Kindle books. A particularly charming recent read was Code: The Hidden Language of Computer Hardware and Software. It is super accessible and a neat, illustrated step-by-step build up from morse code thru Boolean algebra to microprocessors, while also illustrating the meta-points of ‘humans as compulsively narrative animals’ and the ‘combinatorial nature of technology acceleration’.


Positioning: The Battle for Your Mind

I’ve had professional need recently to think about refining and amplifying my own public narrative (rather than analyzing and predicting other people’s) and so have gone back to read some marketing classics.  A very high value, quick read is Positioning: The Battle for Your Mind from 2001. Truly a classic on positioning in advertising, with great insight for analyzing narratives overall, particularly around ‘Cherchez le creneau’: looking for the hole in the narrative that can then be exploited.


The Hour Between Dog and Wolf: How Risk Taking Transforms Us, Body and Mind

I was sure that I had pointed to the book The Hour Between Dog and Wolf: How Risk Taking Transforms Us, Body and Mind on Epsilon Theory previously, but a site search of ET says no, although does reveal a general love of dog-themed articles.

Well, anyway, The Hour Between Dog and Wolf is a very good and easy read written by a derivatives trader turned neuroscientist who writes about how our biological responses translate into trading behaviors.

I was reminded of it recently by ET member Michael Madonna’s comment on a note I wrote a few weeks back where he referenced Yuval Harari’s proposition of ‘shared myths as key evolutionary advantage to work together in large numbers’. I find this very compelling and recalled the thesis advanced by Coates in The Hour Between Dog and Wolf that consciousness (and so collective myths and narrative) are a function of movement: that consciousness evolved from the usefulness of being able to pre-plan our movements (such as the steps required to jump out of tree and capture something edible).

[Ed. note: Endorsed! A wonderful book, although I believe this hour between dog and wolf is a particularly male concept. But once you start looking for it, you will see it EVERYWHERE. It’s also my second favorite French expression, just after “l’appetit vient en mangeant”.]


Spiral dynamics

Every couple of years someone exceptionally smart with a really well developed mental model of human interaction brings up ‘Spiral dynamics’ and why it is such a powerful framework. I then try to read one of the Spiral Dynamics books and remember that it is like the worst, most impenetrable writing of Veblen but with thick tie-dye coat of woo-woo painted on top. Ghastly.

Nonetheless, stylistics aside, I think there is genius hidden in there, and in particular that there is genius of a segmentation of how various agents will react to narratives and in different game constructs. So, if you can actually read and process the thing then glory in narrative-reaction analysis will probably be yours. Good luck.

Rabbit Hole – Who’s Being Naive, Kay? Also, DARPA, Ribbon Farm, and Unknown Knowns

For the past few week I’ve been meaning to write Rabbit Hole notes about, variously, Anti-metrics, Painkillers and Vitamins, The Objective Function of the CCP, and The Amoral Exportation of Technology (in the Cobb–Douglas sense). But, alas, instead of writing any of these things I have been suffering under a kind of writing ennui brought about by a misguided bet that I could stop reading on Kindle and go 100% paper books, which in turn has led me to start hanging out at The Mechanics Institute Library.

The Mechanics Institute Library in San Francisco is a terrific, terrific place (and also the home of the oldest continuously running chess club in the US). It is so terrific that it is in fact too terrific and so a terrible place for writing with the weight of so many great words and thoughts literally towering above.

But finally, mercifully, my writing listlessness was broken by ‘Bezos Exposes Pecker’, and my faith restored that there are new and important words to write in the English language.

Thank you, New York Post !

So, I’ll try to take on the Objective function or Anti-metric note soon, but in the meantime, here are some links to interesting things written by other people:


Technology and time

The BBC has a new series about the long view of humanity, which aims to stand back from the daily news cycle and widen the lens of our current place in deep time. This long-ish piece gets into a combinatorial account of technology and time:

“From the perspective of technology, humans have been getting exponentially slower every year for the last half-century. In the realm of software, there is more and more time available for adaptation and improvement – while, outside it, every human second takes longer and longer to creep past. We – evolved creatures of flesh and blood – are out of joint with our times in the most fundamental of senses.”

It is just so important to be able to step out of our day-to-day perception of time and be able to think about technology (and other things) on a broad arc like this.

There’s a great Steve Jobs quote on the long view of being a tech builder:

“This is a field where one does not write a principia, which holds up for two hundred years. This is not a field where one paints a painting that will be looked at for centuries, or builds a church that will be admired and looked at in astonishment for centuries. No. This is a field where one does one’s work and in ten years it’s obsolete, and really will not be usable within ten or twenty years. It’s not like the renaissance at all. It’s very different. It’s sort of like sediment of rocks. You’re building up a mountain and you get to contribute your little layer of sedimentary rock to make the mountain that much higher. But no one on the surface, unless they have X-ray vision, will see your sediment. They’ll stand on it. It’ll be appreciated by that rare geologist.”

I think the combinatorial point is most important and missing from the Jobs analogy but, still: True words.

As a pragmatic point, in software architecture in recent years we have all adopted the combinatorial / sediment technology paradigm (although perhaps not all with such philosophical reasoning) by moving to ‘no-end state architecture’. For a neat, pragmatic, wide ranging talk on ‘no-end-state architecture’ in a corporate environment, take a look here.


Marketing alpha

Some years ago, Ben wrote the canonical note on a Narrative trade, “Who’s Being Naive, Kay?“, illustrating with the canonical Narrative stock Salesforce.

This blog post is a neat breakdown of the Salesforce ‘strategic narrative’ by a former Salesforce marketing person.

Realistically, we all already know perfectly well that Salesforce is doing this (telling a great story in the format of the second link, and broadcasting it well for stock price management as described by Ben in the first link) but Benioff is just so good at it, and we are hackable animals, so on it goes.

In many ways Benioff is the Arjen Robben of Software-as-a-Service, and we are all the hapless defensive lineup (scroll to the bottom ‘Ode to the Hack’ link and watch video).


DARPA’s new “Schema” approach to understanding the world

The Defense Advanced Research Project Agency (DARPA) has created a new program called KAIROS (Knowledge-directed Artificial Intelligence Reasoning Over Schemas) aimed at creating a machine learning system that can sift through the many, many events and pieces of media generated every day and identify any threads of connection or narrative in them.

[ Ed. note: Wheeee! ]

The approach is interesting as it uses a “Schema” approach, in this case “Schema” meaning the process humans use to understand the world around them by creating little stories of interlinked events. For instance when you buy something at a store, you know that you generally walk into the store, select an item, bring it to the cashier, who scans it, then you pay in some way, and then leave the store. This “buying something” process is a schema we all recognize, and could of course have schemas within it (selecting a product; payment process) or be part of another schema (gift giving; home cooking).

This is interesting as, in some ways back, it goes back to ur-semantic AI classification system concepts, but maybe now with the compute power to make it work.


Epsilon Theory’s odd cousin, Ribbon Farm

My favorite technologist / hemp farmer / Epsilon Theory reader turned me on to a long form blog called Ribbon Farm. It’s odd. I quite like it. It strikes me as kind of like Epsilon Theory if, instead of going into asset management, Epsilon Theory had spent 20 years as a kind of dilettante grad student, reading widely, getting stoned and arguing with other grad students.  

[ Ed. note – in the trade, this is called “being an NYU professor.” Six years was enough for me. ]

Here’s Ribbon Farm on the Narrative:

“A story or narrative is a mental projection of characters and events embedded in a particular causal logic. Listening to a story seems passive, but in order to process the narrative, the listener must construct a coherent mental world out of the details provided. Unconscious predictions are made, and then winnowed and changes as more evidence is presented and conflicts resolved …As human beings, “projecting and sharing stylized model worlds in mental space” is both our ancestral job and our favorite hobby. The world that we interact in is mostly imaginary, constructed by all of us out of fantasies and guesses. As we get more intelligent, we will get more imaginary.”


Unknown knowns

And, finally, I found myself recently digging out the Donald Rumsfeld ‘known unknowns’ quote:

Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones.”

I then found myself falling down the rabbit hole of thinking about about Slavoj Žižek’s fourth category of unknown knowns“the disavowed beliefs, suppositions and obscene practices we pretend not to know about, even though they form the background of our public values.”

As I previously wrote about in ‘Take Back Your Thinking’ I’m a big fan of, and investor in, meditation as I find it reveals to me my own unknown knowns , which I’ve found over the years are the real ‘gotchas’. More broadly, it seems that it is the unknown knowns that are currently, very clearly getting us into trouble as a society.

[Ed. note: both Orwell’s “collective solipsism” and Zizek’s “unknown knowns” are terrificly important aspects of Common Knowledge. Dark aspects, for sure, but no less important for that.]


Rabbit Hole: Mathematical Toys, Moral Injuries, and Odes to the Hack

After tiring myself out with a longer note on ‘Building the Narrative System’ last week, this week I offer a round up of my favorite links from recent months:


Interview with Tadashi Tokieda, collector of mathematical toys

This is a wonderful interview with Tadashi Tokieda in Quanta (the Jim Simons financed magazine with the public service philanthropic mission of “Illuminating basic science and math research through public service journalism”). Favorite quotes:

If you project on the wrong axis, something looks very complicated.

“I decided, as a personal revenge on Landau, to study the subject up to the point where I could solve this exercise. Landau said, in the biography, “Don’t waste your time on mathematicians and lectures and so on — instead, find a book with the largest number of solved exercises and go through them all. That’s how you learn mathematics.” I went back to the library and found the mathematics book with the largest number of problems.”

I’m trying to jolt myself out of my complacency. When I share, I just want to share with people. I hope that they’ll like it, but I’m not trying to educate them, and I don’t think people are complacent. People are struggling in their own ways and making efforts and trying to improve. Who am I to jolt them out of complacency?


Shockingly, auditors say the world needs more auditing (but they are probably right)

In an HBR article, several execs at Deloitte execs write about ‘Why We Need to Audit Algorithms’. It’s actually a really good point, but hard not to mock the self-interest.

(Note: I write this whilst cowering in my glass house after having interviewed Kiva’s Head of Refugee Investments for Epsilon Theory recently.)


Moral injury

I had not previously encountered not the clinical term ‘moral injury’, but it makes so much sense. Explanation here by Dr. Michael D. Matthews, Professor of Engineering Psychology at the United States Military Academy in the Department of Behavioral Sciences and Leadership.


Free software

Here is a post on ‘Why Open Source misses the point of Free Software’ by Richard Matthew Stallman (RMS) who knows a lot about software (and also it seems has strong views on the TSA). It is an important topic and I really hope we can return to a world with a better signal to noise ratio on important topics like databases, security and free software (rather the the free-for-all silliness that blockchain seems to have dragged the conversation to … although I guess I am thankful that at least we are talking about database structures and their impact at all).


Can you guess who said it? – China edition

Can you guess who said it:

“Anybody who does business in China compromises some of their core values. Every single company, because the laws in China are quite a bit different than they are in our own country.”

  1. The really drunk, chatty guy from Boston I was sat next to on a flight back to San Francisco last week;
  2. The current US President;
  3. The former President of Stanford University and current President of Alphabet;
  4. All of the above.

Inconclusive answer on this link.


Ode to the hack

And finally, I think this is, improbably, the finest piece of sports journalism of 2018.

I admit that odd, amatuer-ish, lowbrow millennial-Gonzo journalism is a guilty pleasure of mine but, regardless, this article from Vice UK is a genuinely wonderful tribute to ‘the hack’. In this case to a football (soccer) hack, but it could equally be written about a certain rare type of entrepreneur, a certain rare type of product person:

The Dr. Manhattan of football hacks

You know what he’s going to do but it’s impossible to stop it. Arjen Robben has been scoring the same goal for so long now that he’s gone fully bald while doing so… he is the Dr Manhattan of running really fast down the right touchline before cutting inside on his left foot, shifting it, shifting it, shifting it, and then launching the ball with barbarous force into the far corner of the net … With relentless repetition, Robben’s trick is passing beyond the realms of tedium and mild annoyance into something that is pleasing and even, in these late-autumn flushes of his career, weirdly poignant.

For full impact make sure to watch the video half way down. Incredible.

Building the Narrative Machine

This week, inspired by Ben’s note We’re Doing It Wrong, I thought that I would write a follow up note on ‘Eight learnings on incorporating Narrative observations into a system’.

This note is not written to be deeply technical, nor is it written from an envelope-pushing theoretical perspective. Rather it is from the perspective of a practitioner and therefore from a practical – and hopefully digestible – point of view on how to use visualizations of Narrative-space in real-world decisions and analysis.

By way of background, I’ve stared at and tried to make actionable sense of many, many thousands of machine-generated (or semi-machine generated) narrative analysis over the years, in areas ranging from political campaigns to military intelligence to corporate disaster response to equities trading systems.

And yet I feel like I’ve only touched the very surface of the power of this approach and what can be done. There is so much work to do in this area, so much potential, and while the Narrative is as probably old as language itself (probably older), it feels more relevant that ever right now to be able to observe, understand and incorporate the Narrative into our systems for making sense of the world.

Couple of framing comments before we get going with ‘the learnings’:

  • I’m assuming that most Epsilon Theory readers are not deeply technically engaged in Machine Learning so I’ve used terms such as ‘vector’ and ‘dimensionality reduction’ in somewhat liberal, expressionist ways that I think are intuitive and most usefully convey core concepts, rather than in precise, formal ways (and stayed away from terms like ‘centrality’ and ‘vertices’ and other less intuitive but more precise graph theory terminology).
  • If you are interested in exploring some of the concepts mentioned below in more depth and with more formality, I would suggest starting by working your way through the book Python Machine Learning by Sebastian Raschka. It is a good, foundational blend of theory and practical application of Machine Learning and requires no prior knowledge of, or experience in, coding (of course, there are many other good resources on this topic too, I just happen to be familiar with and like this one).
  • For full transparency, I was previously the CEO of Quid, a pioneer in Natural Language Processing (NLP) and Graph Theory that generates many of the Narrative maps seen on Epsilon Theory. This note is not Quid-specific, but rather takes on the overall topic of machine-assisted Narrative observation. Some of the examples below can be very well executed on Quid, some can be performed using free open source software (with some configuration work), some require custom extensions of both / either.

Learning #1: It’s not unstructured data, it’s really complex structured data

Firstly, and foundationally, to state the obvious, the Narrative is most often expressed in language (sometimes in pictures, dance and other forms, too, but for today let us stick to language).

Oftentimes language is referred to as ‘unstructured data’, which is database data model terminology.

However, ‘unstructured data’ has gradually crept into general parlance and led to this kind of implicit, half-formed notion that the Narrative is therefore intractable except in a thin, reductionist way.

This is a mistake.

Clearly we know that language itself is not unstructured, otherwise you could not read this; it just has a high degree of complexity in its structure.

This notion of language and the Narrative being intractable except in a thin, reductionist way is the first mental block to rid ourselves of.

We will come back to this point, but this is why using high dimensional graphs is a useful technique for analyzing the Narrative and why squishing the dimensionality way down into a ‘factor’ to put alongside categorical and numerical variables in a regression-type approach is typically pretty unrewarding.


Learning #2: Narrative ≠ Sentiment

The only word that is more irritatingly misused than ‘factor’ when talking about Narrative is the ‘S word’: Sentiment.

Sentiment is to NLP as sushi is to Japanese food. It’s fine, it’s in the set, but is very far from the whole cuisine.

And most sentiment analyzers are like the $10 takeout lunch special with green-dyed horseradish instead of wasabi – it’s not capturing the right flavor. At all. For example, imagine you are trying to evaluate the sentiment of equity analyst reports, where the word ‘overweight’ is a positive thing, but you have trained your sentiment analyzer on general data (such New York Times articles), where ‘overweight’ is part of the same negative vector as ‘morbid obesity’. Your sentiment analysis isn’t going to be just in error, it’s going to be perversely in error.

Meanwhile we have very good okonomiyaki, yakitori, tempura, onigiri, sukiyaki and hundreds of other kinds of refined deliciousness we are ignoring.

Beyond Sentiment we can classify and score language by:

  • Affect (level of emotion)
  • Assurance (level of confidence)
  • Technicality (level of subject-area specificity)
  • Partisanship (level of social organization embeddedness)
  • Fiat-ness (level of opinion-leading effort, as Rusty has been doing here)
  • … and thousands of other vectors we can conceive of

Looking exclusively or even primarily at Sentiment as your vector of meaning in a narrative map is almost always a recipe for confusion. For example, below is a short document marked up with ‘sentiment’ in green and red, but also with “Growth” vocabulary and “Value” vocabulary highlighted in fuschia ellipses.

Question: Is the Barclays report below ‘positive’?

Answer: No, if you like Value-oriented constructs like EPS and lower Operating Expenses.

Answer: Yes, if you like Growth-oriented constructs like Sales, Gross Margins and Non-GAAP revenue.

Taken alone, Sentiment tells you almost nothing. Combined with other vectors of narrative meaning, Sentiment can be one (of many) useful dimensions of narrative analysis.

So, please don’t be (or let your friends be) that person who thinks Japanese food is sushi – there’s a whole world of cuisine and language analysis out there to discover!


Learning #3: Graphs are our friend

To do the analysis noted above of ‘Sentiment’ or ‘Growthiness’ for a large corpus of documents, an auto-clustering graph can be very helpful to help prune outliers, boost the score of ‘canonical’ documents etc., but it is not necessary.

For other type of analysis graphs are super, super useful.

With a graph we can group (cluster) and measure the similarity of documents. For example, here is a graph that Rusty recently generated on the Inflation Narrative using Quid where he has clustered documents based on their linguistic similarity in order to see the key themes:

This is very, very helpful in order to be able to understand the Narrative.


Learning #4: The art of the graph

Once you really get into NLP clustering graphs you realize that there is a real art – a very human art – to conceiving of and extracting insight by observation from these graphs.

This is because (with flexible software) the permutations are, for all practical purposes, infinite. As a result, being hypothesis driven on the question you are asking, having domain expertise to craft a query, and then having a certain type of intuitive analytical ability to iterate the analysis creates a strong edge.

To try to give an example of this, we might have a question about how the future looks like for Facebook, and so we spin up a graph about this.

Starting with a graph clustered by topic we might then have a sense that (using some of the examples from Learning #2) it would be insightful to score and then observe the documents in the graph on the following dimensions:

  • Technicality
  • Affect
  • Confidence (see below for an old CIA mapping of language to probability)

Having done this, we can can then re-cluster and, for example, distinguish a ‘highly technical, low emotion, high confidence tightly clustered cluster’ from a ‘non-technical, high emotion, low confidence loosely clustered cluster’.

This is clearly valuable and very, very hard to do without a graph that is visualized.


Learning #5: Enter the Missionary

The worst sin of all is looking at Narrative without considering the Missionary.

The number of times someone has proudly told me “we analyze a gazillion tweets in real time with our super bad-ass data munger” … but in a way that does not distinguish whether there is, and who is/are, the Missionary(s) on a specific topic, and at a specific time …

Ben has written so extensively on this I will not re-hash here, but if you don’t know who the Missionaries are – on the specific topic, at a specific time – then it is very unlikely your Narrative analysis will be very fruitful (except in racking up AWS fees for munging massive, fruitless data sets).


Learning #6: Be the Centaur

We used to talk about Centaur chess – a combined human and machine intelligence as the most formidable chess player possible – until DeepMind ruined it for everyone by constantly winning with a machine intelligence alone.

But Narrative analysis is still way, way, way more complex than chess and so a Centaur approach is the right one for Narrative. But in a specific way.

Clearly, computers are useful for computing graphs based on language similarity.

To be clear we don’t absolutely need a machine to calculate a linguistic similarity graph: it is conceivable to take a stack of 500 documents (say, analyst reports), mark up each document with a highlighter by its unique n-grams, copy the n-grams onto a post-it note per document, score each n-gram on each post it note by a global tf-idf score, and then use our judgement to group post-it notes together by high score post-it notes.

But, man, would that be tedious, and probably not very accurate.

So, computers are useful.

But so are humans. Especially ones with domain expertise, quantitative abilities and non-linear creative minds (especially, non-linear creative minds).

Bottom line is that in all but the simplest systems, we are currently at the stage where the machine is best at generating a base map of current Narrative reality, but a human is better at then asking insightful questions of the map and / or predicting how the map will evolve and / or its interaction with ‘other bodies’ (see below), which then leads to actionable insight.


Learning #7: Narrative analysis in markets is a ‘three-body problem’, but with each body having a continuously changing, long-term unpredictable mass

Generally, simplistically, for the purposes of developing a system, we can think of Narrative in equity price movements as one body in a real life ’three body problem’:

  1. Fundamental information
  2. Technical information
  3. Narrative information

If we are going to get serious about building a system that performs in the real world, we must understand that Narrative information does not replace the first two or simply reflect the first two, but is a separate body.

This is really, really, really important.

(note: I add the ‘continuously changing, long-term unpredictable mass’ clause, as it does not seem conceivable to me that this ‘full system’ can be brute force ‘solved forwards’ like the classical physics example Ben described in his note The Three-Body Problem, whereas it does seem conceivable that the Narrative alone can be a Three Body Problem as Ben describes – more on this and quantum computing at the end of this note)

Now, please take a minute to accept or reject the notion of Narrative as one body in a ‘three-body – but with each body having a continuously changing, long-term unpredictable mass – problem’, as I feel fully resolved on this point and so am going to carry on this section with the ‘3rd separate body’ taken as fact (while considering that you should please feel free to add more bodies or sub-dive the first two to conform to your mental model of markets and make it an n-body problem, that’s not the important point, the important point is that Narrative is its own body in a three or greater body problem ) …

… so, accepting as fact Narrative as a third body and that the first two bodies are super well understood conceptually and many smart people are hyper-optimizing and hyper-incorporating the available information, it logically leads us to certain practical approaches, such as looking for periods when the other Fundamental and Technical informational inputs are ‘weak form’ and the Narrative information can become dominant and strong form.

If your interest in this stuff is making money then this is the really key point.

It’s not that the other forces will ever be zero, or that you can really predict how long they will stay weak (per the ‘continuously changing, long-term unpredictable mass’ clause), but when the Narrative is strong it will set direction (or cause volatility), and even if other forces such as new fundamental information re-emerge in an unexpected way, the Narrative will help create an asymmetric elasticity bound around price movement driven by the new information.

Inversely, as Ben pointed out, if you are betting on Narrative and the Narrative is very weak form (i.e., no one is looking) you won’t get paid.


Learning #8: Need more resolution!!!

Does the Narrative Machine work? – Yes, it works.

I’ve seen it so many times in so many different contexts with systems I would consider to be really quite naive delivering really surprisingly strong results. Oftentimes to the extent that I’m suspicious of the results and spend days and days digging into them. But invariably the results are the results, we can know why as it’s not a black box, and by working hard the systems improve.

So, if it works and is relatively un-picked over, then why isn’t everyone doing it?

I think there are three main reasons:

1. Mental model

Ad agency folks, political campaign folks, Department of Defense folks and most creatives seem to get it very well, so it is not a general mental model problem, but I have bumped into a distinct mental model problem around Narrative for hedge fund / markets folks:

Candidly, the mental model problem is so strong I have pretty much avoided discussing this ‘computational approach to Narrative’ stuff with hedge fund folks for the past year or so as it almost always goes the same:

  • The fundamental-type people tell me about their ‘process’ and require the Narrative to fit into their existing process as a subservient input into their mental model (including crypto traders which is … well … sobering) as, for example, a way of improving the timing or sizing of what they are already doing.
  • Meanwhile, the ‘quantitative’ folks just seem bemused that I’m so excited about graphs and say ‘we already do NLP and have a proprietary model’. Considering the amount of time and money it takes to get this to work as an even half-decent system (at least in the way that I’m describing it), this seems improbable given the resourcing and backgrounds of technical people at most funds I’ve met, at least as of 12 – 18 months ago.
  • The ‘quantamental’ folks are truly the worst, as they are obsessed with reducing Narrative to a ‘factor’ in a regression alongside thousands of other structured data sets.

To be clear, my experience is that all categories mentioned above are full of very smart people, but somehow the mental model I believe is true about the Narrative just doesn’t seem to fit with the mental model of folks who build systems for trading / investing in markets for a living. Whereas folks who market shampoo and yoga pants for a living seem to really quickly and intuitively get it. Odd, perhaps, until you consider that FMCG ad agency people, DoD intelligence analysts, and political campaigners all truly live the Narrative and are relatively unencumbered by the Physics Doctorate and MBA predictive analytics orthodoxy.

Anyway, as I started with, it was actually this point as noted by Ben in We’re Doing It Wrong that prompted me to write this note.

2. Quite a bit of time and money investment

As noted above, building a scalable, reasonably accurate, extensible system that will allow you conceive of fairly arbitrary Narrative questions, quickly spin them up, and have the system learn from them is, in my view, at least a ‘15 strong engineers for 12 – 18 months’ problem to get to V1.0. So ~$3M – $5M cost to get to a basic system that can then be built upon, and then at least a $5M run rate cost (ideally more) to keep extending, with really interesting results taking a couple of years to get to. So, a reasonable sized dollar and time commitment for a new approach.

I think this is why you really don’t see many shops building their own systems and rather see people using sell-side text analytics tools that are relatively thin applications (i.e. they are ‘hard coded’ to extract certain features from certain types of reports which are then output as a ‘buy/sell’-type signal) or 3rd party point solution providers (like DataMinr, Bottlenose etc.) which are focused on single point solutions sold to many clients (e.g., Dataminr for getting early warnings of event by processing Tweets) but are not true Narrative solutions as we are talking about it here.

3. Still low resolution

The first two reasons given here are primarily bias barriers, but there is a 3rd barrier – a technical barrier – which is very real: Resolution.

Per above, for about $5M a year you can build and run a decent, fit-for-purpose, reasonably flexible system for this type of analysis.

However, make no mistake about it, the resolution with which you can see the Narrative through this system is relatively low, and your ability to take a constant stream of images (graphs) and in particular to compare images (graphs) is very, very limited.

My sense is that we are today at the animation equivalent of ~6 dpi, ~1 frame a minute. It’s blurry, you can kind of follow the story, but you gotta interpret (guess) quite a bit and it is pretty painful after a while.

Unfortunately, it is just a basic physical fact that comparing large, complex graphs using classical computing is very, very compute intensive (at least with currently available algorithms). So this puts a limit on the computational approach and is why human interpretation is still critical in anything other than quite simple systems.

To be clear, these low-res Narrative observation and calculation systems work really surprisingly well and you can make money from them, they are just nowhere near what they can, should and will be.

So, how will we get to the full Narrative Machine?

To my mind this ability to compare complex objects at low cost and at high frequency will be the ‘killer app’ of quantum computing and will make this stuff really work.

I remember speaking on the same bill as quantum computing companies D-Wave and 1Qbit two or three years back (an age ago in quantum computing land!) and even then this hit me as absolutely true. This 2016 paper by 1Qbit sets out the case well.

We are not there yet with QC, but my bet is that we will get there within the coming years and that we will then truly, finally be able to achieve the Narrative Machine.

To calibrate what an acceleration of compute power looks like, I leave you with this image of the evolution of Lara Croft rendering resolution as a function of GPU processor improvement.

My point here is a simple one: once a technology starts on a path of increasing resolution, it ALWAYS follows a Moore’s Law-esque trajectory of improvement, with uses and implementations at higher levels of resolution that were never even considered in early days. It took 17 years for Lara Croft to become a digital character indistinguishable from imagery of a human actor. It won’t take nearly that long for a similar resolution intensity of Narrative-space.

Is it early days with the Narrative Machine?

Yes. But not as early as you might think.

And the future will be here faster than you suspect.


The ET Interviews: Banking the Unbankable

After interviewing Alex Gladstein of Human Rights Foundation last week and getting into ‘censorship resistant money’, this week I wanted to go deeper into the ‘on the ground reality’ of some of the most vulnerable people in the world: forcibly displaced populations.

So, at the risk of ‘talking our own book’, I’m interviewing my colleague Lev Plaves, a Senior Investment Manager at Kiva, as he has about as deep and broad a knowledge of working with forcibly displaced populations as anyone I’ve ever met. – Neville Crawley


Welcome to Epsilon Theory, Lev! Could you give us a bit about your background and how you came to be leading this work?

I joined Kiva in 2012, not long after the war in Syria began. For my first 4.5 years with Kiva I was based in Istanbul, overseeing our work in the Middle East. I spent much of my time traveling in Turkey, Lebanon, and Jordan, the three countries which host more than 40% of Syrian refugees displaced globally. It was what I saw day to day throughout my time in the region that led me to focus on this work.

A 2015 trip to Lebanon specifically stands out to me. I recall checking into my hotel located in the trendy Hamra district of Beirut. Unlike previous trips to Lebanon, it was not the constant honking and scooters zipping through the streets that caught my attention. Instead, I was drawn to the half-constructed abandoned building across from me, most units filled with Syrian refugees looking for some semblance of shelter ahead of what is usually a cold and wet winter in Beirut.

For the refugees in the building across from my hotel, basic humanitarian assistance such as food and shelter was what they needed most. And that need remains today for many of the 68.5 million forcibly displaced people around the world.

But throughout this trip to Beirut, I was also struck by the many refugees I met who were eager to move beyond humanitarian assistance and were desperately trying to generate livelihoods for themselves and their families. This matched the reality I was seeing in my home-city at the time, Istanbul, where many of the Syrians I spoke to were well-educated or highly-skilled, but had sacrificed everything to escape the violence in Syria.

I realized that for many Syrian refugees, finding economic opportunities was now critical. The international development community as a whole was also coming to a similar conclusion — while emergency humanitarian assistance plays a key role, especially in addressing early needs, we must begin thinking about more sustainable solutions to the global refugee crisis.

I began to see that access to finance was crucial for many displaced individuals, as a loan has the power to help refugees start businesses, pay for urgent medical needs, or continue their education. I decided to focus my efforts at Kiva on what we could do to make financial inclusion a reality for refugees.

What are the basic stats on Refugees and Internally Displaced People (IDPs)? How many people in the world are there in this situation?

Today there are over 68 million people forcibly displaced. Nearly one person is forcibly displaced every two seconds. These are the highest numbers since World War II. According to the World Economic Forum 84% of refugees live in developing countries. And sadly these numbers are only going to increase in the coming years.

You launched the World Refugee Fund at Kiva. What is it and why did you launch it?

Despite the need for access to finance, most financial institutions around the world are unwilling to serve refugees. Refugees are often seen as too risky to lend to due to a concern over flight risk, specifically around the perception that refugees are highly transient. Refugees also may not have documented credit history and have few fixed assets or limited collateral in their new countries.

In response, we launched the World Refugee Fund (WRF) in an effort to mobilize Kiva’s unique capital to help financial institutions overcome the perceived risks of lending to refugees and catalyze refugee lending around the world.

Kiva works through a network of local organizations and financial institutions which we call our Field Partners. With the WRF, we began working with Field Partners in areas with large refugee populations to use Kiva funding to develop or scale lending programs that provide loans to refugees and internally displaced peoples (IDPs). Because our loans are crowdfunded by individuals in increments starting as little as $25, our capital is risk tolerant and uniquely compassionate. We saw that our funding had the potential to serve as R&D capital, allowing local financial institutions to pilot refugee lending despite their concerns around risk.

After working with our existing Field Partners, we then began finding other financial institutions interested in working with refugees and brought them on to the Kiva platform.

What have been the results thus far with the World Refugee Fund?

In our first year in 2016, we provided more than $1 million in loans to displaced populations. That more than tripled in 2017. In addition to serving Syrian refugees in the Middle East, our lending has expanded to IDPs in Colombia, Burundian and Congolese refugees in Rwanda, Central American refugees in Mexico, and we will soon be working with refugees in Kenya and Uganda. Today, the World Refugee Fund has provided $10 million in loans to over 11,000 refugees and IDPs around the world.

You recently put out a report on lending to Refugees and IDPs with some powerful data around credit risk in these populations. Could you share an overview of these findings?

The World Refugee Fund is more than just lending, as we believe our work can lead to systems change. On June 20th of this year (World Refugee Day), we released our first Refugee Impact Report, which challenges the perception of refugees as “too risky.” Our findings show that refugees and IDP borrowers repay their loans at a rate on par with non-refugee borrowers. Since the start of 2016:

  • Loans to refugees and IDPs have a repayment rate on Kiva of 96.6%
  • Loans to non-refugee populations have a repayment rate on Kiva of 96.8%

The data is clear: refugees can, and do, pay back loans. Our goal is to continue to share our results around refugee lending, as we believe that doing so will change the perception around refugees being too risky and encourage other lenders to begin serving displaced populations.

As you know, I think and write a lot about changes in technology in this Rabbit Hole column and the effect (both good and bad) on society. Is there anything you are seeing in this area that is particularly relevant to Refugees and IDPs?

Technology has a major role to play. We are beginning to see ways in which technology can solve some of the key problems refugees are facing. The lack of formal identity, for example, is a challenge facing many individuals displaced around the world. As efforts around digital ID gain more traction, I think refugees stand to benefit greatly.  

Kiva recently announced the launch of Kiva Protocol, a new initiative which will provide unbanked people with decentralized self-sovereign digital identity. I am personally excited about how we can expand this project to support refugees, especially those who are without formal identity. This would also be hugely impactful for those who may, unfortunately, become displaced in the future.

Digital identity is just a beginning. Technology has the potential to help refugees in areas such as credit history, remittances, and carrying money across borders. For a refugee who has settled in Jordan or Lebanon, a digital wallet with their credit history, education records, employment history, and so on, would be a great asset. Leaf, a digital savings platform, has become another leader in this space, looking to provide refugees with the ability to safely transport savings across borders.

In the future, I see the potential of this work leading to digital visas, providing refugees with access to digital work, which is especially important for those in countries where their right to work is limited.

Bank accounts are another major obstacle. Even in many countries where refugees legally have the right to work, they are often unable to open a bank account. Could technology solve this problem by offering a digital bank for the displaced?

Could you relate a personal story of where we have been able to put money to work and it has helped a family or community to thrive?

Last year I met Samira, who fled violence in Syria with her family and settled in Lebanon. Here is an excerpt of Samira’s story, the full version of which can be read in this blog post:

“We didn’t bring anything from our home, except for some clothes because we thought we would be back in 2 months,” Samira explained. Seven years later, the family is still not able to safely return home. In those early days adjusting to life in Lebanon, Samira struggled to connect with her new surroundings.

“When I came here, I had just come out of a state of war. I was depressed and didn’t want to see anyone. I kept on thinking about war. I was always scared,” Samira said. “Everything was ‘Syria, Syria, Syria.’ Until I slowly started to meet people.”

One of the people who started to bring Samira out of her depression was her Lebanese neighbor, Souad. A tiny but vivacious woman, Souad is quick to smile and always ready to provide tea, compliments and advice.

Making a living was hard for Samira and her family too. She was doing makeup and hair for weddings but wasn’t able to make enough. Souad suggested they take out a loan, funded by Kiva lenders, so they could both build their businesses. With the Kiva loan, Samira bought used wedding dresses to rent to Syrian brides for affordable prices. Souad and Samira helped each other pay back the loan successfully. Thanks to this new business, Samira was able to double her income from $300 a month to $600 a month. She was also able to help move her family into a larger apartment and buy supplies her kids needed for school.

Meeting Samira not only showed me the impact a small loan can have, but I was also struck by Samira’s relationship with Souad. Especially in Lebanon, there is often tension between refugees and their host communities. With Samira and Souad’s joint group loan, I saw how economic opportunities can bring people together and encourage social cohesion.

What do you think the outlook for Refugees and IDPs is over the next decade?

Unfortunately, the number of forcibly displaced peoples is going to increase. Humanitarian assistance will continue to be vital, but economic opportunities and supporting the long-term needs of refugees will only become more important.

Today’s discourse often frames refugees as a burden; a population solely in need of aid. And while refugees certainly need the support of the international community, we need to shift the paradigm to one that understands that refugees also have the ability to be significant contributors to local economies and societies as a whole.

I saw how true this is first-hand throughout the time I spent living in Istanbul and traveling often to Lebanon and Jordan. And many others have seen it too, whether in developing countries, such as Rwanda, or in communities in developed countries, from Denmark to cities in the United States.

To truly improve the long-term wellbeing of refugees, we need to look at the whole picture of what is needed to rebuild their lives and create healthy communities. Demonstrating that refugees are viable microfinance clients is our first step, and our long-term goal is to continue to serve as a proof of concept that will unlock capital at scale for refugees. Bringing digital identity and credit histories to displaced populations will be a key next step for us. But these are only small pieces of the puzzle in empowering refugees.

It will take a massive effort to see real change become a reality for more refugees, one that will require NGOs, the private sector, and governments all to play key roles. It is my belief that if we all come together, we can truly help refugees and displaced people build a brighter future for themselves and their families.

Who else do you think is doing impactful work in this space?

The list of people doing impactful work in this space is endless. From UN agencies, namely The United Nations High Commissioner for Refugees (UNHCR), to both local and international NGOs, first responders on the ground are providing life-saving humanitarian assistance to refugees and IDPs. Many NGOs, such as the International Rescue Committee, MercyCorps, and Save the Children are looking both at the humanitarian side and also creating sustainable livelihood opportunities, such as providing trainings to refugees focused on entrepreneurship skills and business development. This work is key in helping displaced populations get to a place where a loan is even appropriate.

And we are already seeing impact in the digital and technology space as well. In addition to Kiva Protocol and Leaf, mentioned previously, Making Cents is piloting a digital ID platform for Syrian refugees in Jordan. Last year, the World Food Programme rolled out its Building Blocks pilot, an effort to use blockchain as a means of making transfers more efficient, transparent and secure.

Foundations and the private sector, especially those in the US, are also already playing an important role and their support will only become more necessary. USA for UNHCR, a Washington DC based non-profit, was one of the first supporters of Kiva’s World Refugee Fund. Another supporter of the WRF, the Tent Partnership for Refugees, is bringing some of the biggest private sector actors together to support refugees.

Kiva is also proud to be on the steering committee of the Refugee Investment Network (RIN), the first impact investing and blended finance collaborative dedicated to creating long-term solutions to global forced migration. The RIN recently released a landscape report which shows how investment can unlock the potential of refugees.

As I previously mentioned, ensuring that these different efforts support each other, rather than exist in silos, will be key. Open Society Foundations and The United Nations Development Programme (UNDP) have begun exploring ways to more formally coordinate and bring together the work of existing initiatives. Such an ecosystem or enabling environment will foster the collaboration and innovation we need in the space.

If someone wanted to directly help and get involved what can they do?

All of the organizations I’ve referenced are great ways to get involved, whether you are looking to volunteer, donate, or invest in the refugee space.

Speaking to our own work, now that we have proved the credit risk profile of this population through $10 million of lending, we believe there is a clear business case to lend to refugees. We just announced that we are scaling our efforts by raising a new $50 million Kiva Refugee Investment Fund that will be an institutional, positive IRR fund putting money to work via deeply impactful loans to refugees. For any portfolio managers out there looking to add this to their mix please be in touch by emailing refugees@kiva.org.

The ET Interviews: Anti-Authoritarian Technology

[Ed. note: Neville Crawley is more plugged-in than anyone I know, so when he offered to interview smart people on the front lines of the technology/mass society battleground as part of his Rabbit Hole series, I figured it would be good stuff. As it turns out, it’s GREAT stuff. Here’s the first in what I hope will be an ongoing feature for Epsilon Theory. – Ben]

This week I am interviewing Alex Gladstein, Chief Strategy Officer of Human Rights Foundation and guest lecturer at Singularity University. I met Alex a couple of years ago when he was moderating an exceptionally interesting and lively Human Rights Foundation (HRF) panel on identity, distributed systems and human rights. Alex’s work has helped me gain a deeper appreciation for how fundamentally identity and human rights are tied together, and the importance of considering freedom and control of the most vulnerable populations when designing technology infrastructure. Alex is a deep thinker on the intersection of technology, freedom and decentralization and so I am very pleased to welcome him to Epsilon Theory. – Neville Crawley


Welcome to Epsilon Theory, Alex. Firstly, what is the mission and origin story of HRF?

The Human Rights Foundation was founded in 2006 by the Venezuelan activist Thor Halvorssen. The world was 7 years into the Hugo Chávez experiment, and things weren’t going well in Venezuela. The Chávez regime was jailing critics, cutting off independent media, fatally compromising the independence of the legislature and judiciary, and presiding over monstrous corruption. Thor was watching his country — which, before Chávez, was a constitutional (if imperfect) democracy — slide into outright authoritarianism. Today it’s easy to look at the human rights and starvation disaster in Venezuela (now home to one of the world’s largest humanitarian crises, producing more daily refugees than Syria) and say we should have done something. But before Chavez’s death, the world did very little. In fact, the mainstream political establishment at the time seemed to at times to be cheering for Chávez. Human rights groups were quiet until late in his rule. So, with this experience in mind, Thor chose to found HRF as a non-profit organization to focus specifically on promoting individual rights and civil liberties in closed and closing societies. As far as I know, HRF is the world’s only organization that focuses on authoritarianism as a global problem. We work simultaneously on challenging and exposing the crimes of dictatorships everywhere from Cuba to Saudi Arabia to Vietnam, while at the same time running programs to support democracy activists, civil society organizers, at-risk journalists, and others who labor under authoritarian regimes. Our programs include the Oslo Freedom Forum conference series, the Flash Drives for Freedom initiative to smuggle outside information into North Korea, PutinCon, and a range of impact litigation, technology, and educational initiatives to support rights advocates operating in tough environments. By HRF’s count, there are approximately 4 billion people in today’s world who live under some type of closed society, where there is no ACLU, no Washington Post, no ability to hire a human rights lawyer, no chance at organizing a successful public protest, no way to safely run a pride parade or expose government corruption. HRF specializes in helping dissidents in these conditions, the future Havels and Mandelas of the world.

Could you give us a bit about your background and how you came to be Chief Strategy Officer of HRF?

In early 2007 I was studying in London and interning at the British Parliament. I managed to get a summer position at HRF, and my first task was to put together backpacks which would be brought by my Latin American colleagues into Cuba and given to the island’s underground library movement. Inside the backpacks were innocent-looking cases of music CDs–Britney Spears, and the like. But despite their labels, I had secretly burned onto the discs various dubbed films ranging from Braveheart to V for Vendetta. Cuban civil society organizations would watch them quietly in tiny groups inside their homes on portable DVD players which we also supplied. The program was hugely popular, and there was always a demand for more content. In a country where the dictatorship approves all books and educational content, a movie can act like a red pill in The Matrix. This type of activity later become what is now known as the paquete, a Netflix-meets-Milk Man system where Cubans now get video on demand, delivered to their home. I worked on a few other meaningful programs, and in 2009 we launched the first Oslo Freedom Forum, and I was forever hooked on HRF. Thor saw that the world had prominent, popular, high-level gatherings for finance (the World Economic Forum), ideas (TED), and development (the Clinton Global Initiative) — but nothing similar for human rights. Thor’s filmmaking background and Norwegian connections led us to do a theater production in Oslo, where dissidents would tell their personal stories on stage to an audience of industry leaders. The goal was to find the most effective individuals pushing peacefully for freedom in places like Russia and China and give them a platform, media attention, resources, new technical skills, and a global network. Over the years I worked very closely on this project, while also working in media and development areas. In 2015 I was appointed Chief Strategy Officer and since then have led our communications and development efforts and helped shape our overall growth strategy.

I know that you personally think a lot about ‘anti-authoritarian technologies’ and spend a lot of time with the blockchain community. What projects are you particularly interested in right now and why?

Through my work at HRF I’ve gained a great and deep appreciation for liberal democracy, or, as we could just as easily say, decentralized government. In fact, I would argue that separation of powers is the single most important ingredient for a liberal democracy — far more important and fundamental than elections. All dictators have elections. And we’ve had various forms of tyranny ever since the agricultural revolution. The real innovation in governance — arguably first sparked by Cleisthenes in ancient Greece 2,500 years ago — was that humans should be ruled by rules, not rulers. In today’s liberal democracies, power is distributed across executive, legislative, and judicial institutions, and is constantly checked by the people through a free press and by civil society organizations. In a healthy democracy, no single person or small group of people is in charge. I am drawn to bitcoin because it brings this same concept to money and to technology. There are other technologies that I view as anti-authoritarian that are really interesting to me, ranging from censorship-resistant storage (IPFS) to distributed internet access (goTenna) to zero knowledge cryptography (ZCash) to decentralized payment networks (Lightning) to encrypted messaging (Signal). I think they (or their counterparts) will all eventually be used in conjunction with each other, but to me, the most groundbreaking is bitcoin.

Bitcoin is widely debated, including amongst the Epsilon Theory community. You have a particular view of bitcoin as ‘censorship resistant money’ – could you talk more about that and why it is important?

In the bitcoin network, no single person or small group of people are in charge. Power is divided in a similar way to representative democracies. Instead of the executive branch sitting in the White House, we have the miners, who expend enormous amounts of energy to add new blocks of transactions onto the historical bitcoin ledger. Instead of the legislative branch, we have the coding community, who come up with new ways to improve bitcoin, whose software has been upgraded hundreds of times since its inception in 2009. But just like with a Supreme Court and judicial system, the ultimate power in the bitcoin network is in the hands of the users, who run full nodes all around the world. Each of these nodes — who number in the thousands and are largely unknown to each other — hold the entire transaction history of bitcoin, and decide independently which blocks to approve, and which coding upgrades to allow. When I look at the bitcoin governance model from a political science perspective, it’s the power of the users that makes the network so interesting. Miners and developers can’t simply take over the network. A coup cannot be orchestrated by one person or branch. Power is decentralized.

But decentralization is only a means to an end. In politics, decentralization in the form of liberal democracy gives us a superior society than centralized tyranny. There are of course exceptions but generally speaking — Estonia or Belarus? Costa Rica or Cuba? South Korea or North Korea? Tunisia or Egypt? Ghana or Equatorial Guinea? Whether you care about innovation, growth, entrepreneurship, equality, prosperity, long-term stability, life expectancy, social welfare, or even peace — no two liberal democracies have ever fought each other — you’ll want a free and open society, not a dictatorship. In bitcoin, decentralization gives us censorship-resistance. Because of the distributed architecture of the network, it is impossible to censor individual transactions. They are truly peer to peer and the “ordering service” normally done by a centralized entity at Visa or PayPal, is done by a global competition, where someone will always process your translation, as long as you have enough bitcoin to complete it. This may not be very important for those of us living in democracies where we can more or less trust our governments and banking systems — but it’s a revolutionary development for the billions living under authoritarian governments. For the first time, people can transact in a global, borderless way, within minutes, with a very low fee, in a way that cannot be stopped. So whether you are up against hyperinflation in Venezuela or capital controls in China, bitcoin is a really important, disruptive technology that demands to be understood. Can it be used for bad? Of course. That’s like asking if the internet can be used for bad. But in general, it’s going to change the world, and there are market and human impact reasons to study it closely.

What problems do you think still need to be solved with Bitcoin for to fulfill its potential, and who is working on them?

There are social and educational problems with bitcoin, and then there are technical challenges. Right now I’d actually say the former are more important to tackle. First of all, very few people on this planet have ever used bitcoin, and far fewer understand how it works or why it would be important for someone living under a dictatorship. I’ve seen some people say that no more than 40 million people have ever interacted with bitcoin or any cryptocurrency. So that’s well less than 1% of the world’s population. And even in hyper-connected places like San Francisco and London — or, honestly, even at blockchain conferences — people generally can’t describe to you how and why bitcoin works. We need a world-class effort to explain the technological power and potential of bitcoin to the average person. This information needs to be clear, fun, engaging, and in many different languages. And we must address the conflation problem. The conflation problem is the circumstance we find ourselves in today when everyone starts talking about cryptocurrency and blockchain and bitcoin as if they are the same things. Bitcoin is a decentralized money network that runs on proof of work. Ethereum aims to be a decentralized world computer that wants to use proof of stake. Enterprise blockchains (i.e. blockchains with a backdoors) claim to bring more transparency and accountability to corporate functions like supply chains. Regardless of how bullish or bearish we are on these different projects, we need to stop conflating them with one another. The “bitcoin” blockchain has a radically different set of characteristics than any other blockchain. And it has a particular set of characteristics that give it the unique quality of censorship-resistance. This is why it is important for people who live under dictatorships. So I believe that in human rights-centric educational materials, we need to separate out bitcoin from other projects in the blockchain space, and give it its own chapter, or own brochure, or own book. Unfortunately, and partly because bitcoin is leaderless, there isn’t a coordinated effort to do this.

On the technical challenges side, I’m more optimistic. In order to achieve censorship-resistance, you necessarily are going to have to sacrifice speed and cost. So I believe that on-chain bitcoin transactions are always ultimately going to be more expensive and slower than the competition. Also, due to the public nature of its blockchain, bitcoin is not strictly a privacy technology. So while it’s not easy or cheap to do chain analysis to figure out who is sending which bitcoins to whom, it’s possible, and that’s not great if you are living in a dictatorship. Luckily, brilliant people are working on improvements in all of these areas. On the user side, there are wallets being developed that help increase the privacy of bitcoin transactions. And on the infrastructure side, there’s improvements happening on the bitcoin base layer and on “second layer” technology, like, for example, the Lightning Network. There are a handful of companies and lots of individual developers working on Lightning, which is a decentralized payment network that essentially sits on top of bitcoin. The network just launched earlier this year, and is in the early stages of its architecture, but it should eventually allow you to transact bitcoin very fast, with a very low fee, in a very private way (it in fact uses similar encryption technology to the Tor browser), and thus should be very interesting to people living under closed societies. It also introduces the concept of being able to “stake” your bitcoin into the Lightning Network and provide a service and make a small fee, all without giving up control over your bitcoin, which is of course interesting from a financial perspective.

You might ask why, despite all of these interesting developments, bitcoin is tanking in price. Well, ask yourself, were there major breakthroughs in bitcoin technology between October 2017 and December 2017? No, but the price quadrupled. Did the bitcoin network’s technology get compromised between January and today? Far from it — but the price has gone down by 85%. Remember that the fluctuating price of bitcoin is not reflecting technological advancement.

I remember I was in Cairo during Tahrir Square in 2011 and Twitter was an incredibly useful tool for staying safe and staying in contact. Are there are other bits of ‘mainstream tech’ today that are playing an important role in human rights and freedom?

I tend to agree with Yuval Noah Harari that technology today is, generally speaking, authoritarian by nature. Big data, machine learning, artificial intelligence — these are all being used by governments and companies to control us. The most striking example, of course, is happening in the world’s largest country — China. There, more than a billion people are part of a grand social engineering experiment where the Communist Party is vacuuming up all kinds of communication, location, behavior, health, and financial data from citizens via apps like WeChat and Alipay and beginning to sort through all of that data to understand who are good citizens and who are bad. There are many different “social credit” experiments happening across China where companies or municipalities are taking personal data and using it to score people according not just to their financial responsibility but also political loyalty. And this is beginning in some areas to dictate what kind of basic goods and services you can have — fast internet, a good rate on a mortgage, the ability to buy a plane ticket, leave the country, or send your kids to a good school. This technology isn’t perfect — the New York Times described it right now as more Kafkaesque than Orwellian — but Orwellian is certainly the goal, and this centralized surveillance tech is now being exported to countries like Venezuela. So while I’m interested in the potential of bitcoin and the other decentralized technology that I mentioned above to provide alternative models for us to scale our societies while preserving our freedoms and privacy, I’m fearful of most mainstream tech from a human rights point of view. Certainly, it’s amazing that we can communicate so effortlessly around the world, and that such a large percentage of humans have access to a cell phone, but increasingly, the control of all of these communications, devices, and data is being centralized and that’s not good. In fact, Harari has said that “if you dislike the idea of living in a digital dictatorship… then the most important contribution you can make is to find ways to prevent too much data from being concentrated in too few hands, and also find ways to keep distributed data processing more efficient than centralized data processing. These will not be easy tasks. But achieving them may be the best safeguard of democracy.” Amen to that.

I wrote recently a take on the Chinese system and ‘The Two Worlds Data Infrastructure‘ for Epsilon Theory. What would be your take, builds, challenges to this?

Neville, I really appreciate your take on this. I also believe we are at a crossroads, where we could head down one of these two paths, either a very centralized world where all of our communications and transactions are surveilled, censored, and policed; or a more decentralized one, where we preserve some freedoms and privacy. And unfortunately, we don’t need to run a thought experiment to see what might happen if we go down the centralized road. There are hundreds of millions of people in China who are living through this experiment right now. The Financial Times ran an interview with a 23-year-old Chinese millennial, and she said that she wasn’t sure if she was living in a futuristic society, or if she was building a cage for herself, which is about right. I am happy to see a lot of people making noise about why our current data infrastructure is bad — and not just in China, but here in the United States and elsewhere, too. Obviously, centralized data storage exposes us to many kinds of vulnerabilities, ranging from Equifax-style hacking to Facebook-style manipulation. There are a lot of sharp minds speaking loudly about the problems of our current system, including Tristan Harris, Jaron Lanier, and Renee DiResta. And I do agree with you that ownership of data will be key to providing an alternative to the WeChat model. Where I might challenge you is to consider that bitcoin may play a key role in all of this. If bitcoin is the world’s first censorship-resistant network — then what might we be able to build on top of it? That’s one of the most important questions facing today’s engineers.

Could you talk about the recent ‘Flash Drives for Freedom’ project. What is it? How did it come about? What impact has it had?

10 years ago HRF started working with North Korean defectors. People who had risked their lives to escape hell on earth in North Korea and traveled thousands of miles through China (without speaking the language and with all the trappings of modernity being completely alien to them) to make it to freedom at a South Korean embassy in a country like Thailand or Mongolia. People who had resettled in South Korea, found freedom, and then decided to help those they left behind. After several years of working with many different defector-led organizations, we decided that arguably the most important thing we could do was help get more outside information into North Korea. It’s difficult to imagine a better future for people in North Korea, but its impossible to imagine a better one where they are kept under the same kind of total brainwashing invented by the Kim dynasty. The information monopoly must be broken. So we started supporting groups like the North Korea Strategy Center, led by Kang Chol-hwan, whose incredible work is described in this epic Andy Greenberg WIRED cover story. They were taking USB sticks, loading them up with films, interviews, books, and articles, and sending them into North Korea via the black markets on the Chinese border. In many ways, it was a similar project to the work we once did in Cuba. But NKSC and the other organizations had shockingly little support. To this day, they don’t receive any money from the South Korean government. So we decided to see if we could help. In 2014 we organized the world’s first hackathon for North Korea (as seen on Fareed Zakaria), and, in late 2015, gathered a small group of Silicon Valley leaders to brainstorm the best way of getting outside information in. The solution? A flash drive drive. My colleague Jim Warnock came up with the title “Flash Drives for Freedom”, a team at Leo Burnett did some pro-bono creative design, and we launched at SXSW 2016. Since then, we’ve sent more than 70,000 USB sticks into North Korea, reaching hundreds of thousands (and possibly millions) of people. You can watch a video about the impact and learn how to send us your flash drives here.

I read the columns Jamal Khashoggi wrote while attending HRF’s Oslo Freedom Forum in Norway just months before he died, that you then translated. They are really powerful and important words. What, in your view, are the implications of the murder of Khashoggi and the US and others’ response to it?

Jamal was on the one hand inspired by the Oslo Freedom Forum, and on the other hand, depressed. He told friends that he loved hearing the stories of so many activists and learning about so many similar struggles around the world. From Oslo, he even called an editor friend of his to pitch an idea to put together a new publication that would assemble investigative journalism from across the Arab World. At the same time, he was frustrated by the fact that so little was being done to help these people. He focused particularly on Leyla Yunus, an incredibly brave human rights activist from Azerbaijan, who had been jailed, tortured, and even had her home destroyed by the dictatorship for her peaceful activism. You can watch her Oslo testimony here. When she shows a photo of what she looked like before her arrest, and then shows the photo of her after her release, it’s impossible not to gasp. And Jamal was right there with us, yelling in his mind, why can’t we help this person? The good news is that, through HRF’s work, we are helping people like Leyla. In fact, in the past few months, one of the individuals attending the conference decided to financial support her organization, which is wonderful news. We aim to spark a lot more of that kind of generosity and partnership through our work.

When we heard the news about Jamal’s disappearance — and then later, the grisly details — we were of course devastated. It was initially shocking that the Saudi regime would do something so brazen. As it turns out, they were sending a loud message to all Saudi journalists and dissidents: don’t mess with us. And now, we’ve found out, tragically, that MBS has been torturing the women’s rights activists that he arrested earlier this summer. The world’s response, of course, hasn’t been strong enough. Politically, the response from the White House has been disappointing, to say the least. Unfortunately, it has been long-standing, bi-partisan US policy to uncritically support the Saudi dictatorship in exchange for resource and security guarantees. Realistically, we can’t expect that to change. But maybe the private sector can help make a difference. The business community initially made a lot of noise about not attending a large financial conference held in Riyadh a few weeks ago, and the CEOs of Uber, Siemens, and JP Morgan pulled out. But many attended anyway, and it seems like it’s business as usual. What would be great is if Western companies stopped helping the Saudi regime build blockchain technology. Will IBM stop its collaboration with the regime to build a blockchain smart city in Riyadh? Will R3 allow the Saudis to remain in its blockchain consortium? Will speakers like Nick Spanos remain on the bill for the March 2019 World Blockchain Summit in Riyadh, or will they pull out? Will software developers boycott the Saudi government’s plan to make its own cryptocurrency? Now is time to make a stand.

What makes you hopeful?

The cryptographer Wei Dai once said that “there has never been a government that didn’t sooner or later try to reduce the freedom of its subjects and gain more control over them, and there probably will never be one. Therefore, instead of trying to convince our current government not to try, we’ll develop the technology that will make it impossible for the government to succeed.” I find some solace in that. I’ve seen what encrypted communications can do to help us send messages in a way that preserves privacy. I’ve seen what bitcoin can do to enable censorship-resistant money. We can start to see the potential of zero knowledge cryptography to give people the power to own their data and disclose it selectively to governments and companies. Necessarily, if we believe that an alternative to the WeChat future (which the Venezuelans and Saudis and North Koreans and maybe even the Americans will all gobble up) exists, then it must be built on this kind of infrastructure. And what really makes me hopeful is the persistence of humans. Defeating the surveillance state and challenging authoritarianism might seem like daunting tasks but I wouldn’t want to bet against the world’s dissident community. All of the people I’ve had the honor to get to know through HRF’s work and through the Oslo Freedom Forum have taught me one thing — people don’t give up so easily. Take the example of Ji Seong-ho, for instance. He dragged himself 6,000 miles on crutches to escape from North Korea. You read that correctly. Here is his Oslo testimony. If he could do what he did, then we can all find fuel to achieve our goals.

Finally, what can Epsilon Theory readers do to promote and preserve open societies?

The good news is, there are many ways. I would encourage readers to check out HRF.org and OsloFreedomForum.com and contact me if you’d like to get involved. Attending the Oslo Freedom Forum (coming up on May 27-29 in Norway) is a special experience that will definitely open your eyes and introduce you to people who are making a real difference in this struggle around the world. Is there a particular initiative or program or research project that you’d like to see carried out in this area? Contact me at alex@hrf.org and let’s see if we can make it happen. Then there’s the technology and investment side of things, which will come more naturally to your readers. If you’re going to fight the surveillance state, you have to first arm yourself with knowledge. I think it’s an extremely good idea to learn more about how bitcoin works, if you really want to understand decentralization in practice. Maybe the best place to start is by reading or listening to The Internet of Money by Andreas Antonopolous, and then diving into his remarkably educational YouTube channel. A closing thought is that so very few people on this planet have interacted with  technology like bitcoin or encrypted messaging or censorship-resistant storage. Now is your time to make a human impact and a profit by investing in these areas. We talk about impact investing in HealthTech or EdTech or CleanTech, which are all great ways to do well and do good at the same time. What about DemTech, or Democracy Tech? Start thinking about technology and infrastructure that can help challenge authoritarianism, and help the world build it. That’s a fantastic legacy to leave and probably the best thing your readers can do, given their skill set and knowledge base. Now is the time to complement the existing impact investing space by supporting projects that promote and protect civil liberties and open societies. And today, that means protecting our data, money, and communications.


Take Back Your Thinking

Riding on the coattails of  Ben’s ‘Take Back Your Distance’ section of last week’s Things Fall Apart (Part 3) – Politics, I thought I would share the personal journey (with links at the bottom of this note) I have been on for the past few years to take back the ability to think about things for sustained periods of time, and to know what I am thinking about and why.

I started on the journey to ‘take back my thinking’ as I could feel myself getting caught up in the fast moving swirl of communication and ‘news’, and losing the distinction between what I was thinking and what I had simply been exposed to and thought that I was thinking.

You could say that I had developed ‘Fiat Thought’.

As a citizen and as a leader, it seems to me that mistaking Fiat Thought for real thought is the single most dangerous thing one can do, and so I decided to develop and deploy ‘three lines of defense’ to try to take back my thinking:

  • Make my personal tech somewhat inconvenient and limited.
  • Introduce a couple of hours per day of ‘boring’ (low external stimulation) time.
  • Take on daily doses of Śūnyatā.

Overall it has been a much more difficult journey than I thought it was going to be.

Most things I tried in building these defenses were at least initially quite unpleasant (the inconvenient tech irritating and friction-y; the boring time boring; the Śūnyatā doses occasionally quite disturbing), and many things I tried simply didn’t work or didn’t stick. But after a solid couple of years of sustained effort I’ve stabilized on a set of protocols for the three lines of defense that, as far as I can tell, are collectively fairly effective.

Unfortunately the Fiat Thought defense protocols I arrived at are more like the malaria prevention protocol (daily Malerone pre-, during- and post- + bug spray + nets) rather than a one-and-done (well, two-and-done) inoculation like the measles vaccination, and so I keep them up whenever I am in a high risk area (e.g., a major metropolitan area with unrestricted internet access), which is kind of a chore.

As it happens, whenever I’m not in a high risk Fiat Thought area, I’m usually in a high risk malaria area, so you pick your poison, I guess.

Anyway, here are the three lines of defense I’ve stabilized on and have been running for the past couple of years:

Make my personal tech inconvenient and limited

  • Turned off notifications on my phone, with phone always in silent mode (switch from ‘push’ to ‘pull’).
  • Turned my phone to greyscale (makes apps literally dull).
  • Set phone screen brightness to minimum (makes apps even more dull).
  • Removed all non-utility apps, so just left with: SMS, calendar, clock, Google Maps, Uber, bike share app, Spotify (note: on iPhone I couldn’t actually figure out how to remove Safari but I could hide it and password protect it with a password I don’t know).
  • Stopped carrying my phone on the weekend.
  • Read the WSJ daily print edition instead of online aggregated news (The FT print edition would be better, but I’ll take what I can get).
  • Use an old 1st generation Kindle for reading books (instead of reading on my phone).
  • Use only an eight-year-old iMac desktop at home, so I have to intentionally go to the computer and then wait for it to boot instead of having an ‘always on’ device around.
  • Got off Facebook and Twitter (I haven’t deleted my profiles as I can’t be bothered to figure out how, but I no longer post to either, which has removed the interest for me).

Introduce a couple of hours per day of ‘boring time’

  • Walk to any appointment that is a 30 minute or less walk time, and take public transit for any journey where it is less than a 25% time increase vs. taking a car (Google maps is very good as predicting this).
  • An hour-ish simple daily meditation practice, with some longer more intensive periods a few times a year to really stare at my thoughts.

Absorb daily doses of doses of Śūnyatā

This one is tricky to write about.

I use the romanized Sanskrit term ‘Śūnyatā’  here in the in the way it is commonly used in translations of the Tibetan Buddhist canon, rather than the romanized Tibetan of ‘stong pa nyid’ , which is quite a mouthful, or the typical English translation of ‘emptiness’, which is misleading.

Regardless, whatever word we use, the exercise I ended up taking on and maintaining is something like Marcus Aurelius advocated in Meditations – daily consideration of the true nature of things (for Stoics the logos) and their impermanence, one’s own impermanence, etc. As Aurelius considers and notes in Meditations book 4.4, “The world is truly nothing but change. Our life is only perception.”

After a fair bit of exploration and experimentation, I believe that the Tibetans have far and away the most sophisticated and reliable technology for acquiring Śūnyatā, although for sure many other traditions have equivalent concepts and sophisticated methods for acquisition.

In summary

So, the culmination of this journey to ‘take back my thinking’ is that, outside of the office, I’m limited to an iPhone that I have spent a lot of time and effort turning into a greyscale dumb phone, an old desktop computer that takes a couple of minutes to boot, and a ten-year-old Kindle. I spend a fair amount of time sitting on a cushion half-staring at a blank wall. I’ve become a bad Uber customer. And I spend a bunch of time thinking about (literally) nothing.

I appreciate what an immense privilege it is to have the time / money / freedom to do this, and so the question is: Is it valuable, or is it just some next-level-tech-elite-anti-tech-BS?

I say without a doubt that it is beyond valuable.

In a world of Fiat News that quickly becomes Fiat Thought, taking back my thinking is absolutely foundational to my identity.

As Christopher Beirn commented to a recent Rabbit Hole note: homo sapiens is a hackable animal. So the only question really is whether you are hacking yourself or someone else is hacking you … and if someone else is hacking you, then you’re just the unwitting host for the program.

Links follow:

Why and how to make tech inconvenient:

  • Firstly, to know who you are competing with in the race to hack yourself, check out BJ Fogg, a leading thinker and practitioner on how computers can be designed to influence attitudes and behaviors.  He is the author of the seminal book, Persuasive Technology, (subtitled: Using Computers To Change What We Think and Do). This is a somewhat overwrought, but really quite good Medium post that examines that dark side of using the type of ‘persuasive techniques’ that BJ Fogg developed.
  • Tristan Harris offers his take here on ‘How Technology Hijacks People’s Minds — from a Magician and Google’s Design Ethicist’.
  • From a practical perspective, here’s a bunch of ideas conveniently collected together by Tristan Harris’s Center For Human Technology on how to make your tech dull and inconvenient.

Why and how to have periods of limited external stimulus:

  • There are literally thousands of books on ‘Why meditation is great’ but ‘10% happier’ is one of the least irritating and easiest to read. Full title: 10% Happier: How I Tamed the Voice in My Head, Reduced Stress Without Losing My Edge, and Found Self-Help That Actually Works–A True Story by Dan Harris (a TV new anchor).
  • If you don’t have a meditation practice and want to get one going, my best advice is to kick start it by doing a minimum of five days in a silent Vipassana-style retreat. Here is a Medium post of a pretty average experience of attending a 10 day Goenka (a common variety) one. As the writer makes very clear: It will most likely hurt.

Śūnyatā:

In many ways I hesitate to offer any links or thoughts on this.

For calibration, even Pema Chödrön – arguably the leading Western light on Tibetan Buddhism, someone who has been a serious, full time student of Tibetan Buddhism for 40 years, someone who studied directly under the legendary Chögyam Trungpa – skipped commenting on the Śūnyatā chapter (chapter nine) in her commentary on the classic ‘The Way of the Bodhisattva’.

But then, in the noble spirit of Silicon Valley, after briefly hesitating and realizing I am fundamentally unqualified, I proceed anyway:

  • As mentioned above, while Meditations by Marcus Aurelius covers much more ground then just concepts of impermanence and emptiness, I find it extremely accessible and inspiring as an account of a real-world struggle to integrate this type of ‘philosophic’ thinking and perception into day-to-day action. The Modern Library edition also has a terrific introduction by Gregory Hays.
  • For the Zen version I would go straight to the writing of Eihai Dogen (the 13th century founder of the Soto Zen school) who offers such sage advice as “When you ride on a boat and watch the shore, you might assume that the shore is moving. But when you keep your eyes closely on the boat, you can see that the boat moves. Similarly, if you examine myriad things with a confused body and mind, you might suppose that your mind and essence are permanent. When you practice intimately and return to where you are, it will be clear that nothing at all has unchanging self” … hmm …
  • The Rinzai sect has its own method of ‘koan study’ (“What is the sound of one hand clapping?” etc.) to push through conceptual thought to the “selfless-self”. I personally have never gotten along with koan study. Others swear by it.
  • The Tibetan canon is so vast it’s hard to say where to start. The writings of Chögyam Trungpa are pretty available and accessible (Trungpa was a kind of maniac rock-n-roll Buddhist meditation master with some pretty troubling behaviors but, man, could he write).

One final comment: If you decide to go get yourself some Śūnyatā, and go after it in an intensive and sustained way (say, spending more than an hour or two a day on a combination of contemplation and meditation for more than a few months), I would strongly advise working with a professional as you will likely bring about significant adaptations to your brain and nervous system. So, y’know, if you’re not a trained brain surgeon better not to self-operate.


Cards of Control and a Brave Little Toaster

Returning to the 2017-vintage Rabbit Hole format: No grand theme this week, just some links I thought were noteworthy.


Cards of Control

If you only read one thing this week read this 👉Cards of control: How ZTE helps Venezuela create China-style social control. This is an exceptionally well-sourced long form article on the implementation and implications of ZTE ID cards in Venezuela.


Decentralized Identity: Ideology & Architecture

If you want to understand self-sovereign identity I think this is about as good a primer presentation as any. It is no more than a 15 minute read time even if you are new to digital identity and, I think, hits the major points in a sensible way.

Btw: don’t be put off by the ‘Bitcoin Association of Switzerland’ logo on the cover … there is no further mention of bitcoin (or Switzerland) in the presentation.


Going Underground, as a Toaster

Despite writing in recent weeks of the rise and reach of ‘the Chinese system’, I don’t believe we will actually get full, unavoidable surveillance in most of the real world any time soon.

For most people in the general populace (i.e. groups who are not specifically and intensively targeted) of most countries the rise in surveillance tech just means staying outside the surveillance system will be inconvenient not impossible, and so most people won’t bother.

For example, if you want to stay out of the video recognition system you (sort of) just have to put a ‘adversarial perturbation’ sticker on your head – see link here for how to get yourself classified as a toaster. For a more technical explanation of why you can get yourself classified as a toaster, or panda, or whatever, there is a good paper here.

This is also why I think real world ID and app data are currently much more effective surveillance techniques than video as video processing is still expensive, imprecise and hackable. But video surveillance still gets the headlines as it just feels so much more like surveillance.


Defining and Designing Fair Algorithms

While researching SB-10 bill (referenced in last week’s Rabbit Hole here) I found Stanford Computational Policy Lab and their work on SB-10 and then their presentation on Defining and Designing Fair Algorithms – check it out, it’s  long (112 pages), but really good work.


Sinister News Readers

And, finally, there is something deeply sinister about this Chinese news bot (scroll down to the YouTube video to see it in action). I think the sinister thing is something so human-like presenting news with no conscience of regard for ‘truth’ (>> insert preferred partisan joke here<<) … I don’t know, just deeply, deeply sinister in a Minsky / Shannon Ultimate / Useless Machine kind of way.


Working to Protect the World from Bananas

I started writing a follow up note toThe Two Worlds of Data Infrastructure on some new pieces of ‘the Chinese system’ starting to click together, for example, how real name ID is now required for playing video games, how gait-recognition surveillance system  (so begging for a Monty Python joke, but really can’t bring myself to make one) is coming on line, and on China’s global advocacy to normalize the system with other countries.

However, in many ways I don’t think the story here is the ‘play-by-play’ of each system clicking in, rather I think the story here is twofold:

The main story: The inflection point

The main story is the increased pace and arc of the Chinese system overall, not the ‘play-by-play’.

With technology, even totalitarian surveillance technology, there typically is no ‘big bang’, just a bunch of independent systems coming on line, getting adopted over time, then getting networked together, resulting in a series of subtle shifts in personal behavior, and then a tipping point.

Having watched this system come on line for nearly 20 years, the deployment of the Chinese technology-driven domestic surveillance system was pretty limited even up until 2010, but has been absolutely rip-roaring and accelerating over the last five years thanks to the same driving forces of most other tech advances since 2010:

  • Ubiquitous handheld connected device
  • App adoption
  • Cheap sensors (inc. cameras)
  • Cheap massive data storage
  • Sophisticated statistical algorithms
  • Leaps forward in compute power and cost

All of these advances are so powerful for surveillance with its inherent big, unstructured data characteristics that I think we are now really close to an inflection point where the system is starting to really work in a functional day-to-day way, which will then lead to a behavioral tipping point.

The sub-story: The almost total lack of interest in the West

I don’t think the main story is that controversial at this point, i.e., I don’t think anyone, even the Chinese government, denies this system is being built, the intention of it, or that it is starting to work in a practical way.

Therefore, I think the more interesting story in many ways is the sub-story of the willful ignorance of the main story by the West.

I was at an event last week where a new fancy think tank on AI ethics based here in San Francisco was presenting and expounding their tenet of “Working to protect the privacy and security of individuals”, whilst simultaneously welcoming Baidu into their organization.

I’m sorry, but that’s like “Working to protect the world from bananas” while signing up Del Monte as a member.

Bananas.

With hypocritical sprinkles.

And a big ignorant cherry on top.

Anyway, maybe we (in the West) shouldn’t care, and each country should be free to follow its own national agenda without the moralizing of other nations on its approach to technology and human rights.

But then let’s at least let’s just say so, or at least admit that “We are all Nationalists now”.

Just in case you think I am uniquely calling out the Chinese system – anyone who thinks the US is not on a path to using problematic algorithms to classify people and determine punishment has not been paying attention.

Check out the text of the recent California SB10 bill to end cash bail … it’s no more than a 10 minute read. It basically sets out that a person whose risk to public safety and risk of failure to appear is determined to be “low” would be released with the least restrictive non-monetary conditions possible. “Medium-risk” individuals could be released or held depending on local standards. “High-risk” individuals would remain in custody until their arraignment.

Contained in the bill (and pretty lightly reported on) are a bunch of clauses that set out the requirement to use a “Validated risk assessment tool” to assess high / medium / low risk, with the definition of a “Validated risk assessment tool” as:

“Validated risk assessment tool” means a risk assessment instrument, selected and approved by the court, in consultation with Pretrial Assessment Services or another entity providing pretrial risk assessments, from the list of approved pretrial risk assessment tools maintained by the Judicial Council. The assessment tools shall be demonstrated by scientific research to be accurate and reliable in assessing the risk of a person failing to appear in court as required or the risk to public safety due to the commission of a new criminal offense if the person is released before adjudication of his or her current criminal offense.

To be clear: this means an algorithm decides who is a risk.

And who knows what ‘demonstrated by scientific research’ means  … perhaps it means it passed a backtest assuming normal distribution under an arbitrary definition of a cycle? … what could possibly go wrong …


Control Point

[Ben’s note: I don’t like to beg, but after publishing “The Two Worlds of Data Infrastructure“, I resorted to outright begging my friend Neville Crawley to reinstitute the regular note he used to write for Epsilon Theory, a series called “Rabbit Hole”. Luckily for my self-esteem, Neville has relented, and I am SO pleased to announce that we’ll be getting a new “Rabbit Hole” note every week or so. These notes on the nexus of government, society and technology (and how we might think about it), will change your worldview. I know they’ve changed mine.

PS. When he’s not writing guest posts for Epsilon Theory, Neville Crawley is the CEO of Kiva, which is an amazing company that you should get to know.]


I’ve been thinking a lot about product strategy and ‘control points’ recently.

I used to work on strategy with semiconductor manufacturers back in the day and the smartest ones only ever really had two strategy questions:

  1. “What’s going to have chips in it 10 years from now?”
  2. “What’s the control point?”

If you’re a semiconductor manufacturer “What’s going to have chips in it 10 years from now?” is a pretty obvious question to ask, and relatively easy to think about, build models around, etc. (although much harder to get right in terms of scale and timing … sitting in 2008 it was very hard to call relative scale and timing of adoption for VR, IoT, machine learning etc. etc. a decade out).

The more interesting question though, I think, is around control points, and how this relates to product strategy. What I mean by a ‘control point’ is that sometimes, for some period of time, a piece of an ecosystem becomes dominant and ‘controls’ the rest of the ecosystem, and typically sucks in most of the economic profits.

In personal computing, in the Western world, I’d argue that, over the past 25 years or so, the control point shifted through Windows OS, through to mobile OS (with iOS hardware integration creating a particularly powerful control point), through to application layer personal data collection – with Google and Facebook dominant.

Clearly, application layer personal data collection is the control point right now.

I sit here now typing this Rabbit Hole column in Google docs (which I will end up writing on 3 different hardware devices as I grab a minute here and there through the day), before doing some light fact checking for it in Google search, before sending to Ben via Gmail, and then looking at another device to check my Google calendar to find a lunch meeting that I will navigate to via Google Maps.

Honestly, given the amount of data I’ve given Google today (and over the past 20 years) I should just let Google order lunch for me – their external algorithm probably has (or at least could have) a better sense of what I should eat for lunch today than my human ‘internal lunch decision algo’ does. (Yuval Harari writes very convincingly on this point in Homo Deus).

But, my bet is that, despite the convenience of Google knowing I should have the bisque and saving me from the club sandwich, we are coming up to a shift in control points whereby the next control point is going to be around personal empowerment of control over personal data and authorization.

GDPR points in this direction (in a very EU legislative kind of way) and in technology circles this is currently being hotly discussed in terms of ‘wallets’, ‘self sovereignty’, ’encryption keys’ and ‘data distribution’.

I’m not advocating for any one particular system, and don’t have clarity on exactly how or when this shift in control points will happen, but I do think that there is a strong chance we (in the Western world, at least) are going to see this shift in control points over the next 5 – 10 years, and see similarly large changes in personal behavior and value creation.

Here are some links that I think point in the direction of control over personal data and authorization.:

  • This NY Times piece is a long, fascinating account of how Alastair Mactaggart, an Oakland, California resident, “became the most improbable, and perhaps the most important, privacy activist in America” … a great read on a super important topic that gets into the nuances and quite some details.
  • Profile of Tim Berners-Lee / Solid project here and a direct link to Solid which aims “to change the way Web applications work today, resulting in true data ownership as well as improved privacy”
  • A short (blockchain centric) primer on Self Sovereign Identity.