Expedition to the lost net, BBC, 26 Dec 2001.

ETA, from @syn:

“I’m pretty sure that text is based on misunderstanding. Yeah, the author didn’t get routing properly. The article assumes a static routing model, which is not how we do things :)”

(via hauntology)

On the subject of fuzzy things…

photo by Miss Voodoo

Code of conduct: The relentless march of the algorithm by Robin Barton, The Independent, 15 Jan 2012.

I wrote my Masters’ thesis on dust, on what it meant exactly that we are constantly sloughing off hair and skin - bodily fragments - which transform into waste strewn thinly and evenly across our living spaces. Distributed presence, former presence - a body was here.

Now I ask, what does it meant to be doing that with data?

If 2012 is the year of Big Data, it will likely be the year vendors and consultants start to over-promise, under-deliver, and put processes in motion that will generate insights and potential risks for years to come. […]

As Big Data becomes the next great savior of business and humanity, we need to remain skeptical of its promises as well as its applications and aspirations.

Existential Issues With Big Data
Determinism teaches that what will be, will be. Existentialism deals with a humanity in the throes of chaos. Big Data can be seen as either a lens through which determinism is revealed, or a tool for navigating an existential world. As a scenario planner, I take the existential position and see a number of existential threats to the success of Big Data and its applications.

To summarise and paraphrase the threats Rasmus perceives:

1. Overconfidence: most managers are overconfident and miscalibrated. In other words, they don’t recognize their own inability to forecast the future, nor do they recognize the inherent volatility of markets. Both of these traits portend big problems for Big Data as humans code their assumptions about the world into algorithms
2. When learning happens: “If organizations rely on Big Data to connect far-ranging databases [..] -who, it must be asked, will understand enough of the model to challenge its underlying assumptions, and re-craft those assumptions when the world, and the data that reflects it, changes?”
3. Complexity: Complex models reflect the worldviews & personal understandings of the people who’ve built them, and may not be easily transferable to new staff - or combinable with other models.
4. Feedback loops: Creating connections between datasets can amplify the impact of errors or incorrect assumptions
5. Algorithms & a lack of theory: for some fields of endeavour, there is no consensus theory about how they work. Consequently “data scientists can’t create a model because no reliable underlying logic exists that can be encoded into a model”
6. Confirmation bias: “Every model is based on historical assumptions and perceptual biases. Regardless of the sophistication of the science, we often create models that help us see what we want to see”
7. The world changes: “We must remember that all data is historical. There is no data from or about the future. Future context changes cannot be built into a model because they cannot be anticipated.”

The company that keeps getting mentioned as the one best able to handle the “fuzziness” of big data (i.e. different datasets having similar but not isometric categories) is Palantir, the slightly Orwellian firm focusing on post-9/11 security and government data. But here I find Rasmus’s comment particularly interesting:

“They have to be cautious about applying their ideas to different domains where underlying rules might not be so clear or data so well-defined.”

Indeed. Fuzziness is not trivial!

protoslacker:

 Anti-Counterfeiting Trade Agreement (ACTA) is a multilateral agreement which  proposes international standards for enforcement of intellectual property rights.

The Electronic Frontier Foundation (EFF) opposes ACTA, calling for more public spotlight on the proposed treaty.

The Free Software Foundation (FSF) has published “Speak out against ACTA”, stating that the ACTA threatens free software by creating a culture “in which the freedom that is required to produce free software is seen as dangerous and threatening rather than creative, innovative, and exciting.

Europe: this is our SOPA, our PIPA. Time to get hasslin’ our representatives (inasmuch as the EU is representative or democratic…)

Poland’s politicians don Anonymous-style Guy Fawkes masks in anti-piracy protest [Slashgear]

Extracts from The Origins of Sex: A History of the First Sexual Revolution by Faramerz Dabhoiwala, which’ll be published on 2 Feb 2012.

I wish ideas like these were more widely known - that it was common knowledge quite how culturally contingent and historically specific our attitudes to gender and sexuality are. This would give people a lot more freedom.

wildcat2030:

Knowmads, Infocology of the future

Growing up with the Internet gives today’s children a very unique view on the way the world works — one that is vastly different from that of older generations. These kids, the ‘digital natives,” are raised with modern technology deeply…

@machinestarts (Chris Baraniuk) commented, “I am not a fan of this research. Children 30 years ago would basically have said the same thing”.

Which suggests that before we jump to this conclusion we need to prove that “robots are human” is not an effect of either:

• the research design
• or the cognitive development of children surveyed (i.e. kids start off not understanding self/other, so it seems likely they’ll be pretty shaky on human/non-human until a certain age)

To examine only the first point:

The question posed was, “What would happen if robots were a part of your everyday life — at school and beyond?” Note that it’s a question about robots - which is a word in everyday English indicating a humanoid form, a general category including the advanced (and hard to distinguish from human “android”), but not hybrid and indistinguishable in the way of the “cyborg”. It’s a question framed to elicit commonalities - if the kids didn’t humanise robots, that would be the unexpected finding.

Second, Survey design 101: if your question’s about robots, to assume the answer tells you about attitudes to technology (a much wider category) is unjustified extrapolation.

Thirdly it doesn’t appear to test null hypotheses, two being (i) how children would imagine they’d react to cats in their everyday lives - would they humanise them too? I’d expect so; and (ii) how adults would imagine interacting with robots in their everyday lives - which likewise I would expect would come out. The idea that adults perceive robots as “separate to humanness” appears to be a cultural assumption of the researchers, nothing more.

But echt, press releases publicity lalala.

More information about the research process here.

(via stoweboyd)

I’ve found myself discussing this article on the comments thread, in the FACE office with my colleagues, and on Twitter with at least half-a-dozen people. It’s getting stacks of traction, so I figure it’s worth sharing it here too.

@SLadner asks the big question both academic and commercial ethnographers rather guiltily wonder - is what the other lot are doing any good? Surely not, right? Well…

To sketch out my POV:

• Academic and commercial anthropology are attempting to achieve very different goals. Academic work has to position itself in relation to the whole preceding canon, whereas commercial work simply has to provide enough insight to help a business make a decision. Naturally this results in rather different methods, especially regarding duration.
• Quite a lot of what passes for commercial ethnography is not really ethnography, just “qual”.
  Admittedly I went to the LSE which is super-hardcore and old-school on the notion of proper anthropological fieldwork. If you’re not in a jungle learning a language only 63 other people know and getting dysentery, then what you’re doing is probably really sociology, or cultural studies, or some other sort of fluff.
• However a lot of academic work shies away from intelligibility and Actually Bloody Saying Something, preferring jargon, pointless academic infighting and wilful obscurity.
• Corporate ethnography’s deep weakness lies in its loyalty. Personal ethics and MRS codes of conduct may mitigate the worst excesses, but fundamentally the researcher is aligned with the interests of their corporate paymaster. Their job is to provide insights to hep the company sell something - and whether this is in the interests of the informants is a moot point. Mostly it’s brushed under the carpet and denied, the taboo no-one must mention. However the design researcher / tech anthropologist Jan Chipchase has done a brilliant job addressing this in his recent piece Imperialist Tendencies, which is a must-read
• I was reminded by reflexive turn of the 80s there has been a concern for not “exploiting the natives” through your research, demonstrated through practices such as giving your informants copies of your work (translated & in a medium that’s comprehensible to their level of literacy), giving them veto power, and giving them a right of response. Great! But this is the ideal. The reality is academics’ need to please the head of department, or the RAE assessor, or the journal editors… And these loyalties can pull them some distance away from their informants’ interests.
• The truth value or rigour of academic vs. commercial anthropology is also not an entirely one-sided fight. On the one hand, academic research has to hold up against the pre-existing canon and the direct critique from journal reviewers and other scholars. On the other, commercial research should hold up against real-world implementations - if the insights were crap, the client’s implementation is likely to founder. But it’s a few steps down the line, so perhaps more avoidable than the challenge of peer review…

These are not finished thoughts, just idea starters. What am I missing? What’s your take?

I’m guessing you’re mostly here from the Tumblr Technology Spotlight. Thanks Tumblr! And thanks for following.

The 101:

Who: Jay Owens
What: social (media / research / anthropology / theory). Interested in what technology means and what it does to us psychologically and socially.
Especially: identity, privacy, big data.
Basically: social nerd.
Where: London, @hautepop and JayOh.net.
Weekdays 9-7: working at FACE

Two other of my favourite Tumblrs were also spotlighted, so I want to share the love and recommend:

1. Modern Im/Material Things // @CDennaoui
Social media strategist by day, critical theory nerd by night, and former anthropology student to boot. (Sounds familiar!) But Christina studied Middle Eastern politics and religion, and also makes abstract electronic music and digital collage.
[I’ll update with links to my favourite of her posts when her SOPA block comes down tomorrow ;)]

2. Stowe Boyd the Underpaid Genius // @stoweboyd
Stowe describes himself as a “Social anthropologist, clairvoyant, postfuturist. My work is social tools and their impact on media, business, and society.” He’s got an interest in social media tools for work (like Yammer and Basecamp) but envisioning a future where they’re (a) properly social and (b) change how we work.
But I’m recommending him because he also thinks a lot about political implications, economics and green issues.

There are enough people just writing about technology. What’s interesting is to leave the hype-y Silicon Alley bubble and really mash it up with the complexity of the whole wide world out there.

I was directed to this Ars Technica article by Aden Davies (banking innovation chap at HSBC), who pointed out the comments thread as rather more insightful than the article itself.

Indeed it was, and I’m just starting a new mobile payment project, so I wanted to aggregate the key points into one post for reference. What might actually be the solution to secure card payment?

First, the idea in the article: dynamic credit card numbers.

How much do you worry about your credit card information falling into the wrong hands, either due to online security breaches or a lost or stolen card? Dynamics Inc. is a company that claims to have the solution: a credit card that generates a one-time use code every time it is used, both for online and physical transactions. The company showed off a number of credit card options here at CES, including the ability to keep a single card for multiple accounts. The secret lies in the company’s innovative magnetic strip, which can be programmed in real time, and—more importantly—wiped clean just as quickly.

Some useful clarification from Syon (in comments): for this to be secure, what you want is both a hidden credit card number and also a dynamic one that changes for each use.

The advantage of this technology over other security measures is that it doesn’t require any change to merchant terminals or systems - dramatically decreasing cost of uptake. [It is of course this issue that’s holding back NFC.]

Looking at other security solutions, there’s a key thing I have to remember: The US (still) doesn’t have chip & PIN - they’re mag-stripe only. However a few years ago Amex Blue “*did* put a chip on the cards, and you could order a chip reader, plug the card into the reader, and then do chip & pin on your own PC.” [ZPrime]. What a faff - at least as bad as those little caclulator/dongle things UK banking customers have as an additional security layer for setting up new online transfers.

For one commenter, the “checkout” option is the obvious security fix:

IMO the solution to fraud online is to stop allowing sites to have any access to card details, and make all processing have to go thru third parties like paypal etc, IMO its time that anyone accepting online payments has to foward you offsite to an accredited processor, and get handed back to the merchant as paypal does.
[RichMS]

It’s interesting to see it advocated, because I’m pretty skeptical. I don’t feel this is an especially compelling offer, because most people are making online purchases relatively infrequently and mostly from the same set of big-name providers (Amazon, ASOS, etc). These brands are trusted as much as any check-out provider (Google, Amazon), and rather more than Paypal. So how much of a need is there? If I were regularly more under-the-counter Ritalin or fake designer handbags from China - I’d want this layer. Mostly though it seems an additional hassle to set up a new Google Checkout account rather than using my existing ASOS or Topshop one to pay…

A much more interesting idea: stop merchants being able to “pull” money off the customer’s card at all:

Why [are we] even bothering with this? [More secure credit cards] The basic enabler of fraud is the idea that random parties can at any time order a withdrawal from someone’s account. Why are we even doing “pull” transactions where the merchant orders the withdrawal from your account? Why aren’t we doing “push” transactions where the merchant tells *you* their receiving account number and a transaction code and you order your bank to send the payment to the merchant? For on-line purchases it should be easy enough. If you’ve got a cell phone you can do it via the Web or a text message or if all else fails a voice call to your bank
[Todd Knarr]

Now this is a really interesting idea, potentially a real game-changer. As stands setting up new payment recipients is quite a hassle in the UK at least (the joys of dongle verification), but for offline purchases there have to be ways to streamline it by using proximity in the verification mechanism - e.g. bump to confim? Enter a code on the other phone’s screen?

A more detailed walk-through of the security requirements for push transactions - anything connected to the internet is potentially hackable. So how to structure a system around that?

The ultimate thing is just a card that has private key in it and a keyboard so that you can type in a code and see how much you are being charged before pressing ok. If customer and bank have 100% control over the keys and the card there is no possible fraud as all the stuff in between is just there to allow the card to communicate with the bank servers.

Breaking public crypto is not going to be easy any time soon so danger of criminals doing anything is low or non existent. Sure the cards are a bit more expensive but it might be cheaper to go for a truly secure system as compared to snake oil stuff they are doing now.

[AxMi-24]

It’s even potentially a business-model disrupter:

“Interesting ideas. The thing about ‘push’ transactions like that is that they require both parties to be online. This is not really an issue - just build it into phones. However, once you’ve required everyone to be online there is a LOT you could do. e.g. You could then standardise the protocol so that money goes between the two banks directly - mastercard and visa can be dis-intermediated. I’d be very happy to remove those monopoly players.”
[Lliwynd]

But is this possible? “I’m afraid your plan won’t really work. In Europe alone, there are over 4000 issuers. Suggesting that each and every one of them makes a connection to 3999 others in order to have a workable payment service doesn’t make any sense. That’s why you have payment processors.” [mrsilver]

Still need to stop & note the consumer objection: “Sounds like a lot of work on the part of the consumer. I’d rather take the risk that my card be stolen then go to my bank’s website every time I want to make a purchase online.” [Eupfhoria]

hautepop:

“One company getting buzz is ConnectEDU, sometimes described as an eHarmony for college matchmaking. Its founder, Craig Powell, dreams that students won’t even have to apply to college “because an algorithm will have already told them and the schools where they would fit best,”

The algo dream: to replace human agency and choice.

We must start to ask, what is so bad about making a non-“optimised” decision? Do we not learn things - do we not sometimes learn more - from the things we do that don’t quite work?

[…]

We regret the roads not travelled. Let’s be careful about letting the gospel of “efficiency” too near these choices: rational “optimisation” may potentially be distinctly sub-optimal for a sense of life satisfaction.

mortari:

Agree with this entirely. While optimisation may be very important for decisions in business or resource allocation, it cannot allow for that which we struggle to quantify: life satisfaction. Education does not just convey information or skills, it also fills out our world view by exposing us to new ideas and other people who have different priorities. The astronomy course which I took in my undergraduate studies has been of zero practical use to me in my academic career, but has left me with a true sense of wonder at the possibilities of science.

In the past 10 years I’ve hoped from studying philosophy, to psychiatry, to neuroscience, to psychoanalysis and now to psychology, and I don’t regret any of these choices. This could be seen as inefficient in terms of material learned which was not essential to understand my current field of study. But it has provided an understanding of the much broader context in which my research is situated, and the ability to analyse and incorporate insights from other fields.

Creativity and original thinking requires a degree of flexibility and openness, and in my experience this is best encouraged by a broad and varied education, in which people are exposed to new ideas from different topics. My fear over the optimisation of education is that it encourages the opposite of this: that students focus purely on the subjects which align closely with each other and reinforce each others’ assumptions. Efficiency is just another word for stagnation.

Thanks for the response Georgie - eloquent.

Two more points to flag from the article’s comments take the critique in a different direction - in fact, the socio-economic, slightly Foucauldian lens I tend to use. Worth summarising:

1. The real world doesn’t put you in a meeting or a job interview with people who’ve been pre-selected for optimised learning. Success requires developing the capabilities to handle a challenge and people / situations you might not get on with very well. Avoiding this in college doesn’t do the student a favour.
2. The economic argument: the UK has now joined the US in the vast, near-mortgage-sized debts 18-year-olds are expected to take out to render themselves “employable”. Under this circumstance, it may be more rational to continue on an economics or science degree you don’t like and get a 2:2 than switch to art history, get a 1st, and face much more constrained employment choices.
3. Admin increasing the role for itself in preference to teaching staff; creating technocratic “solutions” to the problem of student performance and uncertainty which don’t address the real problem - don’t make a structural critique of the university and its relationship to capital.

Two more, from further thought and discussion:

• Students already have plenty of data on their own performance - their marks, plus their own self-knowledge. This is enough to make a good decision about what to study. Outsourcing this to a piece of software abnegates responsibility and delays maturity.
• From @megblight: Feedback loops. The new data would over a few years become wholly based on its own predictions. Random effects in initial data would surely be replicated?

The algo dream: to replace human agency and choice.

We must start to ask, what is so bad about making a non-“optimised” decision? Do we not learn things - do we not sometimes learn more - from the things we do that don’t quite work?

This quotation is taken from an article, Colleges Mine Data to Tailor Students’ Experience, where “analytics” is posited as the saviour of everything from college choice, to course choice, to who you work with on a calculus problem.

I offer myself as a counter-example: applied to university to read Philosophy. Realised it didn’t interest me, applied for Social Anthropology and started a course at LSE. Realised I actually needed to find out what I should be doing with Mathematics: left, went to Bristol, started a maths degree. Realised my heart was in Anthro, returned to LSE, finished that degree.

Any salesman with an algorithm would think they could “optimise” that journey. But for me at least, the chance to make those choices on my own and get empirical experience of studying both subjects was essential to be at peace and commit to my final decision.

We regret the roads not travelled. Let’s be careful about letting the gospel of “efficiency” too near these choices: rational “optimisation” may potentially be distinctly sub-optimal for a sense of life satisfaction.

Design researcher & tech anthropologist Jan Chipchase was questioned at the Pop!Tech conference about the ethics of doing his kind of work.

» What is it like working for BigCorps pillaging the intellect of people around the world for commercial gain?

» How do you sleep at night as the corporations you work for pump their worthless products into the world?”

As he says, “There are a number of misconceptions about consumers in highly income/resource constrained (poor) communities that seem to repeat themselves with a depressing regularity and is often directed from passionate minds with a particular, accusatory venom:”

» Consumers on low levels of income are incapable of making rational or “right” choices for themselves

» These same consumers are duty bound only to make rational choices (“rational” as in on things that have an immediate benefit to their current socio-economic situation, as defined by the person making the argument)

» Any time a consumer makes an “irrational” choice the “fault” lies with the company providing the products

» Companies that target consumers in countries with very low levels of income are inherently evil

As any anthropologist will immediately see, these are a patronising set of assumptions unable to allow that people on low incomes (people not “consumers”, Jan!) can think for themselves - which Jan rebuts clearly and in depth, with lots of great examples from his work.

Well worth a read.

Massive, crucial point, beautifully expressed - and by an undergrad no less (by name of Evan Freedman).

Comment on The Limits of Big Data by Klint Finley on RWW, June 2011