Lockstep

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Email: swilson@lockstep.com.au

Facebook's lab rats

It's long been said that if you're getting something for free online, then you're not the customer, you're the product. It's a reference to the one-sided bargain for personal information that powers so many social businesses - the way that "infomopolies" as I call them exploit the knowledge they accumulate about us.

Now it's been revealed that we're even lower than product: we're lab rats.

Facebook data scientist Adam Kramer, with collaborators from UCSF and Cornell, this week reported on a study in which they tested how Facebook users respond psychologically to alternatively positive and negative posts. Their experimental technique is at once ingenious and shocking. They took the real life posts of nearly 700,000 Facebook members, and manipulated them, turning them slightly up- or down-beat. And then Kramer at al measured the emotional tone in how people reading those posts reacted in their own feeds. See Experimental evidence of massive-scale emotional contagion through social networks, Adam Kramer,Jamie Guillory & Jeffrey Hancock, in Proceedings of the National Academy of Sciences, v111.24, 17 June 2014.

The resulting scandal has been well-reported by many, including Kashmir Hill in Forbes, whose blog post nicely covers how the affair has unfolded, and includes a response by Adam Kramer himself.

Plenty has been written already about the dodgy (or non-existent) ethics approval, and the entirely contemptible claim that users gave "informed consent" to have their data "used" for research in this way. I draw attention to the fact that consent forms in properly constituted human research experiments are famously thick. They go to great pains to explain what's going on, the possible side effects and potential adverse consequences. The aim of a consent form is to leave the experimental subject in no doubt whatsoever as to what they're signing up for. Contrast this with the Facebook Experiment where they claim informed consent was represented by a fragment of one sentence buried in thousands of words of the data usage agreement. And Kash Hill even proved that the agreement was modified after the experiment started! These are not the actions of researchers with any genuine interest in informed consent.

I was also struck by Adam Kramer's unvarnished description of their motives. His response to the furore (provided by Hill in her blog) is, as she puts it, tone deaf. Kramer makes no attempt whatsoever at a serious scientific justification for this experiment:

  • "The reason we did this research is because we care about the emotional impact of Facebook and the people that use our product ... [We] were concerned that exposure to friends’ negativity might lead people to avoid visiting Facebook.

That is, this large scale psychological experiment was simply for product development.

Some apologists for Facebook countered that social network feeds are manipulated all the time, notably by advertisers, to produce emotional responses.

Now that's interesting, because for their A-B experiment, Kramer and his colleagues took great pains to make sure the subjects were unaware of the manipulation. After all, the results would be meaningless if people knew what they were reading had been emotionally fiddled with.

In contrast, the ad industry has always insisted that today's digital consumers are super savvy, and they know the difference between advertising and real-life. Yet the foundation of the Facebook experiment is that users are unaware of how their online experience is being manipulated. The ad industry's illogical propaganda [advertising is just harmless fun, consumers can spot the ads, they're not really affected by ads all that much ... Hey, with a minute] has only been further exposed by the Facebook Experiment.

Advertising companies and Social Networks are increasingly expert at covertly manipulating perceptions, and now they have the data, collected dishonestly, to prove it.

Posted in Social Networking, Social Media, Science, Privacy, Internet, Culture

Hotel database security

International hotels are a fantastic target for identity thieves. Hotel databases don't just hold credit card numbers and billing addresses (which are held for weeks in advance of a stay and for weeks afterwards to cover incidentals), but for many customers the hotel also has their home address, mobile phone number, driver licence number, airline memberships and arrival flight details. And even passport number is routinely collected by hotels in Asia. It's a complete cornucopia for criminals.

And the most dangerous, most difficult to control threat vector in the hotel industry won't be war-driving or SQL injection attacks or any of the other high tech hacking tools used by organised crime. It will be the inside job. Thousands of itinerant hotel workers in every corner of the world have the opportunity to access office systems after hours, and simply download the contents of central databases to a thumb drive.

The vulnerability of hotel databases to identity thieves has clear implications for national security. I trust that counter terrorism agencies are working on this problem? These databases reveal the forward travel plans for thousands of VIPs worldwide.

We should expect that organised criminals and terrorist organisations are tapped into hotel databases as we speak, and are mining them systematically.

Posted in Fraud, Security

Webinar: Big Privacy

I'm presenting a Constellation Research webinar next week on my latest research into "Big Privacy" (June 18th in the US / June 19th in Australia). I hope you can join us.

Register here.

We live in an age where billionaires are self-made on the back of the most intangible of assets – the information they have amassed about us. That information used to be volunteered in forms and questionnaires and contracts but increasingly personal information is being observed and inferred.

The modern world is awash with data. It’s a new and infinitely re-usable raw material. Most of the raw data about us is an invisible by-product of our mundane digital lives, left behind by the gigabyte by ordinary people who do not perceive it let alone understand it.

Many Big Data and digital businesses proceed on the basis that all this raw data is up for grabs. There is a particular widespread assumption that data in the "public domain" is free-for-all, and if you’re clever enough to grab it, then you’re entitled to extract whatever you can from it.

In the webinar, I'll try to show how some of these assumptions are naive. The public is increasingly alarmed about Big Data and averse to unbridled data mining. Excessive data mining isn't just subjectively 'creepy'; it can be objectively unlawful in many parts of the world. Conventional data protection laws turn out to be surprisingly powerful in in the face of Big Data. Data miners ignore international privacy laws at their peril!

Today there are all sorts of initiatives trying to forge a new technology-privacy synthesis. They go by names like "Privacy Engineering" and "Privacy by Design". These are well meaning efforts but they can be a bit stilted. They typically overlook the strengths of conventional privacy law, and they can miss an opportunity to engage the engineering mind.

It’s not politically correct but I believe we must admit that privacy is full of contradictions and competing interests. We need to be more mature about privacy. Just as there is no such thing as perfect security, there can never be perfect privacy either. And is where the professional engineering mindset should be brought in, to help deal with conflicting requirements.

If we’re serious about Privacy by Design and Privacy Engineering then we need to acknowledge the tensions. That’s some of the thinking behind Constellation's new Big Privacy compact. To balance privacy and Big Data, we need to hold a conversation with users that respects the stresses and strains, and involves them in working through the new privacy deal.

The webinar will cover these highlights of the Big Privacy pact:

    • Respect and Restraint
    • Super transparency
    • And a fair deal for Personal Information.

Have a disruptive technology implementation story? Get recognised for your leadership. Apply for the 2014 SuperNova Awards for leaders in disruptive technology.

Posted in Social Media, Privacy, Constellation Research, Biometrics, Big Data

Watson the Doctor is no laughing matter

For the past year, oncologists at the Memorial Sloan Kettering Cancer Centre in New York have been training IBM’s Watson – the artificial intelligence tour-de-force that beat allcomers on Jeopardy – to help personalise cancer care. The Centre explains that "combining [their] expertise with the analytical speed of IBM Watson, the tool has the potential to transform how doctors provide individualized cancer treatment plans and to help improve patient outcomes". Others are speculating already that Watson could "soon be the best doctor in the world".

I have no doubt that when Watson and things like it are available online to doctors worldwide, we will see overall improvements in healthcare outcomes, especially in parts of the world now under-serviced by medical specialists [having said that, the value of diagnosing cancer in poor developing nations is questionable if they cannot go on to treat it]. As with Google's self-driving car, we will probably get significant gains eventually, averaged across the population, from replacing humans with machines. Yet some of the foibles of computing are not well known and I think they will lead to surprises.

For all the wondrous gains made in Artificial Intelligence, where Watson now is the state-of-the art, A.I. remains algorithmic, and for that, it has inherent limitations that don't get enough attention. Computer scientists and mathematicians have know for generations that some surprisingly straightforward problems have no algorithmic solution. That is, some tasks cannot be accomplished by any universal step-by-step codified procedure. Examples include the Halting Problem and the Travelling Salesperson Problem. If these simple challenges have no algorithm, we need be more sober in our expectations of computerised intelligence.

A key limitation of any programmed algorithm is that it must make its decisions using a fixed set of inputs that are known and fully characterised (by the programmer) at design time. If you spring an unexpected input on any computer, it can fail, and yet that's what life is all about -- surprises. No mathematician seriously claims that what humans do is somehow magic; most believe we are computers made of meat. Nevertheless, when paradoxes like the Halting Problem abound, we can be sure that computing and cognition are not what they seem. We should hope these conundrums are better understood before putting too much faith in computers doing deep human work.

And yet, predictably, futurists are jumping ahead to imagine "Watson apps" in which patients access the supercomputer for themselves. Even if there were reliable algorithms for doctoring, I reckon the "Watson app" is a giant step, because of the complex way the patient's conditions are assessed and data is gathered for the diagnosis. That is, the taking of the medical history.

In these days of billion dollar investments in electronic health records (EHRs), we tend to think that medical decisions are all about the data. When politicians announce EHR programs they often boast that patients won't have to go through the rigmarole of giving their history over and over again to multiple doctors as they move through an episode of care. This is actually a serious misunderstanding of the importance in clinical decision-making of the interaction between medico and patient when the history is taken. It's subtle. The things a patient chooses to tell, the things they seem to be hiding, and the questions that make them anxious, all guide an experienced medico when taking a history, and provide extra cues (metadata if you will) about the patient’s condition.

Now, Watson may well have the ability to navigate this complexity and conduct a very sophisticated Q&A. It will certainly have a vastly bigger and more reliable memory of cases than any doctor, and with that it can steer a dynamic patient questionnaire. But will Watson be good enough to be made available direct to patients through an app, with no expert human mediation? Or will a host of new input errors result from patients typing their answers into a smart phone or speaking into a microphone, without any face-to-face subtlety (let alone human warmth)? It was true of mainframes and it’s just as true of the best A.I.: Bulldust in, bulldust out.

Finally, Watson's existing linguistic limitations are not to be underestimated. It is surely not trivial that Watson struggles with puns and humour. Futurist Mark Pesce when discussing Watson remarked in passing that scientists don’t understand the "quirks of language and intelligence" that create humour. The question of what makes us laugh does in fact occupy some of the finest minds in cognitive and social science. So we are a long way from being able to mechanise humour. And this matters because for the foreseeable future, it puts a great deal of social intercourse beyond AI's reach.

In between the extremes of laugh-out-loud comedy and a doctor’s dry written notes lies a spectrum of expressive subtleties, like a blush, an uncomfortable laugh, shame, and the humiliation that goes with some patients’ lived experience of illness. Watson may understand the English language, but does it understand people?

Watson can answer questions, but good doctors ask a lot of questions too. When will this amazing computer be able to hold the sort of two-way conversation that we would call a decent "bedside manner"?

Have a disruptive technology implementation story? Get recognised for your leadership. Apply for the 2014 SuperNova Awards for leaders in disruptive technology.

Posted in Software engineering, Science, Language, e-health, Culture, Big Data

Three billion was a Snap

The latest Snowden revelations include the NSA's special programs for extracting photos and identifying from the Internet. Amongst other things the NSA uses their vast information resources to correlate location cues in photos -- buildings, streets and so on -- with satellite data, to work out where people are. They even search especially for passport photos, because these are better fodder for facial recognition algorithms. The audacity of these government surveillance activities continues to surprise us, and their secrecy is abhorrent.

Yet an ever greater scale of private sector surveillance has been going on for years in social media. With great pride, Facebook recently revealed its R&D in facial recognition. They showcased the brazenly named "DeepFace" biometric algorithm, which is claimed to be 97% accurate in recognising faces from regular images. Facebook has made a swaggering big investment in biometrics.

Data mining needs raw material, there's lots of it out there, and Facebook has been supremely clever at attracting it. It's been suggested that 20% of all photos now taken end up in Facebook. Even three years ago, Facebook held 10,000 times as many photographs as the Library of Congress:

Largest photo libraries
[Picture courtesy of the now retired 1000memories.com blog]

And Facebook will spend big buying other photo lodes. Last year they tried to buy Snapchat for the spectacular sum of three billion dollars. The figure had pundits reeling. How could a start-up company with 30 people be worth so much? All the usual dot com comparisons were made; the offer seemed a flight of fancy.

But no, the offer was a rational consideration for the precious raw material that lies buried in photo data.

Snapchat generates at least 100 million new images every day. Three billion dollars was, pardon me, a snap. I figure that at a ballpark internal rate of return of 10%, a $3B investment is equivalent to $300M p.a. so even if the Snapchat volume stopped growing, Facebook would have been paying one cent for every new snap, in perpetuity.

These days, we have learned from Snowden and the NSA that communications metadata is just as valuable as the content of our emails and phone calls. So remember that it's the same with photos. Each digital photo comes from a device that embeds within the image metadata usually including the time and place of when the picture was taken. And of course each Instagram or Snapchat is a social post, sent by an account holder with a history and rich context in which the image yields intimate real time information about what they're doing, when and where.

The hallmark of the Snapchat service is transience: all those snaps are supposed to flit from one screen to another before vaporising. Now of course that idea is contestable; enthusiasts worked out pretty quickly how to retrieve snaps from old memory. And in any case, transience is a red herring, perhaps a deliberate distraction, because the metadata matters more, and Snapchat admits in its Privacy Policy that it pretty well keeps the lot:

  • When you access or use our Services, we automatically collect information about you, including:
  • Usage Information: When you send or receive messages via our Services, we collect information about these messages, including the time, date, sender and recipient of the Snap. We also collect information about the number of messages sent and received between you and your friends and which friends you exchange messages with most frequently.
  • Log Information: We log information about your use of our websites, including your browser type and language, access times, pages viewed, your IP address and the website you visited before navigating to our websites.
  • Device Information: We may collect information about the computer or device you use to access our Services, including the hardware model, operating system and version, MAC address, unique device identifier, phone number, International Mobile Equipment Identity ("IMEI") and mobile network information. In addition, the Services may access your device's native phone book and image storage applications, with your consent, to facilitate your use of certain features of the Services.
  • Location Information: With your consent, we may collect information about the location of your device to facilitate your use of certain features of our Services, determine the speed at which your device is traveling, add location-based filters to your Snaps (such as local weather), and for any other purpose described in this privacy policy.

Snapchat goes on to declare it may use any of this information to "personalize and improve the Services and provide advertisements, content or features that match user profiles or interests" and it reserves the right to share any information with "vendors, consultants and other service providers who need access to such information to carry out work on our behalf".

So back to the data mining: nothing stops Snapchat -- or a new parent company -- running biometric facial recognition over the snaps as they pass through the servers, to extract additional "profile" information. And there's an extra kicker that makes Snapchats extra valuable for biometric data miners. The vast majority of Snapchats are selfies. So if you extract a biometric template from a snap, you already know who it belongs to, without anyone having to tag it. Snapchat would provide a hundred million auto-calibrations every day for facial recognition algorithms! On Facebook, the privacy aware turn off photo tagging, but with Snapchats, self identification is inherent to the experience and is unlikely to be ever be disabled.

NSA has all your selfies

As I've discussed before, the morbid thrill of Snowden's spying revelations has tended to overshadow his sober observations that when surveillance by the state is probably inevitable, we need to be discussing accountability.

While we're all ventilating about the NSA, it's time we also attended to private sector spying and properly debated the restraints that may be appropriate on corporate exploitation of social data.

Personally I'm much more worried that an infomopoly has all my selfies.

Have a disruptive technology implementation story? Get recognised for your leadership. Apply for the 2014 SuperNova Awards for leaders in disruptive technology.

Posted in Social Networking, Social Media, Privacy, Biometrics, Big Data