I have been thinking for a while about a model that describes the interdependencies between public, private, identity, reputation and privacy (laws).  This is mostly driven by the need to try and find an approach to define different types of “identity” based on characteristics that have some degree of stability and repeatability.

The vertical axis represents the perceptions of how people can be perceived by everyone else; this provides a range from a private citizen (general public) to a public figure (politician). The horizontal axis represents the how we conduct ourselves from being a private self (protected) to being public (15 seconds of fame)

The quadrants are defined by the extremes of the axis definitions as follows:

Obscurity - a private citizen who wants to remain private. An example at an extreme is a hermit, but this category tries to incorporate “the general public”

Professional Status - a private citizen who has a public role. An examples would be a doctor or consultant and increasingly those who have influence.

Privacy Laws – a public figure who wants to hide their private self and will look to privacy laws as a defence. Examples are celebrities who take out a super-injection.

Broadcast – a public figure that has a public self. An example could be a reality TV celebrity or Katie Price (aka Jorden)

 

 

The structural model is about the linkage between the forms of identity (certification, recognition, reputation and anonymity) and perceptions of how I am viewed and how others view me.

In the Obscurity quadrant identity is built for private citizens who remain private, from both certification (documents of public record… birth, marriage, NI, Tax, driving licence) and “I am who I say I am”.  Individuals decide about having one ID (identity) or presenting the world through persona(s).  This is not taking away how we all receive some level of identity at the most basic level, but unlike other cases certification is the primary identifier.

For the Professional Status quadrant Identity is enhanced in the form of reputation.  Reputation giving both status and authority [influence] (potentially to authenticate oneself and others … trusted status)

The quadrant of “Privacy Laws” is the odd one as identity is hidden by those who are public figures who try to protect their private lives and demand some level of anonymity.

The Broadcast quadrant has an identity that is enhanced in the form of recognition.  Recognition in this context is the ability to recognise.  Recognition introducing the ideals of celebrity and brand.me as some of the outcomes.

The model shows how the relationships between self (private to public) and Citizen (private to public) lead to four outcomes which show different requirements and characteristics of identity and hence why “identity” is an impossible topic to discuss with a framework.

Further comments to the post of facial recognition earlier today http://blog.mydigitalfootprint.com/facial-recognition-is-it-part-of-my-digital-f

And other comments on the blog here http://blog.mydigitalfootprint.com/?sort=&search=facial

So the short version is that you can take a picture of someone, use the image to search images on say Facebook, match the two images using some sort of facial recognition algorithm and therefore find out someone's name (given the match and the different database entries).  This would apply even for someone just walking down the street, or tracking them where they walked, find you where they live and any other data.... shock.  It simple terms it is allowing databases to be paired to create value or make it really creepy.

Test cases prove it all works but they use data that was "selective" to make it quicker, but the reality is here and these services will be rolled out and you will be identified without being asked from your ID, which for some is the issue. “I want to hide”

As we realise and struggle with the fact that democracy entitles everyone who has a voice to be counted (freedom of expression), so we also realise that certain digital technology makes it harder to do harm.

Mr Policeman stops you;  "diving licence please" even for the trained eye and a data base detecting the forgery is hard but has real costs for Joe Public. However with the shoulder strap videocam the true person ID comes back allowing the  police to do his/ her job.  Where else can this tech be used that we would see value - Identification of people in a disaster, being identified as a VIP at your bank (assuming longevity of jobs has gone); criminal activity, names of guests, boarder control....

So all criminals will work this out and have ID photos on Facebook etc that are not them but similar enough to fool the algorithm or they wear a few facial extras, which makes them easy to identify!? 

But I still have the same question – who’s data is it?

US: The Federal Trade Commission has announced that it is seeking public comments on the privacy and security implications raised by the use of facial recognition technology, specifically seeking public comments on the following:

• What are the current and future commercial uses of these technologies?

• Comment : let’s immediately limit this to what we can understand or gather what the fear could be. This is the right question to get the wrong answer.  A better question would be, “which problem will facial recognition solve on its own?

• Comment : Consumers only benefit if the eco-system or society benefit. Consumers don’t often seen benefit until after the policy.  Why let the animals run the zoo!

• Comment : fear, uncertainty and doubt. What concerns where there when photographic or CCTV equipment was developed, was there originally fear of electricity, telephones, plastics, radios, TV and the internet.  Why is the policy taking the stance “Let’s stop the ship now and get off as the sea may be less dangerous here to jump into than over there in a boat.”

• Comment : this makes an assumption about the application and who is running the service and assumes that data is collected, stored, associated and then used (abused) – Again the question should be focussed on what and where should regulation be applied and how should we be creating market dynamics that provide rights to those who need them. Let’s stop being focussed on collection and storage and focus on where the value is…. Grown up regulation !

• Comment : Assumption already implied in the questions is that the consumer does not see or gain any value from the exchange of their face being recognised.  Basic question – why do you need facial recognition and what are you trying to associate an image to.  Facial recognition has no value without being able to link it to some form of database…. Ahem – where should we focus !
• So the announcement was put out by Amanda Koulousias – Google Images gives me her image, Radaris gives me some connections, Search engines give me CV, BIO, profile etc.  What step are we actually talking about here – is it the capture or the association, the right to hide, freedom or something else?

• Comment : My heart says again wrong question as I cannot work out what the concern is…. Are you taking about capture of your image, storage of the image, analysis of the image, association of the image or creating value from the process?  The problem I would contend is not the service by the presentation of the data/ analysis back to the user. The same applies with location. Depending on how I (the service provider) feeds back the knowledge of location will either be creepy or value enhancing. Creepy services tend to die fast. Or are we concerned about Government tracking?

• Comment : No

• Comment : Big assumption and who made the judgement that your privacy trumps national security ?

Workshop by FTC : http://www.ftc.gov/bcp/workshops/facefacts/

Whilst this is an equally contentious issue in EU – especially in Germany, is facial recognition part of my digital footprint?

Facial recognition poses complex privacy issues that do not fit squarely with present laws as explored in the “Seeing is ID’ng,” a CDT report on facial recognition and privacy. The report describes the state of facial recognition technology and its commercial applications, the lack of laws that address facial recognition, and policy approaches to preserving consumer privacy.

The key privacy interest that commercial facial recognition affects is, of course, identification of an individual through facial features alone. Without facial recognition technology, it is very difficult for a stranger to easily and quickly identify an individual on this basis. Individuals in public currently expect that most businesses and passersby cannot recognize their faces, fewer still can connect a name to their faces, and few – if any – can associate their faces with internet behaviour, travel patterns, or other personal information. Facial recognition technology fundamentally changes this dynamic, enabling any marketer or random stranger to collect – openly or in secret – and share the identities and associated personal information of any individual in public.

Publicly available facial recognition is a transformative technology that demands nuanced solutions to preserve consumer privacy and free expression.

Back to my point of the blogs this week – you don’t have control, so don’t pretend you can, do or can get it back….

Image from UnderLogic

Facebook revamped its photo services by adding “Tag Suggestions”, a facial recognition feature which scans faces in your photos and offers up suggestions of who they are from your list of friends. Even though it is being tested with a small, undisclosed group of users, Tag Suggestions will roll out soon. One practical result is that is  that it is more likely that Facebook friends will tag you in photos and made it easier for friends to tag a large number of photos of you at once.

Some find the notion of facial recognition “creepy” as it conjures ideals of Minority Report, terrorist watch lists and generally “big brother.” But don’t worry as the EU privacy regulators have said that they will investigate the Facebook facial recognition move and U.S. privacy watchdog group EPIC said it was considering an FTC complaint. To address user concerns, the social network will also introduce a privacy setting that allows you to opt out of Tag Suggestions – but I am sure that it should have been opt-in given all the previous problems

So what?

Is this new feature really about sharing, being more open or having more connections?  Is the motivation that this data give more details about influence and more access to marketing? Whilst I personally don’t have an issue with facial recognition programs and use one; it is not about sharing or being open.  Given that “Facebook's mission is to give people the power to share and make the world more open and connected.” this feature sits in the open bucket, but not everyone wants open and I did not actually sign up to Facebook with the intention of having algorithms scan my photo (Good article on its evolution of FB mission). 

The next phase has to be that I can buy/ sell my facial recognition imprint (the details that allows an algorithm to know it is you) that will be used to run over someone else’s data and I  will discover where you have been caught, or where I are now but is that sharing or open?

Google shelved technology that would mesh mobile location with facial recognition because of fears it would be misused, Executive Chairman Eric Schmidt told attendees at the opening session at All Things Digital. May 2011.  An ‘evil dictator’ could use that against you, Schmidt said. “We built that technology and withheld it [because] people could use in a very bad way,” Schmidt said.

But Google won’t keep the two technologies from meshing via apps on its Android or Chrome platforms. “Any platform app strategy has to allow for people to do that kind of stuff,”.

Pressed by Walt Mossberg about allowing others to do what Google won’t, Schmidt commented: “There are plenty of apps I don’t like that are still legal.”

Reality mining is according to MIT is “the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.”

We know that every time you search (text, image, video), you give Google some value, you give even more value when you click on a result.  From each search and click Google ‘learns’ and increases it knowledge and value.  Google doesn’t need you name or address to do this, but with Picasa facial recognition, oddly enough they do know what you and your family look like. However android opens up the opportunity to gain all the mobile operator data as well.

Mobile operators know who you are and where you live and from your calling pattern who your friends are or who you work with.  With location aware devices, they know your location at all time and as devices increasingly become packed with sensors, they could have more data.

Facebook and Twitter know your extended social network and who influences you and who you influence.

Apple knows everything and what music you and your friends like.

So who should partner with who and if they did would it create any value for the user. Lets assume that Apple will do their own thing and will not partner with anyone.

Google + Mobile operator = could be interesting and should be a power play in terms of the value of the data that they bring.  Google wins though as it has the ability to take the analysis and deliver the value.  Operators have data but no real means of using it.  Google can buy operator data.  No partnership.

Google + Facebook = Both can get data and both can deliver value. Facebook knows who you influence and who influences you. This is new value and not worth giving up at present. No partnership

Mobile operator + Facebook = would be interesting if they both focussed on value and what data they have and how they could create new value.  Facebook could buy operator data pattens, but probably could get the same data from different means.  No partnership

We may have to wait for a new start up to solve this one.