Guillaume's blog | Thoughts on the future of money

How to compute someone’s Whuffie

Imagine yourself in a world where nanotechnology has made scarcity and the associated traditional form of money a thing of the past. In this world, the only currency is the goodwill that people give electronically to one another and everyone’s overall resulting reputation score is accessible by anyone in real-time. This reputation is Whuffie and the term and world was coined and imagined by Cory Doctorow in his sci-fi novel, Down and Out in the Magic Kingdom.

Fast rewind to present time. We are a world where people increasingly publish digitally their life i.e. are “life streaming”: they publish pictures, blog posts, twits, videos, wikis, etc. Other people subscribe to these life streams (RSS/friendfeed), give attention to the ones they find the most relevant and sometimes comment positively or negatively on these life stream items. These comments are themselves life streaming items and subject to views and positive/negative comments from others.

One thing is missing to get us closer to Cory’s vision: real-time computation of anyone’s Whuffie, the Web 2.0 equivalent of your FICO score. How do we compute it?

I have only found one blog post so far on the the problem of the so-called Whuffie algorithm, but I was not convinced by the arbitrary number of points won/lost for specific actions, and by the difficulty of implementing the tracking of some of these actions:

Trash talk somebody: -1000
For every conference you attend: +200 (Plus bonus +5 for each #tweet)

I know that Jeff Ward wrote that he was just posting for fun on this one, but since there seemed to be interest in the comments for an actual implementation, I decided tonight in BART to take a stab at what such algorithm would look like.

Here are the basic principles:

The algorithm should take into account how many positive/negative comments or citations your life stream items have got from other people, weighted by the Whuffie score of each of these people.
- The use of the weight here is important as it allows to remove completely the arbitrary point amounts: for instance, instead of “For every conference you speak at: +10,000″, speaking at a conference would essentially be equivalent to posting a summary of your speaking engagement and have the conference organizers or the conference itself comment on it/cite you on their Web site, with the Whuffie value of the comment being a function of the Whuffie of the conference or conference organizers themselves.
- The positive/negative nature of the comment would be determined via semantic analysis or microformats votelinks or voting nanoformats (vote:for:this article, +1/-1).
If the positive/negative nature of the comments cannot be determined, a positive Whuffie point amount of a lesser amount would be attributed, weighted by the Whuffie of the entity issuing the comment.
If no comment is available, views should be used (# of time a video was viewed), agained weighted by the Whuffie of who viewed it if possible. Views should contribute less Whuffie points then comments.
In all cases, for each item published a number of points should be provided multiplied by the number of followers the person/entity has on the site where the life stream item is posted on (# of subscribers to RSS feed, # of Twitter followers, # of Flickr contacts, etc.).

I don’t really have a precise idea of what these point amounts should be. Let’s say +10 for a positive comment, -10 for a negative comment, +5 for a comment, +3 for a view, and +1 for a published item.

Let’s also say that these points would be weighted by 1/100 of the Whuffie of the person commenting, viewing or following the publisher/life stream item. so, if my Whuffie is 1,000,000 and I view an image of someone, but do not comment on it, that gives 10,000 Whuffie points to the person who posted this image.

Of course this algorithm reduces the number of arbitrary constants to a few, but these are still arbitrary. So, the next question that came to my mind is whether there is a set of constant values that would be better than another, better for instance at achieving the goal of a Whuffie system.

What is such goal? do we want a bell curve distribution of Whuffie scores, a very spiky curve or a very flat curve. Do we want Whuffie to last indefinitely, or to self-destroy over time (with the objective of preventing social capital to be too concentrated among too few people). I think this is where I should have started, but that I will the subject of another post hopefully. In the meantime, I will get good ideas/suggestions from you.

Another interesting problem is how we fight spam and reputation hacking in such a system. I think one partial answer would be to allow Internet hosts to have their own Whuffie, and to use that as an additional weighting factor. Ideas here are welcome as well.

Fostering innovations through prizes

I’m not a big fan of Senator McCain but I do think that his proposal announced today for “a $300 million government prize to whoever can develop an automobile battery that far surpasses existing technology” is an excellent tool to foster energy innovation.

The winner-takes-all big prize strategy has proven successful in the past (DARPA Grand Challenge, X Prizes). And $300 million ($1 per American citizen) is much more motivating than the $10M Progressive Automotive X Prize.

I haven’t read the details of his proposal, but I hope that the technology that wins this prize will end up being open sourced for anyone to use. I don’t know how unrealistic these open sourcing terms would be though.

Business method patents: good or bad for the U.S. financial services?

PaymentNews pointed to a research paper title “Business Method Patents and U.S. Financial Services” authored by Robert M. Hunt of the Philadelphia Fed.

As any researcher in knowledge economics would know, maximizing the value of knowledge for society is a difficult problem: on one hand, you need to provide the proper incentives for innovators to invent (typically a patent system that provides a time-limited monopole), and on the other hand you want this knowledge to be used as fast as possible by as many people. Finding the right balance is not easy. This is a subject I’m really interested in, and business method patentability is a very interesting on its own, so I went through the paper. Here are my notes.

Here is the most important part IMO from the conclusion:

There is at present very little evidence to argue that business method patents have had a significant effect on the R&D investments of financial institutions. It is possible that the availability of business method patents has encouraged more entry and R&D by start-up firms or more efficient trading of technologies. At present, however, these represent intriguing possibilities and not outcomes that have actually been measured. In short, we still cannot determine whether financial patents are creating value for the U.S. economy.
[…]
The combination of significant technological overlap among firms, elastic patent boundaries, inadequate enforcement of disclosure requirements, and weak patentability standards raises at least the theoretical possibility of perverse outcomes (Hunt 2006). In such environments, firms may obtain more patents but perform less R&D, since the fruits of such efforts would be subject to an innovation tax imposed by rival firms.

My thoughts:
I think this area of patents is still evolving and regulators are still learning how to best optimize the value of the U.S. economy of patent issuance. There is a risk that startups be issued business method patents that other FIs license only to see themselves fought to death by large FIs in court. I don’t think it will be a big problem for niche markets, but it would be interesting to see what a court would decide if consulted on the non-obviousness of a business method patent issued to a small firm and which possibly has a huge impact/potential to many large FI players.

More excerpts:

A decade after the State Street decision, more than 1,000 business method patents are granted each year. Yet only one in ten are obtained by a financial institution. Most business method patents are also software patents.

That’s 10 business methods per year coming from a FI. Wow! The remainder of the article is basically trying to explain why these numbers are so low. Probably most of banking related business method patents come from startups (ex. SmartyPig has a patent on their business method).

Financial exchanges and the central bank are more research intensive than credit intermediaries (banks and thrifts).

I don’t think that will come as a surprise to anyone. I wrote earlier about the innovation problem at banks (I should have precised credit intermediaries as I’m well-aware that innovation is thriving in the investment side of banks).

Number of financial industries rely heavily on standard setting arrangements esp. payments networks and financial exchanges.

The article seems to imply here, if my understanding is correct, that business method innovation requires multiple parties to implement it, which means it’s hard for any one party to patent it at the same time that it seeks others to use (license if it’s a patent). That’s as if you had to pay to use a standard…

Lerner (2006) finds that business method patents are litigated at a rate 27 times
higher than for patents as a whole.

The reason for this is that the legal aspects of business methods patentability is still evolving. This might be another reason why business patents are few. It’s easier to keep them as good old trade secrets when possible, than try to patent them only to have to pay an army of lawyers to litigate them.

The article also talks about the legitimacy of licensing a patent and fighting in court in validity at the same time.

Les banques devrait-elles devenir des fournisseurs d’OpenID?

This is a translation in French of an earlier post.

Il y a presque dix ans, au sommet du boom Internet, je me rappelle avoir avoir discuté avec un banquier qui me suggérait que dans le future, le rôle des banques ne se limiterait pas a garder l’argent de leur dépositaires, mais aussi à garder leur identité en ligne secrète. D’une certaine manière, cette prediction s’est concrétisée par le biais des programmes de protection contre le vol d’identité. Cela dit, si l’on définit l’identité comme la somme des informations personnelles qui distingue une personne d’une autre et qu’il est difficile voire impossible de se procurer, on voit bien qu’une grand partie de ces informations (et en particulier les secrets tels les mots de passe) sont disséminés dans un grand nombre de services en ligne (60 en moyenne, bientôt 200, d’après une étude du Yankee Group sur OpenID).

Comme chacun sait, OpenID constitue la solution non-propriétaire à ce problème, et pour les raisons présentées ci-après, il semblerait que les banques soient des candidats parfaits pour devenir fournisseurs d’OpenID:

“Qui peut le plus peut le moins”. Le niveau de sécurité imposées par les services en ligne aux mots de passe de leurs utilisateurs ainsi que l’intérêt des utilisateurs à avoir des mots de passe difficiles, varient d’un service en ligne à un autre, mais la banque en ligne est probablement un des services ou le niveau de sécurité des mots de passe est le plus élevé. La raison est simple: il s’agit du service où les utilisateurs ont le plus à perdre si leur mot de passe se retrouve dans de mauvaises mains. Ainsi, on peut difficilement imaginer un utilisateur s’authentifier auprès de son service de banque en ligne avec son le nom d’utilisateur et mot de passe de son compte Google, mais l’inverse est beaucoup plus plausible
Les banques ont plusieurs actifs existants relatifs à la sécurité:
- Elles ont déjà en place une infrastructure technique assurant la sécurité de l’accès en ligne aux comptes bancaires,
- Elles ont pour la plupart une image de marque forte en terms de sécurité, et
- Elles ont déjà en place des programmes de protection contre le vol d’identité qui fourniraient un complément d’assurance à OpenID, et ferait de cette technologie une vraie solution/vrai produit
- Les banques sont tenues légalement de connaître leurs clients, et ont pour cette raison probablement beaucoup plus d’information sur leurs clients (par example, documents officiels comme carte d’identité) que n’importe quel autre service en ligne (mais pour combien de temps encore?). Cela veut dire qu’elle possèdent le plus large éventail d’options d’authentification, leur permettant de supporter plusieurs niveaux d’authentification. Elles ne sont pas limitées au model d’OpenID classique de l’URL et du mot de passe: elles peuvent non seulement décider d’émettre des URLs OpenID qui soient distinctes du nom d’utilisateur, mais elles peuvent aussi et surtout utiliser une authentification multifacteurs, par exemple envoyer un numéro personnel secret par SMS à un téléphone mobile, ou demander à un utilisateur de cliquer sur un bouton pour être appelé par un centre d’appel, comme spécifié par les OpenID policy extensions.
Enfin, il existe de très bonnes raisons économiques. Un service OpenID offert par une banque consituerait:
- Un service à très forte valeur perçue (mot de passe unique pour potentiellement tous les services en ligne utilisés par un utilisateur) que les banques pourraient faire payer
- Une nouvelle façon de promouvoir leur image de marque: compte tenu du fonctionnement d’OpenID (redirection vers le fournisseur OpenID pour chaque authentification) les utilisateurs verraient le logo de la banque à chaque authentification.
- Un formidable outil marketing: les banques auraient connaissance de quand quel utilisateur utilise quel service et pourraient présenter en fonction des offres et publicités liées ou non à leurs produits lors de chaque authentification,
- Une très bonne manière de garder leurs client: le coût de changement de fournisseur OpenID s’ajoutant aux autres coûts de transfer de comptes bancaires à une autre banque.

Fighting Spam with Whuffie

I recently received a pretty aggressive form of spam from a company based in Concord, CA. The outside was designed to look like some highly confidential and urgent material of legal and/or financial content. For instance, you could read on the front: “WARNING The penalty for obstructing or interfering with the delivery of this letter is a fine of $2,000 and up to 5 years imprisonment”.

As I opened it, I was genuinely worried, but quickly discovered it was just some kind of “Free offer* (*well, not really)” from a company called “Pulaski Tickets and Tours” based in Concord, CA according to the content of the spam. A Google query returned that the company is actually based in New York state and headed by a man named Patrick Harthough who lives here. The address in Concord is probably the address of a trash box for complaints.

Like most people, these types of mail waste my time (I shred any mail that is irrelevant) and now abuse my emotions.

I’d like to be able to do a little more than be able to trace this person and his company. I’d like to essentially publish somewhere, in a form that can be easily found and searched by others that this person’s marketing practices are questionable. This way, Mr. Harthough’s reputation is public and if enough people can easily do the same rather then just writing in forums, then people like me could automatically discard Mr. Harthough’s mails and perhaps people like Mr. Harthough would change their practices.

This type of real-time rating system is something I’ve been personally interested for many years, particularly as it applies to the hidden social and environmental costs of products people buy and use their social network of usually like-minded people to re-balance the current asymmetry of power between consumers and marketers. I think we are getting pretty close to a point where this type of system can be implemented (the technology of software UPC barcode scanners is getting to a point of usability, social networks are omnipresent, and Web-wide data queryability about companies and people is also making progress).

I recently discovered that a generalized version of this concept has a cool name: Whuffie, and that a book by Tara Hunt is coming out on the subject later this year.

Twitter: Unified Communications 1.0 (beta)

As I was twittering earlier in BART, I had to switch from the mobile Web twitter interface to the SMS interface. It suddenly occurred to me that just as I was able to choose which communication protocol (HTTP POST, SMS, voice-to-text: Twitterfone) and I suspect the reverse service exists as well) to post a message, my followers would be able to choose to read them using the reader of their choice (Twitterific, SMS, desktop Web, mobile Web).

This reminded of the old concept of Unified Messaging/Communications. Here is the definition from ZDNet:

The realtime redirection of a voice, text or e-mail message to the device closest to the intended recipient at any given time. For example, voice calls to desk phones could be routed to the user’s cellphone when required. E-mail intended for a desktop mailbox could be sent to the user’s PDA or turned into speech for a phone message.

Twitter is indeed pretty close to being the version 1.0 (beta – for its reliability issues) of Unified Communicator, and it probably achieved adoption where others failed or partly succeeded because 1) it limited the problem to 140 characters, a good common denominator for a variety of protocols, in particular SMS, and 2) APIs were exposed for 3rd parties to extend its capabilities.

Using hAtom for pagination of microformatted content

An interesting debate was started by André Luís last month on the microformats-discuss mailing list on the benefits of hAtom. I didn’t have time to read it in details at the time, but read the discussion today and here’s my summary.

For those not familiar with hAtom, it is an XHTML microformat for RSS-like feeds.

Great, but why would someone want to do that, given that blogging platforms already generate the RSS/Atom feed for you? Are there use cases for providing hAtom in addition to the Atom feed?

Zhang Zhen pointed to the WebSlice upcoming IE8 feature, which reuses hAtom syntax and will allow users to subscribe to a portion of a webpage. This pointer is interesting, but not quite exactly hAtom.

Toby Inkster mentioned that hAtom could help avoid the use of blogging software by essentially allowing the Atom feed to be generated by a service (but as André noted, this wasn’t really his question):

<link rel="service.feed" type="application/atom+xml" 
href="hatom2atom.php?uri=http://example.org/page.html" mce_href="hatom2atom.php?uri=http://example.org/page.html"/>

Brian Suda explained that hAtom could be used by Web crawlers to extract valuable metadata, and by browser plugins to provide a better user experience as a user is reading Web content.

While all these were valid benefits, the one that captured the attention of the group was the use of hAtom and rel='next' or rel='prev' for pagination of microformats, i.e. linking microformat entries listed on multiple pages together.

Let’s say you have a collection of hCalendar entries or hCard entries on your Web site, you could mark these up as hAtom and use a link between them, so that a microformat parser could navigate the site and generate a single collection of hCalendar and hCard entries.

Consequence of Peak Oil for Banks

I watched A Crude Awakening yesterday and here are my notes and thoughts.

This movie essentially makes the case for Peak Oil theory: that in recent years we have reached a plateau of worldwide production of oil and that oil production will go downhill from here. The movie presents the economic, political and sociological consequences in a truly apocalyptic vision, but even if like me, you believe in human technological creativity to get us out of this mess, I think it is worth watching to bring awareness of the issues and crisis that the end of cheap oil might bring about in the next 10 years, keeping in mind that noone has the ability to predict whether this transition to other technologies will be abrupt at times or smooth and will happen in an orderly manner.

The most striking comparison presented was that oil is a very dense energy, which offers extreme productivity levels, with which other energy sources have a very hard to compete with, which in turn makes the challenge of oil transition humongous, and will be particularly difficult for our financial system.

Here is a good comparison mentioned in the movie: 1 barrel of oil (42 gallons) = 25,000 man hours of work = 12 people working full-time for one year. Another interesting comparison is that at $4 a gallon of gasoline and with a 20 miles per gallon 4-person car, you can take with a 4-person family for 1 mile for 20 cents at 60 miles per hour, definitely not a wage the driver of human-powered vehicle like a pedicab /rickshaw would or could physically work for. If we want to pay the driver $10 per hour (minimum wage in California is $8/hr), and assume he will ride 2 people at 10mph, 1 mile for 4 people will come at a minimum cost of $2, which is 10 times the current cost in 1/6th of the time.

What does Peak Oil theory means for banks?

The following text I borrowed from LifeAfterTheOilCrash.net is the clearest answer I’ve read to this question:

It is becoming evident that the financial and investment community begins to accept the reality of Peak Oil, which ends the First Half of the Age of Oil. They accept that banks created capital during this epoch by lending more than they had on deposit, being confident that Tomorrow’s Expansion, fueled by cheap oil-based energy, was adequate collateral for Today’s Debt. The decline of oil, the principal driver of economic growth, undermines the validity of that collateral which in turn erodes the valuation of most entities quoted on Stock Exchanges.

Update 6/1/08: WSJ Article on the value of second-hand SUVs. Excerpt:

About 36% of the people who tried to trade in a large SUV in May owed more on the truck than it was worth, according to data from the Power Information Network. That’s up from just under 33% a year ago. (It’s worse for large pickups. Recent PIN data suggests 40% of large pickups traded during May fetched less than the loan balance.)

A three-year-old large SUV today is worth about $2,000 to $3,000 less at trade-in than a three-year-old large SUV would have been in 2007, before gas prices began to soar, according to Marc Cannon of AutoNation Inc., the largest U.S. auto retailer. A three-year-old Chevy Tahoe that might have fetched $19,700 in September 2007, he says. Today, a three-year-old Tahoe might be worth $16,400 at trade-in.

What the IT at Google Bank would look like

As I was watching the Google I/O keynote presentation, I thought about how all the development tools provided by Google (Google Gears, GData, OpenSocial, etc.) could be put to work to create a Google-powered Bank, and what the IT architecture of this Google Bank would look like.

Here is how I think it could look like:

All user interaction devices, whether it is a teller workstation, mobile phone, ATM machine, kiosk would provide access to the bank via any of the standard Web browsers (Opera, IE, Firefox, Safari).

If access to device-specific functionality is required, it would be done by Google Gears (say for instance, that I want to access the ATM’s cash dispensing functionality, or I want to access the mobile phone’s built-in GPS or accelerometer). Ideally, these devices would be running a single application that would adapt according to the services discovered on the device on on the service cloud. But realistically, they would be running variant of a single GWT Java code base that GWT would compile in JavaScript for browser-based deployment.

Contacting customer support would be done via Google Talk click-to-call buttons. Interactive Voice Response systems would be powered by 1-800-GOOG-411 voice technology.

All these user facing app would leverage a cloud of shared GData services based on Atom Publishing Protocol. These services would be used to retrieve and update any data and transaction: update accounts, customer profiles, schedule payments, withdraw money, consult account balances, etc.

These services would be available to any developer who registered for an API key to create new 3rd party applications, with online documents, code examples, tutorials, videos, etc. There would be a related developer challenge that would award prizes ranging from $25K to $100K to motivate developers to create 3rd party applications. Google Bank would monitor usage and success via the API key, and acquire the apps that can contribute the most to their bottom line or user growth. OAuth would be used to allow 3rd party apps to accesss customer data without the user having to give away their Google login/password.

OpenSocial would be leveraged by Google Bank to provide an easy framework for friends to share bills, family member to send money to one another via any device, and to loan money to friends/families or friends of friends. Google Bank would use this data to provide preferential loan rates or optimize transaction fees.

Google Bank analytics would analyze my transaction patterns, build nice spending usage pie charts for me, and suggest relevant ways to save or make more money via competitive offers aggregated in Google Shopping. Bank marketing managers would use Google Bank analytics to analyze usage patterns, create marketing campaigns and target specific demographics and customer types in Google Adsense.

And last but not least, users would be able to search all their personal data using a simple one input field user interface.

Did I miss anything?

23andMe personal DNA analysis service review (Part 1)

I got myself a genotyping kit from 23andMe for my birthday. Part of my commitment to stop buying physical “stuff”, and instead buy intangible/digital gifts. I thought it would be fun and possibly useful. I mentioned this to my friend Steven who convinced me to share my experience on my blog.

First of all, I’d like to say that the packaging is very good. Almost Apple-ish. These genotyping kits make excellent gifts for friends and family members ($999 per kit though). You can even ship them internationally and have them be used by non-U.S. residents.

I have a few pictures below but the most interesting part to me was to read the Consent and Legal Agreement & Waiver. It was the first time I’ve read one in a long time, and this one contained unusual and interesting comments:

RISKS:
You may learn information about yourself that you do not anticipate. This information may evoke strong emotions and has the potential to alter your life and worldview. You may discover things about yourself that trouble you and that you may not have the ability to control or change (e.g. your father is not genetically your father, surprising facts related to your ancestry, or that someone with your genotype may have a higher than average chance of developing a specific condition or disease. These outcomes may have social, legal, or economic implications

and a little further down:

Genetic data you share with others could be used against your interests. You should be careful about sharing your genetic information with others. Currently, very few businesses or insurance companies request genetic information, but this could change in the future. If an employer or insurance company obtained your genetic information through your sharing of it or by legally binding requirements, they could use your genetic data to deny your employment or coverage. Some but not all jurisdictions have laws that protect individuals from this kind of conduct.

Scary…
Anyway, here are the pictures:

I’m going to fill the container up this WE and in 4-6 weeks I will get my results and will post Part 2 of this post. Stay tuned!