The nine circles of philanthropic giving

The New Yorker, in a January "Shouts and Murmurs", offers a glimpse into the world of philanthropic giving levels.

The theory of giving levels is that donors either like to be identified (and published) as giving at a certain level, and/or donors like the benefits (whether public or private) that accrue to giving at a certain level. For example, donors become members of the President's Circle of an art museum with a gift of $50,000 per year which allows them to have a private museum tour, with 12 of their friends, guided by the museum director.

The theory creates a circle of action (vicious or virtuous, I am not sure which). Charities set up giving levels and encourage donors to reach into those levels. Once you are a member of the President's Circle you don't want to be demoted, and so the price increases each year are an easy way to get you to increase your gift.

You can probably sense my ambivalence to these ideas. They work, but they are hardly appealing to the purest motives within us as donors.

The New Yorker article gets it exactly right:

The Benefit Committee wishes to remind all Subscribers that the thrill for those pledging as much money as they can afford to attend this Gala Charity Event will always be outweighed by the shame felt by those pledging as little as possible.
Please consult the Subscriber categories below.

The top (Grand Panjandrum's Diamond) level includes the right to ejection of any two undesirable table companions. The lowest (Huddled Masses) level allows merely for a complimentary official event program (depending on supply at conclusion of event).

While we are at it, please consider attending Matters of Taste, the wonderful JCDS fundraiser. Watch out for those giving levels, and I look forward to seeing you on the ninth circle!

Social Shopping

NYC gets with the social media program, creating separate interest-based spaces (one for husbands, separate from wives inside) for social-shopping during full-sensory-overload accessory shopping.

Social Media Jungle Boston

I am going to be addressing an interesting question soon, as a speaker at an event coming up in March. The question is: "What if the twitter stream told us every time a can of soda is sold?” What about every physicians' prescription (not the patient info, just the prescription, maybe with the diagnosis code)? We already have some automated data on the twitterstream (blog postings, transit updates, job postings, amber alerts)... what happens when more and more data is put out there?

What ideas do you have about unusual, or ridiculous, or mundane, streams of data that could be added to the twitterstream, and what would the implications be - please email me or leave comments below with those ideas.

What is all this about? It is about Social Media, and social media technology.

Social Media, also known as crowd-powered media, user-generated media, social networking and, generally Web 2.0, is (as I recently posted) a bigger trend than many people currently think. It is probably more than one trend, but that is also, as yet, unclear.

If you are interested in the social and commercial implications of these trends, and are in (or can be near) the Boston area on March 10, then consider participating in Jeff Pulver's Social Media Jungle Boston. I even have a $50-off code for you: JF2CFU6F.

If you can't make it in person, Twitter coverage will include the tag #smjbos.

Meanwhile, send me those ideas.

Above the clouds

Cloud computing is a new trend, high on the hype-cycle right now, where you can "plug in" to computing resources almost like you plug in to the electric grid.

In traditional network diagrams, the Internet (or indeed a private network) was represented by the picture of a cloud. This was meant to represent the fact that the internal nature of the connections in the network did not matter for the purposes of this particular diagram. A cloud is opaque, and its inner workings are unknown, but it does the job of connecting the things we care about, those computers that need the connectivity.

So initially, a cloud was a network, often provided by someone else, that connected computers but whose innards were, happily for all, a black box. The network provider could change the routing, the equipment or even the technology inside the cloud, and no-one using the network would even know. The connectivity would continue to work, and the computers would continue to talk to one another.

Now the cloud analogy is being stretched further, to include cloud computing, where computing resources are made available in the same opaque fashion, for customers to use as they need it, without worrying or knowing about the innards. Just as I can increase my use of the network cloud "as much as I want" and it is the vendor's job to make the network appear infinitely scalable, so it goes with cloud computing. If my website gets a massive spike in usage, my cloud computing vendor just provides more computing resources for me "on demand" - all I have to do is pay for the extra usage at that time.

With a nod to Greg Gretsch who brought this to my attention, and James Hamilton who wrote it up, you can get lots more information about this trend from UC Berkeley's "Above the Clouds" paper, presentation and video.

Semantic Web Interoperability

In preparation for attending the second annual Conference on Semantic Web in Healthcare and Life Science (CSHALS 09) next week, I have been reviewing my notes from last year's conference. As I twittered yesterday, my favorite line last year was from conference chair Eric Neumann (herewith properly attributed, unconstrained by the 140 character twitter limit): “What do we mean by semantics?”

The semantic web is all about providing meaning that computers can read (or “understand”, to the level that they can infer new knowledge from old). Using one of the foundational standards, RDF, each semantic web statement is called a “triple” since it is constructed of subject-verb-object triple. Examples would be “Venturecyclist is-a blog” and “Venturecylist is-authored-by Richard-Dale” and “Richard-Dale is-a Venture-Capitalist.” From this, the right kind automated inference engine could calculate “Venturecyclist is-authored-by a-venture-capitalist.” As you can see, writing even simple knowledge in this form is verbose (lots of triples for even simple statements of knowledge). When there are enough triples (millions, or even billions), then automated inferencing does actually produce interesting and novel information, as reported in Scientific American, for example.

Eric Neumann also provided a wonderful definition of the goal of the semantic web community, semantic interoperability: automated interoperating systems where a consumer of semantic web content understands all the needed context and meaning of the content, whatever the use of the content, even though the publisher knows nothing of the use case of the recipient.

My own extension to this is that the publisher should self-certify which ontologies and authorities they are using in publishing the content, and there should be an annotation system available (like link-backs), which allows for anyone to add their own semantic annotations. Self-annotation might include provenance of a triple (where it came from, source, current level of confidence in its truth etc).

In the healthcare arena, semantic web technologies allow for combining clinical data about a patient (Patient blood-sugar-level-is X) with standards of care (Blood-sugar-level-threshold is Y) and (Insulin treats blood-sugar-above-threshold). As life science researchers in the lab discover new knowledge about genes, proteins, pathways and treatments, then this can be matched with clinical data about patients in semantically interoperating systems. This allows for further clinical data about populations to inform further research and also, as implied above, for prescribing evidence based treatments.

This may all seem a little esoteric; it is, and it is still a series of commercially untested technologies (see yesterday's post on betting the bank). However, consider how easy it is to contribute photos and more to Google Earch. KML files are used by Google Earth (and other apps) to provide geographic meaning to anything from photos to facts. KML may not, strictly, be expressed in triples, but it provides an interesting example where real meaning (in this case, of geography) is available in machine-readable form, usable by any application that wants it. Imagine Google Body or Google DNA or Google Heart, where all the lab and medical knowledge can be combined in a model of our body or our DNA or our heart, the same way anyone can contribute new material for Google Earth using KML. As a triple, my conclusion would be:
--> (That-idea has value).

Bet the Bank

With IT spending running as high as 25% of revenue, and a risk-taking culture, Wall Street firms are old favorites as customer prospects for venture capital backed startups.

It is tough to sell information technology products to Wall Street firms right now (if you can find any left). Balance sheets are shrinking, employee counts are shrinking, budgets are shrinking and risk taking has pretty much disappeared. However, smart vendors and smart buyers know that these times of retrenchment can be great times for the right kind of IT investment. In general that means something that pays for itself in a few months even in periods of severe contraction, something that is proven in the field, and provides new capabilities for when the economy starts to pick up, leaving competitors in the dust. This doesn't just go for Wall Street, but for many (or even any) large enterprises.

When thinking about new technology, large enterprises tend to think about whether the new technology has been field-proven to scale and perform, and trade that off against the risks of the new technology failing. Obviously a new, unproven technology will be more readily adopted if it doesn't cause too much harm if it fails a few times. If it is a "bet the bank" situation, then you can bet that only proven technology will be considered.

Here is a chart that illustrates the point, using Sigma Partners portfolio company examples, of course. EqualLogic (sold to Dell last year) provides very stable, low risk, more efficient disk storage systems. Initiate's software for bringing together data about customers from multiple systems is also very well proven, but is used in very high-profile applications (eg call centers) and if it fails then the call center operations may cease. As yet unproven software (at least in commercial applications) such as Acquia's editions of the open source Drupal system can be adopted for intranets and other low-risk areas of a corporation. No-one ever buys "bet the bank" technology which has not been field tested and proven to scale.

How does this compare to my life as a venture cyclist, and most people's buying habits? Answer: it's pretty similar. I am happy to buy a new, fangled "unproven" pair of biking gloves, but I would like my helmet to have a good pedigree!

All Atwitter

If you have not thought much about Twitter, it is time to start thinking. If you think Twitter is just for meaningless chatter, or twenty-something time-wasters, then think again.

Did you hear that the first report, and photo, of the "Miracle on the Hudson" was on Twitter (an example of "crowd powered media")? Did you know CNN (and other news sources) publish important breaking news on twitter, and they really do reserve it for important stories?

What is Twitter anyway?

Twitter is a micro-blogging service for sending out updates of up to 140 characters (exercise to reader: why 140 characters?). Yes, it started as a way to tell your friends that you were awake, brushing teeth, drinking coffee, reading paper ... . But, like the telephone, email, blogs - all equally attractive time-wasters for socialites - new and important utility is emerging.

You can "follow" other people's tweets; I follow CNN, Jeff Pulver, and others; I don't follow the GOP, John Cleese, the UK Prime Minister, Darth Vader (brilliant), or, ... well you get the picture.
You can look at what's hot right now, or how the twittersphere treated a topic recently. You can track specific keywords on twitter (using either twitter search or, even better, TweetGrid or TweetDeck), to see what people are saying about you, your town, your employer, your competitor, your favorite charity. Did you know that someone unauthorized might be misrepresenting you, your company or your favorite charity (check out this Exxon-Mobil story)?

Some folks conjecture that all this may even be a threat to Google's predominance - and from that viewpoint, twitter really is a superior human powered search engine. However, I think there is both more and less to twitter than that. Twitter is less in that it is not about search, and it has a weak position to become a search leader (too easy to spam). Twitter is more in that it is as powerful as email has been, certainly more powerful than blogs, to change how we find and publish information and how we interact with our friends and the world around us.

Get going on Twitter.

Get an account. Go slow. Follow some folks. Don't believe me ... look at what David Pogue (NYT) has to say, and, in a similar vein, see 8 Useful Tips To Become Successful With Twitter.

Top 10 Lies; Top 10 Truths

Some great reading for your weekend.

Guy Kawasaki has a couple of posts from 3 years ago which still ring true:
And some truths from elsewhere:

What Girls Want

I always enjoy reading Caitlin Flanagan's articles in The Atlantic (and anywhere else I find them). I just read another of her wonderful Atlantic articles: What Girls Want. The article wraps a discussion of the Twilight books around a wonderful view into the lives and interior lives of adolescent girls. As the father of a two daughters (and a son), this article, like the others, is helpful, moving, and thought-provoking.
Thanks, Caitlin!

Over engineered vs Social engineered

Social engineering is when you use social techniques to achieve an engineering goal. It is a term mostly used in the technology commnuity to refer to ways to breach computer security systems. I call you up, sound officious (my British accent helps), and assure you I am calling to help you. There have been some suspicious activities on your credit card recently and would you mind reading the three digit security number off the back of the card to verify you still have it in your possession.

I have easily accomplished with social engineering something I could do with much more effort using a key logging program - a program similar to a computer virus that records what you type keystroke-by-keystroke, and sends me the results so I can pick out those magical three digits.

In my venture capital life we often hear about highly engineered, possibly over-engineered, technologies. Compared with other technologies they are clearly masterpieces. Compared with the ability of the human mind to be tricked (positively or negatively), they may not be worth the Powerpoint program they were conceived on.

It is not even clear to me that these guys would need the drugs!

Happiness is a Serious Problem

Over the winter break I read Happiness is a Serious Problem by Dennis Prager. I forget who recommended it to me (will that person please stand up and take a bow), but it is a great read.

Prager begins by asserting that being happy is a moral obligation. He asks us to think about how we feel when our spouse, children and parents are happy: we feel happier. We want them to be happy, and they want us to be happy. It is our moral obligation to those we care about to increase their happiness, and not decrease it. Being happy ourselves is a keystone of that obligation. Somewhere in the book he reports on a study that an unhappy interaction reduces the other person's happiness by 7%, but a happy interaction increases it by 9%.

It turns out that my discussion of happiness and purpose (from August 2006) echoed Prager's chapter 20, "Meaning and Purpose". I had homed in on exactly the idea Prager wrote about in chapter 21 "Happiness is a by-product", where his footnote reads:
Ask parents today what they most want for their children, and the vast majority of them will tell you that they want their children to be happy. As well intentioned as this is, by making happiness the greatest value in their children's lives, these parents are, unfortunately, making it far harder for their children to be happy adults. Parents who want their children to be happy but who raise them to believe that some values are even higher than happiness are more likely to raise happy children.
The book is less trite than the title, or the themes I mention, might suggest. There are some ideas which are compelling, and not so hard to adopt, and there is no dodging the causes and depth of real unhappiness in the world, including in the lives of the materially comfortable.

Many of you may have read about the country of Bhutan and its measurement each year of Gross Domestic Happiness. In these current times of falling GDP and general economic malaise, thinking about our overall happiness rather than our overall wealth is no bad thing.

Have a happy week.