On intelligence, stupidity, and music

This weekend I read three very different books on the human mind and brain.
Jeff Hawkins On Intelligence poses a speculative theory about how the neocortex works. Hawkins asserts that the distinctive aspect of human intelligence is that it allows us to make predictions. Based on a few strands of previous research, some insight, and aggressive reverse engineering, Hawkins proposes a neural architecture that enables humans to generalize patterns from raw sensation, allowing us to predict the next notes of a familiar song and to extend knowledge with analogies.
The hypothesis about how the neocortex works is interesting. The way that it proposes the generation of predictions by a combination of top-down and bottom up feedback is clever. The observation that sense-making requires a dimension of time — not just music, but touch and sight — is insightful. Unlike the evolutionary hypothesis of say, Terrence Deacon on the origins of symbolic thinking, Hawken’s algorithm is testable. However, Hawkins’ understanding of intelligence leaves out some crucial factors. Hawkins is interested in the mind as disconnected from emotions and desires. He believes that computers that have predictive intelligence without ambition, lust or greed will have the good of human intelligence, without the flaws introduced by the passions.
This dualistic vision ignores the insights of Antonio Damasio, a neurologist whose theory of intelligence embraces the emotions. Damasio observes patients with injuries to emotional processing, and finds that they lack the senses of fear and anticipation that enable people to make functional decisions. A lack of normal empathy prevents someone from getting along with other people. A computer that implemented predictive learning without emotions might be some combination of sociopathic and unwise. A computer that implemented learning without boredom and forgetting might not even be optimally effective at synthesis.
Hawkins focuses on the connections between neocortex and senses, but ignores the connections between neocortex and emotional parts of the brain. The neuroscience bits of Deacon’s book explain how in humans, the connections between the limbic system and the neocortex became intertwined as humans evolved. There’s a biological basis to Damasio’s observation that emotions are part of intelligence.
Where Hawkins focuses on human intelligence as a superb prediction engine, Gary Marcus focuses on the flaws and glitches in human smarts in areas such as decision-making, language, pleasure-seeking, and mental illness. In Kluge, the Haphazard Construction of the Human Mind, Marcus counters against evolutionary and anti-evolutionary arguments that the human mind reflects the best of possible worlds. Instead, the mind is a hodgepodge awkwardly cobbled together.
We don’t do a good job of making decisions about financial risk, or resisting temptation, because of our biological tendency to maximize short-term gain. Here, Markus shares a bias with Hawkins, that reason would result in better outcomes. But if you eliminated the motivations of hope, greed and fear, a rational being might not take the risks that drive good as well as bad aspects of human society.
Marcus points out the ambiguities in human language as a sign of the awkward results of evolution assembling a speech system from older parts. Here, what Marcus sees as a bug, Hawkins might see as a feature or at least a side effect. Ambiguity in language is a result of the generalizing, pattern-matching engine that drives human intelligence. The same design that makes it hard for us to remember details makes it possible for us to recognize and create new patterns.
Marcus’ book is flawed because he compares workings of the human brain with a straw man that has perfect reason. The interesting thing is not how the human mind is perfect, or how it breaks, but why it works the way it does, and how the way things break shows the way things work most of the time.
This is the focus of Oliver Sachs’ Musicophilia. Where Hawkins and Marcus are theorists, Sachs is an anecdotalist. He tells story after story of individuals who gained heightened musical abilities, or diminished musical abilities, due to changes in the brain. The stories themselves are fascinating but have little theory to explain why most humans are attracted to music, or to explain the aspects of the brain that govern parts of musical appreciation and skill.
Reading Musicophilia alongside Hawkins, it makes sense that music plays on the human mind’s attraction to structure and mild surprise. The recent advances in therapies depending on neuroplasticitity are also nicely explained with a theory of how the neocortex is designed for continuous learning. The stories of how memory of musical performance and sequence is retained in patients who can’t store new memories can be explained by a theory that old memories and learned processes are storied differently than new stuff.
Summary recommendations, for Peterme.
* I liked On Intelligence. Some reviewers give Hawkins grief because he brings very little evidence of the neurological or biohistorical basis of his speculations. He was frustrated by the lack of academic support for the kind of science he wanted to do as a younger man; and so he thumbs his nose at the establishment and its puny traditions of supporting arguments. Nevertheless, his argument is testable, so evidence will win in the end. The bigger weakness is his discounting of the role of emotion in intelligence.
* I didn’t like Kluge. I thought it was much weaker than Marcus’ earlier books, which had a stronger grounding in scientific detail, melding infant development, evolutionary developmental biology, and computer modeling. In his earlier books, Marcus built interesting arguments about brain development from rich evidence. This book has some interesting anecdotes, but is mostly a polemic against some common fallacies. The fact that the straw men are common doesn’t make debunking them more interesting; the book reads like he is arguing against poorly educated undergrads.
* I liked Musicophilia, despite its limitations. The book consists of anecdote after anecdote, without much connecting theory; but the stories are interesting, and it’s an entree onto some hopefully more robust studies on music, mind, and neuroplasticity.

Data Portability Summit: Data Sharing, Privacy and Context

At the Data Portability Summit, there was some excellent discussion about Data Sharing, Privacy and Context.
In conventional wisdom, data sharing and privacy are seen as black and white opposites. Everything is locked down, private, non portable. Or everything is open, public, and free-flowing. But data sharing and privacy are not black and white. In real life, people share and present information based on social context. There are gradations of privacy and information sharing.
Here are some of the stories we came up with regarding gradations of privacy and sharing. The ideas came from the session, plus pre- and post-conversations with Joseph Smarr and Thomas Vander Wal
Truly Private information
There are times when it is right to share data in a way that preserves privacy. Family members use different photo services, and want to share photos with each other but not the rest of the world. A group working on mergers and acquisitions absolutely needs to keep information confidential. In these cases one give permission to family, friends, or business associates based on membership in a group.
Signal to noise, social context
There are many circumstances where information isn’t truly private. But people choose to share with smaller groups. Someone doesn’t want to bore all of their friends with information about knitting or rock climbing, when that information is relevant only to a few. Information about one’s political or religious affiliation isn’t a secret, but it may not be the information one chooses to share when meeting new people at a professional conference. In these cases, it would be useful to have the ability to create tags for the relevant groups, and share by tag. The tags can capture the nuances of subgroups: knitting hats vs. knitting sweaters, say.
Progressive disclosure
There are circumstances when people want to start by sharing with a smaller group, and invite more people. Or start by sharing a little bit of information about common interest, and later share more sensitive information.
Stream filter
The signal to noise and progressive disclosure patterns are about the person sharing information. Stream filtering is for the recipient. Sometimes one wants to “people watch” a diverse stream of information. And sometimes one wants to focus on the current work project, or upcoming social events. Stream filtering is used by individuals who want to apply a context to the information they receive.
People use identifiers — dress or email address — to represent more than one persona. The same person wears different clothes, with co-workers, at a customer meeting vs. a barbecue.
Personal vs. organizational control
In organizations, there are some things that an individual may want to control, and some things that admins want to control. A person might want to share soccer pictures with the soccer league. An admin may want to ensure that people aren’t sharing the sports illustrated calendar widget.
Wiki notes on data sharing and privacy

Data Portability Summit: Everyone is famous

The session on data sharing and privacy was combined with Kevin Marks session on digital publics. We talked about people’s experiences handling the increased visibility of internet life.
Managing reputation
People share about their experiences in order to get their side of the story out and create a public image. Among digital natives, “it’s not a real breakup until you’ve listed it on facebook.
Handling fame
Before the internet, there were only a small number of people who had more followers than people can comfortably manage socially. Now many more people do. More widespread fame means that more people have the issues with stalkers and pestering fans.
Cautionary and instructive tales
At the session at the data sharing summit, the conversation turned to cautionary tales about social data sharing gone wrong.
Failed white lies
Someone begs out of a work-related social event by claiming the flu. His boss discovers a picture on flickr of the guy wearing a skirt and holding a drink. The picture is timestamped at the same data as the work party. His boss sends him a note suggesting that that may not be an effective way to recover from the flu. The lesson here is that some things that feel private are more public than we think.
Social network molting
It is socially awkward to unfriend people. Some people get around obsolete lists of friends by “forgetting” their password and needing to invite their current lists of friends with a new password. The lesson is that declared, public friends lists are in
The ex-girlfriend effect
The list of “people you should know” in social network recommendations often includes exes and enemies. These are people who are part of your social graph – but you are not connected to directly. In an organization, similar algorithms might locate internally competing projects. The algorithm doesn’t know that some gaps in the social graph are deliberate.

Recent Changes Camp: Media and Science progress toward open content

At Recent Changes Camp, I heard signs from two very different directions — fan fiction and biomedical research — that open content business models are finally reaching the mainstream.
Laura Hale of the Fan History Wiki talked about how, since 2005, big media companies have stopped harrassing independent fan groups with takedown notices and other threats. Instead, they have set up their own commercial fan hosting sites, and use those as a way to promote their brand’s content. Independent communities still exist. The big media companies can dismiss them as “unauthorized”. The indies think of themselves as un-coopted. The main story is, the business model has changed, and the media companies think of communities as ways to make money, and not worth legal prosecution.
Ehud Lamm, a researcher in the philosophy of science, shared that the NIH, after years of debate, had mandated that researchers taking NIH money must make their papers available to the public. This decision was ratified into law in December of last year. Since the NIH is a major funder of biomedical research, this will have a transformative affect.
When the internet reached the mainstream, models based on open access to content and active user communities became more powerful than models based on limited access to physical artifacts. It’s taken a decade for institutions and business models to adapt. But the times are changing, and the participants in wiki communities are seeing up close the results of the change.

Favorite things at Maker Faire

My favorite discovery at Maker Faire was the work of Daniel McCormick, a sculptor whose art helps restore rivers. His installations woven of willow branches are set into the banks of rivers, where they trap sediment and help recreate the meanders and eddies in eroded streams.

On a somewhat related note, I was glad to see that DIY food had started to colonize maker faire. As I munched on jessie cool’s asparagus, I listened to a talk on beekeeping and the environmental risks to bees, and admired the locavore cookbooks and composting worm bins which are ahead of my EQ at the moment.
McCormick lives and works in Marin. I hope the work that he does sets precedents, instead of creating a Disney-demo natural world in .000x of our landscape while big agriculture and poverty erode the rest. There has been really fascinating and inspiring progress in river restoration in recent years, but for each restored stream in Marin and NAPA, there are new CAFO lagoons wrecking more watersheds.
I also hope that the locavore movement sets precedents. The Chron had an excellent article about the rise and very minor successes of real food in the farm bill debate over the last year. On the plus side, it’s on the map, compared to a decade ago when it was fringe. Realignments at the congressional level take more than one cycle to build.
I enjoyed the Engineers Without Borders and the Appropriate Technology group (I think i’ve got the right link for them). These groups are using engineering engenuity to help people get clean water, food, electricity.
My favorite Maker Faire writeup is Liz Henry’s resolution to create disability access hacks project. Hopefully will get to see that next year!