Ethics has a bizarre blind spot around parents and children. For no justifiable reason that I can discern, we deem it perfectly tolerable for a parent to decide unilaterally to raise their child genderless or under the Tiger Mother or laissez-faire method of parenting, but horror at the idea of someone “testing” one of these parental styles on a child. Recall, there is no test to become a parent, no minimum qualification or form of licensing. In fact, if you are so irresponsible as to unintentionally have a child you do not want and cannot support, you have more of a right (and obligation) to rear that child than a stranger with the means and desire to give that child a better life.

We erroneously connect the ability to reproduce with the ability to rear in our social norms and in our laws. As adoption, IVF, sperm/egg donation and surrogate mothers along with new family structures challenge the concept that the person who provides the gametes or womb is also the person who will teach the child to ride a bicycle, we need to investigate the impact of perpetuating the idea that there is a link between reproducing and rearing.

I would like to test this reproduce-rearing correlation with a thought experiment. The details of the thought experiment appear below the fold, but the conclusion is as follows: it would be ethically permissible for a scientist to adopt a large group of children and then perform specific, non-harmful, nature-vs-nurture social experiments on those children. My idea comes from an interview by Charles Q. Choi at Too Hard for Science? with Steven Pinker about just such an experiment:

There is one morally repugnant line of thought Pinker strenuously objects to that could resolve this question. “Basically, every nature-nurture debate could be settled for good if we could raise a group of children in a closed environment of our own design, they way we do with animals,” he says. . .

“The biological basis of sex differences could be tested by dressing babies identically, hiding their sex from the people they interact with, and treating them identically, or better still, dividing them into four groups — boys treated as boys, boys treated as girls, girls treated as girls, girls treated as boys,” he notes. . .

“There’s no end to the ethical horrors that could be raised by this exercise,” Pinker says.

“In the sex-difference experiment, could we emasculate the boys at different ages, including in utero, and do sham operations on the girls as a control?” Pinker asks. “In the language experiment, could we ‘sacrifice’ the children at various ages, to use the common euphemism in animal research, and dissect their brains?”

“This is a line of thought that is morally corrosive even in the contemplation, so your thought experiments can go only so far,” he says.

So let’s test the limits of Pinker’s last line. Ethics is rife with and wrought by horrific thought experiments designed to out our biases and assumptions. And I intend to use a thought experiment to expose our bias that reproductive capacity equals rearing capacity. That is, merely because you can have a kid doesn’t mean you should be allowed to decide how to raise it. Using three scenarios, I’ll prove that a team of scientists adopting a large group of children with the dual intent of raising happy and healthy children while also conducting non-surgical or invasive sociological experiments would be ethically permissible.

The immediate objection against social experimentation on children is that the children would be used as mere means, as objects upon which theories can be tested. That claim is false. Unlike Pinker, I believe you can draw a distinction between the “closed environment” and “sacrificial” kind of experimentation in which, for example, a child is killed and dissected to determine the impact of language on brain formation and social experimentation. “Sacrificial” experimentation shows no concern or respect for the child as a human being and would meet the conditions necessary to be described as being used as “mere means” as Kant intends it. But “sacrificial” experimentation is a gross and barbaric example. Pinker also cites examples of surgical genital alteration and in utero experimentation. These are unacceptable forms of experimentation on a child because, again, the child is treated as mere means and would suffer as a result of the experimentation. I argue that if and only if the experiments to not cause physical damage or severe suffering to the child and that the child is raised in a nurturing, safe, and supportive environment, then it would be acceptable to conduct nature-vs-nurture experiments on children.

To defend my case, I ask you to consider the following three scenarios. We start with the least controversial, which I call the 100 Family Scenario:

1. In a community, there are 100 couples of equal income and education level, each with one biological child. Half the families have a boy, half a girl.
2. In this community, a third of families attempt to raise their children with current gender norms (i.e. boys play in pants with trucks, girls in dresses with dolls), a third attempt to reverse their child’s gender norms (i.e. boys in dresses with dolls, girls in pants with trucks), and a third attempt to raise their children to be neutral (boys and girls wear the same outfits and play with similar toys). The children all live in nurturing, safe, and supportive households.
3. There is no coordination among the families, these numbers are statistical happenstance. Furthermore, by coincidence the families are all vigilant about journaling, recording, and filming unbiased observations and data about their children as they grow up.
4. After 20 years, a team of sociologists collects this data and, upon analysis, uses it to publish a paper about the impact of nurturing environment on gender expression and sexual preferences.

We have no outright ethical problems with this scenario. The data collection and child distribution are all happenstance. No one would find a fault in any one of the above steps. It is true that this isn’t a “closed environment” the way Pinker described, but that would also be an incredibly harsh way to raise a child, raising all sorts of concerns about tainting the data. A controlled approximation of similar life-style among many families acts as a superior variable control than a highly unnatural, closed, laboratory environment.

Now let’s combine steps three and four, in the 100 Sociologist Biological Family Scenario:

1. In a community, there are 100 couples of equal income and education level and within each couple in the community there is at least one parent who is a sociologist. Each family has one biological child. Half the families have a boy, half a girl.
2. In this community, a third of families attempt to raise their children with current gender norms (i.e. boys play in pants with trucks, girls in dresses with dolls), a third attempt to reverse their child’s gender norms (i.e. boys in dresses with dolls, girls in pants with trucks), and a third attempt to raise their children to be neutral (boys and girls wear the same outfits and play with similar toys). The children all live in nurturing, safe, and supportive households.
3. There is no coordination among the families, these numbers are statistical happenstance. The sociologist parents are all vigilant about journaling, recording, and filming unbiased observations and data about their children as they grow up.
4. After 20 years, these sociologists coordinate, collect the data and, upon analysis, use it to publish a paper about the impact of nurturing environment on gender expression and sexual preferences.

Again, there seems to be no major ethical breach in how the data was collected or how the children were raised. Having parents who are sociologists is not an ethical violation. Now consider the final scenario, which I call the 100 Sociologist Adopted Family Scenario:

1. A group of sociologists who wish to start families coordinate to conduct a 20 year study in which they will collect data about children they raise and, upon analysis, use it to publish a paper about the impact of nurturing environment on gender expression and sexual preferences.
2. The sociologists form a community, there are 100 couples of equal income and education level and within each couple in the community there is at least one parent who is a sociologist. Each family has one legally adopted child. The community coordinates to ensure that half the families adopt a boy, half a girl.
3. In this community, a third of families attempt to raise their children with current gender norms (i.e. boys play in pants with trucks, girls in dresses with dolls), a third attempt to reverse their child’s gender norms (i.e. boys in dresses with dolls, girls in pants with trucks), and a third attempt to raise their children to be neutral (boys and girls wear the same outfits and play with similar toys). The children all live in nurturing, safe, and supportive households.
4. There is coordination among the families, the divisions among the children are the result of planning and adherence to scientific standards. The sociologist parents are all vigilant about journaling, recording, and filming unbiased observations and data about their children as they grow up.
5. After 20 years, these sociologists coordinate, collect the data and, upon analysis, use it to publish a paper about the impact of nurturing environment on gender expression and sexual preferences.

My argument here is not that the final scenario is ethically permissible or impermissible, but to show there is no difference between the scenarios. The intent to study the children does not impact their quality of life, how they grow up, or whether or not a paper is published about their rearing. Though the children are a means to studying the nature-vs-nature debate, that is not the sole or primary purpose of the sociologist families adopting their respective children. The parents wish to start families and also wish to study gender norms. The parents in the first scenario have as much parental sovereignty as the parents in the last. Thus, there are no relevant ethical differences between the first and the third scenarios. We only perceive a difference because the children are adopted, which is no basis for a relevant ethical difference. Therefore, if it is morally permissible for parents to independently decide how to raise their children in regards to gender, it should be morally permissible for a team of scientists to conduct a rigorous experiment with their own adopted children on the impact of rearing on gender and sexual preferences.

Follow Kyle on his personal blog, Pop Bioethics, and on facebook and twitter.

Image of a happy family with a “cloned” child (thank you photoshop) by madnzany under cc license via Flickr Creative Commons

Having robots with minds implementing the scientific process rather than math problem solving is essentially what’s happening in a few corners of robotics, most recently with the Xpero project, an effort to develop an embodied cognitive system that learns about its world much like an infant would. It’s one of a host of robo-infants being worked on (here’s a nice overview graphic). This approach has led to some very impressive achievements including an “evil starfish” robot that can quickly learn how to control its body after several of its “limbs” have been chopped off.

Hod Lipson (left) and yours truly pulling legs off the evil starfish in 2006.

In 2006, Hod Lipson and co-workers published a short paper with the sexy title “Resilient Machines Through Continuous Self-Modeling.” In it, he demonstrated how a small, starfish-like robot (aka, “the evil starfish”) could automatically learn its own body shape and movement capabilities. It did this through an automatic process of scientific inquiry. It worked something like this: first, make an arbitrary movement. What this means is that the robot sends out signals to its body, without knowing what those signals will do. While sending these movement signals out, the robot records sensory signals that tell it about what happened to the body due to that movement (scientific process analog: experiment). Second, generate a small number of models of the body that are compatible with movements resulting in the recorded sensory information (analog: hypothesis generation). Third, through some fast on-board simulation (aka, thinking), the robot figures out what movement(s) would give it the most information to distinguish between the different body models that are compatible with the information it has collected (analog: prioritizing hypotheses for testing). Fourth, the robot executes these movements, and uses the resulting sensory information for further refinement of its guess as to what its body is (analog: hypothesis testing and refinement).

What is great about this process, as I discovered when I visited Lipson’s lab some years ago to give a talk at Cornell, is that the robot has an amazing degree of robustness. The starfish robot shown in the photo has had one of its arms pulled off, and after a brief learning process, it figures out its new body shape and saunters off! It was slightly unnerving to witness this process. There is something about an animal recovering from damage that gives us a sense that it cares about its continued existence. In some sense, this is part of the essence of what it means to be a living organism: something that cares about its continued existence and acts so as to further that goal. When you see a machine act in this manner, it triggers certain associations that make it feel biological.

If indeed, as Alison Gopnik and others have argued, we all grow up absorbing all the important things we need to know through something like the scientific process, then the current work on making an algorithm that emulates the scientific process may be just the thing that AI needs for making breakthroughs on solving the problems we really want our robots to solve, such as making us a coconut mojito with just the right amount of muddled mint.

For more information on the European Xpero project, visit their website. A prior project, also EU-sponsored, was the iCub. A nice overview graphic of different robot infant approaches was in this July’s issue of IEEE Spectrum. Some interesting recent work on formalizing the discovery of regularities through experiments can be found in Hod Lipson’s “Selected Recent Publications.” Here is a thoughtful commentary on the starfish robot work by Chris Adami. Using data to automatically do science has also received attention in bioinformatics, most recently highlighted in articles about Sergey Brin’s datamining efforts to find a cure for Parkinson’s, in this podcast, and in academic circles here and here.

Image of robot in crib by Malcolm MacIver using free 3-D models on TurboSquid.

While I was still a doctoral student, I had the opportunity work with a relative of interactive holographics, 3D virtual reality data CAVEs. This particular one, at the National Center for Supercomputing Applications (NCSA) in Urbana Illinois (the birthplace of HAL) circa 1999, was a cube with back projection on five of the six walls. You wore a headset that tracked your head position and orientation, and goggles that were LCD screens that blocked images to your right eye when the projectors were rendering images for your left eye, and vice versa when the projector was displaying images for your right eye. As you walk through space or move your head, what you see in the virtual space changes as you would expect it to.

The problem that had pushed me to use this system was trying to analyze 3D motion data of a fish that I was conducting research on. I’d developed a motion capture system for the fish, which gave fantastic 3D data of the fish moving while it was attacking its prey, but looking at this 3D data on 2D computer monitors turned out to be quite difficult. Even replaying the motion from several different views didn’t quite do the trick. So Stuart Levy at NCSA put my data set into a system called “Virtual Director” and I was able to playback the data in the cave. It was something of an unbelievable experience the first time I tried it – suddenly I could walk around the animal as it engaged in its behavior, manipulate it to get any view, rotate the wand I held to wind the behavior forward or back at different speeds. Visitors particularly enjoyed my “Book of Jonah” demo where I positioned them so that they ended going into the mouth of the fish during a capture sequence.

For my technical problem, the VR CAVE was appropriate technology: 3D display and interaction for an inherently 3D data set. It helped me see patterns in the data that I had not clearly seen before, which were incorporated into some of my subsequent publications that analyzed the movement data. It was worth the effort, and the physicality of it was fine since I didn’t need to spend multiple days working through the data.

Other uses of these kinds of “direct manipulation” interfaces that mix 3D data and real world interaction have not found such a receptive audience, as people complain that it seems tiring to make sweeping (if dramatic) gestures to go through photos that would just as well be navigated through with an arrow key. As someone who still uses “vi” to edit my text with, I can relate to criticisms of interfaces that offer more than is needed.

The important question, for any given interface, is whether simplifies difficult problems of control or analysis, or gets in the way. My former colleague Don Norman at Northwestern University has contributed a great deal to our understanding of this question, in books like The Design of Everyday Things. One of my favorite examples from that book considers two different interfaces to manipulating the position of a car seat. In one interface, on a luxury American car, there is a panel of knobs and buttons almost hidden below the left side of the dashboard. To go from a state of discomfort to a new chair position requires translating your discomfort into a series of knob pulls and twists on a console of many controls with tiny labels below each. In contrast, a German luxury car had a small version of the driver’s chair in the dashboard. To move the back of your chair down, you manipulated the chair in the dashboard accordingly; to move it forward, you would move it in the direction the chair was facing, and so on. One interface placed a large cognitive load on the user to solve the discomfort problem, while the other placed minimal demands.

Another favorite example is the “speed bug” – a tab that a plane pilot puts on the edge of an airspeed indicator to mark the velocities for critical changes to shape of the wing. Were it not for those bugs, the pilot would have to remember the velocity to do the wing adjustments – and that’s not easy, because it changes with things like the weight of the plane.

The virtual fish, miniature car seat adjuster, and speed bug are all examples of interfaces that make problems easier, and in this sense, amplify our brain power. Interactive holographic interfaces can do the same for problems where space is a convenient or needed basis for navigating the information. This isn’t always apparent in sci-fi depictions of these interfaces, but their use speaks to our hope that such 3D holographic wizardry will help us cope with the flood of data we contend with on a daily basis.

The film raises the issue of how much we understand about the neuroscience of dreams. Due to its need for invasive experiments, neuroscience typically works with non-human animals, which raises a significant difficulty: how do you know that a rat is dreaming? You can’t wake it up from REM sleep and ask. (Well, you can, but don’t expect a cogent response.) There’s no accepted objective indicator that a person or animal is having a dream, as opposed to sleeping. But, we can still learn something useful by looking at the neuroscience of sleep.

The neuroscience of sleep has told us a few important things over the years. For example, we know that our pattern of sleep and wakefulness (the “circadian rhythm”) has much of its basis in the activity of the suprachiasmatic nucleus, a rice-grain-sized group of cells just above where the optic nerves from our eyes crossover. We know that our free running rhythm—what we go to if we are completely in the dark, with no indicator of solar activity—is slightly over 24 hours, and that the length of the rhythm can be affected by things like cannabinoids found in pot. We know that the brain activity of a person dreaming is very similar to that of an awake person—were it not for the fact that our body is paralyzed during dreaming, we’d probably do a lot of things we’d regret.

While we’ve made a lot of progress in understanding sleep, we’ve a long way to go to understand dreaming. What makes it a challenge, perhaps as big a challenge as understanding consciousness itself, is the subjective aspect of dreaming. For example, we know that vivid dreaming occurs during REM sleep in humans. We also know that other animals have REM sleep. Do they also dream? How can we know, since, as I mentioned above, we can’t wake them during REM sleep and ask (the way we determined this fact with humans)? How we can go from objective facts like the presence of REM sleep to subjective ones, like a dream of a pink elephant bouncing down along a high tension power line (from one of my own dreams) is as unclear as how we get from neurons firing to awareness. Nonetheless, significant work has occurred on some of the neuronal correlates of REM sleeping in rodents and songbirds.

The most intriguing result from recent work is that during sleeping, the brain appears to “play back” patterns of activity that occurred during the day. For example, Matt Wilson and colleagues have found that patterns of “place cell” activity — brain cells that light up, like crumbs left on Hansel and Gretel’s path in the woods, corresponding to a specific path that the animal (in these experiments, a rodent) took during the day — and this playback seems to be integral to the animal learning the path it took. In birdsong, from work by Dan Margoliash and others, we’ve learned that birds playback patterns of activity almost identical to singing while they sleep, and again, it seems to be integral to the bird learning its songs from its tutor. Why does the brain play back patterns of daytime activity at night? It isn’t completely understood, but some backstory on memory research helps motivate one hypothesis.

It’s been known for some time that a structure called the hippocampus is responsible for acquisition of new memories. Without it, we still have our memories, but anything new that happens is completely lost (think of the movie Memento, one of Christpher Nolan’s previous films) — we are stuck in the continual present. Real-life patient HM taught us this many years ago, after he had this structure removed as part of an experimental operation to cure his epilepsy. He, and many similar cases, lose all memory but for those events that happened some time before the loss of their hippocampus, typically a few months. Over time, the idea has emerged that perhaps the hippocampus “trains” the neural networks in other regions of the brain to store memories through repeated playback during sleep. Like crickets trying to attract females in the night, in the world of memory nothing succeeds like persistent repetition.

So if in REM sleep the brain is repeating patterns of activity from periods of wakefulness, perhaps that process helps the brain to remember, over the long term, the items that are temporarily stored in the hippocampus.

What is not understood from these studies, which were done in rodents and song birds after all, is the basis of all the strange subjective aspects of dreaming — such as how or why in our dreaming we seem to borrow from real experience while adding a good dollop of stuff from elsewhere. This aspect of dreaming seems like it would be crucial in order to have any hope of building a dream experience a la Inception. There is not a whole lot of creative potential in simply regurgitating the day’s brain patterns.

Until these and many other mysteries of dreaming are solved, what the research is showing is that the best way to architect a dream is to architect the experience you have during wakefulness, since dreaming appears to be a lot about learning patterns you were exposed to while awake. Our understanding of the coupling is not clear enough to think about designing dreams by structuring our awake behavior, but perhaps with further research we will come to that point where we can do inception of ideas into our own heads.

Image: Midlands Rat Club
Corrections: Aug 11, 2010: “…neuroscience typically works with animals, rather than humans…” adjusted to “…neuroscience typically works with non-human animals.” Reference to length of circadian rhythm also adjusted. Aug 12, 2010: “integral to the bird learning its large repertoire of over a million syllables” changed to “integral to the bird learning its songs from its tutor.”

These are remarkable effects with many potential implications, and applications (next time you’re trying to sell something, make sure you’re seated in a hard chair, and your buyer is in soft chair, for example; and clothes designers have a whole new dimension to consider). What is their underlying basis? The researchers hypothesize that our experiences with touch early in our development provides a scaffold for the development of conceptual knowledge. In adult life, these same touch experiences activate the scaffold in the same way, and lead to unconscious influences on our attitudes and decision making. The experience of weight gets metaphorically associated with seriousness and importance. Idioms like “that’s heavy” reflect this association. Similarly, rough textures get associated with difficulty, and we say “having a rough day.”

This research is another example of how the way we think is all wrapped up in the way we body. The new results add to our growing understanding of the ways in which embodiment and thought are more intertwined than was previously believed. The ways in which cognition is embodied was also the topic of a recent volume in the Cambridge Handbook series, called “The Cambridge Handbook of Situated Cognition”, which I had the pleasure of writing a chapter for.

Research into the ways in which cognition is intertwined with bodily experiences raise interesting issues regarding common science fiction fables and science fact predictions. Many of these hinge on being able to dispense with the body. The body, in this view, is just a convenient output device, easily replaced with another, or not replaced at all so as to be a disembodied intelligence like Hal of 2001. Our body is the computer, and who we are is the software, so if the hardware falls short we can just get new hardware. But what if who we are is this particular software running on this particular kind of hardware? The Cylons of Battlestar Galactica are an interesting mix of these ideas. They never died: as soon as their current body was eliminated, their consciousness was uploaded to another body. But they were not into body swapping: you got uploaded to the same body model, or not at all (aka, death), potentially compatible with embodiment ideas.

St. John the Baptist wearing a hairshirt, by Jacopo del Sellaio, 1485.

Number Six of Battlestar Galactica, a Cylon.

Moving on (and spoilers below). The linchpin of the episode was a character who, thanks to the experimental and fictional) Cortexifan treatment he received as a child, developed the ability to spread his emotions to people nearby. When he’s depressed and considering suicide, a nearby person might consider, say, jumping in front of the No. 7 Train (which is the most reliable train in New York. Again, just trying to be helpful here).  Obviously, here in the real world, emotions can’t be aggressively spread to random strangers…well, unless they’re looking at you…and talking to you… and generally interacting with you. OK, they can be spread to random strangers, just less strongly.

There’s a tower of research amply demonstrating that human groups respond to each other’s emotional moods.   We read other people for facial expressions, posture, and gestures and we respond by modifying our own responses to fit theirs. The tone and word selection of people we are talking to also influences our moods, especially when these people use strong negative terms like “hate” or “awful.” Recent research even shows that these emotional cues other people give off trigger different reactions in the parts of our brains that govern emotional response.

But those are all small group or person-to-person interactions. In December, Harvard and UC-San Diego scientists published findings showing that happiness can even spread across large groups. Their 20-year study of 4,739 people, they showed that happiness spread across different small group sub-units of the larger sample. A happy person could affect the moods of people with three degrees of separation.

But in Fringe we understand that the reverse-empathetic effect is caused by Cortexifan, an experimental drug from Walter Bishop. As yet, there are no drugs that amplify our ability to impose our emotions on others, but there’s a whole class of them that do amplify our ability to respond. Entactogens or empathogens (the debate rages over the proper name) are a whole class of drugs that improve our ability to empathize with those around us. The most famous member of this group, Ecstasy, has been heavily studied for its legendary ability to make people love one another, which is why it gets the fabulous nickname, the Hug Drug. You know when a nickname makes it’s way into scientific papers, it’s fabulous. Also, no longer cool. Again, just trying to help.

The ignorance of the population is actually the result of a deliberate decision by the city’s builders. In order to keep the population tucked safely away for 200 years, the builders decided to remove the temptation of the surface world by excluding any record of its existence–and to make sure curious inhabitants stay within the cavern, technologies such as batteries and candles are excluded as well, literally tethering would-be explorers to a power outlet.

In this City of Ember is exploring a problem that science-fiction writers have wrestled with for decades, and which real-life space agencies have realized they must also address. In a nutshell, the problem is that the type of people who build cities, or want to fly spaceships, are not the best suited to sitting around doing nothing. In science fiction, as with City of Ember, this often crops up on the level of entire societies: how do you keep a closed society from either outgrowing the capacity of the systems that sustain it, or maintain good mental health among those generations who are doomed to being just a link in a chain not of their own making? Harry Harrison’s 1969 book, Captive Universe, is probably the classic of this genre, set onboard a so-called Generation Ship (a spaceship that takes centuries to cross between stars, with several generations of passengers living and dying before it reaches its destination). For a modern twist, check out Greg’s Egan’s recent Incandescence, about a civilization that must eke out an existence within the confines of a planetoid orbiting close to a neutron star.

Space agencies haven’t got to point of worrying about Generation Ships, but they are getting worried about the psychological health of the crews that will one day explore Mars. Unless radical and unexpected improvements in propulsion technology happen, people who explore Mars will have to endure a many-month-long voyage from Earth (and an equally long return journey). The problem is that a crew composed of the hard-charging, driven, and competitive Type-A personalities that dominate today’s astronaut corps may not do well once cooped up onboard a spaceship for a few months–a more mellow personality may ultimately be more successful. As a result, space agencies and private organizations like the Mars Society are conducting simulations to find out what happens to people sealed up together in a few rooms for long periods of time, and what mix of personalities is most likely to prevent murder or mutiny in outer space.