Saturday, April 23, 2016

The Ethics of Intimate Surveillance (2): A Landscape of Objections

(Part One)

This is the second in a two-part series looking at the ethics of intimate surveillance. In part one, I explained what was meant by the term ‘intimate surveillance’, gave some examples of digital technologies that facilitate intimate surveillance, and looked at what I take to be the major argument in favour of this practice (the argument from autonomy).

To briefly recap, intimate surveillance is the practice of gathering and tracking data about one’s intimate life, i.e. information about prospective intimate partners, information about sexual and romantic behaviours, information about fertility and pregnancy, and information about what your intimate partner is up to. There are a plethora of apps allowing for such intimate surveillance. What’s interesting about them is how they not only facilitate top-down surveillance (i.e. surveillance by app makers, corporate agents and governments) but also interpersonal and self-surveillance. This suggests that a major reason why people make use of these services is to attain more control and mastery over their intimate lives.

I introduced some criticisms of intimate surveillance at the end of the previous post. In this post, I want to continue that critical mode by reviewing several arguments against their use. The plausibility of these arguments will vary depending on the nature of app or service being used. I’m not going to go into the nitty gritty here. I want to survey the landscape of arguments, offering some formalisations of commonly-voiced objections along with some critical evaluation. I’m hoping that this exercise will prove useful to others who are researching in the area. Again, the main source and inspiration for this post is Karen Levy’s article ‘Intimate Surveillance’.

1. Arguments from Biased Data
All forms of intimate surveillance depend on the existence of data that can be captured, measured and tracked. Is it possible to know the ages and sexual preferences of all the women/men within a 2 mile radius? Services like Tinder and Grindr make this possible. But what if you wanted to know what they ate today or how many steps they have walked? Technically this data could be gathered and shared via the same services, but at present it is not.

This dependency of these services on data that is and can be captured, measured and tracked creates problems. What if the data that is being gathered is not particularly useful? What if it is biased in some way? What if it contributes to some form of social oppression? There are at least three objections to intimate surveillance that play upon this theme.

The first rests on a version of the old adage ‘what gets measured gets managed’. If data is being gathered and tracked, it becomes more salient to people and they start to manage their behaviour so as to optimise the measurements. But if the measurements being provided are no good (or biased) then this may thwart preferred outcomes. For example, mutual satisfaction is a key part of any intimate relationship: it’s not all about you and what you want; it’s about working together with some else to achieve a mutually satisfactory outcome. One danger of intimate surveillance is that it could get one of the partners to focus on behaviours that do not contribute to mutually satisfactory outcomes. In general terms:

  • (1) What gets measured gets managed, i.e. if people can gather and track certain forms of data they will tend to act so as to optimise patterns in that data.
  • (2) In the case of intimate surveillance, if the optimisation of the data being gathered does not contribute to mutual satisfaction, it will not improve our intimate lives.
  • (3) The optimisation of the data being gathered by some intimate surveillance apps does not contribute to mutual satisfaction.
  • (4) Therefore, use of those intimate surveillance apps will not improve our intimate lives.

Premise (1) here is an assumption about how humans behave. Premise (2) is the ethical principle. It says that mutual satisfaction is key to a healthy intimate life and anything that thwarts that should be avoided (assuming we want a healthy intimate life). Premise (3) is the empirical claim, one that will vary depending on the service in question. (4) is the conclusion.

Is the argument any good? There are some intimate surveillance apps that would seem to match the requirements of premise (3). Levy gives the example of Spreadsheets — the sex tacker app that I mentioned in part one. This app allows users to collect data about the frequency, duration, number of thrusts and decibel level reached during sexual activity. Presumably, with the data gathered, users are likely to optimise these metrics, i.e. have more frequent, longer-lasting, more thrusting and decibel-raising sexual encounters. While this might do it for some people, the optimisation of these metrics is unlikely to be a good way to ensure mutual satisfaction. The app might get people to focus on the wrong thing.

I think the argument in the case of Spreadsheets might be persuasive, but I would make two comments about this style of argument more generally. First, I’m not sure that the behavioural assumption always holds. Some people are motivated to optimise their metrics; some aren’t. I have lots of devices that track the number of steps I walk, or miles I run. I have experimented with them occasionally, but I’ve never become consumed with the goal of optimising the metrics they provide. In other words, how successful these apps actually are at changing behaviour is up for debate. Second, premise (3) tends to presume incomplete or imperfect data. Some people think that as the network of data gathering devices grows, and as they become more sensitive to different types of information, the problem of biased or incomplete data will disappear. But this might not happen anytime soon and even if it does there remains the problem of finding some way to optimise across the full range of relevant data.

Another argument against intimate surveillance focuses on gender-based inequality and oppression. Many intimate surveillance apps collect and track information about women (e.g. the dating apps that locate women in a geographical region, the spying apps that focus on cheating wives, and the various fertility trackers that provide information about women’s menstrual cycles and associated moods). These apps may contribute to social oppression in at least two ways. First, the data being gathered may be premised upon and contribute to harmful, stereotypical views of women and how they relate to men (e.g. the ‘slutty’ college girl, the moody hormonal woman, the cheating wife and her cuckolded husband etc.). Second, and more generally, they may contribute to the view that women are subjects that can be (and should be) monitored and controlled through surveillance technologies. To put it more formally:

  • (5) If something contributes to or reinforces harmful gender stereotypes, or contributes to and reinforces the view that women can be and should be monitored and controlled, it is bad.
  • (6) Some intimate surveillance apps contribute to or reinforce harmful gender stereotypes and support the view that women can and should be monitored and controlled.
  • (7) Therefore, some intimate surveillance apps are bad.

This is a deliberately vague argument. It is similar to many arguments about gender-based oppression insofar as it draws attention to the symbolic properties of a particular practice and then suggests that these properties contribute to or reinforce gender-based oppression. I’ve looked at similar arguments in relation to prostitution, sex robots and surrogacy in the past. One tricky aspect of any such argument is proving the causal link between the symbolic practice (in this case the data being gathered and organised about women) and gender-based oppression more generally. Empirical evidence is often difficult to gather or inconclusive. This leads people to fall back on purely symbolic arguments or to offer revised views of what causation might mean in this context. A final problem with the argument is that even if it is successful it’s not clear what it’s implications are. Could the badness of the oppression be offset by other gains (e.g. what if the fertility apps really do enhance women’s reproductive autonomy)?

The third argument in this particular group is a little bit more esoteric. Levy points in its direction with a quote from Deborah Lupton:

These technologies configure a certain type of approach to understanding and experiencing one’s body, an algorithmic subjectivity, in which the body and its health states, functions and activities are portrayed and understood predominantly via quantified calculations, predictions and comparisons.
(Lupton 2015, 449)
The objection that derives from this stems from a concern about algorithmic subjectivity. I have seen it expressed by several others. The concern is always that the apps encourage us to view ourselves as aggregates of data (to be optimised etc). Why this is problematic is never fully spelled out. I think it is because this form of algorithmic subjectivity is dehumanising and misses out on something essential to the well-lived human life (the unmeasurable, unpredictable, unquantifiable):

  • (8) Algorithmic subjectivity is bad: it encourages us to view ourselves as aggregates of data to be quantified, tracked and optimised; it ignores essential aspects of a well-lived life.
  • (9) Intimate surveillance apps contribute to algorithmic subjectivity.
  • (10) Therefore, intimate surveillance apps are bad.

This strikes me as a potentially very rich argument — one worthy of deeper reflection and consideration. I have mixed feelings about it. It seems plausible to suggest that intimate surveillance contributes to algorithmic subjectivity (though how much and in what ways will require empirical investigation). I’m less sure about whether algorithmic subjectivity is a bad thing. It might be bad if the data being gathered is biased or distorting. But I’m also inclined to think that there are many ways to live a good and fulfilling life. Algorithmic subjectivity might just be different; not bad.

2. Arguments from Core Relationship Values
Another group of objections to intimate surveillance are concerned with its impact on relationships. The idea is that there are certain core values associated with any healthy relationship and that intimate surveillance tends to corrupt or undermine those values. I’ll look at two such objections here: the argument from mutual trust; and the argument from informal reciprocal altruism (or solidarity).

Before I do so, however, I would like to voice a general concern about this style of argument. I’m sceptical of essentialistic approaches to healthy relationships, i.e. approaches to healthy relationships that assume they must have certain core features. There are a few reasons for this, but most of them flow from my sense that the contours of a healthy relationship are largely shaped by the individuals that are party to that relationship. I certainly think it is important for the parties to the relationship to respect one another’s autonomy and to ensure that there is informed consent, but beyond that I think people can make all sorts of different relationships work. The other major issue I have is that I’m not sure what a healthy relationship really is. Is it one that lasts indefinitely? Can you have a healthy on-again off-again relationship? Abuse and maltreatment are definite no-gos, but beyond that I’m not sure what makes things work.

Setting that general concern to the side, let’s look at the argument from mutual trust. It works something like this:

  • (11) A central virtue of any healthy relationship is mutual trust, i.e. a willingness to trust that your partner will act in a way that is consistent with your interests and needs without having to monitor and control them.
  • (12) Intimate surveillance undermines mutual trust.
  • (13) Therefore, intimate surveillance prevents you from having a healthy relationship.

The support for (12) is straightforward enough. There are certain apps that allow you to spy on your partner’s smartphone: see who they have been texting/calling, where they have been, and so on. If you use these apps, you are clearly demonstrating that you are unwilling to trust your partner without monitoring and control. So you are clearly undermining mutual trust.

I agree with this argument up to a point. If I spy on my partner’s phone without her consent, then I’m definitely doing something wrong: I’m failing to respect her autonomy and privacy and I’m not being mature, open and transparent. But it strikes me that there is a deeper issue here: what if she is willing to consent to my use of the spying app as gesture of her commitment? Would it still be a bad idea to use it? I’m less convinced. To argue the affirmative you would need to show that having (blind?) faith in your partner is essential to a healthy relationship. You would also have to contend with the fact that mutual trust may be too demanding, and that petty jealousy is all too common. Maybe it would be good to have a ‘lesser evil’ option?

The other argument against intimate surveillance is the argument from informal reciprocal altruism (or solidarity). This is a bit of a mouthful. The idea is that relationships are partly about sharing and distributing resources. At the centre of any relationship there are two (or more) people who get together and share income, time, manual labour, emotional labour and so on. But what principle do people use to share these resources? Based on my own anecdotal experience, I reckon people adopt a type of informal reciprocal altruism. They effectively agree that if one of them does something for the other, then the other will do something else in return, but no one really keeps score to make sure that every altruistic gesture is matched with an equal and opposing altruistic gesture. They know that it is part of their commitment to one another that it will all pretty much balance out in the end. They think: “we are in this together and we’ve got each other’s backs”.

This provides the basis for the following argument:

  • (14) A central virtue of any healthy relationship is that resources are shared between the partners on the basis of informal reciprocal altruism (i.e. the partners do things for one another but don’t keep score as to who owes what to whom)
  • (15) Intimate surveillance undermines informal reciprocal altruism.
  • (16) Therefore, intimate surveillance prevents you from having a healthy relationship.

The support for (15) comes from the example of apps that try to gamify relationships by tracking data about who did what for whom, assigning points to these actions, and then creating an exchange system whereby one partner can cash in these points for favours by the other partner. The concern is that this creates a formal exchange mentality within a relationship. Every time you do the laundry for your partner you expect them to do something equivalently generous and burdensome in return. If they don’t, you will feel aggrieved and will try to enforce their obligation to reciprocate.

I find this objection somewhat appealing. I certainly don’t like the idea of keeping track of who owes what to whom in a relationship. If I pay for the cinema tickets, I don’t automatically expect my partner to pay for the popcorn (though we may often end up doing this). But there are some countervailing considerations. Many relationships are characterised by inequalities of bargaining power (typically gendered): one party end’s up doing the lions share of care work (say). Formal tracking and measuring of actions might help to redress this inequality. It could also save people from emotional anguish and feelings of injustice. Furthermore, some people seem to make formal exchanges of this sort work. The creators of the Beeminder app, for instance, appear to have a fascinating approach to their relationship.

3. Privacy-related Objections

The final set of objections returns the debate to familiar territory: privacy. Intimate surveillance may involve both top-down and horiztonal privacy harms. That is to say, privacy harms due to the fact that corporations (and maybe governments) have access to the data being captured by the relevant technologies; and privacy harms to due to the fact that one’s potential and actual partners have access to the data.

I don’t have too much to say about privacy-related objections. This is because they are widely-debated in the literature on surveillance and I’m not sure that they are all that different in the debate about intimate surveillance. They all boil down to the same thing: the claim that the use of these apps violates somebody’s privacy. This is because the data is gathered and used either without the person whose data it is consenting to this gathering and use (e.g. facebook stalking), or with imperfect consent (i.e. not fully informed). It is no doubt true that this is often the case. App makers frequently package and sell the data they mine from their users: it is intrinsic to their business model. And certain apps — like the ones that allow you to spy on your partner’s phone — seem to encourage their users to violate their partner’s privacy.

The critical question then becomes: why should we be so protective of privacy? I think there are two main ways to answer this:

Privacy is intrinsic to autonomy: The idea here is that we have a right to control how we present ourselves to others (what bits get shared etc) and how others use information about us; this right is tied into autonomy more generally; and these apps routinely violate this right. This argument works no matter how the information is used (i.e. even if it is used for good). The right may need to be counterbalanced against other considerations and rights, but it is a moral harm to violate it no matter what.

Privacy is a bulwark against the moral imperfection of others: The idea here is that privacy is instrumentally useful. People often argue that if you are a morally good person you should have nothing to hide. This might be true, but it forgets that other people are not morally perfect. They may use information about you to further some morally corrupt enterprise or goal. Consequently, it’s good if we can protect people from at least some unwanted disclosures of personal information. The ‘outing’ of homosexuals is a good example of this problem. There is nothing morally wrong about being a homosexual. In a morally perfect world you should have nothing to fear from the disclosure of your sexuality. But the world isn’t morally perfect: some people in some communities persecute homosexuals. In those communities, homosexuals clearly should have the right to hide their sexuality from others. The same could apply to the data being gathered through intimate surveillance technology. While you might not being doing anything morally wrong, others could use the information gathered for morally corrupt ends.

I think both of these arguments have merit. I’m less inclined toward the view that privacy is an intrinsic good and necessarily connected to autonomy, but I do think that it provides protection against the moral imperfection of others. We should work hard to protect the users of intimate surveillance technology from the unwanted and undesirable disclosure of their personal data.

Okay, that brings me to the end of this series. I won’t summarise everything I have just said. I think the diagrams given above summarise the landscape of objections already. But have I missed something? Are there other objections to the practice of intimate surveillance? Please add suggestions in the comments section.

Friday, April 22, 2016

New Podcast - Ep 1 Tal Zarsky on the Ethics of Big Data and Predictive Analytics

I've started a new podcast as part of my Algocracy and Transhumanism project. The aim of the project is to ask three questions:

  • How does technology create new governance structures, particularly algorithmic governance structures?
  • How does technology create new governance subjects, particularly through the augmentation and enhancement of the human body?
  • What implications does this have for our core political values such liberty, equality, privacy, transparency, accountability and so on?

The first episode is now available. I interview Professor Tal Zarsky about the ethics of big data and predictive analytics. You can download here or listen below. I will add iTunes and Stitcher subscription information once I have received approval from both.

Show Notes

  • 0:00-2:00 - Introduction 
  • 2:00-12:00 - Defining Big Data, Data-Mining and Predictive Analytics 
  • 12:00-17:00 - Understanding a predictive analytics systems 
  • 17:00 - 21:30 - Could we ever have an intelligent, automated decision-making system? 
  • 21:30 - 29:30 - Evaluating algorithmic governance systems: efficiency and fairness 
  • 29:30 - 36:00 - Could algocratic systems be less biased? 
  • 36:00 - 42:00 - Wouldn't algocratic systems inherit the biases of programmers/society? 
  • 42:00 - 54:30 - The value of transparency in algocratic systems
  • 54:30 - 1:00:1 - The gaming the system objection   


Thursday, April 21, 2016

The Ethics of Intimate Surveillance (1)

'Intimate Surveillance’ is the title of an article by Karen Levy - a legal and sociological scholar currently-based at NYU. It shines light on an interesting and under-explored aspect of surveillance in the digital era. The forms of surveillance that capture most attention are those undertaken by governments in the interests of national security or corporations in the interests of profit.

But ‘smart’ technology facilitates other forms of surveillance . One particularly interesting form of surveillance is that relating to our intimate lives, i.e. activities associated with dating and mating. There are (or have been) a plethora of apps developed to allow us to track and quantify data associated with our intimate activities. Although many of these apps have a commercial dimension — and we shouldn’t ignore that dimension — users are primarily drawn to them for personal and interpersonal reasons. They think that accessing and mining intimate data will enhance the quality of their intimate lives. But are they right to think this?

That’s the question I want to answer over the next two posts. Levy’s article does a good job sketching out the terrain in which the conversation must take place, and so I will follow her presentation closely in what follows, but I want to add a layer of philosophical formalism to her analysis. I start, in this post, by sketching out the different forms of surveillance and explaining in more detail what is interesting and significant about intimate surveillance. I will follow this with some examples of intimate surveillance apps. And I will close with what I take to be the core argument in favour of their use. I’ll postpone the more critical arguments to part two.

1. The Forms of Intimate Surveillance
I have thrashed out the concept of surveillance many times before on this blog. In particular, I’ve looked at the frameworks developed by David Brin and Steve Mann to distinguish surveillance from sousveillance. Here, I want to develop a slightly different framework. It starts with a simple and intuitive definition of surveillance as the practice of observing and gathering data about human beings and their activities. I guess, technically, the concept could be expanded to include gathering data about other subjects, and if you wanted you could insist that data analysis and mining is part and parcel of surveillance, but I won’t insist on those things here. I don’t think we need to be overly formal or precise.

What’s more important are the forms of surveillance. What I mean by this is: who exactly is gathering the data? About whom? And for what purpose? Steve Mann might insist that the word ‘surveillance’ has a particular form built into its etymology: ‘sur’-veillance is monitoring and observation from above, i.e. from the top-down. As such, it is to be contrasted with other forms of ‘veillance’, such as ‘sous’-veillance, which is monitoring from below, i.e. from the bottom-up. This can be a useful distinction, but it does not exhaust the possibilities. In fact, we can distinguish between at least four different forms of ‘veillance’:

Top-down Veillance: This is where data is being gathered by socially powerful organisations about their subjects. The most common practitioners of top-down monitoring are governments and corporations. They gather information about their citizens and customers, usually in an effort to control and manipulate their behaviour in desired directions.

Bottom-up Veillance: This is where data is being gathered about socially powerful organisations by their subjects. For example, the citizens in a state could gather information about police abuse of minority populations by recording such abuse on their smartphones. Brin and Mann believe that bottom-up monitoring of this sort is the key to creating a transparent and fair society in the digital age.

Horizontal Veillance: This is where data is being gathered by individuals about other individuals (at roughly the same scale in a social hierarchy). Humans do this all the time through simple observation and gossip. We seem to have strong desire to know more about our social peers. Technology fuels this desire by providing additional windows into their lives.

Self-veillance: This is where data is being gathered by individuals about themselves. It is common enough for us to monitor our own activities. But modern technologies allow us to gather more precisely quantified data about our own lives, e.g. number of steps walked, average heartbeat, hours of deep sleep, daily work-related productivity (emails answered, words written, sales made etc.).

So where does intimate surveillance fit into this schema? Intimate surveillance involves the gathering of data about our romantic and sexual lives. Technically, intimate surveillance could span all four categories, but what is particularly interesting about it is that it often takes the form of horizontal or self-veillance. People want to know more about their actual and potential intimate partners. And they want to know more about their performance/productivity in their intimate lives. This is not to discount the fact that the digital tools that enable horizontal and self-veillance also enable top-down veillance, but it is to suggest that the impact of intimate surveillance on how we relate to our intimate partners and how we understand our own intimate lives is possibly the most significant impact of this technology. At least, that’s how I feel about it.

2. Technologies of Intimate Surveillance
So how does intimate surveillance work? What kinds of information can we gather about our intimate lives? What apps are available to do this? Levy suggests that we think about this in relation to the ‘life-cycle’ of the typical relationship. Of course, to suggest that there is a typical life-cycle to a relationship is a dangerous thing — relationships comes in many flavours and people can make different patterns work — nevertheless there do seem to be three general stages to relationships: (i) searching; (ii) connecting and (iii) committing (with breakdown/dissolution being common in many instances too).

Different kinds of data are important at the different stages in the life-cycle of a relationship, and different digital services facilitate the gathering of that data. In what follows, I want to give more detailed characterisations of the three main stages in a relationship and explain the forms of surveillance that take place at those stages. Levy’s paper is filled with examples of the many apps that have been developed to assist with intimate surveillance. Some of these apps were short-lived; some are still with us; others have, no doubt, been created since she published her article. I won’t review the full set here. I’ll just give some choice examples.

Searching: This is when we are looking for someone with whom to form an intimate connection. We usually don’t want to do this in a reckless fashion. We want to find someone who is suitable, shares our interests, to whom we are attracted, is geographically proximate, doesn’t pose a risk to us and so on. This requires some data gathering. Various apps assist with this. Two examples stick out from Levy’s article:
Tinder/Grindr: These are apps allows you to find people in your geographical locale. You set the parameters on what you are looking for (age range, how close etc) and then you can search through profiles matching those criteria and ‘like’ them. If the other person likes you too, you can make a connection. Note how this is unlike traditional online dating services like or eHarmony. Those services tried to do the searching for you by using a complex algorithm to match you to other people. Tinder/Grindr are much more self-controlled: you set the parameters and surveil the data.
Lulu: This is an app that allows female users to evaluate male users. It works kind of like a tripadvisor for men where women are the reviewers. They rate the men on the basis of romantic, personal and sexual appeal. This allows for women to gather and share information about prospective intimate partners. It is mainly targeted at undergraduate college students.

Connecting: This is when we actually make an intimate connection. Obviously, intimate connections can take a variety of forms. Two main ones are of interest here: (i) sex and (ii) romance. A variety of apps are available that allow you to track and gamify your sexual and romantic performance. Again, I’ll use two examples:
Spreadsheets: This bills itself as a ‘sex improvement’ app. It enables you to record how frequently you and your partner have sex. It also records how long each sexual encounter lasted, the number of ‘thrusts’ that took place, and the moans and groans (decibel level reached). The dubious assumption here being that these metrics are useful tools for optimising sexual performance.
Kahnoodle: This (defunct) app tried to gamify relationships. It allowed partners to rank ‘love signs’ from one another that would then earn them kudos points. Once they accumulated enough points they could be redeemed for ‘koupons’ and other rewards.
With the rise of wearable tech and the development of new more sophisticated sensors, the number of apps that try to gamify our sexual and romantic lives is likely to increase. Apps of this sort explicitly or implicitly include behaviour change dimensions, i.e. they try to prompt you to alter your romantic and sexual behaviours in various ways.

Committing: This when we have made a connection and then try to commit to our partner(s). Again, commitment can take different forms and partners often determine the parameters of commitment for themselves (e.g. some are comfortable with open relationships or polyamorous relationships). For many, though, commitment comes with two main concerns: (i) fertility (i.e. having or not having children) and (ii) fidelity (i.e. staying loyal to your partner). Various apps are available to assist people in ensuring fertility (or lack thereof) and fidelity:
Glow: This is an app that tries to assist women in getting pregnant. It does this by allowing them to track various bits of data, including menstruation, position and firmness of cervix, mood, position during sexual intercourse. The related app Glow Nurture is focused on women who are actually pregnant and allows them to track pregnancy symptoms. Both apps have an interpersonal dimension to them: women are encouraged to share data with their partners; the partners are encouraged to provide additional data, and are then prompted to behave in different ways. The app makers have also partnered with pharmacies to enable refilling of prescriptions for birth control etc. (There were also a bunch of menstrual cycle apps targeted at men that were supposed to enable them to organise their lives around their partner’s menstrual cycle - most of these seem to be defunct, e.g. PMSBuddy and iAmaMan)
Flexispy: This is one of a range of apps that allow you to spy on other people’s phones and smart devices. Though this could be used for many purposes, it explicitly states that one of its potential uses is to spy on ‘cheating’ spouses. The app allows you to see pictures/videos, messages, location data, calendars, listen to phone calls and ‘ambient’ audio. As Levy puts it, with these kinds of apps we enter a much darker world of intimate surveillance.

I have tried to illustrate all these examples in the image below.

3. The Argument from Autonomy
By now you should have a reasonable understanding of how intimate surveillance works. What about its consequences? Is it a good or bad thing? It’s difficult to answer this in the abstract. The different apps outlined above have different properties and features. Some of these properties might be positive; some might be negative. To truly evaluate their impact on our lives, we would have to go through them individually. That said, there are some general arguments to be made. I’ll start with an argument in favour of intimate surveillance.
The argument in favour of intimate surveillance is based on the value of individual autonomy. Autonomy is a contested concept but it refers, roughly, to the ability to make choices for oneself, be the author of one’s own destiny, and perform actions that are consistent with one’s higher order goals and preferences. I suspect that the attraction of these surveillance apps lies predominantly in their perceived ability to enhance autonomy associated with intimate behaviour. They give us the information we need to make better decisions at the searching, connecting and committing phases. Through tracking and gamification they help us to avoid problems associated with weakness of the will and ensure that we act in accordance with our higher order goals and preferences.

Think about an analogous case: exercise-related surveillance. Many people want to be fitter and healthier. They want to make better decisions about their health and well-being. But they find it hard to choose the right diet and exercise programmes and stick to them in the long run. There is a huge number of apps dedicated to assisting people in doing this — apps that allow them to track their workouts, set targets, achieve goals, and share with their peers in order to stay motivated. The net result (at least in principle) is that they acquire greater control or mastery over their health-related destinies. I think the goal is similar in the case of intimate surveillance: the data, the tracking, the gamification allows people to achieve greater control and mastery over their intimate lives. And since autonomy is a highly prized value in modern society, you could argue that intimate surveillance is a good thing.

To set this out more formally:

  • (1) Anything that allows people to enhance their autonomy (i.e. make better choices, control their own destiny, act in accordance with higher-order preferences and desires) is, ceteris paribus, good.
  • (2) Intimate surveillance apps allow people to enhance their autonomy.
  • (3) Therefore, intimate surveillance apps are, ceteris paribus, good.

There are two main ways to attack this argument. The first is to focus on the ‘ceteris paribus’ (all else being equal) clause in premise (1). You might accept that autonomy is an important value but that it must be balanced against other important values (e.g. mutual consent, trust, privacy etc) and then show how intimate surveillance apps compromise those other values. I’ll be looking at arguments along those lines in part 2.

The other way to attack the argument is to take issue with premise (2). Here everything turns on the properties of the individual app and the dispositions of the person using it. I suspect the biggest problem in this area is with the surveillance apps that include some element of behaviour change, e.g. the sex and romance tracking apps described above. Two specific problems would seem to arise. First, the apps might make dubious assumptions about what is optimal or desirable behaviour in this aspect of one’s intimate life. The assumptions might be flawed and might encourage behaviour that is not consistent with your higher order goals and preferences. Second, and more philosophically-minded, by including behaviour prompts the apps would seem to take away a degree of autonomy. This is because they shift the locus of control away from the user to the behaviour-change algorithm developed by the app-makers. Now, to be clear, we often need some external motivational scaffolding to help us achieve greater autonomy. For instance, I need an alarm clock to help me wake up in the morning. But if our goal is greater autonomy, I would be sceptical of any motivational scaffolding that makes our choices for us. I think it is best (from an autonomy perspective) if we can set the parameters for preferred choices and then set up the external scaffolding that helps us satisfy those preferences. I worry that some apps try to do both of these things.
Okay, I’ll leave it there for today. In part two, I’ll consider a variety of objections to the practice of intimate surveillance.

Thursday, April 7, 2016

Blockchains and the Emergence of a Lex Cryptographia

Here’s an interesting idea. It’s taken from Aaron Wright and Primavera de Filippi’s article ‘Decentralized Blockchain Technology and the Rise of Lex Cryptographia’. The article provides an excellent overview of blockchain technology and its potential impact on the law. It ends with an interesting historical reflection. It suggests that the growth of blockchain technology may give rise to a new type of legal order: a lex cryptographia. This is similar to how the growth in international trading networks gave rise to a lex mercatoria and how the growth in the internet gave rise to a lex informatica.

Is this an idea worthy of our consideration? I want to investigate that question in this post. I’ll do so by explaining the rationale for Wright and de Filippi’s claim. I’ll start by going back to first principles and considering the nature of regulatory systems and the different possible forms of regulation. This will allow me to explain more clearly the proposed evolution to a lex cryptographia and the implications this might have.

1. The Nature of Regulation and Regulatory Systems
All human societies try to regulate the behaviour of their members. In simple terms, regulation is the biasing of behaviour. You want to encourage people to act in certain ways and discourage them from acting in other ways. You want to push them towards certain outcomes and pull them away from others. There are two main forms that this biasing can take:

Ex ante biasing: Guiding, directing and incentivising behaviour in advance.
Ex post biasing: Punishing or sanctioning behaviour that does not comply with preferred norms or standards of behaviour in order to encourage future compliance.

[This isn’t to rule out other potential purposes for punishment (such as retribution or revenge), it’s just to suggest that in the regulatory context the biasing function often takes precedence.]

How do we go about biasing people’s behaviour in the desired directions? What tools can we use? In his famous 1999 book - Code and Other Laws of Cyberspace, Lawrence Lessig argued that there were four main tools for regulation:

Architecture: Any natural or man-made structures that shape, constrain and/or permit certain forms of behaviour. Architectures are ubiquitous and are often the first and primary mode of regulation. Most of the other forms require some communication and/or signaling. Architectures don’t: they are structural limitations on possible forms of behaviour. For example, our biological architecture biases us in favour of breathing oxygen: if we didn’t we would die. Similarly, the construction of railroads permitted us to travel faster and further than we had gone before, but only along fixed tracks. The construction of the automobile and the building of modern roads allowed for additional but also limited possibilities. Technologies frequently create new possibilities for human behaviour and interaction, but those possibilities are controlled by the underlying architecture.

Social Norms: These are non-legal social standards, policed and enforced through peer pressure. A simple example would be table manners. There are all sorts of standards of behaviour for dining - these standards vary depending on the culture and the occasion. Formal dining has elaborate norms. You must hold your cutlery in a particular way; proceed through the courses in a particular order; fold your napkin just-so; be served by the waiting staff from a particular side; and so on. These behavioural standards are a creation of custom and social expectation. These forces create norms that govern many aspects of our lives. Failure to comply with these norms often leads to undesirable social repercussions: shunning, gossip, ridicule, mockery and so on.

The Market: Humans trade goods and services on markets. Markets then regulate human behaviour using a simple but often effective tool: They set prices. The prices bias human behaviour in various ways. Creators and suppliers are (usually) biased in favour of the goods and services that have the highest prices. Purchasers and demanders are (usually) biased in favour of those with the lowest prices. The market also disciplines behaviour: those who spend more than they take in are punished and disincentivised from continuing to do what led to that sad state of affairs.

Law: Most societies have a set of norms that are given a special social status. We call these norms ‘the law’. These are norms that are created and endorsed by recognised social authorities, and are usually enforced (ultimately) by the threat of violent coercion. In the modern world, it is governments and states that create these special social norms. They then use an elaborate institutional machinery to bias us in favour of compliance with those norms: police forces, courts, prisons and so on. [Note: I am aware that this assumes a potentially controversial, positivistic theory of law]

According to Lessig, these four tools exhaust the regulatory possibilities. How they are used by different societies, at different times, in response to different challenges, is the interesting thing.

2. Lex Mercatoria and Lex Informatica
The typical pattern over the course of human history has been that new technologies and new discoveries create new architectures. These architectures are the initial and primary regulatory tool: the only limit on behaviour is that provided by the architecture (and the conscience of those using it). Once the new architecture becomes widely available, the other regulatory tools flood-in and further constraints and limitations emerge. Users of the architectures adopt social norms to bias the behaviour of other users. If they exploit the architecture for financial gain, market norms emerge. Some tools are more effective than others. Ironically (given its special social status) legal regulation is often the last to flood into the new architecture and often simply codifies the pre-established norms.

Wright and De Filippi use two historical examples to illustrate this pattern.

The first example is the lex mercatoria. This was a set of (quasi?) legal norms that developed from trading networks in Europe during the middle ages. At the time, Europe was made up of small principalities and states. Within these principalities a local ruler had the authority to pass and create laws. However, merchants did business with people from outside the principalities. Indeed, trading networks were established that covered most of the continent. These networks constituted an architecture. The traders who operated in these networks needed some body of rules to regulate their behaviour. They could not rely on the local rulers to provide these rules since they only had authority within small geographical areas. So they developed them themselves. An impressive body of customary rules emerged that was known as the lex mercatoria. Over time, these rules became more formalised and started to be recognised by local legal systems (often because of tax benefits to the local rulers). That said, the relationship between the lex mercatoria and the local law was sometimes uneasy. Some argue that this is still the case: that there are norms and customs for international trade that constitute a modern day lex mercatoria, and that these norms have an uneasy relationship with national legal systems. You can read about this debate here.

The second example is the lex informatica. This was the set of norms that developed after the emergence of the internet. The internet created a new architecture for social interaction. People could communicate with one another in new ways — ways that minimised the relevance of traditional geographical and legal boundaries. It allowed them to engage in new methods of trade, to create and distribute new goods and services. In the early days, this architecture constituted something of a legal ‘wild west’. Users of the internet had to develop their own norms, relying heavily on private contractual methods such as End-User Licensing Agreements (EULAs). Because the internet wasn’t localised in any particular state or national legal system, these contractually established norms often ignored or supplanted pre-existing legal norms. Eventually, national and international legal regulations started to enter the new architecture, but there continues to be an uneasy relationship between these regulations and the lex informatica to this day.

The question now is whether the emergence of blockchain technologies gives rise to something similar - a lex cryptographia perhaps?

3. Lex Cryptographica: A New ‘Legal’ Order
This is what Wright and de Filippi suggest. To appreciate why they suggest this, you need to know something about blockchain technology. I have written two previous posts that try to explain how it works. I won’t go into the same depth here. Suffice to say, the blockchain is a distributed ledger that records and verifies transactional information (e.g. did X send money to Y; did Y receive it). The ledger (“the blockchain”) is maintained and stored on a network of computers. The network can be distributed over potentially any geographical area (anywhere with network connectivity). Every computer (or node) on the network stores a copy of the ledger. The network then verifies the transactional information using some sort of consensus or majority decision-making rule (e.g. does every computer on the network agree that X sent the money to Y? If so, the transaction is verified).

When explained in these terms, blockchain technology often seems unexciting, but that is far from the case. Any information that can be digitised and sent over a network can, in theory, be recorded and verified by the blockchain. With the growth of the internet of things, this means that the blockchain can be used to verify many different kinds of information and thereby regulate many different human interactions. As a regulatory mechanism, the blockchain has at least three interesting properties:

Decentralisation: The blockchain is set up and maintained by a decentralised network, not by any one individual or organisation. Indeed, one of the alleged virtues of the blockchain is its ability to breakdown the power of ‘trusted third parties’ in society, e.g. governments, banks, large corporations. You don’t need to trust these powerful organisations anymore; you just need to trust the network. This enables people to create their own bespoke blockchain-based regulatory architectures (“smart contracts”) for managing their relationships with other network users.

Encryption: The information that is recorded and verified by the blockchain is encrypted and hence, in principle if not in practice, anonymised. This is good for privacy and for facilitating ‘private ordering’ of how one relates to other users of the network, but means that it can be difficult for traditional legal systems to regulate these relationships.

Architecture-driven: Given the two preceding properties, the main regulatory tool in the case of the blockchain is the underlying technological architecture. What has the system been programmed do? What kinds of information will it receive and verify? How exactly will it verify it? How frequently? How will those who maintain the network be rewarded for their efforts? All these questions are answered at the level of coding. As a result, much of the regulation has to be baked-into the architecture of the system.

A lex cryptographia is likely to emerge from this. Users of these systems will develop norms that will be baked-into the programmes they develop on blockchain technology. How you feel about this largely depends on how you feel about traditional legal systems. Cyber-libertarians tend to love it. They think that the blockchain allows for the creation of self-governing communities that are outside the reach of the law. And since they think that state-driven law is basically evil, they also think we should welcome this new technological regulatory architecture. It is far more freedom-enhancing than what we currently have in place.

Others are less sanguine. They worry that the blockchain is technocratic and elitist. At present, relatively few people know how to create and code private regulatory architectures on the blockchain. How are they to make use of it? If they are not educated to develop their own architectures, they will have to rely on those with the relevant technical expertise. This would seem to create a new set of trusted third parties, with a lot of social power. And, as the old adage goes, power tends to corrupt.
The result is that some people would like for this new regulatory architecture to be brought within the reach of traditional legal systems. Is this possible? Wright and de Filippi argue that it probably is.

Traditional legal systems excel by (ultimately) using force or the threat of force to change how humans act. As long as these traditional legal systems can find the humans that run and operate the blockchain, they can use these tools to enact regulatory changes. What’s more, they don’t need to find everyone who runs and operates the blockchain. They just need to find the people that matter. Although the blockchain is, in theory, a decentralised network — and so, in theory, power is distributed across the network — the reality is that there are centralised “chokepoints” in the system. Internet service providers (ISPs) and other corporate intermediaries (e.g. software developers, hardware manufacturers) are such centralised chokepoints. They provide people with the technology they need to make use of the blockchain. If you bring the law to bear on them, it will be possible to bring some degree of legal regulation into the system.

It looks then like we could be heading for another uneasy relationship between our regulatory tools.

Wednesday, March 30, 2016

Informal Group Work in Class: Four Tips

Every year I start with the best of intentions. I promise myself that I will use more interactive methods of teaching in my classes; that I will incorporate group work into at least some of my lectures; that I will encourage students to collaborate and learn from one another; that I won’t simply lecture from the front of the class.

Every year I seem to fail. As the semesters drag on, I get increasingly discouraged from incorporating group work into my teaching. There are two main reasons for this. The first is that it is actually pretty hard to design effective group work exercises, particularly ones that work in the large classes I teach (sometimes with upwards of 150 students). As other pressures pile up during the course of a given year, I find I have less and less time to design such exercises and so I eventually stop using them. The other reason is that if the first attempts don’t go well, I tend to retreat to my comfort zone, which is to just lecture at groups of students. I’m particularly tempted by this retreat in the larger groups, where students are often more reluctant to cooperate and it can be difficult to manage and organise group-work.

But I don’t intend for this post to be a confessional — as cathartic as that may be. I’m saying all this merely to underscore the fact that I don’t think of myself as being good at using group-work in my own teaching. I struggle with it. But I want to learn how to get better. So I’m going to educate myself in public by reviewing some of the tips and tricks from James Lang’s book On Course: A Week-by-Week Guide to Your First Semester of College Teaching. Along with Ken Bain’s What the Best College Teachers Do, this is one of my favourite books on teaching: it is resolutely practical in its focus, but engages with just enough of the empirical and theoretical literature to give it a firm grounding.

In this post, I’ll focus on Lang’s tips for managing informal group-work in the classroom.

1. Defining Informal Group Work and Overcoming Resistance to It
I’ll start with some definitions. Lang draws a distinction between two kinds of group work:

Informal Group Work: This is where you form ad-hoc groups during a class session (lecture, seminar) and get them to perform some task within that class session. The task does not count towards their final grade.

Formal Group Work: This is where you form groups for the duration of a module and get them to perform some task (e.g. group report/presentation) that will require them to meet and coordinate their actions outside of class. The task will count towards their final grade.

The distinction is somewhat procrustean: you could have in-class tasks that count towards the final grade and out-of-class task that do not. But I think it is useful nonetheless. In this post, the focus is purely on informal group work. There are two reasons for this. It is the type of group work I am more interested in because it is the type I find most difficult to manage and incorporate into my teaching. Furthermore, formal group work has its own challenges — challenges that warrant independent consideration (Lang discusses those challenges in the book; I might do so on another occasion).

Before looking into the practicalities of informal group work, it is worth asking the question: why would you bother? This is something I often ask myself and my propensity to ask it probably drives some of my reluctance to use it in my classes. I am a very reclusive and independent-minded person. Although I do work with others, I generally prefer working by myself. When I was a student, I found that I learned far more by independent research and reading than I ever did in class or in conversation with others. Consequently, I used to dislike group work exercises, finding them to be a waste of time and effort. I still find this to be the case. I am currently taking a course on teaching and learning in higher education that features a good deal of informal group work. When engaging in this group work, I rarely find the exercises to be useful. At most, I think they break-up long class sessions and restore concentration.

One of the nice things about Lang’s book is that he recognises and responds to this sort of resistance to group work. Indeed, he suggests that it is very common among academics. On average, the people who become academics are the people who most enjoy learning via independent research and writing (possibly more true in certain humanities subjects than in the sciences). So, somewhat ironically, I may be part of a self-selecting group that is less receptive to this style of teaching. I shouldn’t take my own experiences to be representative of my students. Some people really do enjoy the collaborative mode of learning.

Lang offers three further reasons for adding group work to your classes:

A. Students will end up working in careers that require collaborative work so you may as well prepare them for it.
B. Studies (cited in Lang’s book) suggest that students retain more from collaborative exercises than they do from lecturing and, as a nice bonus, they tend to give better feedback.
C. Knowledge is collaborative anyway: it emerges from a consensus of peers. Group work adapts students to this view of knowledge.

I have mixed feelings about these reasons. There is something to be said for each of them. The first is certainly true: students will have to work in teams in pretty much any career they hope to enter. But I suspect formal group work is better at preparing them for this than informal group work. The second chimes with my experience. Even though I don’t always enjoy the informal group work I do as part of my current course, I do find that I remember some of the conversations I have had with other members of the class during such group work far better than I remember what was said by the lecturers. Furthermore, the student feedback I have received for my own courses suggests that they really do enjoy these kinds of exercises and do give better feedback when they are included. The third reason is too philosophically-loaded for me to accept in its current form. Suffice to say I think it gets at something true, but I doubt the value of informal group work in adapting students to this view.

Anyway, enough of the preliminaries. How do you successfully incorporate informal group work into your classes? Lang breaks it down into four main steps. They are illustrated in the diagram below. I will elaborate in the ensuing text.

2. The First Step: Develop the Task
The first step is to develop the task you are going to get the groups to perform. If they are going to be working together during class, then they better be working on something valuable and important. It is far too easy to fall into the trap of setting superficial tasks. I know I have fallen into this trap. You get students to discuss something among themselves for a few minutes, partly to break up the monotony of a lecture, and partly to delude yourself that you are including some meaningful group work into your teaching. This is not the right approach to take.

Effective in-class group work should be concrete and should require the students to produce some sort of definite output within the allotted time. Lang suggests that informal tasks should take a maximum of 20-30 minutes and should require students to produce some sort of written output. The written output need not be elaborate: a sentence or paragraph of text; a diagram; a list of keywords etc. You just need to have it so that their minds are focused on doing something particular. Without it, students might feel lost and temptated to distraction. He also suggests that the task might work best if it is divided into solitary and group work phases. In other words, you get students to work on their own initially and then, after a definite period of time, get them to work with the members of their group. This advice is echoed by many others (e.g. Eric Mazur in his ‘peer instruction’ model).

I think organising the task around some concrete written output is a good idea. My own forays into group work have foundered when I simply ask students to ‘debate’ or ‘discuss’ a topic among themselves. This often leaves them uncertain as to what they should be doing. My better attempts have required them to do something specific. For instance, one of my more successful informal group tasks required students to read a short article in advance of class and then identify the major premises and conclusions in the argument presented in that article in class.

With any task, the devil is going to be in the detail. What you want students to do will vary depending on the discipline and subject you teach, and the time at which you introduce the task. Very generally, Lang suggests that any task you might assign students for homework (or in my case for tutorial work) can be adapted for informal group work. Some examples include:

Getting the students to draw a diagram representing the relationships between the characters in a novel.
Getting the students to identify the major issues and areas of law raised by legal problem question (i.e. story about someone’s legal troubles).
Getting the student to identify and (if time permits) query the experimental protocol in a scientific paper.
[As I said above] Getting the students to identify the premises and conclusions in an argument presented in a passage of prose.

The latter of these is definitely my favourite type of task because I think it translates to many different disciplines. It also has natural ‘extensions’ built into it. I’ll come back to that later.

3. The Second Step: Form the Groups
Once you have developed the task (which should of course be done in advance of class) you then need to form the groups. There is a surprisingly large literature on the optimal way in which to form groups. Many authors recommend that you ensure diversity and balance within the groups. Lang suggests that this might be more appropriate when doing formal group work and I tend to agree. I think for informal group work you just want a method that won’t take up too much time. The two methods I use are:

Pairing: Get students to pair-up with the person sitting next to them or, if you want them to form larger groups, with the three or four people closest to them. This is the simplest and quickest method. I use it whenever time is at a premium (e.g. if the task I want them to perform should take no more than 5-10 minutes). Using a more elaborate method for short tasks seems counterproductive to me because you end up spending as much time forming the groups as they do performing the task. That said, pairing obviously has its drawbacks as it can lead to self-selecting groups.

Number Lottery: Go through each seated row of students and assign each student a number up to a given limit (e.g. 1, 2, 3, 4, 5….1, 2, 3, 4, 5). Once you have completed this for every student in the class, get them to pair up with those who were assigned the same number. This may be my favourite method of group formation as it has an air of randomness about it. I’ve often used it to establish formal groups too.

Lang suggests that groups shouldn’t be too large, four to five students max. I tend to agree that this is preferable. On a few occasions I have formed larger in-class groups (up to ten students) but it’s definitely messy and at that size it becomes too easy for individual students to hide (or free-ride) within the groups. I’m often tempted to do so because I teach large groups of students and if you limit group size to a maximum of 5 you can end up with a lot of groups (30 if your class is 150). This can be a bad thing if you want all the groups to feedback to the class as whole, but there are ways to avoid this problem (see step four, below).

4. The Third Step: Manage the Groups
Once you have formed the groups and explained to students the purpose of the task, you need to let them at it. At this point, you have to manage the groups to make sure they get some value out of the exercise. Lang suggests that you give them some space initially. Don’t be too eager to jump in and direct their conversations. This seems like obvious and sound advice to me. I like to hang back for the first few minutes of the group task and then go around to each individual group (if feasible) and see how they are getting on. But I think I am often too interventionist in this regard and that I tend to do the work for the students once I get involved. I’m going to try to be less interventionist in the future.

There are four main problems you can encounter at this stage in the process:

Silent Groups: Some groups might fall silent and be unsure about the task. You can usually set them right by clarifying the output they need to produce and by asking them more specific questions.

Silent Members within Groups: This is a common problem. Some students will take a back seat within their groups, allowing others to do most of the work. I’m unsure how important it is to address their silence. Sometimes it is driven by laziness or resentment; sometimes it is strategic. Certain people like to wait before offering their opinions. If you feel someone really is disengaging from the task, you can try to involve them by directing specific questions towards them (e.g. “What did you think of what student X just said?”), or by assigning them the role of official group recorder. This will force them to pay attention.

Off-track Groups: Inevitably, some students will be distracted from the assigned task and start talking about something that is off-topic. You can usually bring them back on track simply by hovering next to them, or by intervening and attempting to bring them back on track (which strategy is more appropriate depends on how exactly they have got off track).

Fast Groups: Some groups will finish the task with alarming rapidity. You can deal with them by planning for obvious extensions to the initial task. For instance, if you start by getting students to identify the premises and conclusions of an argument in a passage of prose, you can extend the task by asking them to evaluate individual premises or assess the logical strength of the argument. This is a natural (and oftentimes rich) extension and it is one of the reasons why I like this kind of task.

One other point, which I think is important, is that you should time the tasks appropriately. You should allot students enough time to complete the task but not too much that they are tempting to go off track. But once you have set the time limit, you should stick to it. It can be quite annoying to be told by a teacher that you will have 10 minutes for an exercise only for them to call a halt to it after 7 minutes because they get the ‘sense’ that everyone is done.

5. The Fourth Step: Process and Feedback
Once the allotted time has ended, and students have produced their definite output, you’ll need to process that output in some way and give some kind of feedback. The demand for this in informal group work is less stringent than it would be in the case of formal group work, but it is still important. It will help to combat the sense of pointlessness and futility that some students might feel when they are asked to engage in these tasks (remember: I tend to feel this when I’m asked to engage in them).

Lang suggests three simple methods for processing and giving feedback:

Group Reports: Get each group to report back to the class on the results of their discussion, then offer some comments and feedback. This is the simplest method of processing the outputs, but it has two major drawbacks: it can be overly time-consuming, particularly if you have a large number of groups; and it can be repetitive and boring if groups are all saying the same things. It really only works well if you have a small number of groups or if you randomly select a small number of groups.

Pump-priming: Use the group work as a way of ‘priming the pump’ for larger class discussions. In other words, the specific output should provide the students with the material they need to contribute to a broader discussion about the task (e.g. a discussion about the structure of the argument they were supposed to identify), once you start that discussion you just allow them to spontaneously add their contributions. I think this is nice when the stakes aren’t too high (as is usually the case with informal group work).

Follow-up Task: Use the group work as way of preparing for a follow-up task, one that you either get them to perform in-class or as homework/tutorial work.

In some disciplines, a very simple way to provide feedback is simply to provide students with the ‘answer’ to the question/task they were assigned. This allows them to check whether they were on the right track. Obviously, this only works where the discipline lends itself to such feedback. In mathematics, for instance, there will be definitive answers to a problem question. In law (which I teach) this isn’t really true, but oftentimes legal problem questions do lend themselves to general answer outlines that are more correct than other possibilities. Sketching those outlines for the students can help them to check their own progress with the material.

Anyway, those are all the tips on informal group work. Hopefully you find it to be of some use. Writing about it has been useful for me. It has enabled me to identify some of the flaws in my previous strategies and to reduce my own resistance to the practice.

Monday, March 28, 2016

The Evolution of Social Values: From Foragers to Farmers to Fossil Fuels

I was first introduced to the work of Ian Morris last summer. Somebody suggested that I read his book Why the West Rules for Now, which attempts to explain the differential rates of human social development between East and West over the past 12,000 years. I wasn’t expecting much: I generally prefer narrowly focused historical works, not ones that attempt to cover the whole of human history. But I was pleasantly surprised. Morris definitely has a knack for synthesising large swathes of historical data and presenting compelling explanatory narratives. I was particularly impressed by his social development index, a tool for measuring the historical level of social development across different human societies (something explained at great length in his book The Measure of Civilisation). I also enjoyed Morris’s futuristic leanings: he ended the book by speculating about future trends by drawing lessons from the historical ones.

Since my initial foray, I think I’ve read every one of Morris’s ‘popular’ books. His most recent one — Foragers, Farmers and Fossil Fuels — is probably my favourite. Although it may be the flakiest in terms of the empirical data used to back up its central thesis, it is nevertheless the one that comes closest to my own research interests. The book takes the standard Marxist view* — that social values are determined by material culture — and extends it in an effort to explain three different value systems that have dominated human history. The central thesis is that the values expressed and enforced by human societies are primarily a function of the techniques they use for energy capture. There have been three main techniques for energy capture over the course of human history — foraging, farming, and the use of fossil fuels — and hence three main value systems.

The thesis is simple in its general outline, but there is a great deal of complexity in its defence. Morris acknowledges that the three value systems he describes are ‘ideal types’. Actual historical human societies vary greatly in the particular values they express. Nevertheless, he maintains that these variations can be grouped into these general types — exceptions to the categories often tell us something important that reinforces the utility of the general category. And, as in his other books, the real strength of Morris’s work is his ability to assemble a wealth of data on the different types of society to back up his main claims. If you want a readable and well-researched overview of human social evolution, this is about as good a book as I have read on the topic. It also contains critical rejoinders to Morris’s claims, along with a further response by him, so it is not one-sided.

That’s all by way of introduction. In this post, I want to do something relatively modest. I want to describe the three main value systems that Morris identifies in the book. I cannot hope to do justice to the detail of Morris’s actual account — you will need to read the book for that — but I can hope to share what I think is an interesting way of categorising and understanding human society. This is a useful exercise for me because I am hoping to use some of Morris’s insights in my own work about future governance systems and their values (more on that another time). In what follows, I’ll go through each of the three types of society and describe their value systems.

1. Foraging Societies and their Values
Foragers capture energy by hunting and gathering. That is to say, they hunt and kill wild animals, and they gather wild plants. They then consume both to supply themselves with the calories they need to get through the day. They also use animal and plant products to build the shelters and clothes to enable them to survive in different climates. Foraging societies vary considerably (some ethnographers refer to the ‘foraging spectrum’) but most of the variation is explained by differences in geographical location. For example, in tropical climates, most energy is procured from plants; in colder, polar climates, animals are the main source of energy.

Foraging societies share a number of key features. They are generally small groups of people and they move about a lot. Modern foraging groups usually consist of tribes of up to around 500 people, but most individuals spend their days with two to eight closely related people (Morris 2015, 30-31). Foraging groups are close knit, linked by kinship relations. Foraging communities have very low population densities, typically less than one person per square mile. Foraging societies that buck these trends are able to do so because they live in regions of relative abundance, i.e. the local animal or plant population is sufficiently abundant to support larger groups of people.

What kinds of values do foraging societies have? Let’s start with a definition. For present purposes, I’ll define ‘values’ as biases in behaviour and understanding. This is a descriptive definition, not a normative one. A group of people can be said to value X if their behaviour is biased in favour of X, they try to punish or discipline people who deviate from X, and if they express approval or fondness for X. This descriptive approach to values fits with the perspective of Morris’s book. How do we know what foragers value? Morris admits that the evidence isn’t great. There are three main sources: (i) archaeological evidence, which is usually silent about values; (ii) ancient historical accounts, which are usually biased; and (iii) modern ethnographic studies. The latter are the best source of data but they have to be treated with some scepticism. Modern foraging societies have been exposed to farming and fossil fuel societies. This is likely to ‘contaminate’ the set of values they espouse. They are not like their historical predecessors who never encountered farming or fossil fuels.

With those limitations in mind, Morris investigates the values of foraging societies in four main domains: (i) attitudes toward violence; (ii) political inequality; (iii) wealth inequality; and (iv) gender inequality. He uses the same four domains in his analysis of farming and fossil fuel societies. Here is a brief summary of his interpretation of the data:

Violence: Foraging societies usually have a ‘middling’ attitude toward violence. They view it as a necessary means toward solving certain types of social and inter-tribal conflict. In support of this, Morris cites evidence on rates of violent death in foraging societies. Most such societies are small, but the rate of violent death seems to be far higher (per capita) than it is in modern fossil fuel societies. To be clear, it is not that members of these societies favour or condone violence; it is simply that they acknowledge situations in which it is acceptable, e.g. violent raids on rival groups, cycles of tit-for-tat revenge killings and so on.

Political Inequality: Foraging societies are generally flat in terms of political inequality. They do sometimes adopt leaders, but these are often temporary and they favour consensus decision-making. Some studies — such as Richard Lee’s study of the !Kung San — show how foraging societies try to reinforce the lack of political hierarchy. If anyone tries to assert authority over the group, other members of the group resort to mockery, ostracism, blunt criticism and, in extreme cases, exile in order to prevent them from being successful.

Wealth Inequality: Foraging societies are generally flat in terms of wealth inequality. The Gini coefficient — which is a way of measuring inequality of wealth distribution with 0 representing perfect equality and 1 representing perfect inequality — for foraging societies averages at 0.25, which is relatively low (by comparison with farming and fossil fuel societies). There are good reasons for this: resources are scarce and often shared among group members in a form on ongoing reciprocal altruism; and foragers move around a lot and are consequently unable to accumulate much material wealth. There are some exceptions to this (e.g. groups in Sungir in east Russia and North America’s Pacific Coast) but this is usually when foragers live in regions of abundance. ‘[N]o subgroup within a foraging society has ever set itself up as a rentier class that owns the means of production’ (Morris 2015, 38).

Gender Inequality: Foraging societies have some noticeable gender inequalities. There is usually a gendered division of labour — men hunt and do most handicrafts; women gather, prepare food and do some handicrafts. It is also usually taken for granted that men should be in charge in such societies. This is arguably because men are the source of meat and violent protection and women have to bargain for these things. That said, the gender hierarchies are not steep and, compared to farming societies, foragers tend to have more relaxed attitudes toward premarital virginity and marital fidelity.

I have summarised all this in the image below.

2. Farming Societies and their Values
Farmers get their energy from domesticated plants and animals. In other words, instead of moving around to find a natural environment that enables them to survive, they try to manipulate and control their environment in order to supply them with the energy they need. Farming societies tend to be much larger than foraging societies, sometimes growing to encompass empires of millions of people. They also tend to be static, expanding out from some stable geographical core.

There is huge diversity in farming societies. Morris suggests that one useful way to think about it is to use a three-pointed star to visualise the different types of farming societies. At one point, there are the horticulturalists, who are effectively just slightly more sophisticated foragers using food cultivation techniques. They have limited supplies of domesticated plants and animals and continue to live much like foragers. At the second point, you have protoindustrial nations/empires, which are very large social organisations using complex methods of domestication and having elaborate legal and bureaucratic systems. They were still standing at the dawn of the fossil fuel age. Then, at the third point, you have commercial city states like ancient Athens or medieval Venice, which were urban centres of trade and commerce for farming communities. At the centre you have what Morris calls ‘peasant societies’ which are the ideal type of farming society. Peasant societies are noteworthy for one main reason: they consist of a large underclass of agricultural labours who do the main business of energy capture, and then a ruling elite. This already tells us something interesting about the values of such societies.

 The history of the agricultural revolution is fascinating and is recounted in some detail in Morris’s book. He explains how the domestication of plants and animals first arose in certain geographical regions (the Lucky Latitudes) and how farming then spread from those regions. He also explains the differences in average hours worked when you compare farming societies to foraging societies. I won’t go into that historical detail here. What is noteworthy for present purposes is simply how farming enabled a massive ramping-up in our ability to capture energy from our environment. The most successful foraging societies typically captured about 5,000 kcal per person per day. The most successful farming societies peaked at around 30,000 kcal per person per day. This enabled much larger populations and much higher population densities. This forced innovations in social organisation, which in turn led to a shift in values:

Violence: Farmers have a somewhat ambivalent attitude toward violence. Farming societies require a great deal of cooperation and coordination among the peasant class in order to ensure adequate energy capture. They consequently tended to shun interpersonal violence as means to resolve disputes. The state, either a ruling God-like king or a political class, were deemed to be the legitimate users of force. They could use force to pacify peasant labourers and conquer new lands. That said, there were violent uprisings against the state if it was felt that it was not exercising its power legitimately.

Political Inequality: Farming societies have steep political inequalities. People within such societies are often obsessed with rank and class. That said, there was much more innovation in political organisation across farming societies than there was across foraging societies. The classic political organisation involved a God-like ruler (often explicitly recognised as a god) sitting atop a ruling aristocracy, propped up by a large peasant class. Some societies adopted a more bureaucratic or democratic leadership, though there was often movement back-and-forth between modes of political organisation. Alleged exceptions to the steep hierarchy often prove the rule. Athens is usually the go-to example. It was a democracy — indeed, the birthplace of democracy — but only for a privileged group of wealthy male land- and slave-owners. Athens was also unique insofar as it was a commercial trading port situated within a broader farming society.

Wealth Inequality: Farming societies have steep wealth inequalities. Indeed, virtually all farming societies relied upon slavery. A large underclass of forced labourers was used to prop-up an elite and often extremely wealthy upper class. The Gini coefficient in farming societies averaged at about 0.48, which is higher than what we currently have in the Western world. Morris gives some vivid examples of this. The most interesting is probably that of C. Caecilius Isidorus, a wealthy Roman, whose will survives to this day and contains a list of all the property he owned. It included enough cash to feed 500,000 people for a year. Owning property became important in these societies because it was one of the primary agricultural resources. Laws were put in place to protect such ownership. People could now accumulate wealth, keep it in their families and use it to further distinguish themselves from others.

Gender Inequality: Farming societies have significant gender inequalities. Morris argues that this is down to the gendered division of labour that emerged early on in agrarian societies. Possibly because of men’s generally greater upper-body strength, outdoor activity (tending to animals and crops) became men’s work whereas indoor activities (food preparation, home care, childcare) became women’s work. Farming societies could support a lot more people and so women started having more children. This consequently led to women spending more of their adult lives involved in childcare related activities. They had little time or opportunity for anything else. This in turn created systems of norms that reinforced the gendered view of the world. Because of the importance of family and property, societies became obsessed with female sexual purity and fidelity.
A simple way to think of the values of farming societies is in terms of the ‘Old Deal’. This is something that is described at length in Morris’s book. In essence, it was a general theory of who belonged where in the world. The idea was that there was some ‘natural’ order in society. Some people belonged in certain roles (e.g. slaves were best-suited to be slaves; kings were best-suited to be kings). The caste system is the classic instantiation of this worldview. Attempts to deviate from this natural order were treated with suspicion and hostility.

3. Fossil Fuel Societies and their Values
Fossil fuel societies get their energy from…well…from fossil fuels. The vast majority of us (certainly anyone reading this blog) live in fossil fuel societies. These societies got started in the mid-18th century in northern Europe. The invention of the steam engine is usually pinpointed as the spark that ignited the fossil fuel revolution. This was the first major revolution in energy capture. Subsequent revolutions emerged with the invention of electricity, combustion engines and, eventually, non-fossil fuel energy sources like nuclear power.

Unlike the farming revolution, the fossil fuel revolution did not start in several different places at several different times. It only started once. The reason for this is that once the fossil fuel method of energy capture was mastered, the social systems that mastered it managed to project their power globally, eventually colonising much of the known world. This is explored in great detail in Morris’s earlier work Why the West Rules for Now. There is diversity in the organisation of fossil fuel societies — we see that to some extent today — but as Morris points out there have really been two major forms of social organisation: liberal forms, that prioritise individual freedom and autonomy and facilitate democratic politics; and illiberal forms, that prioritise top-down control and often limit political participation. The 20th Century competition between liberalism, fascism and communism suggests to Morris that liberal forms are generally more sustainable.

The rise of fossil fuel societies brought with it another massive ramping-up in energy capture. Where farming societies peaked at around 30,000 kcal per person per day, industrial societies in the West were averaging over 230,000 kcal per person per day by the 1970s. That number is continuing to grow and energy capture is equalising between the East and West. This has in turn facilitated much larger populations and much higher population densities. The largest cities in farming societies tended to have around 1 million people living in them. Today, the largest city in the world (Tokyo) has over 38 million people living in it.

We have much more evidence for the values of people in fossil fuel societies. We live in such societies and so we have a sense of their values ourselves; we can infer the values from social and political organisations; and polling groups such as Gallup regularly conduct worldwide surveys of these values. Indeed, there is possibly too much evidence to categorise. There is also complexity in the picture because many societies inherit pre-existing value systems (particularly the values from farming societies) via their cultures, laws and institutions. Nevertheless, Morris argues that there are some clear trends emerging:

Violence: Fossil fuel societies are opposed to violence. There is very little tolerance for interpersonal violence (Morris cites poll data where the majority of people claim to be total pacifists in their daily lives) and increasingly less tolerance for political or state violence. There is some recognition that this is necessary, but it is generally to be avoided at all cost. The antipathy toward violence is reflected in some studies which suggest a declining rate of violence across the developed world (Pinker’s Better Angels of our Nature being the most famous work on this topic).

Political Inequality: Most fossil fuel societies are politically flat, at least in theory. There is no God-given, normatively validated political ruling class. There may be de facto political elites, of course, but most people express opposition to this idea. Furthermore, most regimes express fealty to the idea that everyone is equal before the law and is entitled to the same rights and protections. Indeed, the transition to fossil fuel societies has often been marked by opposition to pre-existing Old Deal political hierarchies. The most notable form of opposition was probably the abolition of slavery and the rejection of the view that some people naturally deserve to be slaves.

Wealth Inequality: Fossil fuel societies have an ambivalent attitude toward wealth inequality. Some regimes have tried to stamp out such inequality through forceful redistribution (communist regimes being the classic example of this); others tolerate it in an effort to incentivise economic activity. Morris suggests that the compromise position that has emerged in liberal Western societies seems to be winning out across the world: equality of opportunity is encouraged, but not equality of outcome. State taxation and redistribution is then used to correct for the worst excesses of wealth inequality. He also cites data suggesting that the most sustainable level of wealth inequality for fossil fuel societies seems to be a Gini coefficient of between 0.25 and 0.35. Since 1970 the Gini scores within Western countries have been rising, but global wealth inequality has been falling.

Gender Inequality: Fossil fuel societies have become intolerant of gender inequality, though it has been something of a struggle. Morris argues that the technologies supported by the fossil fuel revolution eventually broke down the rationale for the pre-existing gendered division of labour. Muscle power was no longer so important; brain-power became key. Contraception allowed women (and men) to control the number of children they had. Various other technologies reduced the burden of housework (e.g. automated cleaning equipment). Of course, gendered stereotypes and attitudes remained long after the dawn of the fossil fuel age (and linger to this day) but there is widespread recognition that they are undesirable.

I should note here that the chapter on fossil fuel societies is one of the longest in Morris’s book and he explores the nuances and the evidential basis for his claims about values in a lot of detail. I’m skipping over virtually all of that in my summary.

4. Conclusion
As I said at the outset, I think that it is an interesting way of describing and categorising the evolution of human values. And as set out by Morris, it seems to fit the data, but I’m not well-versed enough in the empirical minutiae to dispute what he says.

By way of conclusion, I should say something about why Morris thinks that these changes have taken place. Obviously, he thinks that the changes in techniques of energy capture are the root cause of the changes in values, but he does have a more elaborate explanatory framework. I don’t have time to cover it in great detail here, but in broad outline it all hangs on the relationship between energy capture and population size and density. In essence, he thinks that changes in energy capture encouraged changes in population size and density, which in turn forced changes in social organisation, which encouraged experiments in different value systems. Social organisations that adopted particular sets of values tended to do better than others who adopted alternative values, which eventually led societies to settle down into the general patterns outlined above. This sounds vaguely plausible, but of course it is very difficult to test.

I want to close with one final image, taken from Morris’s book. This is his ‘reductionist, simplifying and doubtless distorting’ attempt to compare the value systems of all three societies. It focuses on the different attitudes toward violence and inequality in those societies (i.e. whether they view violence or inequality as good or bad things). There is something interesting about the patterns this diagram reveals. Take a look:

Did you notice the pattern? Farming societies are relatively more different than fossil fuel and foraging societies. They are, in a sense, the societies with values most alien to our own. Morris suggests that some of the contemporary clash of civilisations can be understood in terms of cultures that continue to cling to agrarian value systems in the face of fossil fuel imperialism.

Morris has some interesting speculations about what all this means for the future as we transition to a post-fossil fuel society. I have some thoughts on this too. I hope to outline them another time.

*Morris doesn’t explicitly endorse the Marxist view in his book - he relies more on the work evolutionary theorists like Boyd and Richerson - nevertheless there is some affinity with the Marxist view.