My presentation to the Information Technology Law students of the LSE on regulatory theory of the Internet. We touch on Lessig, Murray, rationality, pathetic dots, network communitarianism and big data.

1. Dr Mark Leiser FHEA FRSA
Assistant Professor
eLaw – Center for Law and DigitalTechnologies
Leiden University
LSE IT law specialist seminar
19 October 2018, 12h30 – 13h30

2. 2
“Regulability means the capacity of a
government to regulate behavior within its
proper reach”
Code and Other Laws of Cyberspace, p. 19

3. ‘All forms of social control, state and non-
state, intended and unintended’
The Regulation of the online environment, p.18
3

4. 4
 Lessig’s four “constraints on behaviour”:
 Law
 Regulates by sanctions imposed ex post.
 Social Norms
 Social Rules: How one ought to behave.
 The Market
 Regulates by price, and market signals.
 Architecture
 Constraint “of the world as I find it, even if this world as I find it is a world that others have made.”

5.  Lessig argues that the fact that we can harness the
environment in Cyberspace has two important
effects:
 A conflict occurs between legal regulatory designs (East
Coast Code) and environmental regulatory designs (West
Coast Code).
 Lawmakers, (East Coast Code-writers) have had to resort to
indirect regulation through mandated code designs.
▪ SeeThe Communications DecencyAct,The Child On-line Protection Act,
The Digital Millennium CopyrightAct,The E-SignAct, and in Europe the
Electronic Signatures Directive and the Copyright and Related Rights in the
Information Society Directive. 5

6.  Some of the Questions Raised by Lessig’s Approach:
 Who determines the nature of cyber-regulatory settlements?
▪ East Coast orWest Coast Code-makers?
 Are architectural controls too unforgiving?
▪ No need for separate detectors and effectors?
 Who really controls code?
▪ Designers? Or people?
 Are code-makers too US-centric?
6

7. 7
Murray & Scott, 2002
Hierarchy

8.  Accountability is traditionally defined as:
 The obligation to give account of one’s actions to someone else,
often balanced by a responsibility of that other to seek an account.
 Lawmakers (hierarchy), market participants or makers
(competition) and community members (society) engage in
dialogue and accountability.
 Design proves problematic.
 The focus of the work of Brownsword and Scott…
8

9.  Colin Scott
 this is fatal to the originality of
design controls as a regulatory
modality.
 Roger Brownsword:
 Lack of human interaction
found in design controls
negates accountability.
 Lack of responsibility on the
part of the originator of the
control.
 “This lack of accountability for
authors of control, coupled with
the denial of agency for its
objects, causes us to question
whether design is a distinctive
modality of control at all.
 The features of responsibility,
accountability and agency can
only be supplied through one of
the three other modalities.
 In this sense, at best, design is
not a freestanding modality.
 Put more forcefully it is merely
an adjunct or technique of the
other three modalities.”
9

10. 10
Regulatory Modalities
Socially-mediated Modalities Environmental Modalities
Competition Based Controls Design Based Controls
Laws Markets Norms Architecture

11. 11
From control to community?
Lessig’s
‘Pathetic’ Dot Murray’s ‘Active’ Dot
Network

12. Re-evaluating the role of the Community
 Too many regulators see the community as “the problem”
▪ Peer-to-peer
▪ DRM engineering
▪ Reselling
▪ Parallel Importation
▪ Adult Content
 Attempts are made to control the Community
▪ Community seen as passive
▪ Failure to force change = regulatory failure
 Active Community
▪ Opportunity to harness community regulation 12

13.  Introducing Symbiotic Regulation
Designing regulatory interventions to harness
and work with community regulation.
Using the positive power of the community
matrix to reinforce the regulatory message.
The community as the solution not the problem
Disruptive events become positive
developments, not regulatory challenges 13

14. Regulatory Discourse

15. 15
Murray 2011

16. 16
Murray 2011

17. 17

18. 18
 Shakespeare: “What a piece of work is man!
How noble is his reason, how infinite in
faculty! In form and moving how express and
admirable!”
 Verba: “Cool and clear-headed ends-means
calculation after considering all possible courses of
action and carefully weighing the pros and cons of
each of them”
 Stable preferences and engage in maximizing
behaviour
 Humans make optimal decisions when clear
information is provided.

19. 19
 Providing more information about the cost-
benefits of consequences fails to change
behaviour
 Full disclosure
 Where changing direct incentives
(consequences) fails to change behaviour;
 Compliance Pyramid
 Deterrence Pyramid
 Where self-control, not choice, is the critical
determinant of behaviour
 Almonds and dinner party

20.  Heuristics & Biases
 Underpinned by work of
Kahneman &Tversky
 Humans have limited
computational capacities
 “Pessimistic” in nature
 Susceptible to making ‘poor’
judgements
 Poor judgements result in
systematic biases and errors
 Fast & Frugal
 Underpinned by work of Gerd
Gigerenzer
 ‘Optimistic’ in nature
 Mind comprised of ‘modular
heuristics’
 Focus on when is it appropriate
to leave information out, as
“surplus to requirements”
 Advocate ‘heuristic strategies’
20

21. H&B: Three Classifications
 Availability: people assess the frequency of a
class on the probability of an event by the
ease with which instances or occurrences can
be brought to mind;
 Representativeness: Probabilities are
evaluated by the degree to which A
resembles B, that is, the degree by which A
represents B;
 Adjustment and Anchoring: Where
estimations form from an initial value that is
adjusted to yield a final answer.
21

22.  Which US city has more inhabitants? San Diego? San Antonio?
 Germans?
▪ 100%
 Americans?
▪ 62%
▪ Goldstein & Gigerenzer, 2002, Psychological Review
22
Germans:
orrect

23.  Linda is 31 years old, single, outspoken, and very bright. She majored in
philosophy. As a student, she was deeply concerned with issues of
discrimination and social justice, and also participated in anti-nuclear
demonstrations.
 To what degree does Linda resemble the typical member of each of the following
classes?
▪ Linda is a teacher in elementary school.
▪ Linda works in a bookstore and takesYoga classes.
▪ Linda is active in the feminist movement.
▪ Linda is a psychiatric social worker.
▪ Linda is a member of the League of Women voters.
▪ Linda is a bank teller.
▪ Linda is an insurance salesperson.
▪ Linda is a bank teller and is active in the feminist movement.
23

24. Linda is 31 years old, single, outspoken, and very bright. She
majored in philosophy. As a student, she was deeply
concerned with issues of discrimination and social justice,
and also participated in anti-nuclear demonstrations.
Which is more likely?
1. Linda is a bank teller
2. Linda is a bank teller active in the feminist
movement
24

25. 25

26.  A bat and ball together cost £1.10.The bat costs £1 more than
the ball. How much does the ball cost?
 A) .05
 B) .10
 C) .55
 D) .£1.00
 E. £1.10
26

27. 27

28. 28
 Users sometimes fail to behave in their
own interests
 Combination of self-control problems
 Making inappropriate distinctions between
gains & losses
 Difficulties in choosing among large sets of
options
 How information is framed can have
dramatic effects on consumer response

29.  Fully rational decisions online are impossible
 Don’t have enough information to make a fully informed choice.
 Bounded Rationality
 What does the bounded rational man or woman do when faced with all this choice?
▪ Hindsight Bias?
▪ Overconfidence bias?
 “Informed consent” or “Active Consent” = bounded rationality.
 Are there new online specific errors and biases?
 Network effect bias?
 Data authenticity bias?
▪ DataAuthenticity Bias means we place too much reliance on data from digital resources and from digital
tools.
▪ Always over-value the way data is presented in any decision-making process
▪ Digital resources less “nudge” and more “push”.
▪ Lessig was right, they constrain choice and behaviour and therefore are unlikely to be libertarian in their
actions.
29

30. Framing… Loss Aversion… Consent…
30

31.  Lazer et al: “capacity to collect and analyse data with an
unprecedented breath and depth and scale”
 Regulators: informed through analysis of large data sets
 not only to determine elements of causation & correlation
 correct & overcome any erroneous long-held assumptions about
either
 Move away from socially-constructed acceptability to tailored,
subjective form of accountability
 New circle of behavioural regulation
 Empirical regulation informing theories
 Theories requiring empirical data
 Informing more theories 31

32. 32
 “First fixation” of a subject’s gaze showed that when
presented with choices, the first selection was largely
dependent on how many options were placed on the
screen.
 When four options were displayed in a 2x2 matrix, eyes settled on
the top left quadrant 50 per cent of the time
 When subjects were shown nine options, their eyes settled near the
centre option 99 per cent of the time.
 When sixteen options, the subject moved to the first four options 97
per cent of the time.
 “Display Induced Decision Biases” have a huge influence on
the subsequent action a user takes.
 Astoundingly, when subjects were shown nine choices, they chose
the centre option 60 per cent more, regardless of what it was

33.  What is the regulatory problem to tackled?
 Map the terrain:
▪ What are the regulatory goal(s) in relation to this specific societal issue?
▪ What are you hoping to achieve with the intended regulation?
▪ What are the benefits and limitations of using nudging as a regulatory
mechanism for this societal issue?
▪ What is the expected outcome (or are the expected outcomes) when nudging is
applied? E.g. will it lead to a lasting change?
▪ What might be side-effects?
▪ Are these serious/dangerous/important?
33

34. 34
?
?
?
??
?
?
? ?
Thank you for your attention!
Contact: m.r.leiser@law.leidenuniv.nl
Twitter: @mleiser