The Symbiotic Web• A new model to understand the gathering, use and

retention of personal data on the internet

• It helps explain: • Why so much data is gathered • The principle commercial uses to which it is put• Some of the ways it might be used in the future• Why so much data collection and use is covert• The difficulties our legal and regulatory systems

have in controlling it• The threats to our privacy and autonomy that

arise through it

Symbiosis

• Where two different kinds of organism exist together in a state of mutual dependence

• Symbiosis can be mutually beneficial - but can also become parasitic, and detrimental to one or both of the parties

The Symbiotic Web• Individuals and commercial enterprises are

mutually dependent:• Enterprises have built business models reliant on

a currency of private data• Individuals depend on ‘free’ access to many

services - from search engines to price comparison web sites, email to YouTube

Users

Web 1.0

Content Providers

The Symbiotic Web

User/Contributors

Web 2.0

Content Providers

The Symbiotic Web

User/Contributors

Web 2.5Content Providers/

Information Gatherers

The Symbiotic Web

User/Contributors Web 2.5

Content Providers/Information Gatherers

The Symbiotic Web

A fractured web?

• Individualised advertising, content - and links

• For search engines, for example, different search results - or search results in a different order

• Overall, the effect is more than just on the individual page, but on the navigation and the whole web experience

• Potential benefits, but not in the control of the user

Key components of the symbiosis

• Search engines

• Communications providers

• Social Networking Sites

• Geographic services – Google Maps etc• And geolocation services on smartphones

etc

• Media providers/Services - YouTube etc.

• Commercial services – from shops and auction sites to price comparison sites

Competitive drives

• The understanding by businesses that personal information has commercial value

• Organisations gather more and more data, not just for specific current or planned uses, but speculatively

• Once the data has been gathered, there is a drive to find more uses for it, to take advantage of your ‘assets’

• New businesses developed for aggregation and profile generation - and to help other businesses use data

Competitive drives• As competition over personal data develops, so do

competitive and anti-competitive practices - alliances, cartels etc Beacon and Phorm are prime examples

• Drive for more ‘tailored’ services - and potentially price or service discrimination

• The need for covertness - when customers know what is happening, they often object - Beacon and Phorm are again examples. Opt-out, rather than opt-in, is the norm

• As competition increases and margins fall, less attention may be paid to ‘ethics’

Consequences

• A burgeoning market in data - one about which users are being kept deliberately unaware

• Much more data is being held - and hence is vulnerable

• New data types are emerging - profiling data in particular - which have more significant vulnerabilities

• New kinds of risks are emerging - ‘Back-door Balkanisation’ is just one example

Solutions?

• Break the dependence - through stronger, better enforced laws?

• Change the paradigm - effectively give up on privacy. Accept that this is happening, enjoy the positives, penalise excesses.

• Do very little - allow norms and markets to redress the balance.

• Weaken the dependence, but support the symbiosis - strengthen the rights of individuals, particularly in terms of information, consent and choice

Paul Bernalp.a.bernal@lse.ac.uk