Sunday [16 till close of play]

To the bitter end.

20.  Many drops at t'other place

It tends to come and go at the two parts of the site - most of the time, this page has the items; currently though, there are many at t'other from our various correspondents and as I refer to some of these in subsequent posts, it might be worth skimming down that page.

19.  View from the Clif

18.  PD

Just chanced upon:-

"Evidence and Scenarios For Global Data Systems"

̶ Citizen data
̶ Governments
̶ Regional data systems
̶ Regulations
̶ Global trends
̶ Technologies
̶ COVID-19
̶ 2030 scenarios"

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/927547/GOS_The_Future_of_Citizen_Data_Systems_Report__2_.pdf

"evidence suggests people in China typically indicate higher levels of trust and lower levels of
concern over data use and privacy than those in the EU and US. However, it is unclear how
far this is influenced by their governments’ approaches in the first place. Values may change
rapidly over time, and within most countries there is significant variation in attitudes towards
privacy concerns and levels of trust"

Chinese people don't have a choice.

There are more alarm bells
"The UK should take opportunities to steer the formation of new global norms, as well
as respond to them."Examples of what we mean by citizen data include:
• Unique identifiers (e.g. NHS or passport number)
• Shared identifiers (e.g. name, date of birth, address)
• Biometric data (e.g. DNA, fingerprints)
• Medical, educational or other records
• Data generated or observed through interaction with services or devices, such as
o Internet browsing history, tracking cookies, IP addresses
o Video data (e.g. CCTV images)
o Utility usage data (e.g. from smart meters)
o Data generated though interaction with Internet of Things (IoT) devices (e.g.
voice recordings)
o Consumer data (e.g. online shopping behaviour)
o Social media data
o Location data (e.g. through fitness tracker apps)
• Inferences, predictions and assumptions derived from data about people (e.g. digital
profiles used for targeted advertising)
• Metadata relating to data about people (e.g. when and how data was generated)
• De-identified data (e.g. medical records with identifying fields removed or changed,
for use in scientific research and planning)
• Aggregate data such as census information, even if it is reportedly anonymised

2030? UN2030 plan?

17.  Oh to live in California

16.  Steve

It is the eve of mass demonstrations across the world.

War Room - It's all here:

Episode 1,582 – Defeat The Mandates

https://rumble.com/vt30ke-episode-1582-defeat-the-mandates.html

Episode 1,583 – Defeat The Mandates Cont.

https://rumble.com/vt31pi-episode-1583-defeat-the-mandates-cont..html