[The Apprentice]

The end of everything we know.

https://youtu.be/KBlme4px5n4

[awakened53]

David sums it all up very well

https://youtu.be/lz7Tff9P13M

[awakened53]

Zuckerberg calls Facebook users Dumb Fucks

https://www.zerohedge.com/news/2018-03-2...book-users

[awakened53]

Palestinian news site has Facebook accounts deleted

http://www.jpost.com/Arab-Israeli-Confli...ent-547065

[awakened53]

An early interview with Zuckerberg. Listen to him lying and lying and lying

https://youtu.be/NuzmvfGJl0U

[awakened53]

You Tuber tests the Facebook eavesdropping theory

https://youtu.be/U0SOxb_Lfps

http://truepublica.org.uk/united-kingdom...-says-yes/

[Steve]

Worth a read

http://www.whatdoesitmean.com/index2517.htm

Algorithms -

http://theunexplained.tv/paranormal-podc...athy-oneil

Here’s a podcast from August 1, 2017 with New York numbercruncher Cathy O’Neil on “Weapons of Maths Destruction” – how algorithms may harm us… »

Podcast notes

6 min   - introduction to Cathy O’Neil.
7 min   - the elephant in the room, people becoming aware of and waking up to algorithms.
8 min   - a growing group of algorithms is not being kept track of and becoming weaponised.
9 min   - do clever people know best?
10min  - we should be able to complain about flawed algorithms.
11min  - a quant, quantitative analyst who builds algorithms, hedge funds.
12min  - in 2007/8 sub prime loans came to prominence.
13 min  - hedge fund is a management fund for the wealthy - invest, then hedge the bet.
14 min  - investment banks lost the most money in 2008 crash, selling short, betting against. 
15 min  - an important tool is to sell short.
16 min  - the culture in the hedge funds, a financial system that needed mending.
17 min  - sub prime loans, piles of debt (securities), credit rating agencies and disillusionment.
18 min  - agencies didn’t do their job, led to the uninformed buying poor investments.
19 min  - the AAA ratings scam, insider knowledge, facts that were never checked or verified.
20 min  - how the crash unfolded, its inevitability, inflated housing market, derivative misuse.
21 min  - corrupt underlying mortgages, they knew it would happen, the crooks got away with it
22 min  - why are movies making these culprits out as some kind of hero?
23 min  - logically extreme perspectives, wishful thinking causes a bubble, misunderstanding.
24 min  - uncontrollable credit card debts, no savings.
25 min  - example of bad individual debt, people suffering, financial institutions ruthlessness.
26 min  - the rich getricher, the poor get poorer, squeezing out more money by use of algorithms. 
27 min  - human decision making and judgement is replaced by algorithms removing control.
28 min  - it’s tracking huge numbers of people but data is measured wrongly, hurts people, lives.
29 min  - personality tests used in job applications, you don’t even know results, discrimination.
30 min  - illegal practice under disability act, can mean you fail all tests for job applications.
31 min  - poor practice is hidden behind flawed algorithms, and is happening silently. 
32 min  - no individual discretion is used by the potential employer, and promises not kept.
33 min  - patterns of data dictating the nature of the algorithm, affects the poor disproportionately. 
34 min  - minimum wage workers with no access to representation, death spiral loop, the rich.
35 min  - people working within organisations wrongly think they are doing no harm, racist traits.
36 min  - implicit bias, we are not modelling the algorithms, it’s a black box, wrong conclusions. 
37 min  - the designers choose accuracy over truth, Facebook actively choosing profit over truth.
38 min  - fake news is generated by algorithms, faceless entities, need for accountable algorithms 
39 min  - the need for proof that an algorithm is legal, fair and our demand for the evidence of this
40 min  - so many hidden victims are arising out of secret algorithm abuse and misuse. 
41 min  - companies should be held responsible, it’s their legal responsibility but they are claiming
41 min  - plausible deniability to avoid any responsibility. 
42 min  - flawed algorithms used in the justice, police, education systems, cyber war implication.
43 min  - use of sentencing scores and demographics mean the poor are sent to prison for longer.
44 min  - it’s being used all over the US, and misused by political parties and politicians. 
45 min  - minimising insurance costs through wellbeing programs that short change people.
46 min  - the wearing of monitoring devices as a long term goal for data gathering.
47 min  - parameter settings are flawed, giving power over innocent people, discrimination. 
48 min  - charging certain groups disproportionately, to those who can least afford.
49 min  - types of insurance, unfair premium increases, big data is incompatible with insurance.
50 min  - cultural understanding of Insurance is meant to pool risk, big data does the opposite.
50 min  - it segregates us into categories by risk, are we helping or pricing people out?
51 min  - if insurers apply flawed algorithms to risks, they will wrongly charge higher premiums.
52 min  - as everything becomes centralised, we’ve lost the concept of a safety net, people suffer.
53 min  - vicious circle for groups of people, are unable to escape the data trap and imprisoned.
54 min  - a regulatory system is required and should be demanded, we need to shape up.
55 min  - I am not a number I am a free man! 
56 min  - the careful use of numbers and data is needed in order to educate us.
57 min  - the political fight we face, people are too accepting of the gradual change.
58 min  - we need to be more engaged regarding our algotithmically controlled futures.
59 min  - ways to audit algorithms, company involvement. 
60 min  - the book ‘weapons of math destruction’.
62 min  - website details.

[Steve]

Just in case you didn’t know -

http://www.dailymail.co.uk/sciencetech/a...ticle-home

[Steve]

https://www.facebook.com/duckduckgo/post...7262555778

How to Download the Giant File of Everything Facebook Knows About You

Assuming you don’t have the good fortune to live on an isolated island where there is no internet connection and you grow your own produce, oblivious to the horrors of the online world, you’ve no doubt heard that some stuff went down with Facebook this week. Namely that Cambridge Analytica has been banned from the platform for deceiving users to obtain personal data and then (possibly) not deleting that data when Facebook told it to. (That data was later maybe used to sway the 2016 election, so there’s that.)

In light of this mess, now is a good time to take stock of just what personal information Facebook has been compiling on you over the years. Here’s how to do that.

Step 1: Log in to Facebook.
Step 2: Go into your account settings. On desktop, you can find these by dropping down the menu in the upper-right-hand corner of your screen.
Step 3: At the bottom of the “General Account Settings” menu, you’ll see an option to “download a copy of your Facebook data.”
Step 4: Input your email so that Facebook can notify you when your download is ready. (I’ve been on Facebook for over ten years and it took under ten minutes for my email to arrive.)
Step 5: Download your archive. Facebook will ask you to re-input your password.
Step 6: Start digging. Arm yourself with ample alcohol for when you scroll back far enough to realize just how embarrassing you were in 2007 — also for when you realize just how much information Facebook has on you.

Related
Who Knows Me Better: Google or Facebook?

[Steve]

'Utterly horrifying': ex-Facebook insider says covert data harvesting was routine -

https://www.theguardian.com/news/2018/ma...-parakilas