What is all the fuss about Cambridge Analytica? Part 3

So Part 1 described the background and origins of Cambridge Analytica (CA).

Part 2 described the objective of Robert Mercer and with Carole Cadwallar describing the impact on Vote Leave.

This part is about the methods and implications of CA on electoral processes.

Hitting the Headlines

In March 2018, multiple media outlets broke news of Cambridge Analytica’s business practices: The New York Times and The Observer reported that the company had used Facebook data for its campaign activities and shortly afterwards, Channel 4 News aired undercover investigative videos showing CA CEO Alexander Nix boasting about using prostitutes, bribery sting operations, and honey traps to discredit politicians on whom it conducted “opposition research”. CA claimed it had “ran all of (Donald Trump’s) digital campaign” in 2016 Presidential election. In response in the UK, the Information Commissioner’s Office (ICO) issued a warrant to search the company’s servers. Meanwhile Facebook banned CA from advertising on its platform, saying that it had been deceived. On 23 March 2018, the ICO was granted a warrant to search Cambridge Analytica’s London offices.

Amazon said that they suspended CA from using their Cloud Hosting Services. The governments of India and Brazil demanded that CA report how their data was used in political campaigning.

In early July 2018, the United Kingdom’s Information Commissioner’s Office announced it intended to fine Facebook £500,000 ($663,000) over the data scandal, this being the maximum fine allowed at the time of the breach, saying Facebook “contravened the law by failing to safeguard people’s information”.

Also in July 2019, in the USA, Facebook was fined $5billion for its minor part in the data breach.

Rather too late… CA is now “gone” but their methods, their “genie” is now out of the bottle.

What did they do?

Wikipedia describes the method CA used to gain personal data. CA developed a Facebook app called “This Is Your Digital Life.” Aleksandr Kogan, a data scientist at Cambridge University, developed the app sometimes called “thisisyourdigitallife” and provided the app to CA who then posted it to Facebook. This third-party app then had permission to acquire data from Facebook users that not only entered data into a quiz-like game but also gave the app access to information on the user’s friends network; this resulted in the data of about 87 million users, the majority of whom had no idea their personal data was being collected for political ends. It goes without saying that the app breached Facebook’s terms of service but Facebook did not police any app particularly well (hence the reason for the $5b fine).

Follow this link to hear Alexander Nix describe the CA Big Data approach elections or this one to hear how big data helped Senator Ted Cruz in 2016. Nix claims that CA had 4000 parameters for every voter in the USA. From these parameters, not only demographics and location were uncovered but also psychographic profiles, the attitudes of each person distilled down to a few variables! This allowed, for any given political campaign, what kind of advertisement would be most effective to persuade a particular person for vote (or not vote) for any particular candidate or cause.

What CA has invented is the technology to subvert the traditional election processes to introduce:

  • Personalised messages – Nix claims top down broadcasting is dead. All future elections will be personalised messages based on a person’s psychographic profile.
  • Psychographic profiles are used to identify, and then reinforce, bias and prejudices.
  • Political promises are not on mainstream media, so not open to secutiny and debate, but are on social media. Fired up and forgotten with no follow up – reverting back to before Hansard when politicians were not held to account for any commitments.
  • Complete Situation Awareness of each individual’s motivations so that in all probability, each person can be manipulated using targeted messages to vote in the way expected (plus leaving the election to nefarious manipulation).

What are Psychographics?

Psychographic profiles can be valuable in the fields of marketing, demographics, opinion research, prediction, and social research in general.

All the research for political ends has already been established for marketing and advertising of products. Demographic information includes gender, age, income, marital status – the dry facts. In the past marketing was all about Demographics: making sure your advert went out to males or females of a partical age. Psychographics are kind of like demographics. Psychographic information might be your buyer’s habits, hobbies, spending habits and values. Demographics explain “who” the buyer is, while psychographics explain “why” they buy. Advertisers now reach their target audience both by demographics and psychographics. What does it say about you if you drive BMW and read the Telegraph… or if own an allotment and make jam? All this information has been condensed down into a set of number. This approach was proven in the commercial market, CA weaponised Psychographics for electioneering…

Psychographics gained prominence in the 2016 US presidential election since both Hillary Clinton and Donald Trump used them extensively in microtargeting advertisements to narrow constituencies.

So CA’s “This Is Your Digital Life” basically provided a mainline feed into pyschographic data. But CA also collected data on voters using sources such as consumer behaviourinternet activity, and other public and private sources. According to The Guardian, CA used psychological data derived from millions of Facebook users, largely without users’ permission or knowledge. Another source of information was the “Cruz Crew” mobile app that “gamified” election campaigning by giving points for the number of political social media messages circulated by the player. But more than that it tracked physical movements and contacts on the player’s smart phone and so invaded personal data more than any previous electioneering method.

Alexander Nix, chief executive of Cambridge Analytica, October 2016, said “Today in the United States we have somewhere close to four or five thousand data points on every individual … So we model the personality of every adult across the United States, some 230 million people.”

CA’s data analysis methods were to a large degree based on the academic work of Michal Kosinski. In 2008, Kosinski had joined the Psychometrics Centre of Cambridge University where he then developed with his colleagues a profiling system using general online data, Facebook-likes, and smartphone data. He showed that with a limited number of “likes”, people can be analysed better than friends or relatives can do and that individual psychological targeting is a powerful tool to influence people.

This aspect of facebook-likes is absolutely key and – as far as I can tell – is missed in most write-ups of the Presidential Election 2016 and GE2019 Fraud.

Facebook “Likes”

Most, but not all. It was discussed extensively in 2018 by CBS which states “Facebook ‘likes’ can signal a lot about a person. Maybe even enough to fuel a voter-manipulation effort like the one a Trump-affiliated data-mining firm stands accused of — and which Facebook may have enabled. The social network is under fire after The New York Times and The Guardian newspaper reported that former Trump campaign consultant Cambridge Analytica used data, including user likes, inappropriately obtained from roughly 50 million Facebook users to try to influence elections.

The issue of the addictive nature of facebook and the dopamine hit when someone “likes” your post is well known. So how important is that “like” if it just came from a bot? Can they even do that? Yes.

Technology to Support CA

If the data collected by CA was all performed by party workers then would it all be bad? Probably not: doorstepping in elections trys to collect similar type of data. But CA introduced the mechanism to do this quite automatically, without permission, by impersonation and by the the “backdoor”. Besides the (illegal) aggregation of data from a various sources, this is the type of technology that CA used in order to recognise and give facebook “likes”:

  • Artificial Intelligence (AI) – Sentiment Analysis – this sort of AI can read thousands of posts and determine whether any particular post supports the camapign, against it or whether it is just another cat video.
  • Robot Process Automation (RPA) This allows a series of automatic actions to occur online, for instance: read a facebook message, work out if the sentiment supports the camapign, clicks the “like” button.
  • Bots and Sock Puppets – basically fake accounts – either a Bot which is a fake account which performs a repetative RPA action, for example, “liking” a facebook message; or a sock puppet, a human controlled fake account, that can enter into hundreds of discussions online dissing the opponents and/or talking up the camapign with prepared slogans.

The set up and running of this technology requires a huge amount of capital intensive investment (this is where the rich, organised “few” outgun the poor, disorganised “many”). So democracy is now a hidden war between people-powered electioneering (“the people”) against a limitless army of hidden robots controlled and funded by a few billionaires. This technological army is not even in party headquarters but can be outsourced to friendly front organisations, commercial organisations or even foriegn powers.

The Hub

The only thing needed for any political HQ is the data collection hub. HQ will ensure the right campaign messages are being fed in a way that is compelling… to a “plan”. That requires technology again but it is cheaper and readily available off the shelf in the form of a Customer Relationship Management (CRM) system. This a tool to manage an organisations interaction with current and potential customers – everytime you phone up a major corporation nowadays you are being managed by a CRM system such as Microsoft Dynamics CRM, Salesforce or SugarCRM. Now replace the word “customers” with “voters” and the tool works just as well. Just look at the (proven) results of CRM and see how they apply to election campaigns.

  1. Enhanced ability to target profitable customers. (Replace “profitable customers” with “likely voters”)
  2. Integrated assistance across channels. (Use of Bots, Sock Puppets, Newspapers or leaflets to promote your propaganda)
  3. Enhanced sales force efficiency and effectiveness. (Replace “salesforce” with “campaign staff”)
  4. Improved pricing. (Instead of pricing, think “extract donations”)
  5. Customized products and services. (Tailor message for particular poltical concern: health, environment, business etc)
  6. Improved customer service efficiency and effectiveness. (Improve approval ratings)
  7. Individualized marketing messages (also called plans). (A set of messages just to engage each individual voter, there can be multiple plans depending on the voter’s concern)
  8. Connect customers and all channels on a single platform. (A complete view of Voter Intentions).

Architect of the Vote Leave and Conservative GE2019, Dominic Cummings, called his central database of voters, the Voter Intention Collection System (VICS). It is described in his blog. He describes how he developed ads for social media, trialed them and targetted them. The data feeding VICS was both “conventional and unconventional” – from that we can assume conventional = demographic data – freely available to political parties – and unconventional = psychographic… as described above – illegal. Illegal to the price of $5billion just to facebook alone for allowing a loophole in its software. How much more illegal is it for people to deliberately exploit that loophole?

But wait there’s more…

Just consider the power now available to the rich elites with such technology at their disposal:

  • A list of every voter.
  • With social media data then the on-line accounts can be linked to voters in the electoral register probably in 80% of all cases.
  • This enables the identification of all people strongly aligned with campaign messages and will vote.
  • And the identification of all people strongly opposing the campaign.
  • This identifies the battle ground! The non-aligned people.

Pyschographics help sort out the battleground. Since the social network shows who is friends with whom, then the probability of voter intentions can be calculated with different levels of certainity… until you have complete and utter situation awareness of how people will vote. People do respond to the information they’ve received but if all the information is biased and plays into pre-set grooves enabled by the mainstream media then, people respond collectively in herd like behaviour. Dominic Cummings tested his “messaging” in carefully selected groups. When the message had the right effect, he sent out targeted political ads and using the AI and Big Data analysis re-calculated the expected voter intentions so that he could predict an 80 seat majority for the Tories. And he got an 80 seat majority for the Tories. This level of estimation precision requires computers. And probably coercion (see below). The Conservative Party was able to deliver an astonishing efficiency at delivering seats in 2019: One seat for every 38264 votes (a 10% efficiency improvement over 2017) while the LibDems were amazingly less efficient: one each seat for every 300,000 votes, a 50% decrease in efficency. And, unlike Jo Swinson travelling the country in a bus (and even losing her seat), Boris Johnson never really needed to go out and campaign or even do many TV interviews.

Minimum Fraud / Maximum Outcome

There are further tools in the toolchest. Having complete situation awareness allows other useful things:

  • it identifies marginal consistencies.
  • it identifies people that are unlikly to vote
  • it identifies people that will be using a postal vote
  • it identifies people that are misaligned with the electoral registers

We know postal voting fraud exists and is widespread. Complete situation awareness of voter intentions now allows two useful forms of election fraud, which can be set at the minimum level that arouses the least suspicion:

  • Voter Suppression for those people of the wrong demographics and pyschometrics that are misaligned with the electoral register and/or registered for postal votes. (eg postal votes not delivered, arrive late or invalidated). Voter suppression is regarded as a non-crime – the voter is always blamed for any administrative error.
  • Ballot Box Stuffing, by postal votes, impersonating people that are unlikely to vote. A virtually undetectable crime!

What’s all the fuss?

Now do you see what the fuss is all about?

  • No need to campaign
  • Lower campaign costs (as long the computer system costs can be hidden)
  • No need to be held to account for any promises or policies
  • Set up the perfect way to secure a seat with the minimum level of fraud – so small that it is hardly detectable.
  • Confidence of predicting the election result nationally (100% accuracy)
  • Confidence of securing any particular local seat (as long as there is a high level of postal votes!)

8 Comments

  1. Who writes these articles please? A friend and myself are piecing together the role of Bill Gates in ‘Covid19’ but also his role with the UK Govt and vaccines patented in the UK (Oxford & Pirbright), his role with Change.org and other entities.
    I’d like to share with you…

    Like

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