24 Feb 2021

Sri Lankan government proposes tiny wage rise to deflect plantation workers’ unrest

M. Thevarajah & W.A. Sunil


On February 8, a Sri Lanka wage board approved an utterly inadequate wage rise for estate workers proposed by the Rajapakse government in collaboration with the plantation unions. It consists of an increase in the daily wage to 1,000 rupees ($US5.09), comprising a 900-rupee basic wage and a 100-rupee allowance.

While union and labor ministry representatives, who hold a majority on the board, voted for the proposal, the Employers’ Federation of Ceylon (EFC), Sri Lanka Tea Factory Owner’s Association (SLTFOA) and the Regional Plantation Companies (RPCs) voted against the tiny increase.

Uda Rathalla Estate workers picketing last September against austerity measures (WSWS Media)

The Ceylon Workers’ Congress (CWC), which is part of the Rajapakse government, the National Union of Workers (NUW), Democratic Workers Congress (DWC), Upcountry People’s Front (UPF) and the Lanka Jathika Estate Workers Union (LJEWU) all participated in the wage board meeting.

While the board’s decision is pending because of the objections of the plantation companies, the labour commissioner told the media that the wage increase will be gazetted because it was a government-determined proposal. The commissioner, however, is due to hold another discussion with the plantation company representatives on March 1.

The Rajapakse government made the proposal, not out of any sympathy for the low-paid workers but to defuse growing opposition over the surging cost of living and growing poverty.

The government fears that a major pay fight in the estates will draw in broader layers of the working class facing similar attacks. Sporadic strikes and protests over low pay and increased workloads continue to erupt in the plantations.

On February 5, around 200,000 estate workers participated in a one-day national strike. The walkout won broad support from teachers in estate schools and small traders in the plantation districts.

The plantation unions have hailed the wage board’s pay rise decision as a ‘victory.’ This is a lie. CWC leader Jeevan Thondaman, who is currently Rajapakse’s minister of estate infrastructure, along with other estate union leaders who have served in previous governments, serve the interests of the plantation owners.

The unions’ initial demand of a 1,000-rupee basic daily wage, which was first made in 2015, is grossly inadequate due to sharp increases in the cost of living. In comparison with 2015 figures, the real wage of agricultural workers, according to the Central Bank data in 2019, has dropped by about 16 percent.

While plantation workers have participated in numerous strikes and protests since 2015 to demand a 1,000-rupee basic daily wage, these struggles have been consistently betrayed by the unions. In December 2018, hundreds of thousands workers went on strike for 11 days over this demand. The unions, led by the CWC, sold out the strike agreeing to a 700-rupee daily wage.

Many estate workers have voiced their anger and concerns about the latest proposed pay increase.

As one female worker Ushananthini, from Gartmore Estate in Maskeliya told the WSWS: “The cost of living has increased terribly since we first asked for a 1,000-rupee wage. Even if we were paid 1,500 rupees per day it would not be enough to meet ends. And if we do get a small wage increase, they [the companies] will use it to increase our workload. According to some news reports, the companies want to reduce our working days to just 13 a month.

“We will not accept it and even if it the increase is implemented we will oppose it. I’m an NUW member but all the trade unions are useless. They only come to see us during the election time and that’s to get our vote with false promises.”

The Rajapakse government with the assistance of the unions wants to “restructure” the Sri Lankan plantation industry, including by dismantling some estates and diverting tea production into more commercial crops.

Plans are also being prepared to further develop the tourist industry and boost garment production using cheap labor. This so-called restructuring will see further attacks on jobs and social rights. While specific details have not been released, future plans along these lines were indicated in last November’s annual budget.

The Regional Plantation Companies (RPC) have consistently and vehemently opposed the latest wage increase proposal. According to Planters’ Association (PA) spokesman Roshan Rajadurai, almost 200 objections to the increase have been filed by RPCs, small holders, factory owners and others.

Instead, the RPCs are proposing two wage formulas, both based on driving up productivity. The first, a so-called revenue-share system, is for workers to be given a plot of land with a certain number of tea bushes and provided with fertiliser and agro-chemicals. Workers must maintain the bushes and harvest the leaves. They would receive an income from the sale of the leaves, following the deduction of expenses for the fertiliser and other supplies provided by the plantation companies.

The other RPC proposal is for plantation employees to work three days for a 1,000-rupee daily wage and for three days at 50 rupees per kilo of plucked tea leaves, or 125 rupees per kilo of extracted rubber milk (in the rubber plantations).

Opposing the wage board’s latest pay rise proposal, PA spokesperson Rajadurai declared that the payment of 1,000 rupees was “unsustainable” and claimed that the industry had “no capacity to earn the additional 12.5 billion [rupees] needed” to pay for the increase.

If the RPCs were compelled to accept the new wage proposal, he added, “we will cut the coat according to the cloth, and if we cannot fertilise we won’t… [and] a vast majority of people will suffer eventually.”

In other words, thousands of workers will lose their jobs and those that remain will face increased workloads, longer workdays and the abolition of the limited social rights won in previous struggles.

In fact, the RPCs, with government and union support, have already implemented the revenue-share system in some estates, as well as increasing workloads and cutting wages in others.

While the RPCs claim that a higher wages increase would drive up the cost of production, export earnings by tea and rubber companies increased during 2020 despite the impact of the COVID-19 pandemic.

According to the January export development board report, tea export income increased by 6.78 percent in comparison to 2019 while rubber and rubber finished product export income increased by 6.22 percent in the same period.

Plantation companies in Sri Lanka maintain a network of brokers and export companies in their own right or through joint ventures with giant multinationals, such as Unilever and Tetley, which manipulate world market prices in order to maximise profits.

Wherever they happen to live, plantation workers are among the lowest paid and most heavily exploited workers in the world.

Visa Everywhere Initiative Global Competition 2021

Application Deadline: 

  • Ethiopia: 9th April 2021
  • Rest of CEMEA: 7th May 2021

Eligible Countries: Global

About the Award: Visa Everywhere Initiative is a global open innovation program tapping into startup communities to drive regional business objectives, curate the startup ecosystem for Visa clients and accelerate bigger and bolder ideas, enriching consumer experience.

Wherever you want to be, Visa’s Everywhere Initiative helps you get there. Visa’s Everywhere Initiative offers participants a chance to win up 50 000usd and a chance to have a support development program with Visa business or partnership with Visa’s partners.

Fields: 

  • To move away from cash on delivery (COD) culture for ecommerce in Africa: How can your startup leverage Visa Developer APIs to either: Enable smaller merchants to accept payments in-store digitally OR Provide a safe and secure solution for online merchants to drive eCommerce and reduce cash on delivery?
  • Leveraging partner social media platforms like FaceBook to create amazing bank to business onboarding user journeys in order to remotely enable businesses to accept digital payments: How can your company use Visa’s APIs to leverage mass reach partner platforms like Facebook to help businesses operating in fast-paced consumer centric environments improve cash flow and receive payments?
  • Driving Financial Inclusion: How can your startup leverage technology to provide services that are functional for illiterate customers to provide them with secure transaction experiences that build and enhance their confidence in the banking system?

Type: Entrepreneurship

Eligibility: The Visa Everywhere Initiative for Middle East & Africa is open to fin-tech entrepreneurs in MEA countries.

Number of Awards: 4

Value of Award: Four monetary prizes will be awarded during the global finals event:

  1. Overall Winner: $50,000 USD
  2. Audience Favorite: $25,000 USD
  3. 2nd Place: $15,000 USD
  4. 3rd Place: $10,000 USD

The overall winner, 2nd place-winner, and 3rd place-winner are also eligible to win the Audience Favorite prize.

Duration of Programme: The Visa Everywhere Intiative CEMEA Finals will take place on 8th June 2021.

How to Apply: Apply Here

Visit the Programme Webpage for Details

Google News Initiative (GNI) Innovation Challenge 2021

Application Deadline: 12th April 2021 at 23:59 GMT.

Eligible Countries: countries in Middle East, Africa and Turkey

About the Award: As part of our continuous effort to support the news industry around the world, we are launching our second Google News Initiative Innovation Challenge in Africa, the Middle East and Turkey. It’s an open call for projects that increase reader engagement and explore new business models to build a stronger future for journalism.

Last year, we selected 21 projects from 13 countries: Côte d’Ivoire, Ghana, Iraq, Israel, Jordan, Kenya, Lebanon, Morocco, Nigeria, Rwanda, South Africa, Turkey, and the UAE. In South Africa, online news publisher Daily Maverick developed a “relevancy engine” for small and medium publishers to help them better understand reader insights and increase relevancy and increase subscriptions. Ringier Africa Digital Publishing in Nigeria was awarded funding to increase personalisation across its platform using a blend of prediction, recommendation and local information pages to increase user engagement. Kenyan awardee Africa Uncensored is aggregating news from members of the public to produce at scale. You can find out more about all of last year’s recipients in this Keyword post.

Type: Contest

Eligibility: Established publishers, online-only players, news startups, publisher consortia and local industry associations are all eligible to apply.

Selection Criteria: Projects will be evaluated against five criteria: impact on the news ecosystem, innovation, diversity, equity and inclusion; inspiration; and feasibility.

Number of Awards: Not specified

Value of Award: The selected projects will be eligible to receive up to $150,000, not to exceed 70% of the total project cost. We will not be funding any editorial-only projects, but instead are focusing on projects aimed at increasing reader engagement and exploring new business models.

How to Apply: Applications, in English only, must be made online via our website and are open until Monday, April 12 at 23:59 GMT. We will also be holding an online town hall on March 3 at 13.00 GMT with a live presentation and the opportunity to ask questions. (Please note that Google does not take any equity or IP in any projects or submissions.)

We are looking forward to seeing new ideas, projects and big bets come out of the Middle East, Turkey and Africa, a region rich with talent, potential and opportunity. For more information about the challenge, visit g.co/newsinnovation.

  • It is important to go through all Terms and Conditions in the Award Webpage (see Link below) before applying.

Visit Award Webpage for Details

ADAPTED European Joint Doctorate (EJD) Scholarships 2021

Application Deadline: 31st March 2021

About the Award: The EJD ADAPTED is a consortium of European Universities, important internationally active European development organisations and think tanks and six African partner universities. Within ADAPTED,

  • the European universities – including Ruhr-Universität Bochum, Germany (coordinator), Erasmus University Rotterdam and Vrije Universiteit Amsterdam, Netherlands, Boğaziçi University, Turkey, and Centre National de Recherche Scientifique in partnership with Université Paris 1 Panthéon Sorbonne, France – will host the ESRs, direct their research, organise training and implement the European Joint Doctorate based on project-specific binational agreements (cotutelles de these),
  • the Agence Française de Développement (AFD), the Deutsche Investitions- und Entwicklungs GmbH (DEG) and the Centre for Research on Multinational Corporations (SOMO) host selected ESRs during non-academic secondments and add to the intersectoral relevance of the research done within the consortium while the European Association of Development Research and Training Institutes (EADI) provides ESRs with advice and training on the dissemination of research output and acts as a global dissemination platform for the ESRs,
  • researchers from six cooperating African partner universities, including the University of the Western Cape and the University of Cape Town (South Africa), Bahir Dar University (Ethiopia), University of Development Studies (Ghana), Moi University (Kenya), and University of Douala (Cameroon), will supervise ESRs during field work, provide them with access to local actors and to locally available data sets and link them to the non-academic sector in the fieldwork countries.

Eligible Field(s):

Type:

Eligibility: Recruiting is in accordance with the European rules of the Marie Skłodowska-Curie ITN regulations for Early Stage Researchers (ESRs). Applicants can be of any nationality but must not have resided or carried out any main activity (work, studies, etc.) in the country of the recruiting university for more than 12 months in the last 3 years prior to being recruited as ESR. In addition, applicants must have less than 4 years of postgraduate research experience at the time of recruitment.

Selection Criteria:

General selection criteria:
Applicants shall demonstrate a proven interest in interdisciplinary and inter-sectoral research as well as a specific interest in the ADAPTED research areas as evidenced by the application documents. The following requirements are to be met: (1) a previous degree (Master or equivalent) from a recognized university which qualifies for doctoral studies, (2) graded at least upper 2nd or equivalent, (3) in a subject relevant for the planned doctoral studies (Economics, Social or Political Science, Law, and related relevant disciplines), proved by submission of degree certificates and transcripts, (4) English language proficiency proof for non-native speakers equivalent to CEFR level C1 (IELTS 7) or above.

Specific selection criteria:
Specific selection criteria for individual ESR projects are detailed in the respective project description below.
Please also make yourself familiar with specific offers for ESRs and procedures at the respective recruiting institution. Relevant information is provided in individual ESR offers.

Number of Awards: 15

Value of Award:

ADAPTED is committed to offer equal opportunities and therefore seeks to recruit a gender balanced group of ESRs. It further aims to support Early Stage Researchers through a family friendly working environment. This is in line with benefits offered by the MSCA programme, which offers highly competitive and attractive salary and working conditions. Successful candidates will be offered a full-time position for a duration of 36 months. In accordance with the MSCA regulations for ESRs the salary includes the following elements:

  • Living allowance: basic, gross amount before taxation and compulsory deductions for contributions to social insurance schemes according to national law. These deductions include the employee’s plus the employer’s share to social insurance schemes!
    The basic gross amount of the living allowance is EUR 3 270 per month. To ensure equal treatment and purchasing power parity, this amount is then adjusted through the application of a correction coefficient based on the country in which the ESR will be recruited. For more details, please refer to the FAQ section of this website.
  • Mobility allowance of EUR 600 per month
  • Family allowance of EUR 500 per month for ESRs who have a family (persons linked to the researcher by marriage or a relationship with equivalent status to a marriage recognised by the legislation of the country where this relationship was formalised or dependent children who are actually being maintained by the researcher) at the time of recruitment.

Duration of Award: 36 Months

How to Apply: Documents to be submitted
(as one pdf-file)

  • Motivation letter (max. 2 pages) which includes a statement explaining the interest in the particular ESR project the application is referring to (1st priority ESR). Applicants interested in more than just one ESR project should share this information in the motivation letter by indicating a 2nd and max. 3rd
  • Current CV (please use the Europass template)
  • Certified copies of relevant university degree certificates and related detailed transcripts of records.
  • Recognised English language proficiency certificate (equivalent to CEFR level C1 = TOEFL 94, IELTS 7)
  • Short literature review (4-5 pages) linked to the topic of the ESR project which is the 1st priority of the applicant.
  • At least two current academic recommendation letters
  • Copy of the passport valid at least until the end of 2021. Applicants with two or more nationalities can use just one passport and apply only once.

Please submit your application electronically (one pdf-file) by email to adapted@rub.de

  • It is important to go through all application requirements in the Award Webpage (see Link below) before applying.

Visit Award Webpage for Details

Africa Geographic Photographer of the Year 2021

Application Deadline: 31st May 2021 midnight (CAT)

Eligible Field(s): Entries must encompass the Celebration of Africa!

Type: Contest

Eligibility: Only entries that are of African wildlife, landscapes, and/or culture will be accepted.

Selection: The selection process administered by the judges will be as follows:

• The ‘Weekly Selection’ will be the top entries submitted via our website and Instagram page. This selection will be published at the end of each week on our website as a gallery and in an album on Facebook;
• During the month of June 2021, once the submission deadline has come and gone, the judges will judge all accumulated entries from the Weekly Selections, gradually reducing the number of qualifiers to a list of ‘Finalists’, from which the winners will be selected and announced in July 2021;

Eligible Countries: African countries

To be Taken at (Country):

Number of Awards: Entries will compete for the following coveted titles:

• The overall winner – 2020 Photographer of the Year
• The first runner-up;
• The second runner-up;
• The top highly commendable finalists;

Value of Award: For more information about our fabulous prize go to our dedicated PRIZE page.

How to Apply:

  • Entries can be submitted from Friday, 1 January 2021 until midnight (CAT) on Monday , 31 May 2021.
  • Entrants must submit photos via the online entry form.
  • By entering the Africa Geographic Photographer of the Year 2020 participants confirm that they have read and agree to the rules of the competition.
  • It is important to go through all application requirements in the Award Webpage (see Link below) before applying.

Visit Award Webpage for Details

The Mass Deception Machine of Computational Propaganda

Thomas Klikauer & Nadine Campbell


mass deception machine is a socio-technical apparatus that broadcasts deceptive claims like falsehoods, lies, accidental misinformation, deliberate disinformation, untruths, conspiracy fantasies, etc. It works in the service of right-wing ideology. A mass deception machine uses computational propaganda, often based on algorithms to engineer and mass distribute deceptive messages that serve right-wing ideologies.

Today, these techniques are increasingly used on voters in democratic countries by politicians, lobbyists,  astroturf PR and political parties. Telling organised lies and creating mass deception helps right-wing politicians get elected and stay in power once elected. Britain’s BoJo and Donald Trump are prime examples. Boris Johnson’s lies got so bad that a special website has been created: boris-johnson-lies.com while Trump runs on the “15 most notable lies” and well above 20,000 falsehoods.

Today, in conjunction with computational propaganda, the mass deception machine has made sure that in several democratic countries, political leaders have been elected. They tend to reject scientific findings – on global warming, for example – and the concept that governmental decision should be based on evidence rather than myths, conspiracy fantasies and alternative facts.

Mass deception machine and computational propaganda are not specific to Great Britain and the USA. They are a global problem. Increasingly, they operate like Henry Ford’s assembly line mass-producing deceptions and broadcasting them across national borders. The tripod of (1) right-wing politicians, (2) willing online platforms run by a handful of multi-national corporations, and (3) plenty of campaign financing (dark money and otherwise) assure that the entire setup of the mass deception machine is continuously fine-tuned and perfected.

Inside the mass deception machine’s organisational structure, computational algorithms provide one of the most effective means of transporting right-wing propaganda to a targeted audience. To make all this possible, a mass deception machine is set in motion. The machine has just three key components:

1) The first part of the mass deception machine is where right-wing propaganda and ideologically framed public relations are manufactured. This is the place where right-wing organisations such as lobbyists camouflaged as think thanks, right-wing politicians, and plenty of campaign money meet. The idée fixe is that mass deception serves right-wing ideology.

2) The second part of the machine is a massive crankshaft that functions as a distributor of right-wing ideologies created by the machine’s first section. This segment consists of online platforms such as the usual suspects – Twitter, Facebook, YouTube, TikTok, etc. Their sophisticated algorithms turn right-wing ideology into computational

3) Finally, the third part of the mass deception machine is the contraption’s marketing department. It uses dark money and adjacent campaign funding. This part consists of shady backroom operators but also consulting firms pretending to be respectable. It has lobbyists peddling ideology, hired guns for dirty politics and think tanks that lobby by stealth. They profit from marketing, augmenting, and promoting right-wing ideologies.

For the mass deception machine to work at full capacity, big data provide the oil for the machine. Computational propaganda is the very opposite of Coca Cola’s marketing strategy. Its message is not a broad stroke hitting everyone. Computational propaganda is a highly targeted affair that carefully selects its embattled audience. At the same time, it avoids wasting money on so-called “non-persuadables” – people who are unlikely to be converted to a right-wing cause.

To avoid spending valuable funding on a lost cause, the non-persuadables, the mass deception machine uses micro-targeting that delivers highly pinpointed, tailored and even customised messages to a very specific political consumer – the persuadables. For example, it allows messaging to those interested in hunting or those living in key areas to be targeted. This mega-data is collected from marketing information like credit card use, Amazon shopping, Google searches, and websites consumers visit like Facebook, Twitter messages, etc.

Simultaneously, this is used for what is known as redlining so that those deemed non-persuadable aren’t besieged. City dwellers may not need right-wing pro-hunting messages, for example. One of the most significant advantages of the mass deception machine is that most people have no idea how much it knows about them and which information the mass deception machine has already collected.

At the most superficial level, any search for a product like camping equipment is used. Very soon after the Google search, a customer will start receiving ads on tends and camping cookware. This is just the beginning. Increasingly, we might not only be worried about sophisticated algorithm machines like Google, but people might also worry about their own devices – the so-called wearables – transmitting our location 24/7, our heartbeat, movements, time spend in a café, in a hotel room in with Stormy Daniels, or in a cinema.

Mass deception machine uses algorisms to analyse a vast array of data feeding into computational models for targeting political advertisements, design an election campaign and structure voter contacts. Many still see the 2016 US presidential election as the first great triumph of the mass deception machine and computational propaganda. It was won by Donald Trump on a razor-thin margin narrowly winning a few key states. The mass deception machine furnished by computational propaganda delivered an unexpected victory – even to Donald Trump himself.

For the first time in human history, computational propaganda was used massively and successfully persuading enough voters in key areas to vote for Donald Trump. Computational propaganda enabled the mass deception machine to disseminate a large number of messages to a relatively small group of persuadables.

They were contacted almost on a personal level. Many were fooled into believing that these messages originated from their personal network – family, relatives, and friends. Today, computational propaganda engineers know that these messages reach their victims much better than standard political advertisements. Not surprisingly, the mass deception machine operates with everything the world of the Internet has to offer:

+ from Russian or Pilipino troll farms to automated online robots called bots or bot networks;

+ from fake news, operations to purposefully build right-wing websites peddling conspiracy fantasies.

For example, trolls can operate a highly negative campaign against those the radical right perceives as its enemies – the infamous “enemy of the people” – and against individuals such as academics and journalists highlighting the danger and criminal pathologies of the radical right. It can even do what is called dogpiling. This happens when a large number of online militia fighters harass a perceived enemy by bombarding a victim into submission, creating a sense of utter helplessness.

Beyond that, computational propaganda increasingly relies on Chatbots – the new kid on the block. Right-wing lobbyists the right-wing extremists of the mass deception machine use Chatbots to advocate junk science – nonsense dressed up as scientific facts. Some have even started imagining the moment when AI – artificial intelligence merges with computational propaganda and are placed in the bowels of the mass deception machine. This would allow machine learning to develop more sophisticated online weapons for the radical right.

Given what we have seen in the 2016 US election, during the 2016 Brexit referendum, Donald Trump’s attempted re-election in 2020 and the rise of disinformation, conspiracy fantasies, etc., one can be certain that there will always be enough right-wing online militias working to perfect the mass deception machine. They want to understand our thoughts, behaviours and attitudes better than we do and to use this to manipulate us.

Overall, we should no longer naïvely see social media as an instrument to simply connect people but as an apparatus to manipulate public opinion into the radical right direction. The radical right will use computational propaganda primarily for five reasons:

1) to get right-wing politicians elected;

2) once elected, right-wing computational propaganda is used to protect those leaders from reputational harm;

3) to make their ideology accepted by society;

4) to preserve the order of capitalism, neoliberalism and profit-maximisation and secure the continued existence of corporate capitalism; and

5) to maintain a political culture that is supportive of the value of the business.

To achieve these five goals of the right-wing mass deception machine, computational propaganda quite often starts rather innocently. Automated bots of computational propaganda, for example, can entice people accessing an “innocent” website like Tinder (dating, make friends & meet new people). Step by step, it draws the unsuspecting victim into the right-wing orbit by merely starting a conversation – even flirtatious. At some point, it moves the victim on to more serious issues on the radical right’s ideological agenda.

Finally, it draws the unsuspected deeper into the jungle of right-wing conspiracy fantasies leading them onto right-wing news websites. Such bots often target eighteen to twenty-five-year-olds in a particular constituency who are identified as needing to swing a few votes in favour of a right-wing candidate. The success of computational propaganda comes when a critical electorate turns to the right even by a narrow margin.

The right-wing mass deception machine also knows that in the US, for example, 85% of adults use the Internet, and 80% are on Facebook. This is the battlefield of the right-wing mass deception machine. Its feeds on easy pray – voters deemed to be persuadables – while simultaneously degrade public debate. In one case, such disinformation and conspiracy fantasies had deliberately targeted military personnel on active duty. Bots can target them with messages coming from across multiple devices.

Such bots can easily pass as real people on social networks. It is already next to impossible to protect your own identity on the net, and it is even harder to verify someone else’s identity. Bots introduce another layer of ambiguity about the communication people have on social media.

Well-engineered bots effortlessly blend into online debates. More sophisticated bots even use socially acceptable spelling mistakes and slang words that are not found in a standard dictionary to mimic a real person. Right-wing computational propaganda has identified Twitter as one of the preferred battlefields for bots.

Today, in almost every election, political or environmental crisis, complex humanitarian disasters and global pandemics, computational propaganda algorithms distribute misinformation, disinformation, and conspiracy fantasies. Right-wing online messaging often includes extremist viewpoints, conspiratorial sources, and sensationalism. What is relevant for the right-wing mass deception machine is the fact that algorithms and automated messaging exponentially speed up the flow of communication as well as the increased range and cost-effectiveness of its distribution.

One of the reasons why digital technologies and computational propaganda has become so crucial for the radical right is that these machines can respond to what is on the new agenda extremely quickly. It can spit out automated lying to counteract facts provided by the quality press. Beyond that, it can also frame a debate and even better, it can set an agenda.

Boris Johnson’s £350 million Brexit lie was a superb example of how this was done. Furnished with plenty of dark money, the campaign to leave the EU told voters that the UK pays £350 million to the EU every week and that this money could be better spent on health and education.

The problem was that the UK’s statistic office announced that the number was totally wrong. Months after that, even the Brexit demagogues of the £350 million lie themselves acknowledged this. Yet, immediately before the Brexit referendum, almost ½ of the British people was convinced that BoJo’s £350-million-claim was true. This is the stunning success of the mass deception machine. The Brexit campaign relied heavily on computational propaganda targeting a specific group of about nine million persuadables, but it also targeted so-called opinion leaders such as journalists, politicians, bloggers, and activists.

Yet, one should not underestimate the level of human labour, attention, planning and funding that goes into right-wing computational propaganda. Such human labour is also needed when inventing junk news. Junk news’ relevance comes not just from its logical fallacies, doctored images, exaggerations, extremism, sensationalism, and conspiratorial content. It comes when junk news is broadcasted at the expense of investigative journalism when it uses feigned criticism to disseminate right-wing ideology,

Online platforms allow junk news and fake news stories from deceitful sources to spread like wildfire across several platforms and networks of family, relatives, and friends rather rapidly. This, of course, aids right-wing echo-chambers and cognitive dissonance. It favours plausible-sounding content that often reinforces existing prejudices. On the political side of the equation is the task of computational propaganda not to generate an immediate massive nation-wide swing of the popular vote. Instead, it targets a small change in key areas that allows a right-wing candidate to cross the line and hold office and power.

The US Republican Party, for example, finds it increasingly hard to win the popular vote. Consequently, it becomes ever more important for the right to win key areas to conjure up a narrow majority in the electoral college. As a consequence, the radical right targets persuadables in particular geographical areas. It is designed to achieve two things – voter suppression; and long-term political polarisation.

For both, not just big data but also data mining has become ever more relevant. To fine-tune its computational propaganda, the mass deception machine needs a supply of trustworthy information on their victims. It needs to engineer a successful campaign strategy on whom to target, where and when and with which message, and most importantly, over which device and platform.

The mass deception machine and computational propaganda will continue to launch disinformation campaigns against democracy in the foreseeable future. The machine’s strategy will remain pretty much the same, consisting of three key elements:

+ sell disinformation to attack what Aristotle once called the polis;

+ dispute and demean science, democratic politicians and experts; and

+ prevent those deemed “enemies of the people” from voting – voter suppression.

In the end, the mass deception machine and computational propaganda will be amplified by the radical right. It has already shown significant success in recent years and in many countries. If anything, it is safe to expect that the mass deception machine’s activities will only increase in years to come. On the qualitative side of the equation, one needs to expect the use of artificial intelligence will turbo-charge right-wing extremism.

USA: A Covid-19 Hell on Earth

Rajan Menon


Economic crises shine a spotlight on a society’s inequities and hierarchies, as well as its commitment to support those who are most vulnerable in such grievous moments. The calamity created by Covid-19 is no exception. The economic fallout from that pandemic has tested the nation’s social safety net as never before.

Between February and May 2020, the number of unemployed workers soared more than threefold — from 6.2 million to 20.5 million. The jobless rate spiked in a similar fashion from 3.8% to 13.0%. In late March, weekly unemployment claims reached 6.9 million, obliterating the previous record of 695,000, set in October 1982. Within three months, the pandemic-produced slump proved far worse than the three-year Great Recession of 2007-2009.

Things have since improved. The Bureau of Labor Statistics (BLS) announced in December that unemployment had fallen to 6.7%. Yet, that same month, weekly unemployment filings still reached a staggering 853,000 and though they fell to just under 800,000 last month, even that far surpassed the 1982 number.

And keep in mind that grim statistics like these can actually obscure, rather than illuminate, the depths of our current misery. After all, they exclude the 6.2 million Americans whose work hours had been slashed in December or the 7.3 million who had simply stopped looking for jobs because they were demoralized, feared being infected by the virus, had schoolchildren at home, or some of the above and more. The BLS’s rationale for not counting them is that they are no longer part of what it terms the “active labor force.” If they had been included, that jobless rate would have spiraled to nearly 24% in April and 11.6% in December.

Degrees of Pain

To see just how unevenly the economic pain has been distributed in America, however, you have to dig far deeper. A recent analysis by the St. Louis Federal Reserve did just that by dividing workers into five separate quintiles based on their range of incomes and the occupations typically associated with each.

The first and lowest-paid group, including janitors, cooks, and housecleaners, made less than $35,000 annually; the second (construction workers, security guards, and clerks, among others) earned $35,000-$48,000; the third (including primary- and middle-school teachers, as well as retail and postal workers), $48,000-$60,000; the fourth (including nurses, paralegals, and computer technicians), $60,000-$83,000; while employees in the highest-paid quintile like doctors, lawyers, and financial managers earned a minimum of $84,000.

More than 33% of those in the lowest paid group lost their jobs during the pandemic, and a similar proportion were forced to work fewer hours. By contrast, in the top quintile 5.6% were out of work and 5.4% had their hours cut. For the next highest quintile, the corresponding figures were 11.4% and 11.7%.

Workers in the bottom 20% of national income distribution have been especially vulnerable for another reason. Their median liquid savings (readily available cash) averages less than $600 compared to $31,300 for those in the top 20%.

Twelve percent of working Americans can’t even handle a $400 emergency; 27% say they could, but only if they borrowed, used credit cards, or sold their personal possessions.

Under the circumstances, it should scarcely be surprising that the number of hungry people increased from 35 million in 2019 to 50 million in 2020, overwhelming food banks nationwide. Meanwhile, rent and mortgage arrears continued to pile up. By last December, 12 million people already owed nearly $6,000 each on average in past-due rent and utility bills and will be on the hook to their landlords for those sums once federal and state moratoriums on evictions and foreclosures eventually end.

Meanwhile, low-income workers struggled to arrange child-care as schools closed to curtail coronavirus infections. Women have borne the brunt of the resulting burden. By last summer, 13% of workers, unable to afford childcare, had already quit their jobs or reduced their hours, and most held low-wage jobs to begin with. Forty-six percent of women have jobs with a median hourly wage of $10.93 an hour, or less than $23,000 a year, far below the national average, now just shy of $36,000. In some low-wage professions, like servers in restaurants and bars, women are (or at least were) 70% of the workforce. A disproportionate number of them were also Black or Hispanic.

Before the pandemic, 57% of women in low-wage occupations worked full-time and 15% of them were single parents. Close to one-fifth had children under four years old and contend with full-time care that, on average, costs $9,598 yearly. If that weren’t enough, at least 25% of such low-wage jobs involved shifting or unpredictable schedules.

Much has been made recently of the wonders of “telecommuting” to work. But here again there’s a social divide. People with at least a college degree, who are more likely to possess the skills needed for higher-paying jobs, have been “six times more likely” to telecommute than other workers. Even before the pandemic, 47% of those with college degrees occasionally worked from home, versus 9% of those who had completed high school and a mere 3% of those who hadn’t.

Now, add to the economic inequities highlighted by the pandemic slump those rooted in race. Black and Hispanic low-income workers have been doubly disadvantaged. In 2016, the median household wealth of whites was already 10 times that of Blacks and more than eight times that of Hispanics, a gap that has generally been on the increase since the 1960s. And because those two groups have been overrepresented among low-wage occupations most affected by unemployment in the last year, their jobless rate during the pandemic has been much higher.

Unsurprisingly, an August Pew Research Center survey revealed that significantly more of them than whites were struggling to cover utility bills and rent or mortgage payments. After Covid-19 hammered the economy, a much higher proportion of them were also hungry and had to turn to food pantries, many for the first time.

In these months Americans who are less educated, hold low-income jobs, and are minorities — Asians excepted, since they, like whites, are underrepresented in low-wage professions — have been in an economic Covid-19 hell on Earth. But isn’t the American social safety net supposed to help the vulnerable in times of economic distress?  As it happens, at least compared to those of other wealthy countries, it’s been remarkably ineffective.

Sizing Up the Social Safety Net

In a Democratic presidential debate in October 2015, Bernie Sanders observed that Scandinavian governments protect workers better thanks to their stronger social safety nets. Hillary Clinton promptly shot back, “We are not Denmark. We are the United States of America.”  Indeed we are.

This country certainly does have a panoply of social welfare programs that the federal government spends vast sums on — around 56% of the 2019 budget, or nearly $2.5 trillion. So, you might think that we were ready and able to assist workers hurt most by the Covid-19 recession. Think again.

Social Security consumes about 23% of the federal budget. Medicare, Medicaid, and the Children’s Health Insurance Program together claim another 25% (with Medicare taking the lion’s share).

Social Security and Medicare, however, generally only serve those 65 or older, not the jobless.  With them excluded, two critical areas for most workers in such an economic crisis are healthcare and unemployment insurance.

About half of American workers rely on employer-provided health insurance. So, by last June, as Covid-19 caused joblessness to skyrocket, nearly eight million working adults and nearly seven million of their dependents lost their coverage once they became unemployed.

Medicaid, administered by states and funded in partnership with the federal government, does provide healthcare to certain low-income people and the 2010 Affordable Care Act (ACA) also required states to use federal funds to cover all adults whose incomes are no more than 30% above the official poverty line. In 2012, though, the Supreme Court ruled that states couldn’t be compelled to comply and, as of now, 12 states, eight of them southern, don’t. (Two more, Missouri and Oklahoma, have opted to expand Medicaid coverage per the ACA, but haven’t yet implemented the change.)  People residing in non-ACA locales face draconian income requirements to qualify for Medicaid and, in almost all of them, childless individuals aren’t eligible, no matter how meager their earnings.

While Medicaid enrollment does increase with rising unemployment, not all jobless workers qualify, even in states that have expanded coverage. So unemployed workers may find that they earn too much to qualify for subsidies but not enough to purchase private insurance, which averages $456 a month for an individual and $1,152 for a family. Then there are steeply rising out-of-pocket expenses — deductibles, copayments, and extra charges for services provided by out-of-network doctors. Deductibles alone have, on average, gone up by 111% since 2010, far outpacing average wages, which increased by only 27%.

The American health care system remains a far cry from the variants of universal health care that exist in Australia, Canada, most European countries, Japan, New Zealand, and South Korea. The barrier to providing such care in the U.S. isn’t affordability, but the formidable political power of a juggernaut healthcare industry (including insurance and drug companies) that opposes it fiercely.

As for unemployment insurance, the American version — funded by state and federal payroll taxes and supplemented by federal money — remains, at best, a bare-bones arrangement. Coverage used to last a uniform 26 weeks, but since 2011, 13 states have reduced it, some more than once, while also paring down benefits (especially as claims soared during the Great Recession).

So if you lose your job, where you live matters a lot. Many states provide benefits for more than half a year, Massachusetts for up to 30 weeks. Michigan, South Carolina, and Missouri, however, set the limit at 20 weeks, Arkansas at 16, Alabama at 14. The weekly payout also varies. Although the pre-pandemic national average was about $387, the maximum can run from $213 to $823, with most states providing an average of between $300 and $500.

Except in unusual times like these, when the federal government provides emergency supplements, unemployment benefits replace only about a third to a half of lost wages. As for the millions of people who work in the gig economy or are self-employed, they are seldom entitled to any help at all.

The proportion of jobless workers receiving unemployment benefits has also been declining since the 1980s. It’s now hit 27% nationally and, in 17 states, 20% or less. There are multiple reasons for this, but arguably the biggest one is that the system has been woefully underfunded. Taxes on wages provide the revenue needed to cover unemployment benefits, but in 16 states, the maximum taxable annual amount is less than $10,000 a year. The federal equivalent has remained $7,000 — not adjusted for inflation — since 1983. That comes to $42 per worker.

The $2-trillion Coronavirus Aid, Relief, and Economic Security Act and the subsequent $900-billion Pandemic Relief Bill did provide federal funds to extend unemployment benefits well beyond the number of weeks set by individual states. They also covered gig workers and the self-employed. However, such exceptional and temporary rescue measures — including the one President Joe Biden has proposed, which includes a weekly supplement of $400 to unemployment benefits and seems likely to materialize soon — only highlight the inadequacies of the regular unemployment insurance system.

Other parts of the social safety net include housing subsidies, the Supplementary Nutrition Assistance Program (SNAP, formerly the Food Stamp Program), Temporary Aid to Needy Families, and childcare subsidies. After surveying them, a recent National Bureau of Economic Research study concluded that they amounted to an ill-funded labyrinthine system rife with arcane eligibility criteria that — the elderly or the disabled aside — actually aids fewer than less half of low-income families and only a quarter of those without children.

This isn’t an unfair assessment. The Government Accountability Office reports that, of the 8.5 million children eligible for child-care subsidies, only 1.5 million (just under 18%) actually receive any. Even 40% of the kids from households below the poverty line were left out.

Similarly, fewer than a quarter of qualified low-income renters, those most vulnerable to eviction, receive any Department of Housing and Urban Development subsidies. Because median rent increased 13% between 2001 and 2017 while the median income of renters (adjusted for inflation) didn’t budge, 47% of them were already “rent burdened” in the pre-pandemic moment. In other words, rent ate up 30% or more of their annual income. Twenty-four percent were “severely burdened” (that is, half or more of their income). Little wonder that a typical family whose earnings are in the bottom 20% had only $500 left over after paying the monthly rent, according to the Bureau of Labor Statistics, even before Covid-19 hit.

SNAP does better on food, covering 84% of those eligible, but the average benefit in 2019, as the Center for Budget and Policy Priorities noted, was $217, “about $4.17 a day, $1.39 per meal.” Mind you, in about one-third of recipient households, at least two people were working; in 75%, at least one. Not for nothing has the term “working poor” become part of our political vocabulary.

Is Change in the Air?

During crises like the present one, our moth-eaten safety net has to be patched up with stopgap legislation that invariably produces protracted partisan jousting. The latest episode is, of course, the battle over President Joe Biden’s plan to provide an additional $1.9 trillion in relief to a desperate country.

Can’t we do better? In principle, yes. After all, many countries have far stronger safety nets that were created without fostering indolence or stifling innovation and, in most instances, with a public debt substantially smaller relative to gross domestic product than ours. (So much for the perennial claims from the American political right that attempting anything similar here would have terrible consequences.)

We certainly ought to do better. The United States places second in the Organization for Economic Cooperation and Development’s overall poverty index, which includes all 27 European Union countries plus the United Kingdom and Canada, as well as in its child-poverty-rate ranking.

But doing better won’t be easy — or perhaps even possible. American views on the government’s appropriate economic role differ substantially from those of Canadians and Europeans. Moreover, corporate money and that of the truly wealthy already massively influence our politics, a phenomenon intensified by recent Supreme Court decisions. Proposals to fortify the safety net will, therefore, provoke formidable resistance from armies of special interests, lobbyists, and plutocrats with the means to influence politicians. So if you’re impatient for a better safety net, don’t hold your breath.

And yet many landmark changes that created greater equity in the United States (including the 13th Amendment, which abolished slavery, the 19th Amendment, which guaranteed women voting rights, the New Deal, the creation of Medicaid, and the civil rights legislation of the 1960s) once seemed inconceivable. Perhaps this pandemic’s devastation will promote a debate on the failures of our ragged social safety net.

Here’s hoping.