Deplatforming between democratic hygiene and cancel culture

In the end, it was not the U.S. Senate that pulled the plug on Donald Trump, but social media platforms, notably Twitter and Facebook. Since it is well known that the greatest weapon of mass destruction are the masses themselves, social networks have increasingly scrutinized those who want to seduce the masses with populism, demagogy, or just plain lies. The fact that Donald Trump, now the former president of the United States, has been ousted from the most impotant social meda platforms is unlawful censorship for some and an overdue correction of an obvious aberration for others. But one step after another.

Deplatforming, the withdrawal of access to the digital public sphere of social networks, is not a new phenomenon, but a well-known moderation technique that has been used for years in online forums, such as when dealing with spam accounts. Nor is Trump the first politician to have this access revoked. In 2018, millions of users were banned from Twitter for their proximity to the Islamic State. Also in 2018, facebook stripped Myanmar’s military leaders of their official accounts after the platform was used to demonize Muslim Rohingya, hundreds of thousands of whom were then forced to flee ethnic cleansing to Bangladesh. Similarly, the removal of the right-wing conservative social media service parler by Amazon Web Services, Google and Apple also has precedent: Wikileaks was banned from Amazon back in 2010 after publishing secret documents about potential war crimes. So while it was by no means the first time a politician lost his speaking platform on the internet, the case of former President Donald Trump got the discussion going on the topic of deplatforming.

How did Trump’s deplatforming come about?

Long before Trump was even close to running for president, he was using his social media platforms to spread lies and conspiracy theories, such as that then-President Obama was not born in the United States. The far-reaching effects of the constant lies on large sections of the population led to an acceleration and intensification of the discussion on social media’s practical handling of this problem. As recently as 2017, Twitter let Trump get away with anything under the pretext of special news value – even when he threatened North Korea’s dictator Kim Jong Un with its extinction in a dispute over nuclear weapons testing. Ever since Trump’s presidential candidacy, the two major social media services went to incredible lengths to avoid having to rein in their biggest crowd-puller. It wasn’t until three years and countless lies and hate messages later that Twitter felt compelled to correct its line: under its “civil integrity” policy, created in 2018 and tightened in 2020, Twitter classified a tweet from Trump as “misleading information” for the first time on May 26, 2020, and put a warning label on it.

On Jan. 7, 2021, a day after the Trump-inspired riots at the Capitol in Washington that left 5 people dead and 138 injured, Twitter suspended Trump’s account for 12 hours. The short messaging service tied the temporary nature of the suspension to the requirement that Trump delete three tweets and warned that the suspension would be extended indefinitely on the next offense. Shortly before, facebook and instagram had also suspended the president’s account. Finally, one day and two tweets later, Twitter completed the step to permanent suspension. In addition to facebook and instagram, other services such as snapchat, twitch, spotify and shopify also blocked Trump’s user accounts.

Deplatforming in Germany

Private companies in the U.S. are allowed to deny politicians their services even if they provide elementary communication channels with the public. In Germany, however, this case is somewhat different. According to a decision by the Federal Constitutional Court, intermediaries are “bound by fundamental rights” as soon as they reach a decisive size that is relevant to public communication. In this context, the Federal Constitutional Court has confirmed that “private spaces” are no longer private if public communication is severely restricted without them.

Accordingly, a politician of Trump’s caliber could not so easily have been deprived of access to the digital public sphere in Germany, because judicial protection of political statements takes a higher priority here. According to the Federal Constitutional Court, private companies are not directly bound by fundamental rights such as freedom of expression, but fundamental rights “radiate” into other areas of law, including the T&Cs of social networks. In practice, this means that facebook had to take back the deletion of a statement by an AfD politician because the exercise of freedom of expression did not violate “the rights of another person,” as the T&Cs required.

At the same time, government politicians in Germany have greater obligations to tell the truth than their American counterparts do. Public expression law demands principles such as objectivity and accuracy from the speeches of public officials more rigorously than in the United States. In November 2015, for example, then-Federal Research Minister Johanna Wanka had to delete a “red card” she showed the AfD on her ministry’s website for “incitement of the people” as a result of an injunction from the Federal Constitutional Court. So legally, a German Trump could have been fought much earlier.

Even if the legal situation in Germany makes a similar course of events as in the U.S. seem unlikely, this does not answer the question of how we will deal in the future with politicians who divide our societies and incite them against each other, and whether blocking important digital communication channels is one of them. What is clear and indisputable is that social media platforms have too much power. But what to conclude from this interim finding is less clear. That’s because two sides are diametrically opposed in the discussion about what social networks should and should not be allowed to do now.

One perspective goes like this: deplatforming should be allowed, because real censorship can only come from the state, and certainly not from private companies. The right to freedom of expression is not restricted by a simple deletion of accounts on social networks, Donald Trump can continue to make use of this right, the reasoning goes, just not on twitter and facebook. Moreover, the state cannot force companies to give people like him a platform – especially not if that person has previously agreed to the terms of use and then violates them in his statements.

The opposing side, represented by Chancellor Merkel among others, also argues that freedom of expression, as a fundamental right of elementary importance, can only be restricted by politicians, not at the whim of influential corporate leaders. The conclusion here is albeit a different one, namely that deplatforming should be rejected, at least insofar as it is executed by social media themselves. After all, freedom of expression in social networks has also led to very desirable developments such as the Arab Spring and should therefore not be touched.

Alternatives to company-driven deplatforming

First of all, scientific evidence shows that deplatforming really does work. A 2016 study showed that mass deletion of accounts of supporters of the Islamist terrorist organization ISIS led to a significant loss of digital influence. Another analysis proved a week after Trump’s platform withdrawal that disinformation about election fraud in the U.S. had declined by 73%. And with a view to Germany, a further study suggested that deplatforming significantly limits the mobilization power of the far right.

In the search for alternatives to corporate-driven deplatforming, some good suggestions have been made. Many of them, however, do not so much concern themselves with the root of the problem (i.e. the creation and popularization of hateful content), but rather with the mere alleviation of symptoms. These suggestions include the Santa Clara principles on content moderation. Some items from this list, such as the right to object to unlawful deletions, have already been adopted by EU and German legislators. In addition to YouTube and Twitter, these principles are also supported by Facebook, but none of the major platforms in the U.S. adhere to them except reddit. So while social media in the U.S. are largely free to delete whoever with no way to formally object to this decision, in Germany they are being held accountable by the updated version of the Network Enforcement Act.

External platform councils, staffed by figures of great legitimacy such as Nobel Peace Prize winners, are also a good start in this regard, albeit one with room for improvement. Examples include the deletion advisory board that Google assembled to define its rules on the “right to be forgotten”, or the facebook oversight board that will decide whether to permanently suspend Donald Trump from the social network. The platforms have realized that the rules they set are enormously influential and that they need to seek legitimacy from outside because they do not have it themselves. However, these boards should not be filled by the social media themselves. Also, in the case of facebook’s oversight board, more than 25% of the council members are U.S. citizens, so the diversity is not representative of a global company.

We need to talk

…because even if those approaches are good first steps, they are only effective in treating the symptoms, but not the problem itself. The problem is the algorithms that give social networks their character as fear mongers. The corporate secrets of twitter and facebook that threaten democracy – namely, those algorithms that are responsible for curating individual social media accounts and, for business reasons, primarily promote fear- and anger-ridden messages – have so far been untouchable. Admittedly, the EU Commission’s Digital Services Act promises a better understanding with a transparency obligation for these algorithms. A major hurdle in effectively regulating social networks is still the lack of knowledge about their internal decision-making and rule-making processes. At the same time, however, according to lawyer and scholar Matthias Kettemann, intermediaries are so complex that legislators still lack the ability to adequately regulate social networks. This is because they fall through many categories because they fulfill many different functions: privacy law, competition law, communications law, media law (if they produce their own content).

However, mere transparency is not enough. More important would be a genuine “democracy compatibility check” of the recommendation algorithms of social media. In addition, filter bubbles should be able to be removed in a new “real world mode” so that users can see their home feed without the automatized recommendation function. Last but not least, users should also be able to pay for social networking services with money instead of data.

Ultimately, the social media have created their own monster in Trump. Deplatforming is only the ultima ratio for correcting an undesirable development that has been destabilizing societies for years. It would therefore be more important to work on the causes, the algorithms, which are calibrated for interaction and spread anger and fear more strongly than moderate and deliberative views.

The diversity dilemma in Silicon Valley

Anyone who thought that Silicon Valley was home not only to the “Frappuccino with hazelnut milk” faction, but also to the diversity-friendly political left, might not have been wrong on the first point, but certainly on the second. For some years now, there has been increasing evidence that – who would have thought – social diversity and issues such as digital ethics only play a role where they do not affect corporate power structures and bubbling profits.

Google recently provided further proof of this itself when it terminated the respected AI ethicist Timnit Gebru. Gebru co-founded the group “Black in A.I.” and became known for influential research into the social impact of facial recognition programs. That research showed that recognition systems miscategorize women and non-White people significantly more often than White men. An article Gebru co-authored in 2018 was widely seen as a “watershed moment” in the effort to point out and address social misperceptions of automated decision-making systems.

In firing Gebru, Google diminished not only (1) its own technological ability to address diversity issues in its algorithms, but (2) the diversity of its workforce itself.

Algorithms reproduce and reinforce social discrimination

The conflict between Gebru and her former employer arose from a dispute over a scientific paper she co-authored that criticized new systems in the field of language analysis that are also part of Google’s search function. Because these automated systems learn how to deal with language through “the internet” itself, i.e., big data analysis of a variety of texts commonly used in everyday life, these systems often contain the same kind of discrimination found in the everyday life of our societies.

According to an experiment by Algorithmwatch, Facebook uses gross stereotypes to optimize ad placement. For example, job ads for professions that are underpopulated by women continue to be shown to only a few women. Photos of trucks, for instance, with ad text directed at women, for example, were shown to only 12% of female users. In practical terms, this means that Facebook discriminates based on images.

Another recent study shows that Google’s image recognition system assigns attributes to women and men that cement traditional and outdated gender roles. For example, automated systems assigned labels such as “official,” “businessman,” “speaker,” “orator” and “suit” to images of men. Images of women, on the other hand, were linked to labels such as “smile,” “hairstyle,” and “outerwear.”

So how might this problem be addressed? One answer to this question is more diversity among software developers. But here, too, Big Tech companies are lagging behind society.

Silicon Valley is not a haven for social diversity

Silicon Valley has had its own diversity problem for some time. Timnit Gebru’s exit came a year after prominent A.I. ethicist Meredith Whittaker quit Google, saying she and other employees had faced internal retaliation for publicly organizing protests against the company’s handling of sexual harassment in the workplace and speaking out against the company’s handling of A.I. ethics. Whittaker, in addition to her work at Google, co-founded the AI NOW Institute at New York University, which is dedicated to ethical issues in artificial intelligence.

More recently, former Google employee Christina Curley also accused her former employer of discriminating against Black people in new hires. Curley’s job responsibilities included recruiting new employees with the goal of increasing the company’s diversity. She reported an incident in which a White supervisor referred to her Baltimore dialect as a “disability.” Baltimore has traditionally had a large African-American population.

Not only Google, but many other Silicon Valley companies don’t put much effort into creating a diverse work environment. Coinbase, a start-up that offers an online trading platform for cryptocurrencies, has seen 15 Black employees leave in the last two years. At least 11 had previously informed their supervisors or HR that they had been treated in a racist or discriminatory manner.

Pinterest, which had posed as a supporter of Black Lives Matter protests as recently as this summer, waged a small-scale war against two now-former Black female employees who were advocating for a better fact-checking system and refused to support them when their personal information was leaked to hate websites.

These are just the latest examples of a long-standing structural problem that is also reflected in U.S. employment statistics: While about 12 percent of U.S. workers were Black in 2019, their share in the tech industry was just six percent. In the case of Facebook, Alphabet, Microsoft and Twitter, that share was even lower. Diversity efforts that have now lasted six years have only resulted in low-single-digit growth in diversity.

Just as the Frappuccino-to-go may save time, but makes no sense ecologically, digital-ethical greenwashing cannot hide the fact that in the apparently progressive Silicon Valley, a strong structural conservatism cements White dominance and prevents a more representative representation of society.

How then can we reduce discrimination?

Generally speaking, the General Equal Treatment Act stipulates that people in Germany who feel discriminated against must prove this discrimination themselves. When using social networks such as Facebook, this is however virtually impossible, as users have no way of finding out what content is not shown to them. One way of countering this deplorable state of affairs would be to improve the legal situation, as the Federal Antidiscrimination Agency has already called for. So far, however, these calls have gone unheard by politicians.

There is also no simple solution to the problem of discriminatory algorithms. Uncritically designed algorithms that are trained on the basis of publicly available data sets often reproduce existing unequal treatment by means of “proxy discrimination.” Even when, for example, employers explicitly exclude potentially discriminatory variables such as gender, skin colour, or religion from their decision criteria, the training data still includes past discrimination. This discrimination creeps in through correlates close to the avoided exclusion criteria. In the case of discrimination against women for example, a correlate to the sex of the applicant could be how often words like “woman” or “female” are found in applications and resumes.

Transparency and traceability of algorithms are the key conditions – insofar as data protection permits – that need to be fulfilled in order to assess and counter the discriminatory effect of algorithms. At present, social networks such as Facebook are doing their utmost to prevent the disclosure of information about their decision-making and ranking algorithms. However, with the current draft of the European Commission’s Digital Services Act, there could be some movement happening here.

The draft stipulates that “very large platforms” (those exceeding 45m monthly users) must provide information interfaces (APIs) that include data on advertising and targeting criteria. In addition, vetted researchers will be given access to data from the corporations to evaluate potential risks emanating from algorithms with respect to fundamental rights and public discourse. Independent evaluators, regulators, and national coordinating institutions would be allowed to conduct audits. According to Algorithmwatch this draft is a good start but does not go far enough in that NGOs won’t be able to get access to platform data and raises further questions about the enforceability of the law.

Notwithstanding all efforts to regulate algorithms, however, another important problem lies in the fact that humans and their decisions in programming algorithms are the ultimate black box. Therefore, not only automated decisions must be documented but also human value judgments need to be made explicit. For where algorithms are created indiscriminately and uncritically based on publicly available texts, they end up simply adopting their inherent values, norms, and prejudices. Therefore, we urgently need to come up with ethical guiding principles against which these algorithms are measured. And by ethics, however, we do not mean those values that people have acquired by chance, but those that they should have. For this reason, the value judgments that automated decision-making systems make millions of times a day should be publicly debated, weighed, and prioritized so that they correspond to our goals as a society and do not simply reflect an outdated past.

Blockchains – carriers of democratic processes?

Democracies worldwide are facing a number of challenges. Technologies are transforming societies and social relations without politics being able to understand these processes of change in time, let alone manage them effectively. Where existing systems reach their limits, windows of opportunity for new technologies emerge. It seems no coincidence that Bitcoin, the first cryptocurrency based on blockchain technology, became established in 2009, immediately after the economic and currency crisis.

An important part of the digital (infrastructure) transformation recently emanated from blockchains. Like TCP/IP, on which the Internet is based, blockchains are protocols that not only allow programmable contracts and transactions but also to predetermine the rules that guide contractual relations. Exchanged over decentralized peer to peer networks, they allow virtually any type of transactions to be validated cheaply and securely. All parties have insight into the full blockchain, where all transactions are stored in a tamper-proof manner.

Despite the current hype, blockchains, like other innovations, are ambivalent in that their repercussions on systems such as society and politics depend on the applications built on this protocol. Nonetheless, one key aspect of this technology is of particular importance. Even though the radical transparency made possible by the complete traceabilty of all transactions in the blockchain can be limited by anonymization, a blockchain in its basic design is capable of permanently altering the current form, perception and actual use of public discoursive spaces. In this context, transparency as a principle has been gaining importance for several years and is also discussed as a human right, since it is itself of fundamental value for the realization of other human rights such as freedom of expression.

Beyond often discussed possible blockchain applications such as elections and outsourcing of administrative tasks, a corresponding research agenda would need to explore under which conditions this technological innovation can be adopted in fluid and flexible societal contexts, who defines its rules, and what this means for shaping the public space in which citizens conduct democratic discourse. Looking at the use of blockchain technology for democratic purposes, three sets of questions are in my view of central importance:

1. What are the repercussions of transparency of blockchain applications on social actors and their participation in discourses in the public sphere, especially through the omnipresent availability of past interactions contained in blockchains? While established news media such as the New York Times are already using blockchains to measure and track the truth of a given text, the focus here should be on how such models can change the public sphere. What impact does the omnipresence of this information have on participation in public discourse and how does the perception of transparency as a fundamental right change?

2. Trust in the sense of legitimacy and enforcement of decisions is the basis for the functioning of democracy. Until now, trust has been generated and guaranteed by democratic institutions. Blockchains offer the prospect of shifting the generation of trust from institutions to the protocol and could thus lead to a loss of legitimacy of the monopoly position of state rule-making and arbitration. Such, among others, is the thinking in institutions such as the European Central Bank when blockchain-based cryptocurrencies take over traditional functions of money. So to what extent do blockchains have the potential to compete with basic state services? What mechanisms characterize a transaction model on blockchain technology between citizens and the state?

3. Social and political processes are constantly changing, relying on negotiation as a central mechanism for establishing consensus and cooperation as the basis of democratic legitimacy. At the same time, modifications in public blockchains occur through consensus, and where consensus cannot be reached due to classical coordination problems, the system fragments through forkings, as the example of Bitcoin shows. The informality necessary for negotiation is in tension with the rigidity and irreversibility inherent in blockchain applications. How can the tension between this rigidity and the need for informality as a characteristic of ever-changing social relations be resolved? To what extent are consensually programmed applications, as sets of rules that are difficult to change, at all suitable for capturing socially fluid contexts?