Authentication and the State

Authentication and the State
By Julie Nguyen

Introduction

For historical and cultural reasons, the American society is one of very few democracies in the world where there is no universal authentication system at the national level. Surprisingly, the Americans don’t trust governments as they do toward corporations because they consider such identifier system a serious violation of privacy and a major opening to Big Brother government. I will argue that it is more beneficial for the US to create a universal authentication system to replace the patchwork of de facto paper documents currently in use in a disparate fashion at the state level in the United States.

Though controversial and difficult to be implemented, a national-level authentication system would entail a lot of benefits.

It is not reasonable to argue that it is too complex to create a national-level authentication system. No, it is hard but possible elsewhere.

The debate on a national-level authentication system is not new. In Europe, national census scheme inspired a lot of resistance as it tended to focus the attention on privacy issues. One of the earliest examples was the protest against a census in the Netherland in 1971. Likewise, nobody foresaw the storms of protests over the censuses in Germany in 1983 and 1987. In both countries, the memories of the World War II and how the governments had terrorized the Dutch and German people during and after the war could explain such kind of reactions.

Similarly, proposals for a national-level identity cards produced the same reactions in numerous countries. Today, however, almost all modern societies have developed systems to authenticate their citizens. Those systems have evolved with the advent of new technologies in particular the biometric cards or e-cards: the pocket-sized “ID cards” have become biometric cards in almost all European countries and E-cards in Estonia.  Citizens of many countries, including democracies, are required by law to have ID cards with them all the time. Surprisingly, these cards are still viewed by Americans as a major tool of oppressive governments and any discussion on establishing a national-level ID cards are not in general considered fit for discussion.

In some countries where people shared the same American view, their governments have learnt their hard lessons. As the result, contemporary national identification policies tend to be introduced more gradually under other symbols than the ID system per se. Thus, the new Australian policy is termed an Access Card since its introduction in 2006. The Canadian government now talks of a national Identity Management policy. More recently, the Indian government has implemented Aadhaar, the biggest world-wide biometric identification scheme containing the personal details, fingerprints and iris patterns of 1.2 billion people – nine out of ten Indians.

It is time that the federal government, taking lessons from other countries, create a national-level authentication system in the Unites States given that the system would create a lot of benefits for the Americans.

The advantages of a national authentication system would outperform its disadvantages in contrast to the argument of the opponents related to privacy and discrimination issues. I will use two main arguments to justify my statement. First and foremost, the most significant justification for identifying citizens is to insure the public’s safety and well-being. Even in Europe where the right to privacy is extremely important, Europeans have made a trade-off in favour of their safety. Documents captured from Al Queda or ISIS show that terrorists are aware that anonymity is a valuable tool for penetrating an open society. For domestic terrorist acts, it would be also easier and simpler to get terrorists caught in the case the country has a universal authentication system. For instance, Unabomber is one of the most notorious terrorists in the United States due to fact that it was extremely hard to track him as he had quasi no identity in the society.

Second, the opponents of a national authentication system argue that traditional ID cards or a national authentication system are a source of discrimination. Actually, universal identifiers could serve to reduce discrimination in some areas. All job applicants would be identified to avoid the fake identity, not only immigrant people or those who look or sound “foreign”. Taking the example of E-Verify which is a voluntary online system operated by the U.S. Department of Homeland Security (DHS) in partnership with the Social Security Administration (SSA). It’s used to verify an employee’s eligibility to legally work in the United States. E-Verify checks workers’ Form I-9 information for authenticity and work authorization status against SSA and Citizenship and Immigration Services (CIS) database. Today, more than 20 states have adopted laws that require employers to use the federal government’s E-Verify Program. As the E-verify entails further administrative costs for potential employers, it is a driver of discrimination towards immigrant workers in the United States. A national “E-verify” system of all US residents would prevent such a source of discrimination.

Lack of a national-wide authentication system results in a lot of social costs.

Identity theft has become a serious problem in the United States. Though the federal government passed the Identity Theft and Assumption Deterrence Act in 1998 in order to crackdown the problem and make it a federal felony, the cost of identity theft has continued to increase significantly[1]. Identity thieves have stolen over $107 billion in the US for the past six years. Identity theft is particularly frightening because there is no completely effective way for most people to protect themselves. Rich and powerful persons can be also caught in the trap. For example, Abraham Abdallah, a busboy in New York, succeeded in stealing millions of dollars from famous people’s bank accounts, using the Social Security Numbers, home addresses and birthdays of Warren Buffet, Oprah Winfrey and Steven Spielberg…

People usually think that identity theft is mainly a case of someone using another person’s identity to steal money from this person, mostly via stolen credit cards or more complicated in the case of the above-mentioned New Yorker. But the reality is much more complex. In his book The Limits of Privacy, Amitai Etzioni lists several categories of crime related to identity theft:

    • Criminal fugitive
    • Child abuse and sex offenses
    • Income tax fraud and welfare fraud
    • Nonpayment of child support
    • Illegal immigration

Additionally, the highest hidden cost for American society due to the lack of a universal identity system is, in my opinion, the vulnerability of their democracy and the inefficient function of the whole society. In most democracies, a universal authentication system permits citizens to interact with government, reducing transaction cost and increasing the trust in governments at the same time. Moreover, it is a step toward an e-election in these countries where, like in the United States, the turnout rate has become critical. Without a universal and secured authentication system, any reform of the election in the country would be very difficult to put in place.

Overall, the tangible and intangible cost of not having a national authentication system is very high.

Conclusion

The United States is one of the very few democracies that has no standardized universal identification system. The social cost is very significant. The new technologies today can make it possible to protect the system from abuse. There is no zero-sum game in a society. Opponents of such kind of authentication system are wrong and their arguments would not hold today anymore. “Information does not kill people; people kill people” as Dennis Bailey wrote in The open Society Paradox. It is time to create a single, secure and standardized national-level ID to replace the patchwork of de facto paper documents currently in use in the United States. An incremental implementation of an Estonian-like system with a possible opting-out solution like Canadian approach can be an appropriate answer to the opponents of a national authentication system in the United States.  

Bibliography

1/ The Privacy Advocates – Colin J. Bennett, The MIT Press, 2008.

2/ The Open Society Paradox – Dennis Bailey, Brassey’s Inc., 2004.

3/ The Limits of Privacy – Amitai Etzioni, Basic Books, 1999.

4/ E-Estonia: The power and potential of digital identity – Joyce Shen, 2016. https://blogs.thomsonreuters.com/answerson/e-estonia-power-potential-digital-identity/

5/ E-Authentication Best Practices for Government – Keir Breitenfeld, 2011. http://www.govtech.com/pcio/articles/E-Authentification-Best-Practices-for-Government.html

6/ My life under Estonia’s digital government – Charles Brett, 2015. www.theregister.co.uk/2015/06/02/estonia/

7/ Hello Aadhaar, Goodbye Privacy – Jean Drèze, 2017. https://thewire.in/government/hello-aadhaar-goodbye-privacy

GDPR: Good Intentions, Unintended Consequences?

GDPR: Good Intentions, Unintended Consequences?
By Jen Patterson-Radovancevic | July 17, 2020

General Data Protection Regulation (GDPR) padlock on european union flag

The EU’s General Data Protection Regulation, or GDPR, has often been lauded for its progressiveness, having seemingly pushed the definition of what can be considered to be under a governing body’s supervision when it comes to technology. The goal was to make Europe “fit for the digital age,” but GDPR has implications for businesses and individuals on a global scale — and only some of them good.

While GDPR protects European residents (it is not exclusive to citizens) and has inspired adherence to its principles and similar policies abroad, there could be some negative economic costs incurred on non-EU countries — and these costs would be most inflicted, potentially, on the most economically vulnerable countries, or those who still catching up from behind in terms of technological globalization.

The EU regulation impacts firms both inside and outside the EU — in effect, it can affect any company that touches the data of EU businesses, residents, or citizens, regardless of having a physical headquarters in Europe. If the business is outside the EU, but handles any European data, it is required to designate a representative to monitor the company’s data practices, notify relevant EU authorities of potential data breaches, and attend enforcement proceedings in the event of GDPR non-compliance. In such a case of noncompliance, the ICO or another European Protection Authority can serve a formal enforcement notice on the company. This would likely take the form of blocking the service in the case of unlawful data processing, or goods seizure in the case of personal data related to the sale of physical goods being processed unlawfully. For repeat offenders, up to €20 million (approximately $23.5 million USD) or 4% of a company’s worldwide turnover can be fined.

This presents a tricky situation for non-EU countries and companies that have high market contact with the EU, in whatever capacity. These might include, for example, “fringe” European countries, like those in Southeastern Europe. Countries must decide whether or not they will follow in the EU’s footsteps, and create their own “progressive” data protection policies. If they do, they may be able to ensure that their companies can maintain business relationships in Europe, but would face the high cost of actually enforcing the regulation — certainly, this would affect the poorer, most vulnerable countries the most. If they do not pursue such policies, they might save regulation costs, but risk losing overall GDP; furthermore, companies within their borders will have to compete amongst themselves and decide if they will meet GDPR’s requirements, possibly with little governmental support. Firms surviving at the edge may be sunk simply from the administrative cost of determining who among their user base is an EU resident. EU countries, and other rich western countries, can more easily afford to switch over to the GDPR standards either via policy or via natural market competition, and likely have the private technical knowledge and public governmental support to do so.

Aside from the economic burden, there’s another effect to consider when it comes to GDPR’s influence: that the rest of the world, as it mimics Europe’s policies and practices to fit into the global economy, will de facto adopt the European model of data privacy. With the European and California models of privacy poised to become the dominant privacy paradigm globally, the question must be asked — is it right for the West to impose its conceptualization of privacy on the rest of the world? No matter how well-intentioned, the ideological effects of GDPR may, in a sense, act as a form of technological imperialism. Furthermore, exacting regulations after the West’s Internet tech companies have been firmly established is a practice reminiscent of other potentially harmful “progressive” movements by the West: imposing environmental laws on industrial-era Stage 2 and 3 countries, while the West’s service-based economies reached their current state of comfort by engaging themselves in environmental exploitation; or even the apparent solidification of national borders in the name of self-determination, once Europe and the US were satisfied with the outcomes. The West generously exporting its morality is not new; nor is the world’s willingness to adopt that morality, if it means staying competitive in the global market.

In this piece, I don’t intend to muddle the benefits GDPR provides. The transparency that it demands from large companies, especially concerning data practices and data breaches, is a huge leap forward from pre-GDPR times. Rather, my goal was to highlight some of the potential negative externalities of the legislation, and hope it may inspire others to deeply consider the true effects of such a premium, global policy on the world’s underdogs.

Tracking Transitions: The Surveillance State, Identification Documents, & Trans Communities

Tracking Transitions: The Surveillance State, Identification Documents, & Trans Communities
By Kai Nham | July 17, 2020

For many trans people, especially trans people of color, visibility is fraught with contradictions. Who gets to be seen as their full selves? Who is forced to be hyper visible? These contradictions are reflected in the processes of the United States’ surveillance mechanisms that continue to police and enact administrative violence on trans communities. While trans people are disproportionately affected by the rise of surveillance technologies, such as facial recognition, another pervasive element of the surveillance state is identity documentation. Cross-referenced throughout many databases, identity documentation serves as an access-point into many of the rights conferred by citizenship, both formally and informally.


Fig. 1: Art credited to Ana Galvañ, originally illustrated for John Seabrook’s New Yorker article, “Dressing for the Surveillance Age”

Policing Trans as a Category
The category of trans has been one that has consistently been policed through formal mechanisms of identification by the state, as well as through social interactions with those who carry the administrative power of the state (e.g. police officers, Transportation Security Administration (TSA) agents, doctors, etc). In order to obtain or change identity documents, many trans people in the United States must obtain doctor’s notes that document their “proper” transition, which historically has been prescribed as one’s ability to conform to norms of whiteness, class privilege, heterosexuality, and able-bodiedness. This poses many problems for trans and gender nonbinary people who cannot conform to these prescriptions of normative gender, do not have the financial or material means to medically transition, do not desire to medically transition, or any combination of the above. Doctors, then, serve as one of the gatekeepers to access to identity-aligned documents. In the 2015 National Transgender Discrimination Survey report, one third of respodents had none of their identity documents updated to align with their gender identity. The consequences of these barriers and practices that make trans people both invisible and hypervisible simultaneously are dangerous. 40% of people who presented an ID that did not appear to match their gender expression were harassed , 15% were asked to leave the establishment, and 3% were physically assaulted.

Additionally the data that is used “as part of these legal processes (along with any form requiring one to identify as a specific gender) form a paper trail through which state agencies [and other private entities] may track, assess, and manage transgender people” (Beauchamp, 2014). These paper trails expose the trans community to the dangers of hypervisibility by the state, which has historically played a large role in the violence enacted on them, whether it be through acts of police violence to housing discrimination.

Identification & Post-9/11 Surveillance Policies
In the post-9/11 era, we have seen an expansion and bolstering of the surveillance state in more visible and explicit ways. Even in technologies and processes that do not explicitly seek to target or harm trans and gender nonbinary communities, it has been found that these surveillance practices disproportionately harm those exact communities. The heightened scrutiny of identity documents due to the United States’ “War on Terror” policies has led to targeting of particularly trans people of color, trans immigrants, and low-income trans people, who are more likely to have inconsistent identity documents. Deeply connected to formations of who is deemed as a citizen versus alien, these surveillance policies work in a nexus of neoliberalism, white supremacy, and cisheteronormativity. For trans and gender nonbinary communities, the lack of access to “proper” and “accurate” documentation excludes them from access to basic needs, such as work or public spaces, and subjects them as undesirable aliens that need to be policed and surveilled.


Fig. 2: A black and white photo of a crowd of protestors with the words “Expect Trans Resistance” printed on a trans flag.

Revealing how the surveillance state continues to violate and harm trans and gender nonbinary communities through technologies that seem as benign as identity documentation calls into question what liberation would look like. This does not include neoliberal reforms that nod at inclusion into a violent state apparatus. Rather, looking to the continued legacy of radical trans politics from riots against state violence at Compton’s Cafeteria to Stonewall, trans and gender nonbinary communities have been working to dismantle these systems of power that systemically harm them and creatively imagine and build new systems that allow them to thrive.

References

  • Beauchamp, Toby. “Surveillance.” TSQ 1 May 2014; 1 (1-2): 208–210. doi: doi.org/10.1215/23289252-2400037.
  • Grant, Jaime M., Lisa A. Mottet, Justin Tanis, Jack Harrison, Jody L. Herman, and Mara Keisling. Injustice at Every Turn: A Report of the National Transgender Discrimination Survey. Washington: National Center for Transgender Equality and National Gay and Lesbian Task Force, 2011.

Computer Vision and Regulation

Computer Vision and Regulation
By Hong (Sophie) Yang | July 3, 2020

What is computer vision?

Computer vision is a field of study focusing on training the computer to see.
“At an abstract level, the goal of computer vision problems is to use the observed image data to infer something about the world.”
(Page 83, Computer Vision: Models, Learning, and Inference, 2012).

The goal of computer vision is to understand the content of digital images. Typically, this involves developing methods that attempt to reproduce the capability of human vision. Object detection is a form of computer vision. Understanding the content of digital images may involve extracting a description from the image, which may be an object, a text description, a three-dimensional model, and so on. During inference of object detection, the model draws bounding boxes around the object based on extracted weights, which are the training coefficient from the labeled images. The bounding boxes give the exact xmin, ymin, xmax and ymax position of the object with the confidence value.

Use cases of Computer Vision

This is the list of professionally researched areas where have seen successful using computer vision.

  • Optical character recognition (OCR)
  • Machine inspection
  • Retail (e.g. automated checkouts)
  • 3D model building (photogrammetry)
  • Medical imaging
  • Automotive safety
  • Match move (e.g. merging CGI with live actors in movies)
  • Motion capture (mocap)
  • Surveillance
  • Landmark detection
  • Fingerprint recognition and biometrics

It is a broad area of study with many specialized tasks and techniques, as well as specializations to target application domains.

From YOLO to Object Detection Ethical issue YOLO (You Only Look Once), the real time object detection model created by Joseph Redmon in May 2016, is a real time object detection model, and Yolov5 was released June 2020, it is the most recent state of art computer vision model. YOLO solved the low-level computer vision problem; more tools can be built on top of YOLO model from automatic driving to cancer cell detection with real time monitoring.

The news in February 2020 shocked the machine learning community, Joseph Redmon announced that he had ceased his computer vision research to avoid enabling potential misuse of the tech – citing in particular “military applications and privacy concerns.”

The news spun the discussion of “broader impact of AI work including possible societal consequences – both positive and negative” and “someone should decide not to submit their paper due to Broader Impacts reasons?” That is where Redmon stepped in to offer his own experience. Despite enjoying his work, Redmon tweeted, he had stopped his CV research because he found that the related ethical issues “became impossible to ignore.”
Redmon said he felt certain degree humiliation for ever believing “science was apolitical and research objectively moral and good no matter what the subject is.” He said he had come to realize that facial recognition technologies have more downside than upside, and that they would not be developed if enough researchers thought about the broader impact of the enormous downside risks.

When Redmon first created Yolo3 in 2016, he wrote about the implications of having a classifier such as the YOLO. “If humans have a hard time telling the difference, how much does it matter?” On a more serious note: “What are we going to do with these detectors now that we have them?” He also insisted on the responsibility of the computer vision researchers to consider the harm our work might be doing and think of ways to mitigate it.

“We owe the world that much”, he said.

This whole debate led to these questions, which might go unanswered forever:

  • Should the researchers have a multidisciplinary, broader view of the implications of their work?
  • Should every research be regulated in its initial stages to avoid malicious societal impacts?
  • Who gets to regulate the research?
  • Shouldn’t the expert create more awareness rather than just quit?
  • Who should pay the price; the innovator or those who apply?

One big complaint that people have against Redmon’s decision is that experts should not quit. Instead, they should take the responsibility of creating awareness about the pitfalls of AI.

The article on Forbes “Should AI be regulated”, published in 2017, had pointed out that AI is a fundamental technology, Artificial Intelligence is a field of research and development. You can compare it to quantum mechanics, nanotechnology, biochemistry, nuclear energy, or even math, just to cite a few examples. All of them could have scary or evil applications but regulating them at the fundamental level would inevitably hinder advances, some of which could have a much more positive impact than we can envision now. What should be heavily regulated is its use in dangerous applications, such as guns or weapons. This led to the tough questions: Who to regulate it? At what level?

Surge Pricing – Is it fair?

Surge Pricing – Is it fair?
By Sudipto Dasgupta | July 3, 2020

What is Surge Pricing?

Surge pricing by rideshare companies like Uber, Lyft originates from the idea to adjust prices of rides to match driver supply to rider demand at any given time. During periods of excess demand, the number of riders is high compared to the cars and customers need to wait for a longer time. The rideshare companies increase their normal fare. The fares are increased by a multiplier which depends on the demand in real time. Whenever rates are raised due to surge pricing, the app lets riders know. Some riders will choose to pay, while some will choose to wait a few minutes to see if the rates go back down. Most of us who are regular users of the apps would have encountered surge pricing as depicted below.


Fig 1 : Surge Pricing

A brief history

Surge pricing is based on the concept of dynamic pricing which is not new. In the 1950s, the New York subway faced a problem. At peak times, it was overcrowded; at other times, the trains were empty. William Vickrey suggested the abandonment of the flat-rate fare in favor of a fare structure which takes into account the length and location of the ride and the hour of the day. This was called as peak-load pricing.

The ride share apps extends the concept of peak-load pricing through their surge prices. The difference is that the price calculation is not only dependent on peak load but also on other factors like driver availability, weather, zip code, special events , rush hours to mention a few. The apps rely on algorithms which are opaque to the consumer to compute the multiplier. The factors which influence the prices are not transparent to the riders.

Consciously or unconsciously we as riders accept the convenience in exchange of cost. We may not even check the fare multiplication factor while availing for a convenient ride.

Fairness Concerns

The opaque algorithms of surge pricing do raise multiple fairness concerns. Prices on Uber and Lyft rose to as much as five times normal rates in the immediate aftermath of a deadly shooting in downtown Seattle in January 2020. The automated surge pricing lasted for about an hour and drew widespread criticism before the companies manually reset prices to normal levels. In 2015, Spencer Meyer, a Connecticut Uber rider, sued Uber co-founder and then-CEO Travis Kalanick, alleging that Uber was engaging in price-fixing. Uber came under criticism for hiking prices during a hostage crisis that was unfolding in Sydney in 2014. They subsequently apologized for the same.

An analysis conducted by Akshat Pandey and Aylin Caliskan from George Washington University indicates possible disparate impact due to social bias based on age, house pricing, education, and ethnicity in the dynamic fare pricing models used by ride hailing applications.


Fig2 : City of Chicago ride-hailing data. The colors in each chart designate the average fare price per mile for each census tract.

The authors analyzed 100 million rides from the city of Chicago from November 2018 to December 2019 and reported increase in ride-hailing prices when riders were picked up or dropped off in neighborhoods with a low percentage of 1) people over the age of 40, (2) people with a high school education or less, and 3) houses priced under the median for Chicago.

The surge pricing manifests as decisional interference for the riders. Biases in the training data influence the outcomes of the algorithm. Hence the question arises what data are the algorithms trained on? How can the ride sharing apps reduce the opacity of the algorithms? Is it possible to explain the AI models behind the algorithms given the apps are used by a diverse group of riders with different levels of technology understanding?

What ridesharing companies have to say?

“When demand for rides outstrips the supply of cars, surge pricing kicks in, increasing the price,”. Uber said that surge pricing reduces the number of requests made during a peak time, while drawing more drivers to busy areas. “As a result, the number of people wanting a ride and the number of available drivers come closer together, bringing wait times back down.”

Looking Forward

Answering the questions on the opacity of the algorithms is important for addressing the fairness concerns. Can the complex algorithms be exposed to the users? The ride sharing apps can have simpler mechanisms to explain the multiplication factor and make it more predictable for the riders.

Addressing the Weaponization of Social Media to Spread Disinformation

Addressing the Weaponization of Social Media to Spread Disinformation
By Anonymous | July 3, 2020

The use of social media platforms like Facebook and Twitter by political entities to present their perspectives and goals is arguably a key aspect of their utility. However, social media is not always used in a forthcoming manner. One such example is the use of these sites by Russia to spread disinformation by exploiting platform engagement and the cognitive biases of the users. The specific mechanisms of their techniques are documented and summed up as a “Firehose of Falsehood”, which serves as a guide to identify specific harms that we can proactively guard against.

The context of the analysis was rooted in the techniques being employed around the time of Russia’s 2014 invasion of the Crimean Peninsula. The techniques employed would go on to be reused to great effect in 2016, when they were used against the United Kingdom in their Brexit referendum, as well as the United States in their presidential election. More recently, the Firehose has been used against many other targets, including 5G cellular networks and vaccines.

While their techniques share some similarities with those of their Soviet predecessors, the key characteristics of Russian propaganda are that they are high-volume and multichannel, continuous and repetitive, and lacking commitment to objective reality or consistency. This approach lends itself well to social media platforms, as the speed at which new false claims can be generated and broadly disseminated far outstrip the speed at which fact checkers operate – polluting is easy, but cleaning up is difficult.


Figure 1: The evolution of Russian propaganda towards obfuscation and using available platforms
(Sources: Amazon, CBS)

The Firehose also emphasizes exploiting audience psychology in order to disinform. The cognitive biases exploited include the advantage of the first impression, using information overload to force the use of shortcuts to determine trustworthiness, use of repetition to create familiarity, the use of evidence regardless of veracity, and peripheral cues such as creating the appearance of objectivity. Repetition in particular works because familiar claims appear are favoured over less familiar ones – by repeating the message frequently, that repetition leads to familiarity, which in turn leads to acceptance. From there, confirmation bias further entrenches those views.


Figure 2: A cross-section of specimens from the 2016 election
(Source: Washington Post)

Given the nature of the methods outlined, some suggested responses are:

1. Do not rely solely on traditional techniques of pointing out falsehoods and inconsistencies
2. Get ahead of misinformation by raising awareness and make efforts to expose manipulation efforts
3. Focus on thwarting the desired effects by redirecting behaviours or attitudes without directly engaging with the propaganda
4. Compete by increasing the flow of persuasive information
5. Turn off the flow by undermining the broadcast and message dissemination through enforcement of terms of service agreements with internet service providers and social media platforms

From an ethical standpoint, some of the proposed measures have some hazards of their own – in particular, the last suggestion (“turn off the flow”) may be construed as viewpoint-based censorship if executed without respect for the users’ autonomy in constructing their perspectives. As well, competing may be tantamount to fighting fire with fire, depending on the implementation. Where possible, getting ahead of the misinformation is preferable, as forewarning acts as an inoculant for the audience – by getting the first impression and highlighting attempts to manipulate the audience, it prepares the users to critically assess new information.

As well, if it’s necessary to directly engage with the claims being made, solutions proposed are:

1. Warn at the time of initial exposure to misinformation
2. Repeat the retraction/refutation, and
3. Provide alternative story while correcting misinformation to immediately fill the information gap that arises

These proposed solutions are less problematic than the prior options, as limiting the scope to countering the harms of specific instances of propaganda, despite the limitations highlighted above, preserves respect for users to arrive at their own conclusions.

In fighting propaganda, how can we be sure that our actions remain beneficent in nature? In understanding the objectives and mechanics of the Firehose, we also see that there are ways to address the harms being inflicted in a responsible manner. By respecting the qualifications of the audience to exercise free will in arriving at their own conclusions and augmenting their available information with what’s relevant, we can tailor our response to be effective and ethical.

Sources:
The Russian “firehose of falsehood” propaganda model: Why it might work and options to counter it
Your 5G Phone Won’t Hurt You. But Russia Wants You to Think Otherwise
Firehosing: the systemic strategy that anti-vaxxers are using to spread misinformation
Release of Thousands of Russia-Linked Facebook Ads Shows How Propaganda Sharpened
What we can learn from the 3,500 Russian Facebook ads meant to stir up U.S. politics