Tag: Social Media

Social media are interactive technologies that facilitate the creation and sharing of information, ideas, interests, and other forms of expression through virtual communities and networks.

Learn To Discern: How To Take Ownership Of Your News Diet

I am tired of keeping up with the news these days. The sheer volume of information is intimidating. It creates a challenge to filter relevant news from political noise only to then begin a process of analyzing the information for its integrity and accuracy. I certainly struggle to identify subtle misinformation when faced with it. That’s why I became interested in the psychological triggers weaved into the news to better understand my decision-making and conclusions. Pennycook and Rand wrote an excellent research paper on the human psychology of fake news.

tl;dr

We synthesize a burgeoning literature investigating why people believe and share false or highly misleading news online. Contrary to a common narrative whereby politics drives susceptibility to fake news, people are ‘better’ at discerning truth from falsehood (despite greater overall belief) when evaluating politically concordant news. Instead, poor truth discernment is associated with lack of careful reasoning and relevant knowledge, and the use of heuristics such as familiarity. Furthermore, there is a substantial disconnect between what people believe and what they share on social media. This dissociation is largely driven by inattention, more so than by purposeful sharing of misinformation. Thus, interventions can successfully nudge social media users to focus more on accuracy. Crowdsourced veracity ratings can also be leveraged to improve social media ranking algorithms.


Make sure to read the full paper titled The Psychology of Fake News by Gordon Pennycook and David G. Rand at https://www.sciencedirect.com/science/article/pii/S1364661321000516

Source: Creative Thinking Project

This recent research paper by psychologists of the University of Regina and the Sloan School of Management at Massachusetts Institute of Technology took a closer look at the sources of political polarization, hyperpartisan news, and the underlying psychology that influences our decision-making on whether news is accurate or misinformation. They answered the question of why people fall for misinformation on social media. Lessons that can be drawn from this research will be helpful to build effective tools to intercept and mitigate misinformation online. It will further advance our understanding of the underlying human psychology when interacting with information on social media. And while the topic could fill entire libraries, they limited their scope of research to individual examples of misinformation rather than organized, coordinated campaigns of inauthentic behavior excluding the spread of disinformation.

So, Why Do People Fall For Fake News?

There are two fundamental concepts that explain the psychological dynamics when faced with misinformation: truth discernment aims to establish a belief in the relative accuracy of news that is greater than known-to-be false information on the same event. Basically, this concept is rooted in active recognition and critical analysis of the information to capture people’s overall beliefs. Another concept that is used to explain why people fall for misinformation is the idea of truth acceptance. Thereunder the accuracy of news is not a factor but the overall belief of it. Instead of critical analysis of the information people chose to average or combine all available information, true or false, to establish an opinion about the veracity of the news that captures people’s overall belief. This commonly results in a biased perception of news. Other concepts related to this question look at motives. Political motivations can influence people’s willingness to reason based on their partisan, political identity. In other words, when faced with news that is consistent with their political beliefs, the information is regarded as true; when faced with news that is inconsistent with their political beliefs, the information is regarded as false. Loyalty to their political ideology can become so strong that it can override an apparent falsehood for the sake of party loyalty. Interestingly, the researchers found that political partisanship has much less weight than the actual veracity of news when assessing information. Misinformation that is in harmony with people’s political beliefs is less trustworthy than accurate information that is against people’s political beliefs. They also discovered that people tend to be better at analyzing information that is in harmony with our political beliefs, which helps to discern truth from falsehood. But if people hardly fall for misinformation consistent with our political beliefs, which characteristics make people fall for misinformation?

“People who are more reflective are less likely to believe false news content – and are better at discerning between truth and falsehood – regardless of whether the news is consistent or inconsistent with their partisanship”

Well, this brings us back to truth discernment. Belief in misinformation is commonly associated with overconfidence, lack of reflection, zealotry, delusionality, or overclaiming where an individual acts on completely fabricated information as a self-proclaimed expert. All of these factors indicate an inability of analytical thinking. On the opposite side of the spectrum, people determine the veracity of information through cognitive reflection and tapping into their relevant existing knowledge. This can be general political knowledge, a basic understanding of established scientific theories, or simple online media literacy.

“Thus, when it comes to the role of reasoning, it seems that people fail to discern truth from falsehood because they do not stop to reflect sufficiently on their prior knowledge (or have insufficient or inaccurate prior knowledge) – and not because their reasoning abilities are hijacked by political motivations.” 

The researchers found that the truth has little impact on sharing intentions. They describe three types of information-sharing on social media:

  • Confusion-based sharing: this concept encompasses a genuine belief in the veracity of the information-shared (even though the person is mistaken)
  • Preference-based sharing: this concept places political ideology, or related motives such as virtue signaling, above the truth of the information shared accepting misinformation as a collateral
  • Inattention-based sharing: thereunder people are only intending to share accurate information, but are distracted by the social media environment

Steps To Own What You Know

If prior knowledge is a critical factor to identify misinformation, then familiarity with accurate information goes a long way. An awareness of familiar information is critical to determine whether the information presented is the information that you already know or a slightly manipulated version. Be familiar with social media products. What does virality look like on platform XYZ? Is the uploader a verified actor? What is the source of the news? In general, sources are a critical signal to determine veracity. The more credible and established a source, the likelier the information is well-researched and accurate. Finally, a red flag for misinformation is emotional headlines, provocative captions, or shocking images.

Challenges To Identify Misinformation

Truth is not a binary metric. In order to determine the veracity of news, a piece of information may be falsified or laced with inaccuracies or compared against established, known information. Therefore the accuracy and precision, or overall quality, of a machine learning classifier for misinformation hinges on the clarity of the provided training data times the depth of exposure on the platform where the classifier will be deployed. Another challenge to consider is the almost ever-changing landscape of misinformation. Misinformation is rapidly evolving, convulsing into conspiracy theories and maybe (mistakenly) supported by established influencers and institutions. This creates problems to discern the elements of a news story, which undermines the chances to determine accuracy. Inoculation (deliberate exposure to misinformation to improve recognition abilities) is in part ineffective because people fail to stop, reflect and consider the accuracy of the information at all. Therefore successful interventions to minimize misinformation may start with efforts to slow down interactions on social media. This can be achieved by changing the user interface to introduce friction and prompts to help induce active reflection. Lastly, human fact-checking is not scalable. For so many reasons: time, accuracy, integrity, etc. Leveraging a community-based (crowd-sourced) fact-checking model might be an alternative until a more automated solution will be ready. Twitter has recently introduced experiments with these types of crowd-sourced products. Their platform is called Birdwatch.

This research paper didn’t unearth breakthrough findings or new material. It rather helped me to learn more about the dynamics of human psychology when exposed to a set of information. Looking at the individual concepts people use to determine the accuracy of information, the underlying motives that drive our attention, and the dynamics for when we decide to share news made this paper a worthwhile read. Its concluding remarks to improve the technical environment by leveraging technology to facilitate a more reflective, conscious experience of news on social media leaves me optimistic for better products to come. 

The Future Of Political Elections On Social Media

Should private companies decide what politician people will hear about? How can tech policy make our democracy stronger? What is the role of social media and journalism in an increasingly polarized society? Katie Harbath, a former director for global elections at Facebook discusses these questions in a lecture about politics, policy and democracy. Her unparalleled experience as a political operative combined with her decade long experience working on political elections across the globe make her a leading intellectual voice to shape the future of civic engagement online. In her lecture to honor the legacy of former Wisconsin State senator Paul Offner she shares historical context on the evolution of technology and presidential election campaigns. She also talks about the impact of the 2016 election and the post-truth reality online that came with the election of Donald Trump. In her concluding remarks she offers some ideas for future regulations of technology to strengthen civic integrity as well as our democracy and she answers questions during her Q&A.

tl;dr

As social media companies face growing scrutiny among lawmakers and the general public, the La Follette School of Public Affairs at University of Wisconsin–Madison welcomed Katie Harbath, a former global public policy director at Facebook for the past 10 years, for a livestreamed public presentation. Harbath’s presentation focused on her experiences and thoughts on the future of social media, especially how tech companies are addressing civic integrity issues such as free and hate speech, misinformation and political advertising.

Make sure to watch the full lecture titled Politics and Policy: Democracy in the Digital Age at https://lafollette.wisc.edu/outreach-public-service/events/politics-and-policy-democracy-in-the-digital-age (or below)

Timestamps

03:04 – Opening remarks by Susan Webb Yackee
05:19 – Introduction of the speaker by Amber Joshway
06:59 – Opening remarks by Katie Harbath
08:24 – Historical context of tech policy
14:39 – The promise of technology and the 2016 Facebook Election
17:31 – 2016 Philippine presidential election
18:55 – Post-truth politics and the era of Donald J. Trump
20:04 – Social media for social good
20:27 – 2020 US presidential elections 
22:52 – The Capitol attacks, deplatforming and irreversible change
23:49 – Legal aspects of tech policy
24:37 – Refresh Section 230 CDA and political advertising
26:03 – Code aspects of tech policy
28:00 – Developing new social norms
30:41 – More diversity, more inclusion, more openness to change
33:24 – Tech policy has no finishing line
34:48 – Technology as a force for social good and closing remarks

Q&A

(Click on the question to watch the answer)

1. In a digitally democratized world how can consumers exercise their influence over companies to ensure that online platforms are free of bias?

2. What should we expect from the congressional hearing on disinformation?

3. Is Facebook a platform or a publisher?

4. Is social media going to help us to break the power of money in politics?

4. How have political campaigns changed over time?

5. What is the relationship between social media and the ethics of journalism?

6. Will the Oversight Board truly impact Facebook’s content policy?

7. How is Facebook handling COVID-19 related misinformation?

8. What is Facebook’s approach to moderating content vs encryption/data privacy?

9. Does social media contribute to social fragmentation (polarization)? If so, how can social media be a solution for reducing polarization?

10. What type of regulation should we advocate for as digitally evolving voters?

11. What are Katies best and worst career memories? What’s next for Katie post Facebook?

Last but not least: Katie mentioned a number of books (and a blog) as a recommended read that I will list below:

Cyber Security and the Financial System

The financial sector is a highly regulated marketplace. Deepfakes or artificially-generated synthetic media are associated with political disinformation but have not yet been linked to the financial system. The Carnegie Endowment for International Peace issued a scintillating working paper series titled “Cyber Security and the Financial System” covering a wide range of cutting edge issues from the European framework for Threat Intelligence-Based Ethical Red Teaming (TIBER) to assessing cyber resilience measures for financial organizations to global policies to combat manipulation of financial data. Jon Bateman’s contribution titled “Deepfakes and Synthetic Media in the Financial System: Assessing Threat Scenarios” takes a closer look on how deepfakes can impact the financial system. 

tl;dr

Rapid advances in artificial intelligence (AI) are enabling novel forms of deception. AI algorithms can produce realistic “deepfake” videos, as well as authentic-looking fake photos and writing. Collectively called synthetic media, these tools have triggered widespread concern about their potential in spreading political disinformation. Yet the same technology can also facilitate financial harm. Recent months have seen the first publicly documented cases of deepfakes used for fraud and extortion. Today the financial threat from synthetic media is low, so the key policy question is how much this threat will grow over time. Leading industry experts diverge widely in their assessments. Some believe firms and regulators should act now to head off serious risks. Others believe the threat will likely remain minor and the financial system should focus on more pressing technology challenges. A lack of data has stymied the discussion. In the absence of hard data, a close analysis of potential scenarios can help to better gauge the problem. In this paper, ten scenarios illustrate how criminals and other bad actors could abuse synthetic media technology to inflict financial harm on a broad swath of targets. Based on today’s synthetic media technology and the realities of financial crime, the scenarios explore whether and how synthetic media could alter the threat landscape.

Make sure to read the full paper titled Deepfakes and Synthetic Media in the Financial System: Assessing Threat Scenarios by Jon Bateman at https://carnegieendowment.org/2020/07/08/deepfakes-and-synthetic-media-in-financial-system-assessing-threat-scenarios-pub-82237

(Source: Daily Swig)

Deepfakes are a variation of manipulated media. In essence, a successful deepfake requires a sample data set of a original that is used to train a deep learning algorithm. It will learn to alter the training data to a degree that another algorithm is unable to distinguish whether the presented result is altered training data or the original. Think of it as a police sketch artist who will create a facial composite based on eye-witness accounts. The more available data and time the artist has to render a draft, the higher the likelihood of creating a successful mugshot sketch. In this paper, the term deepfake relates to a subset of synthetic media including videos, images and voice created through artificial intelligence.

The financial sector is particularly vulnerable in the know-your-customer space. It’s a unique entry point for malicious actors to submit manipulated identity verification or deploy deepfake technology to fool authenticity mechanisms. While anti-fraud prevention tools are an industry-wide standard to prevent impersonation or identity theft, the onset of cheaper, more readily available deepfake technology marks a turning point for the financial sector. Deepfakes may be used to leverage a blend of false or hacked personal identifiable information (PII) data to gain access or open bank accounts, initiate financial transactions, or redistribute private equity assets. Bateman focused on two categories of synthetic media that are most relevant for the financial sector: (1) narrowcast synthetic media, which encompasses one-off, tailored manipulated data deployed directly to the target via private channels and (2) broadcast synthetic media, which is designed for mass-audiences deployed directly or indirectly via publicly available channels, e.g. social media. An example for the first variation is the story of a cybercrime that took place in 2019. A Chief Executive Officer of a UK-based energy company received a phone call from – what he believed – his boss, the CEO of the parent corporation based in Germany. In the phone call, the voice of the German CEO was an impersonation created by artificial intelligence and publicly available voice recordings (speeches, transcripts etc). The voice directed the UK CEO to immediately initiate a financial transaction to pay a Hungarian supplier. This type of attack is also known as deepfake voice phishing (vishing). These fabricated directions resulted in the fraudulent transfer of $234,000. An example for the second variation is commonly found in widespread pump and dump schemes on social media. These could range from malicious actors creating false, incriminating deepfakes of key-personnel of a stock-listed company to artificially lower the stock price or creating synthetic media that misrepresents product results to manipulate a higher stock price and garner more interest from potential investors. Going off the two categories of synthetic media, Bateman presents ten scenarios that are layered into four stages: (1) Targeting Individuals, e.g. identity theft or impersonation, (2) Targeting Companies, e.g. Payment Fraud or Stock Manipulation, (3) Targeting Financial Markets, e.g. creating malicious flash crashes through state-sponsored hacking or cybercriminals backed a foreign government, and (4) Targeting Central Banks and Financial Regulators, e.g. regulatory astroturfing. 

In conclusion, Bateman finds that at this point in time, deepfakes aren’t potent enough to destabilize global financial systems in mature, healthy economies. They are more threatening, however, to individuals and business. To take precautions against malicious actors with deepfake technology, a number of resiliency measures can be implemented: broadcast synthetic media is potent to amplify and prolong already existing crises or scandals. Aside from building trust with key audiences, a potential remedy to deepfakes amplifying false narratives is the readiness to create counter-narratives with evidence. To prevent other companies from potential threats that would decrease the trust in the financial sector, an industry wide sharing of information on cyber attacks is a viable option to mitigate coordinated criminal activity. Lastly, the technology landscape is improving its integrity at a rapid succession rate. A multi-stakeholder response bringing together leaders from the financial sector, the technology sector and experts on consumer behavior with policymakers will help to create more efficient regulations to combat deepfakes in the financial system.

Why You Can’t Quit Social Media

What is the fuel of our social media habits? To answer that question researchers from the University of Southern California in Los Angeles analyzed user behavior across established social media platforms. They offer insights into user habit formation, but also explain the dynamics and technology that prevent users from gaining control over the daily-use habits on social media.

tl;dr

If platforms such as Facebook, Instagram, and Twitter are the engines of social media use, what is the gasoline? The answer can be found in the psychological dynamics behind consumer habit formation and performance. In fact, the financial success of different social media sites is closely tied to the daily-use habits they create among users. We explain how the rewards of social media sites motivate user habit formation, how social media design provides cues that automatically activate habits and nudge continued use, and how strong habits hinder quitting social media. Demonstrating that use habits are tied to cues, we report a novel test of a 2008 change in Facebook design, showing that it impeded posting only of frequent, habitual users, suggesting that the change disrupted habit automaticity. Finally, we offer predictions about the future of social media sites, highlighting the features most likely to promote user habits.

Make sure to read the full paper titled Habits and the electronic herd: The psychology behind social media’s successes and failures by Ian A. Anderson and Wendy Wood at https://onlinelibrary.wiley.com/doi/abs/10.1002/arcp.1063

(Source: Getty Images/iStockphoto)


Social media platforms serve our communities in a variety of functions. Anybody can participate, share stories or become a community leader by creating user-generated content that is available to a specific group of people or the entire public. Connecting with people is human, but the frequency, means and reach as well as the how and who we connect with is not. In particular the dichotomy of conflicting social interests and user habits is discussed in this paper, which explains on a high level fundamental social media platform’s need to draw on user habits and how these habits are cultivated by sophisticated technology. In  fact, social media platforms are designed to encourage habit formation through repeat use. This is demonstrated by its ever-expanding options to find new people to connect and share content, new entertainment products and means to build larger online communities. This is to generate consistent revenue through effective, targeted marketing of its users.

One aspect of the paper explores whether frequent use of social media is habitual use and if overuse is tantamount to an addiction. What are the contributing factors that make people form a habit to frequently check their social media profiles? How can you manage these habits more effectively? What does it take to rewire these habits? The researchers found that users who post more frequently also reported increased automation of their actions. In other words, these users logged onto Facebook or Twitter posted about something without deliberately thinking about the act of posting itself. Some of the factors that contribute to forming a habit are the repeated steps it takes to participate on social media. For example, the login process, posting original content, exploring new content from others, liking, sharing or discussing content. In psychology this phenomenon is called ideomotor response wherein a user unconsciously completes an order of steps to perform a process. Of course the formation of a habit is not only due to repetition but rewards of continuous use. Likes, shares and general interaction with people on social media are a double-edged sword for it brings us closer together while also appealing to our subconscious need for affirmation. The former helps us to build positive attitudes linked with the particular platform. Whereas the latter often remains unrecognized until the habit is already established in one’s daily routine. Initial rewards subside fast, however, as these motivations are replaced by habitual use that is linked to a specific gain arising from a certain community engagement. These habits, once formed and established, are hard to overcome as demonstrated by an experiment with well-known, sugared beverages: 

“In an experiment demonstrating habit persistence despite conflicting attitudes, consumers continued to choose their habitual sugared beverages for a taste test even after reading a persuasive message that convinced them of the health risks of sugar”. 

It must be noted that social media use is not the same as drinking soda pop, smoking cigarettes or snorting cocaine. Social media use is also not a mindless, repetitive action. Rather it is a composition of different, highly individualized behaviors, attitudes and motivations that compound depending on the particular use case. For example a community organizer who uses Facebook Groups to bring together and coordinate high-school students across a county to play pickup ultimate frisbee will establish different habitual behaviors from someone using social media purely to connect online with a closed-circle of family and friends. The researchers found that active engagement on social media is linked to positive subjective experiences of well-being. Users who are more passive, scroll and read only reported lower levels of life satisfaction. Scrolling introduces an element of uncertainty for the user. Thus it is among the top rewards that don’t require active engagement. Unexpected posts tend to surprise users with sometimes highly emotional content such as misinformation or community nostalgia. Needless to state, controversial content tends to spread fast and far increasing the reward for engagement. Moreover it entrenches habitual use for users to come back to discover more emotional content.

To put this into perspective: social media habits form because the platform highlights signals that makes us feel good and keep us engaged. Preexisting emotional and social needs are captured by an easy process to use the platform. Notifications, likes, comments and shares increase participatory experiences that emulate real-world communities. Reciprocity between family, friends and others as well as elements of uncertainty are adjusted based on tailored content delivery through sophisticated algorithms. These lines of code ensure that once a user establishes a footprint on the platform, enough incentives are created to encourage and facilitate repeat use. Therefore further ingraining the platform in our daily lives, daily-use habits.

Maybe We Should Take A Break

In my thought provoking headline I challenge the notion that it is impossible to reduce or quit social media altogether. Note I wouldn’t want anybody to reduce or quit social media if it adds value to your life. Facebook is invaluable with regard to connecting with family and friends. YouTube or TikTok offer some of my favorite pastimes. And Twitter has become the newsstand of the 21st century. Nevertheless I believe this research paper is an important contribution to raise awareness of our daily habits, our time management and how we consume information. I would be remiss to not contemplate options to improve my social media diet. In psychology research the terminology for quitting a habit is coined discontinuance intention. Forming an intent to cease social media is a decision process at times overshadowed by feelings of regret, lack of alternative means to communicate across our social graph and general, societal inertia (take these Google search queries pictured below as an indicator for the impact of societal inertia). If you find yourself wanting to change your social media diet then be on the lookout for these factors: 

  • Familiarity Breeds Inaction: the longer a user is with a social media platform, the more likely feelings of familiarity and a sense of control prevent actions to reduce time spent on the platform
  • Habits Trump Intentions: everyday signals manifested in our phones, computers or environment trigger ideomotor responses to use social media despite social norms, resolutions etc. Remember the old saying “the road to hell is paved with good intentions” is true for managing our social media habits
(Source: Interest over time on Google Trends for delete tiktok, delete facebook, delete twitter, delete instagram, delete snapchat – United States, Past 12 months)


Straight-forward self-control has been found to be an effective strategy to reduce the use of social media. Discipline to use social media with a specific intent and for a specific purpose equals freedom from habitual, time-consuming use. However, the researchers found that self-control is hard to maintain and a more effective strategy is changing the signals upon which we use social media. For example, leveraging silent or airplane mode on our phones, turning off push-notifications or unsubscribing from notification emails help to dig a moat between a healthy daily routine and mindless use of social media. Interestingly, the researchers found short term absences from social media, i.e. only a few days, is less effective than an entire week or longer breaks from social media. It will depend on an individual’s preferences, needs and benefits that must be carefully balanced against the inherent cost of social media use. Of course all of this is highly subjective. I recommend reading this well-written research paper as a start. It helps to formulate a balanced strategy for social media use and online habit management.

Threat Assessment: Chinese Technology Platforms

The American University Washington College of Law and the Hoover Institution at Stanford University created a working group to understand and assess the risks posed by Chinese technology companies in the United States. They propose a framework to better assess and evaluate these risks by focusing on the interconnectivity of threats posed by China to the US economy, national security and civil liberties.

tl;dr

The Trump administration took various steps to effectively ban TikTok, WeChat, and other Chinese-owned apps from operating in the United States, at least in their current forms. The primary justification for doing so was national security. Yet the presence of these apps and related internet platforms presents a range of risks not traditionally associated with national security, including data privacy, freedom of speech, and economic competitiveness, and potential responses raise multiple considerations. This report offers a framework for both assessing and responding to the challenges of Chinese-owned platforms operating in the United States.

Make sure to read the full report titled Chinese Technology Platforms Operating In The United States by Gary P. Corn, Jennifer Daskal, Jack Goldsmith, John C. Inglis, Paul Rosenzweig, Samm Sacks, Bruce Schneier, Alex Stamos, Vincent Stewart at https://www.hoover.org/research/chinese-technology-platforms-operating-united-states 

(Source: New America)

China has experienced consistent growth since opening its economy in the late 1970s. With its economy at about x14 today, this growth trajectory dwarfs the growth of the US economy, which increased at about x2 with the S&P 500 being its most rewarding driver at about x5 increase. Alongside economic power comes a thirst for global expansion far beyond the asian-pacific region. China’s foreign policy seeks to advance the Chinese one-party model of authoritarian capitalism that could pose a threat to human rights, democracy and the basic rule of law. US political leaders see these developments as a threat to their own US foreign policy of primacy but perhaps more important a threat to the western ideology deeply rooted in individual liberties. Needless to say that over the years every administration independent of political affiliation put the screws on China. A most recent example is the presidential executive order addressing the threat posed by social media video app TikTok. Given the authoritarian model of governance and the Chinese government’s sphere of control over Chinese companies their expansion into the US market raises concerns about access to critical data and data protection or cyber-enabled attacks on critical US infrastructure among a wide range of other threats to national security. For example:

Internet Governance: China is pursuing regulation to shift the internet from open to closed and decentralized to centralized control. The US government has failed to adequately engage international stakeholders in order to maintain an open internet but rather has authorized large data collection programs that emulate Chinese surveillance.

Privacy, Cybersecurity and National Security: The internet’s continued democratization encourages more social media and e-commerce platforms to integrate and connect features for users to enable multi-surface products. Mass data collection, weak product cybersecurity and the absence of broader data protection regulations can be exploited to collect data on domestic users, their behavior and their travel pattern abroad. It can be exploited to influence or control members of government agencies through targeted intelligence or espionage. Here the key consideration is aggregated data, which even in the absence of identifiable actors can be used to create viable intelligence. China has ramped up its offensive cyber operations beyond cyber-enabled trade or IP-theft and possesses the capabilities and cyber-weaponry to destabilize national security in the United States.

Necessity And Proportionality 

Considering mitigating the threat to national security by taking actions against Chinese owned- or controlled communications technology including tech products manufactured in China the working group suggests an individual case-based analysis. They attempt to address the challenge of accurately identifying the specific risk in an ever-changing digital environment with a framework of necessity and proportionality. Technology standards change at a breathtaking pace. Data processing reaches new levels of intimacy due to the use of artificial intelligence and machine learning. Thoroughly assessing, vetting and weighing a tolerance to specific risks are at the core of this framework in order to calibrate a chosen response to avoid potential collateral consequences.

The working group’s framework of necessity and proportionality reminded me of a classic lean six sigma structure with a strong focus on understanding the threat to national security. Naturally, as a first step they suggest accurately identifying the threat’s nature, credibility, imminence and the chances of the threat becoming a reality. I found this first step incredibly important because a failure to identify a threat will likely lead to false attribution and undermine every subsequent step. In the context of technology companies the obvious challenge is data collection, data integrity and detection systems to tell the difference. By that I imply a Chinese actor may deploy a cyber ruse in concert with the Chinese government to obfuscate their intentions. Following the principle of proportionality, step two is looking into the potential collateral consequence to the United States, its strategic partners and most importantly its citizens. Policymakers must be aware of the unintended path a policy decision may take once a powerful adversary like China starts its propaganda machine. Therefore this step requires policymakers to include thresholds for when a measure to mitigate a threat to national security outweighs the need to act. In particular inalienable rights such as the freedom of expression, freedom of the press or freedom of assembly must be upheld at all times as they are fundamental American values. To quote the immortal Molly Ivins “Many a time freedom has been rolled back – and always for the same sorry reason: fear.” The third and final step concerns mitigation measures. In other words: what are we going to do about it? The working group landed on two critical factors: data and compliance. The former might be restricted, redirected or recoded to adhere to national security standards. The latter might be audited to not only identify vulnerabilities but further instill built-in cybersecurity and foster an amicable working-relationship. 

The Biden administration is faced with a daunting challenge to review and develop appropriate cyber policies that will address the growing threat from Chinese technology companies in a coherent manner that is consistent with American values. Only a broad policy response that is tailored to specific threats and focused on stronger cybersecurity and stronger data protection will yield equitable results. International alliances alongside increased collaboration to develop better privacy and cybersecurity measures will lead to success. However, the US must focus on their own strengths first, leverage their massive private sector to identify the specific product capabilities and therefore threats and attack vectors, before taking short-sighted, irreversible actions.