addiction – Social Media Legality

Social Media, Minors, and Algorithms, Oh My!

What is an algorithm and why does it matter?

Social media algorithms are intricately designed data organization systems aimed at maximizing user engagement by sorting and delivering content tailored to individual preferences. At their core, social media algorithms collect and subsequently use extensive user data, employing machine learning techniques to better understand and predict user behavior. Social media algorithms note and analyze hundreds of thousands of data points, including past interactions, likes, shares, content preferences, time spent viewing content, and social connections to curate a personalized feed for each user. Social media algorithms are designed this way to keep users on the site, thus giving the site more time to put advertisements on the user’s feed and drive more profits for the social media site in question. The fundamental objective of an algorithm is to capture and maintain user attention, expose the user to an optimal amount of advertisements, and use data from users to curate their feed to keep them engaged for longer.

Addiction comes in many forms

One key element contributing to the addictiveness of social media is the concept of variable rewards. Algorithms strategically present a mix of content, varying in type and engagement level, to keep users interested in their feed. This unpredictability taps into the psychological principle of operant conditioning, where intermittent reinforcement, such as receiving likes, comments, or discovering new content, reinforces habitual platform use. Every time a user sees an entertaining post or receives a positive notification, the brain releases dopamine, the main chemical associated with addiction and addictive behaviors. The constant stream of notifications and updates, fueled by algorithmic insights and carefully tailored content suggestions, can create a sense of anticipation in users for their next dopamine fix, which encourages users to frequently update and scan their feeds to receive the next ‘reward’ on their timeline. The algorithmic and numbers-driven emphasis on user engagement metrics, such as the amount of likes, comments, and shares on a post, further intensifies the competitive and social nature of social media platforms, promoting frequent use.

Algorithms know you too well

Furthermore, algorithms continuously adapt to user behavior through real-time machine learning. As users engage with content, algorithms will analyze and refine their predictions, ensuring that the content remains compelling and relevant to the user over time. This iterative feedback loop further deepens the platform’s understanding of individual users, creating a specially curated and highly addictive feed that the user can always turn to for a boost of dopamine. This heightened social aspect, coupled with the algorithms’ ability to surface content that resonates deeply with the user, enhances the emotional connection users feel to the platform and their specific feed, which keeps users coming back time after time. Whether it be from seeing a new, dopamine-producing post, or posting a status that receives many likes and shares, every time one opens a social media app or website, it can produce seemingly endless new content, further reinforcing regular, and often unhealthy use.

A fine line to tread

As explained above, social media algorithms are key to user engagement. They are able to provide seemingly endless bouts of personalized content and maintain users’ undivided attention through their ability to understand the user and the user’s preferences in content. This pervasive influence extends to children, who are increasingly immersed in digital environments from an early age. Social media algorithms can offer constructive experiences for children by promoting educational content discovery, creativity, and social connectivity that would otherwise be impossible without a social media platform. Some platforms, like YouTube Kids, leverage algorithms to recommend age-appropriate content tailored to a child’s developmental stage. This personalized curation of interest-based content can enhance learning outcomes and produce a beneficial online experience for children. However, while being exposed to age-appropriate content may not harm the child viewers, it can still cause problems related to content addiction.

‘Protected Development’

Children are generally known to be naïve and impressionable, meaning full access to the internet can be harmful for their development, as they may take anything they see at face value. The American Psychological Association has said that, “[d]uring adolescent development, brain regions associated with the desire for attention, feedback, and reinforcement from peers become more sensitive. Meanwhile, the brain regions involved in self-control have not fully matured.” Social media algorithms play a pivotal role in shaping the content children can encounter by prioritizing engagement metrics such as likes, comments, and shares. In doing this, social media sites create an almost gamified experience that encourages frequent and prolonged use amongst children. Children also have a tendency to intensely fixate on certain activities, interests, or characters during their early development, further increasing the chances of being addicted to their feed.

Additionally, the addictive nature of social media algorithms poses significant risks to children’s physical and mental well-being. The constant stream of personalized content, notifications, and variable rewards can contribute to excessive screen time, impacting sleep patterns and physical health. Likewise, the competitive nature of engagement metrics may result in a sense of inadequacy or social pressure among young users, leading to issues such as cyberbullying, depression, low self-esteem, and anxiety.

Stop Addictive Feeds Exploitation (SAFE) for Kids

The New York legislature has spotted the anemic state of internet protection for children and identified the rising mental health issues relating to social media in the youth. Announced their intentions at passing laws to better protect kids online. The Stop Addictive Feeds Exploitation (SAFE) for Kids Act is aimed explicitly at social media companies and their feed-bolstering algorithms. The SAFE for Kids Act is intended to “protect the mental health of children from addictive feeds used by social media platforms, and from disrupted sleep due to night-time use of social media.”

Section 1501 of The Act would essentially prohibit operators of social media sites from providing addictive, algorithm-based feeds to minors without first obtaining parental permission. Instead the default feed on the program would be a chronologically sorted main timeline, one more popular in the infancy of social media sites. Section 1502 of The Act would also require social media platforms to obtain parental consent before allowing notifications between the hours of 12:00 AM and 6:00 AM and creates an avenue for opting out of access to the platform between the same hours. The Act would also provide a limit on the overall number of hours a minor can spend on a social media platform. Additionally, the Act would authorize the Office of the Attorney General to bring a legal action to enjoin or seek damages/civil penalties of up to $5,000 per violation and allow any parent/guardian of a covered minor to sue for damages of up to $5,000 per user per incident, or actual damages, whichever is greater.

A sign of the times

The Act accurately represents the growing concerns of the public in its justification section, where it details many of the above referenced problems with social media algorithms and the State’s role in curtailing the well-known negative effects they can have on a protected class. The New York legislature has identified the problems that social media addiction can present, and have taken necessary steps in an attempt to curtail it.

Social media algorithms will always play an intricate role in shaping user experiences. However, their addictive nature should rightfully subject them to scrutiny, especially in their effects among children. While social media algorithms offer personalized content and can produce constructive experiences, their addictive nature poses significant risks, prompting legislative responses like the Stop Addictive Feeds Exploitation (SAFE) for Kids Act. Considering the profound impact of these algorithms on young users’ physical and mental well-being, a critical question arises: How can we effectively balance the benefits of algorithm-driven engagement with the importance of protecting children from potential harm in the ever evolving digital landscape? The SAFE for Kids Act is a step in the right direction, inspiring critical reflection on the broader responsibility of parents and regulatory bodies to cultivate a digital environment that nurtures healthy online experiences for the next generation.

International Regulation of Social Media- A Survey

The debate on regulation of social media in the United States is a heated one. Lawmakers, fueled by both theoretical concerns and specific incidences, have proposed and debated legislation to regulate social media platforms, thus far – unsuccessfully. Bills have failed both because of constitutional concerns and lack of appetite. Sen. Amy Klobuchar said the tech lobby is so powerful that bills with “strong, bipartisan support” can fall apart “within 24 hours.

Recently, the Biden administration was prohibited from asking sites to remove misinformation content, with the Federal Appeals Court ruling that doing so was a violation of the first amendment. Additionally, Section 230 is alive and well, shielding media platforms from liability for pretty much anything posted on their sites. This is reflected in the recent cases Twitter, Inc. v. Taamneh and Gonzalez v. Google.

Elsewhere in the world, legislation designed to regulate social media is proposed, approved, awaiting and already in process of implementation. Unlike the US, Europe, the UK and others do not have the high First Amendment bar to overcome, making regulation a realistic possibility. A survey of active regulation and proposed regulation shows determination and promise in tackling some of the greatest concerns that social media poses.

Legislation worldwide has been designed to combat a variety of harms and threats, with each country and legislative body disclosing their most important concerns. The harms range from protecting children from viewing inappropriate content to establishing a level playing field to foster innovation, growth, and competitiveness in business. Most regulation places an onus on social media companies to be vigilant, police their own platforms, and remove content that violates the law. Heavy fines, up to 10% of the platform’s gross global profit would be assessed in fines if violated. A survey of the proposed and adopted legislation regulating social media shows progress toward a goal of a happier and safer online existence for all.

In the European Union

The European Union (EU) has elected a regulatory “one-two punch” to both control anticompetitive behavior of the platforms and to stop misinformation in its tracks.

The Digital Services Act (DSA) and the Digital Market Act (DMA) form a single set of rules that apply across the whole EU. They have two main goals: to create a safer digital space and to establish a level playing field to foster innovation, growth, and competitiveness for smaller and new business.

The DSA, passed in September 2023 and to be implemented in the new year, is designed to address social media’s harms to society. Under the DSA, platforms as well as providers of digital services will be required to more aggressively police their platforms. The DSA imposes reporting and monitoring obligations for illegal content and misinformation. Digital service providers, including social media sites, will be compelled to set up new policies and procedures to identify and remove flagged hate speech, terrorist propaganda and other “material defined as illegal by countries within the European Union.” This includes a duty to monitor and report, mandating internal audits and reporting on them. The DSA also requires platforms to disclose how their services amplify divisive content and stop targeting online ads based on a person’s ethnicity, religion or sexual orientation. Using children’s data for algorithms and advertising is also strictly prohibited. Social media giants are held to an even higher standard under the DSA. Very Large online platforms are held to an even higher standard. Platforms like Meta, X, and TikTok will be compelled to analyze the systemic risks that they can create including dissemination of illegal content, effect on fundamental rights, on elections and electoral processes, and gender-based violence or mental health trends.

Penalties for failure to adhere to the DSA are steep. Violation could be assessed with fines of up to 6% of a platform’s global profits per annum.

The DMA, which passed earlier this year, is meant to protect businesses from anticompetitive behavior by platforms, which negatively affects small businesses. Most of the regulation is aimed at creating a level playing field for businesses using platforms, and to combat the grip of platforms over app stores, advertising, and online shopping. Under the DMA, a platform cannot treat services and products offered by the platform better than those offered by a third party on the platform. They must give users access to the data they collect from the third party and can no longer track users beyond the platform’s own site for use in advertising or prevent third parties from directing users to another site from the platform.

Penalties for violation could soar into the billions. Violators can be fined for up to 10% of the platform’s global profits per annum, and up to 20% for repeat offenders.

To enforce the new laws, the EU plans to form a unit of 240 officers dedicated to the purpose.

United Kingdom

Kyiv, Ukraine – September 5, 2019: A paper cubes collection with printed logos of world-famous social networks and online messengers, such as Facebook, Instagram, YouTube, Telegram and others.

In September 2023, Parliament approved the Online Safety Bill. The bill is designed to prevent children from consuming harmful information online. Under the bill, platforms must act rapidly to remove illegal or harmful content from their sites. They must implement more transparent procedures and enforce them. They must implement and enforce age-checking measures to ensure children are not seeing inappropriate content. Platforms must also provide parents accessible ways to report problems as they arise, and to allow parents the ability to make their children’s accounts more secure using parental controls. They also must analyze and publish risk assessments. Critically, the law places a legal responsibility on social media platforms to enforce the promises they make to users when they sign up, through the platform’s terms and conditions. In effect, they are legally bound to enforce their terms and conditions.

Punishment for violations could exceed fines of 18 million Pounds, or 10% of their global annual revenue, whichever is higher.

Australia

Australia also recently proposed legislation aimed at regulating and removing misinformation and illegal content, particularly for the benefit of children. The law would compel platforms to remove “cyber-abusive” information within 24 hours. This regulation would also allow the regulatory body in charge there, the Australian Competition and Consumer Commission (ACCC) and the Australian Association of National Advertisers (AANA), to obtain information and documents from digital platforms relating to disinformation and misinformation.

Indonesia

Indonesia centers its newest proposed legislation on its concern for the local markets and local vendors. Last month, the President of Indonesia announced that the Trade Ministry would be issuing regulation that would ban e-commerce on social media platforms. No specific platforms were mentioned, but TikTok is likely one of the targets. Officials have claimed that e-commerce sellers using predatory pricing on social media platforms are threatening local markets in Indonesia, with some officials specifically citing TikTok. The proposed bill prohibits direct transactions on social media sites, but vendors can still advertise products on social media. No word yet on how or when implementation would commence.

Efforts from around the globe to regulate social media and digital platforms are full of promise. Implementation and enforcement will be a challenge, as the digital world expands and mutates continually, and opposition to change by social media platforms is sure to follow. Here in the United States, there is much we could borrow and implement. From the comfortable position of early and interested observer, let’s see.

Social Media Addiction

Social Media was created as an educational and informational resource for American Citizens. Nonetheless, it has become a tool for AI bots and tech companies to predict our next moves by manipulating our minds on social media apps. Section 230 of the Communications Decency Act helped create the modern internet we use today. However, it was initially a 1996 law that regulated online pornography. Specifically, Section 230 provides legal immunity from liability for internet services and users for content posted online. Tech companies do not just want to advertise to social media users but instead want to predict a user’s next move. The process of these manipulative tactics used by social media apps has wreaked havoc on the human psyche and destroyed the social aspects of life by keeping people glued to a screen so big tech companies can profit off of it.

Social media has changed a generation for the worse, causing depression and sometimes suicide, as tech designers manipulate social media users for profit. Social media companies for decades have been shielded from legal consequences for what happens on their platforms. However, due to recent studies and court cases, this may be able to change and allow for big tech social media companies to be held accountable. A former Facebook employee, France Haugen, a whistleblower to the Senate, stated not to trust Facebook as they knowingly pushed products that harm children and young adults to further profits, which Section 230 cannot sufficiently protect. Haugen further states that researchers at Instagram (a Facebook-owned Social Media App) knew their app was worsening teenagers’ body images and mental health, even as the company publicly downplayed these effects.

There is a California Bill, Social Media Platform Duty to Children Act, that aims to make tech firms liable for Social media Addiction in children; this would allow parents and guardians to use platforms that they believe addicted children in their care through advertising, push notifications and design features that promote compulsive use, particularly the continual consumption of harmful content on issues such as eating disorders and suicide. This bill would hold companies accountable regardless of whether they deliberately designed their products to be addictive.

Social Media addiction is a psychological, behavioral dependence on social media platforms such as Instagram, Snapchat, Facebook, TikTok, bereal, etc. Mental Disorders are defined as conditions that affect ones thinking, feeling, mood, and behaviors. Since the era of social media, especially from 2010 on, doctors and physicians have had a hard time diagnosing patients with social media addiction and mental disorders since they seem to go hand in hand. Social Media addiction has been seen to improve mood and boost health promotions with ads. However, at the same time, it can increase the negative aspects of activities that the youth (ages 13-21) take part in. Generation Z (“Zoomers”) are people born in the late 1990s to 2010s with an increased risk of social media addiction, which has been linked to depression.

A study measured the Difficulties in Emotion Regulation Scale (“DEES”) and Experiences in Close Relationships (“ECR”) to characterize the addictive potential that social media communication applications have based on their measure of the brain. The first measure in the study was a six-item short scale consisting of DEES that was a 36-item, six-factor self-report measure of difficulties, assessing

awareness of emotional responses,
lack of clarity of emotional reactions,
non-acceptance of emotional responses,
limited access to emotion regulation strategies perceived as applicable,
difficulties controlling impulses when experiencing negative emotions, and
problems engaging in goal-directed behaviors when experiencing negative emotions.

The second measure is ECR-SV which includes a twelve-item test evaluating adult attachment. The scale comprised two six-item subscales: anxiety and avoidance. Each item was rated on a 7-point scale ranging from 1 = strongly disagree to 7 = strongly agree, which is another measure of depression, anxiety, and mania were DSM-5. The results depict that scoring at least five of the nine items on the depression scale during the same two-week period classified depression. Scoring at least three of the six symptoms on the anxiety scale was to sort anxiety. Scoring at least three of the seven traits in the mania scale has classified mania.

The objectives of these studies were to clarify that there is a high prevalence of social media addiction among college students and confirms statistically that there is a positive relationship between social media addiction and mental disorders by reviewing previous studies.

The study illustrates that there are four leading causes of social media abuse: 1)The increase in depression symptoms have occurred in conjunction with the rise of smartphones since 2007, 2) Young people, especially Generation Z, spend less time connecting with friends, and they spend more time connecting with digital content. Generation Z is known for quickly losing focus at work or study because they spend much time watching other people’s lives in an age of information explosion. 3) An increase in depression is low self-esteem when they feel negative on Social Media compared to those who are more beautiful, more famous, and wealthier. Consequently, social media users might become less emotionally satisfied, making them feel socially isolated and depressed. 4) Studying pressure and increasing homework load may cause mental problems for students, therefore promoting the matching of social media addiction and psychiatric disorders.

The popularity of the internet, smartphones, and social networking sites are unequivocally a part of modern life. Nevertheless, it has contributed to the rise of depressive and suicidal symptoms in young people. Shareholders of social media apps should be more aware of the effect their advertising has on its users. Congress should regulate social media as a public policy matter to prevent harm, such as depression or suicide among young people. The best the American people can do is shine a light on the companies that exploit and abuse their users, to the public and to congress, to hold them accountable as Haugen did. There is hope for the future as the number of bills surrounding the topic of social media in conjunction with mental health effects has increased since 2020.

AI Avatars: Seeing is Believing

Have you ever heard of deepfake? The term deepfake comes from “deep learning,” a set of intelligent algorithms that can learn and make decisions on their own. By applying deep learning, deepfake technology replaces faces from the original images or videos with another person’s likeness.

What does deep learning have to do with switching faces?

Basically, deepfake allows AI to learn automatically from its data collection, which means the more people try deepfake, the faster AI learns, thereby making its content more real.

Deepfake enables anyone to create “fake” media.

How does Deepfake work?

First, an AI algorithm called an encoder collects endless face shots of two people. The encoder then detects similarities between the two faces and compresses the images so they can be delivered. A second AI algorithm called a decoder receives the package and recovers it to reconstruct the images to perform a face swap.

Another way deepfake uses to swap faces is GAN, or a generative adversarial network. A GAN adds two AI algorithms against each other, unlike the first method where encoder and decoder work hand in hand.
The first algorithm, the generator, is given random noise and converts it into an image. This synthetic image is then added to a stream of real photos like celebrities. This combination of images gets delivered to the second algorithm, the discriminator. After repeating this process countless times, the generator and discriminator both improve. As a result, the generator creates completely lifelike faces.

For instance, Artist Bill Posters used deepfake technology to create a fake video of Mark Zuckerberg , saying that Facebook’s mission is to manipulate its users.

Real enough?

How about this. Consider having Paris Hilton’s famous quote, “If you don’t even know what to say, just be like, ‘That’s hot,’” replaced by Vladimir Putin, President of Russia. Those who don’t know either will believe that Putin is a Playboy editor-in-chief.

Yes, we can all laugh at these fake jokes. But when something becomes overly popular, it has to come with a price.

Originally, deepfake was developed by an online user of the same name for the purpose of entertainment, as the user had put it.

Yes, Deepfake meant pornography.

The biggest problem of deepfake is that it is challenging to detect the difference and figure out which one is the original. It has become more than just superimposing one face onto another.

Researchers found that more than 95% of deepfake videos were pornographic, and 99% of those videos had faces replaced with female celebrities. Experts explained that these fake videos lead to the weaponization of artificial intelligence used against women, perpetuating a cycle of humiliation, harassment, and abuse.

How do you spot the difference?

As mentioned earlier, the algorithms are fast learners, so for every breath we take, deepfake media becomes more real. Luckily, research showed that deepfake faces do not blink normally or even blink at all. That sounds like one easy method to remember. Well, let’s not get ahead of ourselves just yet. When it comes to machine learning, nearly every problem gets corrected as soon as it gets revealed. That is how algorithms learn. So, unfortunately, the famous blink issue already had been solved.

But not so fast. We humans may not learn as quickly as machines, but we can be attentive and creative, which are some qualities that tin cans cannot possess, at least for now.
It only takes extra attention to detect Deepfake. Ask these questions to figure out the magic:

Does the skin look airbrushed?
Does the voice synchronize with the mouth movements?
Is the lighting natural, or does it make sense to have that lighting on that person’s face?

For example, the background may be dark, but the person may be wearing a pair of shiny glasses reflecting the sun’s rays.

Oftentimes, deepfake contents are labeled as deepfake because creators want to display themselves as artists and show off their works.
In 2018, a software named Deeptrace was developed to detect deepfake contents. A deeptrace lab reported that deepfake videos are proliferating online, and its rapid growth is “supported by the growing commodification of tools and services that lower the barrier for non-experts—from well-maintained open source libraries to cheap deepfakes-as-a-service websites.”

The pros and cons of deepfake

It may be self-explanatory to name the cons, but here are some other risks deepfake imposes:

Destabilization: the misuse of deepfake can destabilize politics and international relations by falsely implicating political figures in scandals.
Cybersecurity: the technology can also negatively influence cybersecurity by having fake political figures incite aggression.
Fraud: audio deepfake can clone voices to convince people to believe that they are talking to actual people and induce them into giving away private information.

Well then, are there any pros to deepfake technology other than having entertainment values? Surprisingly, a few:

Accessibility: deepfake creates various vocal personas that can turn text into speech, which can help with speech impediments.
Education: deepfake can deliver innovative lessons that are more engaging and interactive than traditional lessons. For example, deepfake can bring famous historical figures back to life and explain what happened during their time. Deepfake technology, when used responsibly, can be served as a better learning tool.
Creativity: instead of hiring a professional narrator, implementing artificial storytelling using audio deepfake can tell a captivating story and let its users do so only at a fraction of the cost.

If people use deepfake technology with high ethical and moral standards on their shoulders, it can create opportunities for everyone.

Case

In a recent custody dispute in the UK, the mother presented an audio file to prove that the father had no right to take away their child. In the audio, the father was heard making a series of violent threats towards his wife.

The audio file was compelling evidence. When people thought the mother would be the one to walk out with a smile on her face, the father’s attorney thought something was not right. The attorney challenged the evidence, and it was revealed through forensic analysis that the audio was tailored using a deepfake technology.

This lawsuit is still pending. But do you see any other problems in this lawsuit? We are living in an era where evidence tampering is easily available to anyone with the Internet. It would require more scrutiny to figure out whether evidence is altered.

Current legislation on deepfake.

The National Defense Authorization Act for Fiscal Year 2021 (“NDAA”), which became law as Congress voted to override former President Trump’s veto, also requires the Department of Homeland Security (“DHS”) to issue an annual report for the next five years on manipulated media and deepfakes.

So far, only three states took action against deepfake technology.
On September 1, 2019, Texas became the first state to prohibit the creation and distribution of deepfake content intended to harm candidates for public office or influence elections.
Similarly, California also bans the creation of “videos, images, or audio of politicians doctored to resemble real footage within 60 days of an election.”
Also, in 2019, Virginia banned deepfake pornography.

What else does the law say?

Deep fakes are not illegal per se. But depending on the content, a deepfake can breach data protection law, infringe copyright and defamation. Additionally, if someone shares non-consensual content or commits a revenge porn crime, it is punishable depending on the state law. For example, in New York City, the penalties for committing a revenge porn crime are up to one year in jail and a fine of up to $1,000 in criminal court.

Henry Ajder, head of threat intelligence at Deeptrace, raised another issue: “plausible deniability,” where deepfake can wrongfully provide an opportunity for anyone to dismiss actual events as fake or cover them up with fake events.

What about the First Amendment rights?

The First Amendment of the U.S. Constitution states:
“Congress shall make no law respecting an establishment of religion, or prohibiting the free exercise thereof; or abridging the freedom of speech, or of the press; or the right of the people peaceably to assemble, and to petition the Government for a redress of grievances.”

There is no doubt that injunctions against deepfakes are likely to face First Amendment challenges. The First Amendment will be the biggest challenge to overcome. Even if the lawsuit survives, lack of jurisdiction over extraterritorial publishers would inhibit their effectiveness, and injunctions will not be granted unless under particular circumstances such as obscenity and copyright infringement.

How does defamation law apply to deepfake?

How about defamation laws? Will it apply to deepfake?

Defamation is a statement that injures a third party’s reputation. To prove defamation, a plaintiff must show all four:

1) a false statement purporting to be fact;

2) publication or communication of that statement to a third person;

3) fault amounting to at least negligence; and

4) damages, or some harm caused to the person or entity who is the subject of the statement.

As you can see, deepfake claims are not likely to succeed under defamation because it is difficult to prove that the content was intended to be a statement of fact. All that the defendant will need to protect themselves from defamation claims is to have the word “fake” somewhere in the content. To make it less of a drag, they can simply say that they used deep”fake” to publish their content.

Pursuing a defamation claim against nonconsensual deepfake pornography also poses a problem. The central theme of the claim is the nonconsensual part, and our current defamation law fails to address whether or not the publication was consented to by the victim.

To reflect our transformative impact of artificial intelligence, I would suggest making new legislation to regulate AI-backed technology like deepfake. Perhaps this could lower the hurdle that plaintiffs must face.
What are your suggestions in regards to deepfake? Share your thoughts!

Category: addiction

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