Blog #10 - Reaction to Media Policy Presentations

As I listened to my peers' presentations, I began to realize just how quickly media and policy adapt to fit the values and priorities of society at a given time. In the last few decades, we've entered into, what I would refer to as, an extreme digital world. Everything we do, watch, listen to involve the use of some sort of technological invention. 

Cutting the Cord

Cable television first became available in the U.S. in 1948, and by 1968, only 6.4% of American households had cable television. From here, the percentage only continued to rise. 

Cutting the cord, however, refers to the cancellation of cable television by families in favor of wireless methods of receiving programming. These new programs include internet protocol television, digital terrestrial television and satellite television. 

Internet protocol television is television programming streamed over the internet, such as Netflix, Hulu or HBO Max. These popular streaming platforms are common in almost every American household today and have really taken over television industry.

Furthermore, digital terrestrial television is television transmitted using radio frequencies, and satellite television is television received through satellite, typically a paid subscription though cord cutting often refers to free to air satellite televisions. 

Households are cutting the cord mainly because of the high price of cable television and the advantages of other mediums of entertainment. They are cheaper, provide a wider variety and are more convenient.

This is a prediction for the increasing video streaming market size, going all the way to 2030.

The Effects of Embracing Wireless Programming

My peer, Kenny, discussed the transition to a different kind of commercial content as the length of advertisements have decreased. The audiences affected by commercial advertisements have also changed with the introduction of streaming platforms. 

Click here to read more! 

Wealth, age and location all become factors in determining how commercial advertising will impact a viewer. Those that are more wealthy will have to watch less ads as they are able to pay more to bypass them. Similarly, those that live in rural areas may not have access to the internet compared to those living in urban areas. 

This also allowed me to question how my own use of streaming platforms has affected my media consumption, as well as the advertisements that I watch. Streaming platforms allow me and others in my generation to over-consume and even binge-watch television shows. These platforms, along with the rise of social media platforms, are leading individuals to develop unhealthy habits when it comes to the amount of time spent staring at a screen.

On a Path to News Deserts

Television news is also being negatively impacted by those that are cutting the cord. As television news becomes less popular, new forms of spreading information rise. I know many teenagers and young adults who absorb most of their news from social media rather than trustworthy sources.

In her presentation, Halle discussed the concept of "news deserts," or a community that is not covered or reached by any sort of local news coverage. These have more commonly appeared as a result of the 50% reduction in careers in journalism since the 1990s. There has been a net loss of almost 2,000 local newspapers from 2004 to 2018.

This reduction in both print and broadcast news media will have a serious impact on the public's knowledge when it comes to local elections, events and issues. We must ask ourselves if the rapid change in technology and media is truly benefitting our society or causing us to disregard the older technologies that worked for so long? Are we losing more than we're gaining?

Click here to read more about America's news deserts from The Seattle Times!

Blog #9 - In the Age of AI

The PBS Frontline documentary, "In the Age of AI," illustrates that although artificial intelligence is opening the door to so many opportunities in the digital world, it is also raising serious concerns about online privacy, agency and security.

One of my biggest takeaways was that there are so many individuals in society that are oblivious to that fact that AI is incorporated into almost every aspect of our lives, including healthcare, education, criminal justice and human experience. 

Over the years, new technology has been perceived as an improvement; advancements were created with the purpose of simplifying a human task. Unfortunately as a result, we've developed a sense of inevitability that it will always make things better. But, is this the reality? Or is the diffusion of artificial intelligence causing more harm than good?

The Dark Side of AI

To start, AI is increasing inequalities and causing a loss of jobs. There is a group of people on top making all the money and no one in the middle that can support a family. Ultimately, the wealthy are getting wealthier and the poor are getting poorer. 

Artificial intelligence is a form of automation and automation is the substitution of capital for labor. There is no need for human labor when there are supermarket robots that are able to perform the same task to the same ability, or maybe even more efficiently. 

Ethical concerns arise when it comes to the concept of surveillance capitalism, or micro-behavioral targeting that is directed toward the individual based on an intimate, detailed understanding of personalities. Large corporations have realized that they can use cues in the online environment to change real-world behavior. More importantly, they are able to do this in a way that bypasses the users' awareness. 

We think we are the users of social media, but rather social media is using us. 

Anytime we browse or scroll we are leaving digital traces, originally called digital exhaust, that are valuable in the way they are able to predict behavior. As discussed in my previous post, companies have learned to apply machine learning algorithms to predict users' interests and, therefore, reach deeper and deeper into our work, lives and democracy. Artificial intelligence has become the ultimate tool of wealth creation. 

Advertising and marketing are all about uncertainty, whereas behavioral prediction is about taking the uncertainty out of life. 

Real World Implications

In 2018, the Cambridge Analytica scandal consumed the media as its purpose was to target and manipulate voters in the 2016 presidential campaign. Information arose regarding Facebook forcing Mark Zuckerberg to appear before Congress to explain how the data of up to 87 million Facebook users had been harvested by a political consulting company based in the UK.

This was a pivot from AI's main use by advertisers to a new use by political consumers. This example further illustrates the argument that artificial intelligence has taken away our agency. It is now the machines that have control over us.

We have no privacy because everything we do is being monitored. Technology and AI have invaded the intimate, personal aspects of our lives: our thoughts, desires, dreams, friends and so on.

The documentary discusses the California Consumer Privacy Act (CCPA) when it comes to online security and privacy. This law gives users control of their digital data, the right to know and the right to say no.

This is reassuring knowing that the CEO of Google admitted to knowing where users are and where they've been, with the users' permission. With this information, Google is able to more or less guess what you're thinking about and how you'll act. 

Cloud of Data

Everything you do as a consumer of technology and media is producing data, and there are computers looking at that data to learn and essentially try to serve you better. These computers are trying to personalize things to you and adapt the world to you. 

This is great on one hand, but the entities in the companies that are in control of those algorithms don't necessarily have the same goals as you.

Our democracy is threatened by these tools; therefore, we shouldn't take these concerns lightly. The best thing we can do as users is be aware of the negative implications of artificial intelligence so that we can have more control over it. We must continue to protect our privacy.

Blog #8 - Delving into Machine Learning

Artificial Intelligence has already spread into every aspect of our lives. From a simple Google Search to the invention of self-driving cars, its role in our digital lives is important to acknowledge and understand. Though it appears to be a more recent invention, AI has been around a lot longer than we would predict.

The term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, DARPA completed street mapping projects in the 1970s and then produced intelligent personal assistants in 2003, long before Siri or Alexa. 

Some people will use the terms AI and machine learning interchangeably, especially since most of the current advances in AI have involved marine learning; however, they are separate concepts. 

Machine learning is behind chatbots and predictive text, language translation apps, the shows Netflix suggests to you, and how your social media feeds are presented. In other words, machine learning takes the approach of letting computers learn to program themselves through experience. 

It can be time consuming or even impossible to train a computer like we do humans. But, machine learning has proven it could marshal a vast amount of data, beyond anything any human could handle.

How it Works

Machine learning starts with data such as numbers, photos, or text. The data is gathered and prepared to be used as training data, or the information the machine learning model will be trained on. The more data, the better the program. 

Programmers choose a machine learning model to use, supply the data, and let the computer model train itself to find patterns or make predictions. Over time, the human programmer can also tweak the model, including changing its parameters, to help push it toward more accurate results.

The function of a machine learning system can either be...

Descriptive: the system uses the data to explain what happened

Predictive: the system uses the data to predict what will happen

Prescriptive: the system will use the data to make suggestions about what action to take

Additionally, there are three subcategories of machine learning: supervised, unsupervised, or reinforcement. Supervised machine learning deals with a labeled data set, whereas unsupervised deals with unlabeled data. Reinforcement machine learning, on the other hand, is a trial and error method. The computer has a reward system so that it learns from its accuracy and mistakes.

Machine learning is best suited for situations with lots of data so that the computer has thousands or millions of examples. This can be observed in the Google Translate application as it "trained" on the vast amount of information on the web, in all different languages.

Uses in Business

Machine learning is the core of some companies' business models, like in the case of Netflix's suggestions algorithm or Google's search engine. Its ability to gain insight or automate decision-making in cases where humans would not be able to has made it the ultimate tool of wealth creation.

Google search is an example of something that humans can do, but never at the scale and speed at which the Google models are able to show potential answers every time a person types in a question. 

Companies are able to use machine learning in a variety of ways:

From manufacturing to retail and banking to bakeries, even legacy companies are using machine learning to unlock new value or boost efficiency.

Concerns

While machine learning is fueling technology that can help workers or open new possibilities for businesses, there are still concerns and limitations that businesses should understand. 

One of these being explainability, or the ability to be clear about what the machine learning models are doing and how they make decisions. Systems can be fooled and undermined, or just fail on certain tasks, even those humans can perform easily. While most problems can be solved through machine learning, people should assume right now that the models only perform to about 95% of human accuracy.

Another concern is bias and unintended outcomes. Machines are trained by humans, and human biases can be incorporated into algorithms. If biased information, or data that reflects existing inequities, is fed to a machine learning program, the program will learn to replicate it and perpetuate forms of discrimination. 

For example, if a chatbox is trained on how people converse on Twitter, it would pick up on and replicate offensive and racist language.

The most important thing a business can do is making sure its organization embraces human-centered AI. This is rooted in the practice of seeking input from people of different backgrounds, experiences, and lifestyles when designing AI systems.

Conclusion

We have reached a digital age that is practically fueled by artificial intelligence and its subfields: machine learning, neural networks, and deep learning. This technology can open so many possibilities, but it's important to fully understand these tools and think about how to use them well. Being aware of the social, societal, and ethical implications of machine learning is the best thing we can do. 

"Machine learning is changing, or will change, every industry, and leaders need to understand the basic principles, the potential, and the limitations," stated MIT computer science professor Aleksander Madry.

Blog #7 - Addressing the Invasion of Privacy

When you are sitting alone in your bedroom, you would assume to have privacy. When you send private messages to another individual, you would assume that those messages are only seen by you and the receiver on the other end. But are any of our actions truly private in a digital world that prides itself on the ability of tracking our every movement?

With the rise of technology, and social media in particular, the concept of privacy is not what it used to be. Large corporations, such as Facebook and Google, are able to gather mass amounts of data from each one of us, and most of this information we give out voluntarily. We sacrifice our right to privacy when we figuratively sign the contracts that each of these companies place in their terms and conditions. 

Facebook's business model incorporates a contract of adhesion, or a contract in which one party holds all the negotiating power. This allows them to change the terms without communicating with the user, have access to any material that is posted, and still own all material even after a user closes their account. This should be alarming to any Facebook or social media user (so most Americans).

In 2019, the Federal Trade Commission imposed a historic $5 billion penalty and sweeping new privacy restrictions on Facebook.

The Impact on the Individual

In his TED talk, Juan Enriquez compares the digital platforms that we utilize everyday to tattoos in the way they are able to tell our stories without the use of words. He refers to them as electronic tattoos that tell others who we are and what we do. However, this presents multiple issues:

1. Our data and private information will live far longer than our bodies will. 

2. We are not always aware of who will be receiving and abusing our information.

Our information and data is immortal. This can be dangerous for us, our friends and our family because it suggests our reputations, good or bad, can technically live on forever. Even more concerning is the fact that we are unaware of who may be accessing such information. 

Catherine Crump, American law professor and civil liberties expert, discusses the increase of mass surveillance and location tracking that gives the government access into our personal lives. Digital surveillance technology allows police departments to gather sensitive information about each one of us. This can be useful to investigations; however, it also allows the government to know far too much about what happens behind closed doors. The more information, the more easily it can be abused. 

We have lost control over our data and privacy. So where do we go from here?

Regaining Control: The Next Steps

The invasion of privacy this nation is facing should not fall on the individual to solve. It is the government's duty to ensure that American citizens are protected under their rights, and this includes our rights to privacy.

Unfortunately, our government, along with many large tech companies, is benefitting from the overflow of information and data. Mass amounts of data allow the government and corporations to predict our behaviors. Targeted advertising is the key to most business models; therefore, it would be shocking to see these companies give up their access. 

Online privacy depends on us.

Most social media users voluntarily give out so much information about their lives, locations, likes, dislikes, political views and so on. Andy Yen, founder and CEO of Proton, advocates for privacy rights and emphasizes that we are teaching younger generations to share everything on web. The education system is a good place to start.

We need to teach younger users of technology the importance of privacy. We need to highlight the importance of informed consent when giving platforms permission to access our data and personal information.

Introducing secure mediums of communication would also benefit many individuals and allow users to ensure their conversations are not being surveilled by foreign entities or hackers. Crump explains that the best thing we can do is acknowledge the technologies that are tracking our behaviors. Being aware and knowledgeable about the issue will allow us to create an internet where privacy is not only an option but the default.

Use these links to access the TED talks referenced in this post:

Juan Enriquez

Catherine Crump

Andy Yen