Gen Z on “The Social Dilemma”

Undergraduate student of data analytics, Liza Thornell, writes her reaction to the documentary on social media. My earlier post on the same topic is here.

A new Netflix documentary has recently caught the public’s attention. The Social Dilemma has caused speculation to form around big tech companies and has also sparked the deletion of social media applications across the nation. The Social Dilemma explores the steps that were taken to create the powerhouse social media platforms, along with exposing the negative effects the platforms have on its users.

Social media platforms, such as Facebook, gain the majority of their revenue through advertising. Due to its privacy settings (or lack thereof) Facebook is able to obtain astronomical amounts of data about its users. The data that is collected from social media platforms entices marketers because they can reach more customers for less money. These platforms market specific products based on the data that they collect through their users. According to The Social Dilemma not only can social media market products to you, it can also mold and shape your opinion as well, changing your preferences over time. In the Social Dilemma several former Silicon Valley executives explain why this can be bad.

According to the documentary, social media is harmful due to its design and how it affects mental health. The purpose of these apps is to hold your attention captive for as long as possible. In order to do so, it is important that the app keeps providing fresh new content that is relevant to your preferences. Everything we do on our phones becomes predictive data for what we will do next. The ideal situation for social media platforms is that you will end up down the ‘rabbit hole’ of specifically tailored content because the longer you spend scrolling and clicking through social media, the more data these platforms can collect about you. According to the Social Dilemma, the rabbit hole is a dangerous place to be.

Social media in its initial design was not created to be hurtful. It was made to bring people together. The Social Dilemma states that big tech companies have strayed away from their initial creation story. Now, social media is about holding its audience captive, molding public opinion, and increasing sales through tailoring marketing. The content is distracting us from the serious ramifications that can come from spending all of our free time scrolling instead of engaging with the world around us. It makes us crave instant approval at all times, from people and the media.

The Social Dilemma does not condemn social media. This documentary supports social media, just not the way it’s currently working. The biggest take away from this documentary is that we have gotten lost in the rabbit hole and have to find our way out to preserve our privacy.

From the standpoint of a college student, I found this documentary to be eye opening. I believe that the average college student struggles with being addicted to social media platforms and our attention spans are shortening as a result. Reliance on social media directly correlates with the decline of in-person interaction and interpersonal communication skills. Companies such as Apple have released features on phones that track screen time in order to enlighten consumers on their usage. The ability to track usage is a tool for managing and limiting social media use. For college students, cutting down on social media consumption can positively impact mental health and productivity.

Election Forecast by 538

I teach a data analytics course and I asked some students to write blogs on data and current events. This blog is by Jake Fischer.

Every four years, the United States seems to turn upside down with the Presidential election. Now, the nation has turned its eyes to predictive analytics to understand the future of our country. As of October 22, the time of the writing of this post, Joe Biden stands an 87% chance of winning the critical swing state of Florida. This seems like a significant margin, but how did we come to this understanding using data? How reliable is this fivethirtyeight forecast?

For starters, the 87% chance of winning is based on a simulation run by data analysts in 40,000 different scenarios, all of which are measuring different factors from voter turnout to demographics to the economic forecast of the day. This prediction also factors in the polling averages for each candidate from 8 different polls, each of which is given a grade of reliability and weighted accordingly. Hundreds of factors come into play when predicting an election, yet confidence in many of these numbers is at an all-time low. So, in answer to question two, the outlook is anything but certain.

This doubtful outlook is because, although Biden wins 87% of the elections, this does not factor in the margin he wins by. When truly looking at the data, you see that over half of the outcomes weighed in this 87% are decided by less than 1% of votes. Unfortunately, this does not leave much more for a margin of error as is required in most data analysis. 

This very popular website does not factor in the impact that the website itself has on voters. With millions of people reading this data and seeing that Biden stands a 87% chance of winning, there is a high likelihood that voters will simply not turn up at the polls. This distinct percentage of voter turnout that may chose not to turn up at the polls because of analytics like this, would significantly impact the data set and could actually throw the results in the entire opposite direction, particularly when the decision is already being decided by such a slim margin.

Even though data analysis has turned into a booming industry, with more accurate results than ever before, there are some instances in which predictive analytics has placed significant limitations on the outcome of important decisions, such as the presidential election. I say all of this to not place doubt on analytics, nor the credibility of the FiveThirtyEight organization, but rather to remind readers of the important factor that is the human condition. At the end of the day it is important to exercise your right to vote no matter what side of the aisle you stand on, and without allowing polling data to influence your decisions. Vote!

How Bayesians Read a Think Piece

How likely is it that an opinion critical of [topic] will get expressed by someone on the internet?

My good friend (call her Anne) texted me this week. Anne sent me a link to a blog that declared some of her preferred works of art (i.e. musicals) to be inferior. She loves art, so to be told that her tastes were not exceptionally good was disappointing.

In my reply I wanted to make sure that Anne wasn’t putting too much weight on this new evidence:

How should we incorporate blogs into our beliefs about reality? (I see the irony – I’m writing a blog right now.)

The non-technical summary: you should be skeptical of what you read online.

The technical summary: the fact that some writer said “H” on the internet, should make you only slightly more confident that “H” is true.

I can’t improve on the Wikipedia presentation of Bayes’ theorem, so I’ll just paste in:

Let’s consider the probability that it is true that Anne’s favorite musical is bad. We’ll call that hypothesis “H”. What’s the probability of H, given that one person wrote an article stating that the musical is bad?  

The evidence, E, is the article.

Instead of just evaluating whether the article is convincing or not, Bayesian inference requires that we consider

  1. Were we confident that H was true BEFORE seeing the article? Was there good data up until this point that convinced us H is true?
  2. If H is true, what’s the probability of this article being written?
  3. What’s the overall probability of this article being written, regardless of whether H is true?

The probability that musical is bad given that someone wrote an article saying so is :

P(H|E) = P(bad|article)

P(bad|article) = ( P(article|bad) x P(bad) )/ P(article)

The right side of the equation asks whether we are likely to see the article if the musical is bad. If the musical is actually bad, then we are likely to see it condemned in print. HOWEVER, if we had a prior belief that the musical is not bad, then the numerator gets smaller.

Finally, we consider the denominator, P(E) or the probability of seeing an article that is derogatory towards the musical. If that probability is high, then the probability of the musical actually being bad goes down.

Here’s how Anne should think:

P(bad|article) = ( likely that article will be written if bad x prior evidence suggests not bad) / snobby think pieces get written regardless

so

P(bad|article) = (big x small)/ big = small probability that Anne’s favorite musical is actually bad

You should be just the right amount of skeptical when it comes to internet content. Be Bayesian.

Thoughts on “The Social Dilemma” Documentary

I rarely watch things right when they come out. For once, I’m fairly current on something: the Netflix documentary “The Social Dilemma”.

Former employees of tech companies are using their talents to try to make sure that technology takes our society in a good direction. They appear to feel guilty for creating a product that is so fun it has become addictive.

They call attention to the negative effects of social media, which were difficult to foresee. The guy who claims to have created the Facebook “Like” button says that his intention had been to spread happiness. They didn’t realize that the lack of likes could exacerbate teen depression. They worry that in some cases it has even led to suicide.

They mention early on that social media has actually done some good. I know personally someone who was adopted from a foreign company and then reconnected with his birth family by searching his family name on Facebook.  That’s neat.

I think they underrate Facebook as a utility for adults. Parents are using Facebook to notify neighborhood residents of school fundraisers. Adults are using Facebook to sell used furniture.

Facebook is a place to turn for entertainment, but it’s really become more than that for my generation. We don’t have physical address books. We have a phone Contact list and we have our Facebook accounts.

Facebook is not the only service being scrutinized. Former employees of Google and Pinterest, among others, came forward to talk about how those services use customer data to sell advertisements.

One of the good points they make is that the algorithms that maximize ad revenue do not have user well-being in mind and can unintentionally lead to spreading false “news” stories. It’s important for users to know this. I am glad that more people are aware, thanks to the documentary.

The fact that radio is funded by ad revenue never caused us to shut down radio. Maybe it was always more transparent to listeners, and the fact that it is less individualized makes it feel less creepy.

Speaking of creepy, this documentary is creepy. It’s full of creepy music and long pauses in which your mind goes to dark places. They should have made it one hour instead of 1.5 hours. It was very manipulative, which makes sense because it was made by people who confess that they are professional manipulators.

My conclusion is that we should treat social media like alcohol. Most people can live with alcohol, but it kills. Every year, alcohol kills people. The US government estimates that alcohol kills 88,000 people every year in the US. We should be more careful with alcohol and we should all be more educated on the potential for harm.

Some people would be better off if we completely banned alcohol, but currently the strategy is to manage harm through EMTs and medical treatment. There are support groups for people such as Alcoholics Anonymous.

We think young people are more likely to hurt themselves with this dangerous item, so we restrict the sale to youth.

The internet can be very harmful to children and teens. It’s important to point out that respectable social media services like Pinterest are not the only places where kids can go. Kids and “screens” is a whole ball of twine. Regulating Facebook may actually do very little to protect children.

We can do a public health campaign, sort of like what’s going on with sugary sodas right now. I think this documentary is the beginning of a productive conversation.

It’s hard to say that I disagree with the conclusions of the filmmakers. I suspect that I do, and yet they mostly just tell stories and ask open questions and fidget quietly on screen. So, it’s hard to pin them down on precise policy recommendations. Although I resent having to watch them fidget for so many minutes, I also don’t want to sound ungrateful for the effort they made to raise awareness of an issue they feel strongly about.

Let’s have more documentaries, and more blogs, and more in-person conversations about how to make a better world now that the internet genie is out of the bottle. Let’s keep middle school students off of social media. It starts at home and in the neighborhood.

Teaching with SAS Viya: First Report

I teach a 400-level data analytics course to undergraduates at the Samford business school. Every semester, I have students apply the concepts we learn by using some analytics software. This semester, it was imperative that I choose a product that students could access from their own computers. We cannot all be together in the computer labs due to Covid.

For the first time, I am using SAS Viya for Learners. Currently, the students are learning SAS Visual Analytics through the Viya platform. SAS makes detailed tutorials that make it easy to teach software to a class. Something that I’m particularly happy about this Friday is that the product works. Class time is not getting chewed up by students who get errors that are difficult to troubleshoot.

(Of course, I tested the software myself before asking students to use it. Anyone who has taught large classes knows that there is no way to fully anticipate the problems that could arise when dozens of humans with different computers all try to do something.)

Something to know about SAS Viya for Learners is that it is free but the free version does not come with the whole range of functionality that SAS Visual Analytics offers. What seems most significant to me currently is that students cannot upload data into the program. There is a library of datasets to work with. That is what we are using for demonstrations and homeworks.

In previous semesters, students have been instructed to find their own data online and use that for their final project. This semester, students will use data that is pre-loaded into the SAS Viya for Learners library. There are many right ways to do a final project. Having less decisions to make about what data to use will allow students to focus more on the analysis and presentation.

So far, all we have done is logged in and built confidence with the interface. That’s the first step with any software. It works. The tutorials give excellent guidance. I will post another update as we get further along with SAS Viya.

No coding is needed (not even SAS coding). I have concluded that coding and data analytics are separate skills. They are both good skills to have. Sometimes teaching coding along with data analytics is appropriate. But the trade off needs to be recognized. Time spent learning to code, to some extent, takes away time spent learning about data analytics. Feel free to fight me on that in the comments if you disagree.

I also use a textbook to teach this course. So, SAS Viya is not the only resource.